Accelerated GPU based SPECT Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-01
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: 99m Tc, 111In and 131I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational efficiency
Accelerated GPU based SPECT Monte Carlo simulations.
Garcia, Marie-Paule; Bert, Julien; Benoit, Didier; Bardiès, Manuel; Visvikis, Dimitris
2016-06-07
Monte Carlo (MC) modelling is widely used in the field of single photon emission computed tomography (SPECT) as it is a reliable technique to simulate very high quality scans. This technique provides very accurate modelling of the radiation transport and particle interactions in a heterogeneous medium. Various MC codes exist for nuclear medicine imaging simulations. Recently, new strategies exploiting the computing capabilities of graphical processing units (GPU) have been proposed. This work aims at evaluating the accuracy of such GPU implementation strategies in comparison to standard MC codes in the context of SPECT imaging. GATE was considered the reference MC toolkit and used to evaluate the performance of newly developed GPU Geant4-based Monte Carlo simulation (GGEMS) modules for SPECT imaging. Radioisotopes with different photon energies were used with these various CPU and GPU Geant4-based MC codes in order to assess the best strategy for each configuration. Three different isotopes were considered: (99m) Tc, (111)In and (131)I, using a low energy high resolution (LEHR) collimator, a medium energy general purpose (MEGP) collimator and a high energy general purpose (HEGP) collimator respectively. Point source, uniform source, cylindrical phantom and anthropomorphic phantom acquisitions were simulated using a model of the GE infinia II 3/8" gamma camera. Both simulation platforms yielded a similar system sensitivity and image statistical quality for the various combinations. The overall acceleration factor between GATE and GGEMS platform derived from the same cylindrical phantom acquisition was between 18 and 27 for the different radioisotopes. Besides, a full MC simulation using an anthropomorphic phantom showed the full potential of the GGEMS platform, with a resulting acceleration factor up to 71. The good agreement with reference codes and the acceleration factors obtained support the use of GPU implementation strategies for improving computational
Brown, F.B.; Sutton, T.M.
1996-02-01
This report is composed of the lecture notes from the first half of a 32-hour graduate-level course on Monte Carlo methods offered at KAPL. These notes, prepared by two of the principle developers of KAPL`s RACER Monte Carlo code, cover the fundamental theory, concepts, and practices for Monte Carlo analysis. In particular, a thorough grounding in the basic fundamentals of Monte Carlo methods is presented, including random number generation, random sampling, the Monte Carlo approach to solving transport problems, computational geometry, collision physics, tallies, and eigenvalue calculations. Furthermore, modern computational algorithms for vector and parallel approaches to Monte Carlo calculations are covered in detail, including fundamental parallel and vector concepts, the event-based algorithm, master/slave schemes, parallel scaling laws, and portability issues.
2010-10-20
The "Monte Carlo Benchmark" (MCB) is intended to model the computatiional performance of Monte Carlo algorithms on parallel architectures. It models the solution of a simple heuristic transport equation using a Monte Carlo technique. The MCB employs typical features of Monte Carlo algorithms such as particle creation, particle tracking, tallying particle information, and particle destruction. Particles are also traded among processors using MPI calls.
A tetrahedron-based inhomogeneous Monte Carlo optical simulator.
Shen, H; Wang, G
2010-02-21
Optical imaging has been widely applied in preclinical and clinical applications. Fifteen years ago, an efficient Monte Carlo program 'MCML' was developed for use with multi-layered turbid media and has gained popularity in the field of biophotonics. Currently, there is an increasingly pressing need for simulating tools more powerful than MCML in order to study light propagation phenomena in complex inhomogeneous objects, such as the mouse. Here we report a tetrahedron-based inhomogeneous Monte Carlo optical simulator (TIM-OS) to address this issue. By modeling an object as a tetrahedron-based inhomogeneous finite-element mesh, TIM-OS can determine the photon-triangle interaction recursively and rapidly. In numerical simulation, we have demonstrated the correctness and efficiency of TIM-OS.
A tetrahedron-based inhomogeneous Monte Carlo optical simulator
Shen, H; Wang, G
2010-01-01
Optical imaging has been widely applied in preclinical and clinical applications. Fifteen years ago, an efficient Monte Carlo program ‘MCML’ was developed for use with multi-layered turbid media and has gained popularity in the field of biophotonics. Currently, there is an increasingly pressing need for simulating tools more powerful than MCML in order to study light propagation phenomena in complex inhomogeneous objects, such as the mouse. Here we report a tetrahedron-based inhomogeneous Monte Carlo optical simulator (TIM-OS) to address this issue. By modeling an object as a tetrahedron-based inhomogeneous finite-element mesh, TIM-OS can determine the photon– triangle interaction recursively and rapidly. In numerical simulation, we have demonstrated the correctness and efficiency of TIM-OS. PMID:20090182
Kalos, M.
2006-05-09
The Monte Carlo example programs VARHATOM and DMCATOM are two small, simple FORTRAN programs that illustrate the use of the Monte Carlo Mathematical technique for calculating the ground state energy of the hydrogen atom.
Quantitative Monte Carlo-based holmium-166 SPECT reconstruction.
Elschot, Mattijs; Smits, Maarten L J; Nijsen, Johannes F W; Lam, Marnix G E H; Zonnenberg, Bernard A; van den Bosch, Maurice A A J; Viergever, Max A; de Jong, Hugo W A M
2013-11-01
Quantitative imaging of the radionuclide distribution is of increasing interest for microsphere radioembolization (RE) of liver malignancies, to aid treatment planning and dosimetry. For this purpose, holmium-166 ((166)Ho) microspheres have been developed, which can be visualized with a gamma camera. The objective of this work is to develop and evaluate a new reconstruction method for quantitative (166)Ho SPECT, including Monte Carlo-based modeling of photon contributions from the full energy spectrum. A fast Monte Carlo (MC) simulator was developed for simulation of (166)Ho projection images and incorporated in a statistical reconstruction algorithm (SPECT-fMC). Photon scatter and attenuation for all photons sampled from the full (166)Ho energy spectrum were modeled during reconstruction by Monte Carlo simulations. The energy- and distance-dependent collimator-detector response was modeled using precalculated convolution kernels. Phantom experiments were performed to quantitatively evaluate image contrast, image noise, count errors, and activity recovery coefficients (ARCs) of SPECT-fMC in comparison with those of an energy window-based method for correction of down-scattered high-energy photons (SPECT-DSW) and a previously presented hybrid method that combines MC simulation of photopeak scatter with energy window-based estimation of down-scattered high-energy contributions (SPECT-ppMC+DSW). Additionally, the impact of SPECT-fMC on whole-body recovered activities (A(est)) and estimated radiation absorbed doses was evaluated using clinical SPECT data of six (166)Ho RE patients. At the same noise level, SPECT-fMC images showed substantially higher contrast than SPECT-DSW and SPECT-ppMC+DSW in spheres ≥ 17 mm in diameter. The count error was reduced from 29% (SPECT-DSW) and 25% (SPECT-ppMC+DSW) to 12% (SPECT-fMC). ARCs in five spherical volumes of 1.96-106.21 ml were improved from 32%-63% (SPECT-DSW) and 50%-80% (SPECT-ppMC+DSW) to 76%-103% (SPECT-fMC). Furthermore
Monte Carlo based analysis of confocal peak extraction uncertainty
NASA Astrophysics Data System (ADS)
Liu, Chenguang; Liu, Yan; Zheng, Tingting; Tan, Jiubin; Liu, Jian
2017-10-01
Localisation of axial peaks is essential for height determination in confocal microscopy. Several algorithms have been proposed for reliable height extraction in surface topography measurements. However, most of these algorithms use nonlinear processing, which precludes estimating the peak height uncertainty. A Monte Carlo based standard uncertainty analysis model is developed here to evaluate the precision of height extraction algorithms. The key parameters of this model are the vertical sampling deviation and the size of the scanning pitch. Height extraction uncertainty of the centroid algorithm and nonlinear fitting algorithms were calculated using simulations. Our results offer a reference for selecting algorithms for confocal metrology.
Hamiltonian Monte Carlo acceleration using surrogate functions with random bases.
Zhang, Cheng; Shahbaba, Babak; Zhao, Hongkai
2017-11-01
For big data analysis, high computational cost for Bayesian methods often limits their applications in practice. In recent years, there have been many attempts to improve computational efficiency of Bayesian inference. Here we propose an efficient and scalable computational technique for a state-of-the-art Markov chain Monte Carlo methods, namely, Hamiltonian Monte Carlo. The key idea is to explore and exploit the structure and regularity in parameter space for the underlying probabilistic model to construct an effective approximation of its geometric properties. To this end, we build a surrogate function to approximate the target distribution using properly chosen random bases and an efficient optimization process. The resulting method provides a flexible, scalable, and efficient sampling algorithm, which converges to the correct target distribution. We show that by choosing the basis functions and optimization process differently, our method can be related to other approaches for the construction of surrogate functions such as generalized additive models or Gaussian process models. Experiments based on simulated and real data show that our approach leads to substantially more efficient sampling algorithms compared to existing state-of-the-art methods.
Quantitative Monte Carlo-based holmium-166 SPECT reconstruction
Elschot, Mattijs; Smits, Maarten L. J.; Nijsen, Johannes F. W.; Lam, Marnix G. E. H.; Zonnenberg, Bernard A.; Bosch, Maurice A. A. J. van den; Jong, Hugo W. A. M. de; Viergever, Max A.
2013-11-15
Purpose: Quantitative imaging of the radionuclide distribution is of increasing interest for microsphere radioembolization (RE) of liver malignancies, to aid treatment planning and dosimetry. For this purpose, holmium-166 ({sup 166}Ho) microspheres have been developed, which can be visualized with a gamma camera. The objective of this work is to develop and evaluate a new reconstruction method for quantitative {sup 166}Ho SPECT, including Monte Carlo-based modeling of photon contributions from the full energy spectrum.Methods: A fast Monte Carlo (MC) simulator was developed for simulation of {sup 166}Ho projection images and incorporated in a statistical reconstruction algorithm (SPECT-fMC). Photon scatter and attenuation for all photons sampled from the full {sup 166}Ho energy spectrum were modeled during reconstruction by Monte Carlo simulations. The energy- and distance-dependent collimator-detector response was modeled using precalculated convolution kernels. Phantom experiments were performed to quantitatively evaluate image contrast, image noise, count errors, and activity recovery coefficients (ARCs) of SPECT-fMC in comparison with those of an energy window-based method for correction of down-scattered high-energy photons (SPECT-DSW) and a previously presented hybrid method that combines MC simulation of photopeak scatter with energy window-based estimation of down-scattered high-energy contributions (SPECT-ppMC+DSW). Additionally, the impact of SPECT-fMC on whole-body recovered activities (A{sup est}) and estimated radiation absorbed doses was evaluated using clinical SPECT data of six {sup 166}Ho RE patients.Results: At the same noise level, SPECT-fMC images showed substantially higher contrast than SPECT-DSW and SPECT-ppMC+DSW in spheres ≥17 mm in diameter. The count error was reduced from 29% (SPECT-DSW) and 25% (SPECT-ppMC+DSW) to 12% (SPECT-fMC). ARCs in five spherical volumes of 1.96–106.21 ml were improved from 32%–63% (SPECT-DSW) and 50%–80
Radiotherapy treatment planning based on Monte Carlo techniques
NASA Astrophysics Data System (ADS)
Juste, Belén; Miró, Rafael; Campayo, Juan M.; Díez, Sergio; Verdú, Gumersindo
2010-07-01
At the present, treatment planning systems (TPS) used in radiotherapy treatments use determinist correlations based on measurements in water to evaluate doses in the volume of interest and dose distributions around it. Nevertheless, it is well known that doses assigned with this type of planner can be problematic, especially in the presence of heterogeneities. The present work has developed a computational model using the Monte Carlo (MC) code MCNP5 (Monte Carlo N-Particle) for the simulation of a 6 MeV photon beam emitted by Elekta Precise medical linear accelerator treatment head. The model includes the major components of the accelerator head and the cube-shaped heterogeneous water tank " RFA-300". A low-density heterogeneity has been placed inside this water tank. It consists of a extruded polystyrene piece (97% air and 3% polystyrene) whose dimensions are 30 cm×10 cm×8 cm and with a density of 0.0311 g/cm 3. Calculations were performed for a photon beam setting 10 cm×10 cm and 20 cm×20 cm irradiation field sizes at 100 cm distance from source. The MC simulation is able to predict the absorbed dose distribution within the water tank using the *F8 or FMESH4 tally. These results have been compared with experimental values measured at the Hospital Clínic Universitari de Valencia. Dosimetric parameters calculated by simulation at the water tank and the experimental measures agreed, with an average deviation inside the heterogeneity region of 3%. Simulation results have been also compared with dose curves predicted by a commercial TPS in the same irradiation conditions, focusing attention on the accuracy that both systems reach in the dose calculation at the interphase zone and inside the heterogeneity. In contrast, TPS results overestimate the dose inside the heterogeneity and after it, with a maximum deviation of 7% for the 6 MeV photon beam and a field size of 20 cm×20 cm. We can conclude that the algorithms of computation of the TPS are not able to predict
Image based Monte Carlo Modeling for Computational Phantom
NASA Astrophysics Data System (ADS)
Cheng, Mengyun; Wang, Wen; Zhao, Kai; Fan, Yanchang; Long, Pengcheng; Wu, Yican
2014-06-01
The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verfication of the models for Monte carlo(MC)simulation are very tedious, error-prone and time-consuming. In addiation, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling by FDS Team (Advanced Nuclear Energy Research Team, http://www.fds.org.cn). The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients(Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection.
Parameterizations for shielding electron accelerators based on Monte Carlo studies
P. Degtyarenko; G. Stapleton
1996-10-01
Numerous recipes for designing lateral slab neutron shielding for electron accelerators are available and each generally produces rather similar results for shield thicknesses of about 2 m of concrete and for electron beams with energy in the 1 to 10 GeV region. For thinner or much thicker shielding the results tend to diverge and the standard recipes require modification. Likewise for geometries other than lateral to the beam direction further corrections are required so that calculated results are less reliable and hence additional and costly conservatism is needed. With the adoption of Monte Carlo (MC) methods of transporting particles a much more powerful way of calculating radiation dose rates outside shielding becomes available. This method is not constrained by geometry, although deep penetration problems need special statistical treatment, and is an excellent approach to solving any radiation transport problem providing the method has been properly checked against measurements and is free from the well known errors common to such computer methods. This present paper utilizes the results of MC calculations based on a nuclear fragmentation model named DINREG using the MC transport code GEANT and models them with the normal two parameter shielding expressions. Because the parameters can change with electron beam energy, angle to the electron beam direction and target material, the parameters are expressed as functions of some of these variables to provide a universal equations for shielding electron beams which can used rather simply for deep penetration problems in simple geometry without the time consuming computations needed in the original MC programs. A particular problem with using simple parameterizations based on the uncollided flux is that approximations based on spherical geometry might not apply to the more common cylindrical cases used for accelerator shielding. This source of error has been discussed at length by Stevenson and others. To study
Monte Carlo fluorescence microtomography
NASA Astrophysics Data System (ADS)
Cong, Alexander X.; Hofmann, Matthias C.; Cong, Wenxiang; Xu, Yong; Wang, Ge
2011-07-01
Fluorescence microscopy allows real-time monitoring of optical molecular probes for disease characterization, drug development, and tissue regeneration. However, when a biological sample is thicker than 1 mm, intense scattering of light would significantly degrade the spatial resolution of fluorescence microscopy. In this paper, we develop a fluorescence microtomography technique that utilizes the Monte Carlo method to image fluorescence reporters in thick biological samples. This approach is based on an l0-regularized tomography model and provides an excellent solution. Our studies on biomimetic tissue scaffolds have demonstrated that the proposed approach is capable of localizing and quantifying the distribution of optical molecular probe accurately and reliably.
An empirical formula based on Monte Carlo simulation for diffuse reflectance from turbid media
NASA Astrophysics Data System (ADS)
Gnanatheepam, Einstein; Aruna, Prakasa Rao; Ganesan, Singaravelu
2016-03-01
Diffuse reflectance spectroscopy has been widely used in diagnostic oncology and characterization of laser irradiated tissue. However, still accurate and simple analytical equation does not exist for estimation of diffuse reflectance from turbid media. In this work, a diffuse reflectance lookup table for a range of tissue optical properties was generated using Monte Carlo simulation. Based on the generated Monte Carlo lookup table, an empirical formula for diffuse reflectance was developed using surface fitting method. The variance between the Monte Carlo lookup table surface and the surface obtained from the proposed empirical formula is less than 1%. The proposed empirical formula may be used for modeling of diffuse reflectance from tissue.
Jiang, Xu; Deng, Yong; Luo, Zhaoyang; Wang, Kan; Lian, Lichao; Yang, Xiaoquan; Meglinski, Igor; Luo, Qingming
2014-12-29
The path-history-based fluorescence Monte Carlo method used for fluorescence tomography imaging reconstruction has attracted increasing attention. In this paper, we first validate the standard fluorescence Monte Carlo (sfMC) method by experimenting with a cylindrical phantom. Then, we describe a path-history-based decoupled fluorescence Monte Carlo (dfMC) method, analyze different perturbation fluorescence Monte Carlo (pfMC) methods, and compare the calculation accuracy and computational efficiency of the dfMC and pfMC methods using the sfMC method as a reference. The results show that the dfMC method is more accurate and efficient than the pfMC method in heterogeneous medium.
Monte Carlo-based simulation of dynamic jaws tomotherapy
Sterpin, E.; Chen, Y.; Chen, Q.; Lu, W.; Mackie, T. R.; Vynckier, S.
2011-09-15
Purpose: Original TomoTherapy systems may involve a trade-off between conformity and treatment speed, the user being limited to three slice widths (1.0, 2.5, and 5.0 cm). This could be overcome by allowing the jaws to define arbitrary fields, including very small slice widths (<1 cm), which are challenging for a beam model. The aim of this work was to incorporate the dynamic jaws feature into a Monte Carlo (MC) model called TomoPen, based on the MC code PENELOPE, previously validated for the original TomoTherapy system. Methods: To keep the general structure of TomoPen and its efficiency, the simulation strategy introduces several techniques: (1) weight modifiers to account for any jaw settings using only the 5 cm phase-space file; (2) a simplified MC based model called FastStatic to compute the modifiers faster than pure MC; (3) actual simulation of dynamic jaws. Weight modifiers computed with both FastStatic and pure MC were compared. Dynamic jaws simulations were compared with the convolution/superposition (C/S) of TomoTherapy in the ''cheese'' phantom for a plan with two targets longitudinally separated by a gap of 3 cm. Optimization was performed in two modes: asymmetric jaws-constant couch speed (''running start stop,'' RSS) and symmetric jaws-variable couch speed (''symmetric running start stop,'' SRSS). Measurements with EDR2 films were also performed for RSS for the formal validation of TomoPen with dynamic jaws. Results: Weight modifiers computed with FastStatic were equivalent to pure MC within statistical uncertainties (0.5% for three standard deviations). Excellent agreement was achieved between TomoPen and C/S for both asymmetric jaw opening/constant couch speed and symmetric jaw opening/variable couch speed, with deviations well within 2%/2 mm. For RSS procedure, agreement between C/S and measurements was within 2%/2 mm for 95% of the points and 3%/3 mm for 98% of the points, where dose is greater than 30% of the prescription dose (gamma analysis
Applying diffusion-based Markov chain Monte Carlo
Paul, Rajib; Berliner, L. Mark
2017-01-01
We examine the performance of a strategy for Markov chain Monte Carlo (MCMC) developed by simulating a discrete approximation to a stochastic differential equation (SDE). We refer to the approach as diffusion MCMC. A variety of motivations for the approach are reviewed in the context of Bayesian analysis. In particular, implementation of diffusion MCMC is very simple to set-up, even in the presence of nonlinear models and non-conjugate priors. Also, it requires comparatively little problem-specific tuning. We implement the algorithm and assess its performance for both a test case and a glaciological application. Our results demonstrate that in some settings, diffusion MCMC is a faster alternative to a general Metropolis-Hastings algorithm. PMID:28301529
Johannesson, G; Chow, F K; Glascoe, L; Glaser, R E; Hanley, W G; Kosovic, B; Krnjajic, M; Larsen, S C; Lundquist, J K; Mirin, A A; Nitao, J J; Sugiyama, G A
2005-11-16
Atmospheric releases of hazardous materials are highly effective means to impact large populations. We propose an atmospheric event reconstruction framework that couples observed data and predictive computer-intensive dispersion models via Bayesian methodology. Due to the complexity of the model framework, a sampling-based approach is taken for posterior inference that combines Markov chain Monte Carlo (MCMC) and sequential Monte Carlo (SMC) strategies.
A study on tetrahedron-based inhomogeneous Monte Carlo optical simulation.
Shen, Haiou; Wang, Ge
2010-12-03
Monte Carlo (MC) simulation is widely recognized as a gold standard in biophotonics for its high accuracy. Here we analyze several issues associated with tetrahedron-based optical Monte Carlo simulation in the context of TIM-OS, MMCM, MCML, and CUDAMCML in terms of accuracy and efficiency. Our results show that TIM-OS has significant better performance in the complex geometry cases and has comparable performance with CUDAMCML in the multi-layered tissue model.
NASA Technical Reports Server (NTRS)
Everson, John; Nelson, H. F.
1993-01-01
A reverse Monte Carlo radiative transfer code to predict rocket plume base heating is presented. In this technique rays representing the radiation propagation are traced backwards in time from the receiving surface to the point of emission in the plume. This increases the computational efficiency relative to the forward Monte Carlo technique when calculating the radiation reaching a specific point, as only the rays that strike the receiving point are considered.
A study on tetrahedron-based inhomogeneous Monte Carlo optical simulation
Shen, Haiou; Wang, Ge
2011-01-01
Monte Carlo (MC) simulation is widely recognized as a gold standard in biophotonics for its high accuracy. Here we analyze several issues associated with tetrahedron-based optical Monte Carlo simulation in the context of TIM-OS, MMCM, MCML, and CUDAMCML in terms of accuracy and efficiency. Our results show that TIM-OS has significant better performance in the complex geometry cases and has comparable performance with CUDAMCML in the multi-layered tissue model. PMID:21326634
Monte Carlo Reliability Analysis.
1987-10-01
to Stochastic Processes , Prentice-Hall, Englewood Cliffs, NJ, 1975. (5) R. E. Barlow and F. Proscham, Statistical TheorX of Reliability and Life...Lewis and Z. Tu, "Monte Carlo Reliability Modeling by Inhomogeneous ,Markov Processes, Reliab. Engr. 16, 277-296 (1986). (4) E. Cinlar, Introduction
Proton Upset Monte Carlo Simulation
NASA Technical Reports Server (NTRS)
O'Neill, Patrick M.; Kouba, Coy K.; Foster, Charles C.
2009-01-01
The Proton Upset Monte Carlo Simulation (PROPSET) program calculates the frequency of on-orbit upsets in computer chips (for given orbits such as Low Earth Orbit, Lunar Orbit, and the like) from proton bombardment based on the results of heavy ion testing alone. The software simulates the bombardment of modern microelectronic components (computer chips) with high-energy (.200 MeV) protons. The nuclear interaction of the proton with the silicon of the chip is modeled and nuclear fragments from this interaction are tracked using Monte Carlo techniques to produce statistically accurate predictions.
NASA Astrophysics Data System (ADS)
Li, Shengfu; Chen, Guanghua; Wang, Rongbo; Luo, Zhengxiong; Peng, Qixian
2016-12-01
This paper proposes a Monte Carlo (MC) based angular distribution estimation method of multiply scattered photons for underwater imaging. This method targets on turbid waters. Our method is based on applying typical Monte Carlo ideas to the present problem by combining all the points on a spherical surface. The proposed method is validated with the numerical solution of the radiative transfer equation (RTE). The simulation results based on typical optical parameters of turbid waters show that the proposed method is effective in terms of computational speed and sensitivity.
Wollaber, Allan Benton
2016-06-16
This is a powerpoint presentation which serves as lecture material for the Parallel Computing summer school. It goes over the fundamentals of the Monte Carlo calculation method. The material is presented according to the following outline: Introduction (background, a simple example: estimating π), Why does this even work? (The Law of Large Numbers, The Central Limit Theorem), How to sample (inverse transform sampling, rejection), and An example from particle transport.
Monte Carlo eikonal scattering
NASA Astrophysics Data System (ADS)
Gibbs, W. R.; Dedonder, J. P.
2012-08-01
Background: The eikonal approximation is commonly used to calculate heavy-ion elastic scattering. However, the full evaluation has only been done (without the use of Monte Carlo techniques or additional approximations) for α-α scattering.Purpose: Develop, improve, and test the Monte Carlo eikonal method for elastic scattering over a wide range of nuclei, energies, and angles.Method: Monte Carlo evaluation is used to calculate heavy-ion elastic scattering for heavy nuclei including the center-of-mass correction introduced in this paper and the Coulomb interaction in terms of a partial-wave expansion. A technique for the efficient expansion of the Glauber amplitude in partial waves is developed.Results: Angular distributions are presented for a number of nuclear pairs over a wide energy range using nucleon-nucleon scattering parameters taken from phase-shift analyses and densities from independent sources. We present the first calculations of the Glauber amplitude, without further approximation, and with realistic densities for nuclei heavier than helium. These densities respect the center-of-mass constraints. The Coulomb interaction is included in these calculations.Conclusion: The center-of-mass and Coulomb corrections are essential. Angular distributions can be predicted only up to certain critical angles which vary with the nuclear pairs and the energy, but we point out that all critical angles correspond to a momentum transfer near 1 fm-1.
Wormhole Hamiltonian Monte Carlo
Lan, Shiwei; Streets, Jeffrey; Shahbaba, Babak
2015-01-01
In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, especially when the dimension is high and the modes are isolated. To this end, it exploits and modifies the Riemannian geometric properties of the target distribution to create wormholes connecting modes in order to facilitate moving between them. Further, our proposed method uses the regeneration technique in order to adapt the algorithm by identifying new modes and updating the network of wormholes without affecting the stationary distribution. To find new modes, as opposed to redis-covering those previously identified, we employ a novel mode searching algorithm that explores a residual energy function obtained by subtracting an approximate Gaussian mixture density (based on previously discovered modes) from the target density function. PMID:25861551
Wormhole Hamiltonian Monte Carlo.
Lan, Shiwei; Streets, Jeffrey; Shahbaba, Babak
2014-07-31
In machine learning and statistics, probabilistic inference involving multimodal distributions is quite difficult. This is especially true in high dimensional problems, where most existing algorithms cannot easily move from one mode to another. To address this issue, we propose a novel Bayesian inference approach based on Markov Chain Monte Carlo. Our method can effectively sample from multimodal distributions, especially when the dimension is high and the modes are isolated. To this end, it exploits and modifies the Riemannian geometric properties of the target distribution to create wormholes connecting modes in order to facilitate moving between them. Further, our proposed method uses the regeneration technique in order to adapt the algorithm by identifying new modes and updating the network of wormholes without affecting the stationary distribution. To find new modes, as opposed to redis-covering those previously identified, we employ a novel mode searching algorithm that explores a residual energy function obtained by subtracting an approximate Gaussian mixture density (based on previously discovered modes) from the target density function.
A new Monte Carlo simulation model for laser transmission in smokescreen based on MATLAB
NASA Astrophysics Data System (ADS)
Lee, Heming; Wang, Qianqian; Shan, Bin; Li, Xiaoyang; Gong, Yong; Zhao, Jing; Peng, Zhong
2016-11-01
A new Monte Carlo simulation model of laser transmission in smokescreen is promoted in this paper. In the traditional Monte Carlo simulation model, the radius of particles is set at the same value and the initial cosine value of photons direction is fixed also, which can only get the approximate result. The new model is achieved based on MATLAB and can simulate laser transmittance in smokescreen with different sizes of particles, and the output result of the model is close to the real scenarios. In order to alleviate the influence of the laser divergence while traveling in the air, we changed the initial direction cosine of photons on the basis of the traditional Monte Carlo model. The mixed radius particle smoke simulation results agree with the measured transmittance under the same experimental conditions with 5.42% error rate.
Sampling uncertainty evaluation for data acquisition board based on Monte Carlo method
NASA Astrophysics Data System (ADS)
Ge, Leyi; Wang, Zhongyu
2008-10-01
Evaluating the data acquisition board sampling uncertainty is a difficult problem in the field of signal sampling. This paper analyzes the sources of dada acquisition board sampling uncertainty in the first, then introduces a simulation theory of dada acquisition board sampling uncertainty evaluation based on Monte Carlo method and puts forward a relation model of sampling uncertainty results, sampling numbers and simulation times. In the case of different sample numbers and different signal scopes, the author establishes a random sampling uncertainty evaluation program of a PCI-6024E data acquisition board to execute the simulation. The results of the proposed Monte Carlo simulation method are in a good agreement with the GUM ones, and the validities of Monte Carlo method are represented.
Monte-Carlo based prediction of radiochromic film response for hadrontherapy dosimetry
NASA Astrophysics Data System (ADS)
Frisson, T.; Zahra, N.; Lautesse, P.; Sarrut, D.
2009-07-01
A model has been developed to calculate MD-55-V2 radiochromic film response to ion irradiation. This model is based on photon film response and film saturation by high local energy deposition computed by Monte-Carlo simulation. We have studied the response of the film to photon irradiation and we proposed a calculation method for hadron beams.
LMC: Logarithmantic Monte Carlo
NASA Astrophysics Data System (ADS)
Mantz, Adam B.
2017-06-01
LMC is a Markov Chain Monte Carlo engine in Python that implements adaptive Metropolis-Hastings and slice sampling, as well as the affine-invariant method of Goodman & Weare, in a flexible framework. It can be used for simple problems, but the main use case is problems where expensive likelihood evaluations are provided by less flexible third-party software, which benefit from parallelization across many nodes at the sampling level. The parallel/adaptive methods use communication through MPI, or alternatively by writing/reading files, and mostly follow the approaches pioneered by CosmoMC (ascl:1106.025).
Mosaicing of airborne LiDAR bathymetry strips based on Monte Carlo matching
NASA Astrophysics Data System (ADS)
Yang, Fanlin; Su, Dianpeng; Zhang, Kai; Ma, Yue; Wang, Mingwei; Yang, Anxiu
2017-09-01
This study proposes a new methodology for mosaicing airborne light detection and ranging (LiDAR) bathymetry (ALB) data based on Monte Carlo matching. Various errors occur in ALB data due to imperfect system integration and other interference factors. To account for these errors, a Monte Carlo matching algorithm based on a nonlinear least-squares adjustment model is proposed. First, the raw data of strip overlap areas were filtered according to their relative drift of depths. Second, a Monte Carlo model and nonlinear least-squares adjustment model were combined to obtain seven transformation parameters. Then, the multibeam bathymetric data were used to correct the initial strip during strip mosaicing. Finally, to evaluate the proposed method, the experimental results were compared with the results of the Iterative Closest Points (ICP) and three-dimensional Normal Distributions Transform (3D-NDT) algorithms. The results demonstrate that the algorithm proposed in this study is more robust and effective. When the quality of the raw data is poor, the Monte Carlo matching algorithm can still achieve centimeter-level accuracy for overlapping areas, which meets the accuracy of bathymetry required by IHO Standards for Hydrographic Surveys Special Publication No.44.
A measurement-based generalized source model for Monte Carlo dose simulations of CT scans
NASA Astrophysics Data System (ADS)
Ming, Xin; Feng, Yuanming; Liu, Ransheng; Yang, Chengwen; Zhou, Li; Zhai, Hezheng; Deng, Jun
2017-03-01
The goal of this study is to develop a generalized source model for accurate Monte Carlo dose simulations of CT scans based solely on the measurement data without a priori knowledge of scanner specifications. The proposed generalized source model consists of an extended circular source located at x-ray target level with its energy spectrum, source distribution and fluence distribution derived from a set of measurement data conveniently available in the clinic. Specifically, the central axis percent depth dose (PDD) curves measured in water and the cone output factors measured in air were used to derive the energy spectrum and the source distribution respectively with a Levenberg-Marquardt algorithm. The in-air film measurement of fan-beam dose profiles at fixed gantry was back-projected to generate the fluence distribution of the source model. A benchmarked Monte Carlo user code was used to simulate the dose distributions in water with the developed source model as beam input. The feasibility and accuracy of the proposed source model was tested on a GE LightSpeed and a Philips Brilliance Big Bore multi-detector CT (MDCT) scanners available in our clinic. In general, the Monte Carlo simulations of the PDDs in water and dose profiles along lateral and longitudinal directions agreed with the measurements within 4%/1 mm for both CT scanners. The absolute dose comparison using two CTDI phantoms (16 cm and 32 cm in diameters) indicated a better than 5% agreement between the Monte Carlo-simulated and the ion chamber-measured doses at a variety of locations for the two scanners. Overall, this study demonstrated that a generalized source model can be constructed based only on a set of measurement data and used for accurate Monte Carlo dose simulations of patients’ CT scans, which would facilitate patient-specific CT organ dose estimation and cancer risk management in the diagnostic and therapeutic radiology.
Womersley, J. . Dept. of Physics)
1992-10-01
The D0 detector at the Fermilab Tevatron began its first data taking run in May 1992. For analysis of the expected 25 pb[sup [minus]1] data sample, roughly half a million simulated events will be needed. The GEANT-based Monte Carlo program used to generate these events is described, together with comparisons to test beam data. Some novel techniques used to speed up execution and simplify geometrical input are described.
Compressible generalized hybrid Monte Carlo
NASA Astrophysics Data System (ADS)
Fang, Youhan; Sanz-Serna, J. M.; Skeel, Robert D.
2014-05-01
One of the most demanding calculations is to generate random samples from a specified probability distribution (usually with an unknown normalizing prefactor) in a high-dimensional configuration space. One often has to resort to using a Markov chain Monte Carlo method, which converges only in the limit to the prescribed distribution. Such methods typically inch through configuration space step by step, with acceptance of a step based on a Metropolis(-Hastings) criterion. An acceptance rate of 100% is possible in principle by embedding configuration space in a higher dimensional phase space and using ordinary differential equations. In practice, numerical integrators must be used, lowering the acceptance rate. This is the essence of hybrid Monte Carlo methods. Presented is a general framework for constructing such methods under relaxed conditions: the only geometric property needed is (weakened) reversibility; volume preservation is not needed. The possibilities are illustrated by deriving a couple of explicit hybrid Monte Carlo methods, one based on barrier-lowering variable-metric dynamics and another based on isokinetic dynamics.
Kalos, M. H.; Pederiva, F.
1998-12-01
We review the fundamental challenge of fermion Monte Carlo for continuous systems, the "sign problem". We seek that eigenfunction of the many-body Schriodinger equation that is antisymmetric under interchange of the coordinates of pairs of particles. We describe methods that depend upon the use of correlated dynamics for pairs of correlated walkers that carry opposite signs. There is an algorithmic symmetry between such walkers that must be broken to create a method that is both exact and as effective as for symmetric functions, In our new method, it is broken by using different "guiding" functions for walkers of opposite signs, and a geometric correlation between steps of their walks, With a specific process of cancellation of the walkers, overlaps with antisymmetric test functions are preserved. Finally, we describe the progress in treating free-fermion systems and a fermion fluid with 14 ^{3}He atoms.
Marcus, Ryan C.
2012-07-25
MCMini is a proof of concept that demonstrates the possibility for Monte Carlo neutron transport using OpenCL with a focus on performance. This implementation, written in C, shows that tracing particles and calculating reactions on a 3D mesh can be done in a highly scalable fashion. These results demonstrate a potential path forward for MCNP or other Monte Carlo codes.
Effects of CT based Voxel Phantoms on Dose Distribution Calculated with Monte Carlo Method
NASA Astrophysics Data System (ADS)
Chen, Chaobin; Huang, Qunying; Wu, Yican
2005-04-01
A few CT-based voxel phantoms were produced to investigate the sensitivity of Monte Carlo simulations of x-ray beam and electron beam to the proportions of elements and the mass densities of the materials used to express the patient's anatomical structure. The human body can be well outlined by air, lung, adipose, muscle, soft bone and hard bone to calculate the dose distribution with Monte Carlo method. The effects of the calibration curves established by using various CT scanners are not clinically significant based on our investigation. The deviation from the values of cumulative dose volume histogram derived from CT-based voxel phantoms is less than 1% for the given target.
In silico prediction of the β-cyclodextrin complexation based on Monte Carlo method.
Veselinović, Aleksandar M; Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M
2015-11-10
In this study QSPR models were developed to predict the complexation of structurally diverse compounds with β-cyclodextrin based on SMILES notation optimal descriptors using Monte Carlo method. The predictive potential of the applied approach was tested with three random splits into the sub-training, calibration, test and validation sets and with different statistical methods. Obtained results demonstrate that Monte Carlo method based modeling is a very promising computational method in the QSPR studies for predicting the complexation of structurally diverse compounds with β-cyclodextrin. The SMILES attributes (structural features both local and global), defined as molecular fragments, which are promoters of the increase/decrease of molecular binding constants were identified. These structural features were correlated to the complexation process and their identification helped to improve the understanding for the complexation mechanisms of the host molecules. Copyright © 2015 Elsevier B.V. All rights reserved.
Willert, Jeffrey Park, H.
2014-11-01
In this article we explore the possibility of replacing Standard Monte Carlo (SMC) transport sweeps within a Moment-Based Accelerated Thermal Radiative Transfer (TRT) algorithm with a Residual Monte Carlo (RMC) formulation. Previous Moment-Based Accelerated TRT implementations have encountered trouble when stochastic noise from SMC transport sweeps accumulates over several iterations and pollutes the low-order system. With RMC we hope to significantly lower the build-up of statistical error at a much lower cost. First, we display encouraging results for a zero-dimensional test problem. Then, we demonstrate that we can achieve a lower degree of error in two one-dimensional test problems by employing an RMC transport sweep with multiple orders of magnitude fewer particles per sweep. We find that by reformulating the high-order problem, we can compute more accurate solutions at a fraction of the cost.
Monte Carlo Method for Predicting a Physically Based Drop Size Distribution Evolution of a Spray
NASA Astrophysics Data System (ADS)
Tembely, Moussa; Lécot, Christian; Soucemarianadin, Arthur
2010-03-01
We report in this paper a method for predicting the evolution of a physically based drop size distribution of a spray, by coupling the Maximum Entropy Formalism and the Monte Carlo scheme. Using the discrete or continuous population balance equation, a Mass Flow Algorithm is formulated taking into account interactions between droplets via coalescence. After deriving a kernel for coalescence, we solve the time dependent drop size distribution equation using a Monte Carlo method. We apply the method to the spray of a new print-head known as a Spray On Demand (SOD) device; the process exploits ultrasonic spray generation via a Faraday instability where the fluid/structure interaction causing the instability is described by a modified Hamilton's principle. This has led to a physically-based approach for predicting the initial drop size distribution within the framework of the Maximum Entropy Formalism (MEF): a three-parameter generalized Gamma distribution is chosen by using conservation of mass and energy. The calculation of the drop size distribution evolution by Monte Carlo method shows the effect of spray droplets coalescence both on the number-based or volume-based drop size distributions.
Monte Carlo Methods in Materials Science Based on FLUKA and ROOT
NASA Technical Reports Server (NTRS)
Pinsky, Lawrence; Wilson, Thomas; Empl, Anton; Andersen, Victor
2003-01-01
A comprehensive understanding of mitigation measures for space radiation protection necessarily involves the relevant fields of nuclear physics and particle transport modeling. One method of modeling the interaction of radiation traversing matter is Monte Carlo analysis, a subject that has been evolving since the very advent of nuclear reactors and particle accelerators in experimental physics. Countermeasures for radiation protection from neutrons near nuclear reactors, for example, were an early application and Monte Carlo methods were quickly adapted to this general field of investigation. The project discussed here is concerned with taking the latest tools and technology in Monte Carlo analysis and adapting them to space applications such as radiation shielding design for spacecraft, as well as investigating how next-generation Monte Carlos can complement the existing analytical methods currently used by NASA. We have chosen to employ the Monte Carlo program known as FLUKA (A legacy acronym based on the German for FLUctuating KAscade) used to simulate all of the particle transport, and the CERN developed graphical-interface object-oriented analysis software called ROOT. One aspect of space radiation analysis for which the Monte Carlo s are particularly suited is the study of secondary radiation produced as albedoes in the vicinity of the structural geometry involved. This broad goal of simulating space radiation transport through the relevant materials employing the FLUKA code necessarily requires the addition of the capability to simulate all heavy-ion interactions from 10 MeV/A up to the highest conceivable energies. For all energies above 3 GeV/A the Dual Parton Model (DPM) is currently used, although the possible improvement of the DPMJET event generator for energies 3-30 GeV/A is being considered. One of the major tasks still facing us is the provision for heavy ion interactions below 3 GeV/A. The ROOT interface is being developed in conjunction with the
Determination of the spatial response of neutron based analysers using a Monte Carlo based method
Tickner
2000-10-01
One of the principal advantages of using thermal neutron capture (TNC, also called prompt gamma neutron activation analysis or PGNAA) or neutron inelastic scattering (NIS) techniques for measuring elemental composition is the high penetrating power of both the incident neutrons and the resultant gamma-rays, which means that large sample volumes can be interrogated. Gauges based on these techniques are widely used in the mineral industry for on-line determination of the composition of bulk samples. However, attenuation of both neutrons and gamma-rays in the sample and geometric (source/detector distance) effects typically result in certain parts of the sample contributing more to the measured composition than others. In turn, this introduces errors in the determination of the composition of inhomogeneous samples. This paper discusses a combined Monte Carlo/analytical method for estimating the spatial response of a neutron gauge. Neutron propagation is handled using a Monte Carlo technique which allows an arbitrarily complex neutron source and gauge geometry to be specified. Gamma-ray production and detection is calculated analytically which leads to a dramatic increase in the efficiency of the method. As an example, the method is used to study ways of reducing the spatial sensitivity of on-belt composition measurements of cement raw meal.
NASA Astrophysics Data System (ADS)
Hu, Xingzhi; Chen, Xiaoqian; Parks, Geoffrey T.; Yao, Wen
2016-10-01
Ever-increasing demands of uncertainty-based design, analysis, and optimization in aerospace vehicles motivate the development of Monte Carlo methods with wide adaptability and high accuracy. This paper presents a comprehensive review of typical improved Monte Carlo methods and summarizes their characteristics to aid the uncertainty-based multidisciplinary design optimization (UMDO). Among them, Bayesian inference aims to tackle the problems with the availability of prior information like measurement data. Importance sampling (IS) settles the inconvenient sampling and difficult propagation through the incorporation of an intermediate importance distribution or sequential distributions. Optimized Latin hypercube sampling (OLHS) is a stratified sampling approach to achieving better space-filling and non-collapsing characteristics. Meta-modeling approximation based on Monte Carlo saves the computational cost by using cheap meta-models for the output response. All the reviewed methods are illustrated by corresponding aerospace applications, which are compared to show their techniques and usefulness in UMDO, thus providing a beneficial reference for future theoretical and applied research.
NASA Astrophysics Data System (ADS)
Shariatinasab, Reza; Tadayon, Pooya; Ametani, Akihiro
2016-07-01
This paper proposes a hybrid method for calculating lightning performance of overhead lines caused by direct strokes by combining Lattice diagram together with the Monte Carlo method. In order to go through this, firstly, the proper analytical relations for overvoltages calculation are established based on Lattice diagram. Then, the Monte Carlo procedure is applied to the obtained analytical relations. The aim of the presented method that will be called `ML method' is simply estimation of the lightning performance of the overhead lines and performing the risk analysis of power apparatus with retaining the acceptable accuracy. To confirm the accuracy, the calculated results of the presented ML method are compared with those calculated by the EMTP/ATP simulation.
Electron density of states of Fe-based superconductors: Quantum trajectory Monte Carlo method
NASA Astrophysics Data System (ADS)
Kashurnikov, V. A.; Krasavin, A. V.; Zhumagulov, Ya. V.
2016-03-01
The spectral and total electron densities of states in two-dimensional FeAs clusters, which simulate iron-based superconductors, have been calculated using the generalized quantum Monte Carlo algorithm within the full two-orbital model. Spectra have been reconstructed by solving the integral equation relating the Matsubara Green's function and spectral density by the method combining the gradient descent and Monte Carlo algorithms. The calculations have been performed for clusters with dimensions up to 10 × 10 FeAs cells. The profiles of the Fermi surface for the entire Brillouin zone have been presented in the quasiparticle approximation. Data for the total density of states near the Fermi level have been obtained. The effect of the interaction parameter, size of the cluster, and temperature on the spectrum of excitations has been studied.
NASA Astrophysics Data System (ADS)
Einstein, Gnanatheepam; Udayakumar, Kanniyappan; Aruna, Prakasarao; Ganesan, Singaravelu
2017-03-01
Fluorescence of Protein has been widely used in diagnostic oncology for characterizing cellular metabolism. However, the intensity of fluorescence emission is affected due to the absorbers and scatterers in tissue, which may lead to error in estimating exact protein content in tissue. Extraction of intrinsic fluorescence from measured fluorescence has been achieved by different methods. Among them, Monte Carlo based method yields the highest accuracy for extracting intrinsic fluorescence. In this work, we have attempted to generate a lookup table for Monte Carlo simulation of fluorescence emission by protein. Furthermore, we fitted the generated lookup table using an empirical relation. The empirical relation between measured and intrinsic fluorescence is validated using tissue phantom experiments. The proposed relation can be used for estimating intrinsic fluorescence of protein for real-time diagnostic applications and thereby improving the clinical interpretation of fluorescence spectroscopic data.
GPU-accelerated Monte Carlo simulation of particle coagulation based on the inverse method
NASA Astrophysics Data System (ADS)
Wei, J.; Kruis, F. E.
2013-09-01
Simulating particle coagulation using Monte Carlo methods is in general a challenging computational task due to its numerical complexity and the computing cost. Currently, the lowest computing costs are obtained when applying a graphic processing unit (GPU) originally developed for speeding up graphic processing in the consumer market. In this article we present an implementation of accelerating a Monte Carlo method based on the Inverse scheme for simulating particle coagulation on the GPU. The abundant data parallelism embedded within the Monte Carlo method is explained as it will allow an efficient parallelization of the MC code on the GPU. Furthermore, the computation accuracy of the MC on GPU was validated with a benchmark, a CPU-based discrete-sectional method. To evaluate the performance gains by using the GPU, the computing time on the GPU against its sequential counterpart on the CPU were compared. The measured speedups show that the GPU can accelerate the execution of the MC code by a factor 10-100, depending on the chosen particle number of simulation particles. The algorithm shows a linear dependence of computing time with the number of simulation particles, which is a remarkable result in view of the n2 dependence of the coagulation.
Quantum Gibbs ensemble Monte Carlo
Fantoni, Riccardo; Moroni, Saverio
2014-09-21
We present a path integral Monte Carlo method which is the full quantum analogue of the Gibbs ensemble Monte Carlo method of Panagiotopoulos to study the gas-liquid coexistence line of a classical fluid. Unlike previous extensions of Gibbs ensemble Monte Carlo to include quantum effects, our scheme is viable even for systems with strong quantum delocalization in the degenerate regime of temperature. This is demonstrated by an illustrative application to the gas-superfluid transition of {sup 4}He in two dimensions.
Quantum Monte Carlo for Molecules.
1984-11-01
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Error in Monte Carlo, quasi-error in Quasi-Monte Carlo
NASA Astrophysics Data System (ADS)
Kleiss, Ronald; Lazopoulos, Achilleas
2006-07-01
While the Quasi-Monte Carlo method of numerical integration achieves smaller integration error than standard Monte Carlo, its use in particle physics phenomenology has been hindered by the absence of a reliable way to estimate that error. The standard Monte Carlo error estimator relies on the assumption that the points are generated independently of each other and, therefore, fails to account for the error improvement advertised by the Quasi-Monte Carlo method. We advocate the construction of an estimator of stochastic nature, based on the ensemble of pointsets with a particular discrepancy value. We investigate the consequences of this choice and give some first empirical results on the suggested estimators.
NASA Astrophysics Data System (ADS)
Fasnacht, Marc
We develop adaptive Monte Carlo methods for the calculation of the free energy as a function of a parameter of interest. The methods presented are particularly well-suited for systems with complex energy landscapes, where standard sampling techniques have difficulties. The Adaptive Histogram Method uses a biasing potential derived from histograms recorded during the simulation to achieve uniform sampling in the parameter of interest. The Adaptive Integration method directly calculates an estimate of the free energy from the average derivative of the Hamiltonian with respect to the parameter of interest and uses it as a biasing potential. We compare both methods to a state of the art method, and demonstrate that they compare favorably for the calculation of potentials of mean force of dense Lennard-Jones fluids. We use the Adaptive Integration Method to calculate accurate potentials of mean force for different types of simple particles in a Lennard-Jones fluid. Our approach allows us to separate the contributions of the solvent to the potential of mean force from the effect of the direct interaction between the particles. With contributions of the solvent determined, we can find the potential of mean force directly for any other direct interaction without additional simulations. We also test the accuracy of the Adaptive Integration Method on a thermodynamic cycle, which allows us to perform a consistency check between potentials of mean force and chemical potentials calculated using the Adaptive Integration Method. The results demonstrate a high degree of consistency of the method.
Tennant, Marc; Kruger, Estie
2013-02-01
This study developed a Monte Carlo simulation approach to examining the prevalence and incidence of dental decay using Australian children as a test environment. Monte Carlo simulation has been used for a half a century in particle physics (and elsewhere); put simply, it is the probability for various population-level outcomes seeded randomly to drive the production of individual level data. A total of five runs of the simulation model for all 275,000 12-year-olds in Australia were completed based on 2005-2006 data. Measured on average decayed/missing/filled teeth (DMFT) and DMFT of highest 10% of sample (Sic10) the runs did not differ from each other by more than 2% and the outcome was within 5% of the reported sampled population data. The simulations rested on the population probabilities that are known to be strongly linked to dental decay, namely, socio-economic status and Indigenous heritage. Testing the simulated population found DMFT of all cases where DMFT<>0 was 2.3 (n = 128,609) and DMFT for Indigenous cases only was 1.9 (n = 13,749). In the simulation population the Sic25 was 3.3 (n = 68,750). Monte Carlo simulations were created in particle physics as a computational mathematical approach to unknown individual-level effects by resting a simulation on known population-level probabilities. In this study a Monte Carlo simulation approach to childhood dental decay was built, tested and validated.
Naglič, Peter; Pernuš, Franjo; Likar, Boštjan; Bürmen, Miran
2017-01-01
Analytical expressions for sampling the scattering angle from a phase function in Monte Carlo simulations of light propagation are available only for a limited number of phase functions. Consequently, numerical sampling methods based on tabulated values are often required instead. By using Monte Carlo simulated reflectance, we compare two existing and propose an improved numerical sampling method and show that both the number of the tabulated values and the numerical sampling method significantly influence the accuracy of the simulated reflectance. The provided results and guidelines should serve as a good starting point for conducting computationally efficient Monte Carlo simulations with numerical phase function sampling. PMID:28663872
GMC: a GPU implementation of a Monte Carlo dose calculation based on Geant4.
Jahnke, Lennart; Fleckenstein, Jens; Wenz, Frederik; Hesser, Jürgen
2012-03-07
We present a GPU implementation called GMC (GPU Monte Carlo) of the low energy (<100 GeV) electromagnetic part of the Geant4 Monte Carlo code using the NVIDIA® CUDA programming interface. The classes for electron and photon interactions as well as a new parallel particle transport engine were implemented. The way a particle is processed is not in a history by history manner but rather by an interaction by interaction method. Every history is divided into steps that are then calculated in parallel by different kernels. The geometry package is currently limited to voxelized geometries. A modified parallel Mersenne twister was used to generate random numbers and a random number repetition method on the GPU was introduced. All phantom results showed a very good agreement between GPU and CPU simulation with gamma indices of >97.5% for a 2%/2 mm gamma criteria. The mean acceleration on one GTX 580 for all cases compared to Geant4 on one CPU core was 4860. The mean number of histories per millisecond on the GPU for all cases was 658 leading to a total simulation time for one intensity-modulated radiation therapy dose distribution of 349 s. In conclusion, Geant4-based Monte Carlo dose calculations were significantly accelerated on the GPU.
Isotropic Monte Carlo Grain Growth
Mason, J.
2013-04-25
IMCGG performs Monte Carlo simulations of normal grain growth in metals on a hexagonal grid in two dimensions with periodic boundary conditions. This may be performed with either an isotropic or a misorientation - and incliantion-dependent grain boundary energy.
Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy.
Bonenfant, Éric; Magnoux, Vincent; Hissoiny, Sami; Ozell, Benoît; Beaulieu, Luc; Després, Philippe
2015-07-07
The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm(3) calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.
Fast GPU-based Monte Carlo simulations for LDR prostate brachytherapy
NASA Astrophysics Data System (ADS)
Bonenfant, Éric; Magnoux, Vincent; Hissoiny, Sami; Ozell, Benoît; Beaulieu, Luc; Després, Philippe
2015-07-01
The aim of this study was to evaluate the potential of bGPUMCD, a Monte Carlo algorithm executed on Graphics Processing Units (GPUs), for fast dose calculations in permanent prostate implant dosimetry. It also aimed to validate a low dose rate brachytherapy source in terms of TG-43 metrics and to use this source to compute dose distributions for permanent prostate implant in very short times. The physics of bGPUMCD was reviewed and extended to include Rayleigh scattering and fluorescence from photoelectric interactions for all materials involved. The radial and anisotropy functions were obtained for the Nucletron SelectSeed in TG-43 conditions. These functions were compared to those found in the MD Anderson Imaging and Radiation Oncology Core brachytherapy source registry which are considered the TG-43 reference values. After appropriate calibration of the source, permanent prostate implant dose distributions were calculated for four patients and compared to an already validated Geant4 algorithm. The radial function calculated from bGPUMCD showed excellent agreement (differences within 1.3%) with TG-43 accepted values. The anisotropy functions at r = 1 cm and r = 4 cm were within 2% of TG-43 values for angles over 17.5°. For permanent prostate implants, Monte Carlo-based dose distributions with a statistical uncertainty of 1% or less for the target volume were obtained in 30 s or less for 1 × 1 × 1 mm3 calculation grids. Dosimetric indices were very similar (within 2.7%) to those obtained with a validated, independent Monte Carlo code (Geant4) performing the calculations for the same cases in a much longer time (tens of minutes to more than a hour). bGPUMCD is a promising code that lets envision the use of Monte Carlo techniques in a clinical environment, with sub-minute execution times on a standard workstation. Future work will explore the use of this code with an inverse planning method to provide a complete Monte Carlo-based planning solution.
Quantum Monte Carlo for Molecules.
1986-12-01
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Monte Carlo Simulations of Microchannel Plate Based, Fast-Gated X-Ray Imagers
Wu., M., Kruschwitz, C.
2011-02-01
This is a chapter in a book titled Applications of Monte Carlo Method in Science and Engineering Edited by: Shaul Mordechai ISBN 978-953-307-691-1, Hard cover, 950 pages Publisher: InTech Publication date: February 2011
PEREGRINE: Bringing Monte Carlo based treatment planning calculations to today's clinic
Patterson, R; Daly, T; Garrett, D; Hartmann-Siantar, C; House, R; May, S
1999-12-13
Monte Carlo simulation of radiotherapy is now available for routine clinical use. It brings improved accuracy of dose calculations for treatments where important physics comes into play, and provides a robust, general tool for planning where empirical solutions have not been implemented. Through the use of Monte Carlo, new information, including the effects of the composition of materials in the patient, the effects of electron transport, and the details of the distribution of energy deposition, can be applied to the field. PEREGRINE{trademark} is a Monte Carlo dose calculation solution that was designed and built specifically for the purpose of providing a practical, affordable Monte Carlo capability to the clinic. The system solution was crafted to facilitate insertion of this powerful tool into day-to-day treatment planning, while being extensible to accommodate improvements in techniques, computers, and interfaces.
Dynamically stratified Monte Carlo forecasting
NASA Technical Reports Server (NTRS)
Schubert, Siegfried; Suarez, Max; Schemm, Jae-Kyung; Epstein, Edward
1992-01-01
A new method for performing Monte Carlo forecasts is introduced. The method, called dynamic stratification, selects initial perturbations based on a stratification of the error distribution. A simple implementation is presented in which the error distribution used for the stratification is estimated from a linear model derived from a large ensemble of 12-h forecasts with the full dynamic model. The stratification thus obtained is used to choose a small subsample of initial states with which to perform the dynamical Monte Carlo forecasts. Several test cases are studied using a simple two-level general circulation model with uncertain initial conditions. It is found that the method provides substantial reductions in the sampling error of the forecast mean and variance when compared to the more traditional approach of choosing the initial perturbations at random. The degree of improvement, however, is sensitive to the nature of the initial error distribution and to the base state. In practice the method may be viable only if the computational burden involved in obtaining an adequate estimate of the error distribution is shared with the data-assimilation procedure.
Morton, April M; Piburn, Jesse O; McManamay, Ryan A; Nagle, Nicholas N; Stewart, Robert N
2017-01-01
Monte Carlo simulation is a popular numerical experimentation technique used in a range of scientific fields to obtain the statistics of unknown random output variables. Despite its widespread applicability, it can be difficult to infer required input probability distributions when they are related to population counts unknown at desired spatial resolutions. To overcome this challenge, we propose a framework that uses a dasymetric model to infer the probability distributions needed for a specific class of Monte Carlo simulations which depend on population counts.
Variance reduction for Fokker–Planck based particle Monte Carlo schemes
Gorji, M. Hossein Andric, Nemanja; Jenny, Patrick
2015-08-15
Recently, Fokker–Planck based particle Monte Carlo schemes have been proposed and evaluated for simulations of rarefied gas flows [1–3]. In this paper, the variance reduction for particle Monte Carlo simulations based on the Fokker–Planck model is considered. First, deviational based schemes were derived and reviewed, and it is shown that these deviational methods are not appropriate for practical Fokker–Planck based rarefied gas flow simulations. This is due to the fact that the deviational schemes considered in this study lead either to instabilities in the case of two-weight methods or to large statistical errors if the direct sampling method is applied. Motivated by this conclusion, we developed a novel scheme based on correlated stochastic processes. The main idea here is to synthesize an additional stochastic process with a known solution, which is simultaneously solved together with the main one. By correlating the two processes, the statistical errors can dramatically be reduced; especially for low Mach numbers. To assess the methods, homogeneous relaxation, planar Couette and lid-driven cavity flows were considered. For these test cases, it could be demonstrated that variance reduction based on parallel processes is very robust and effective.
GFS algorithm based on batch Monte Carlo trials for solving global optimization problems
NASA Astrophysics Data System (ADS)
Popkov, Yuri S.; Darkhovskiy, Boris S.; Popkov, Alexey Y.
2016-10-01
A new method for global optimization of Hölder goal functions under compact sets given by inequalities is proposed. All functions are defined only algorithmically. The method is based on performing simple Monte Carlo trials and constructing the sequences of records and the sequence of their decrements. An estimating procedure of Hölder constants is proposed. Probability estimation of exact global minimum neighborhood using Hölder constants estimates is presented. Results on some analytical and algorithmic test problems illustrate the method's performance.
Refinement of overlapping local/global iteration method based on Monte Carlo/p-CMFD calculations
Jo, Y.; Yun, S.; Cho, N. Z.
2013-07-01
In this paper, the overlapping local/global (OLG) iteration method based on Monte Carlo/p-CMFD calculations is refined in two aspects. One is the consistent use of estimators to generate homogenized scattering cross sections. Another is that the incident or exiting angular interval is divided into multi-angular bins to modulate albedo boundary conditions for local problems. Numerical tests show that, compared to the one angle bin case in a previous study, the four angle bin case shows significantly improved results. (authors)
Thermal transport in nanocrystalline Si and SiGe by ab initio based Monte Carlo simulation
Yang, Lina; Minnich, Austin J.
2017-01-01
Nanocrystalline thermoelectric materials based on Si have long been of interest because Si is earth-abundant, inexpensive, and non-toxic. However, a poor understanding of phonon grain boundary scattering and its effect on thermal conductivity has impeded efforts to improve the thermoelectric figure of merit. Here, we report an ab-initio based computational study of thermal transport in nanocrystalline Si-based materials using a variance-reduced Monte Carlo method with the full phonon dispersion and intrinsic lifetimes from first-principles as input. By fitting the transmission profile of grain boundaries, we obtain excellent agreement with experimental thermal conductivity of nanocrystalline Si [Wang et al. Nano Letters 11, 2206 (2011)]. Based on these calculations, we examine phonon transport in nanocrystalline SiGe alloys with ab-initio electron-phonon scattering rates. Our calculations show that low energy phonons still transport substantial amounts of heat in these materials, despite scattering by electron-phonon interactions, due to the high transmission of phonons at grain boundaries, and thus improvements in ZT are still possible by disrupting these modes. This work demonstrates the important insights into phonon transport that can be obtained using ab-initio based Monte Carlo simulations in complex nanostructured materials. PMID:28290484
Thermal transport in nanocrystalline Si and SiGe by ab initio based Monte Carlo simulation.
Yang, Lina; Minnich, Austin J
2017-03-14
Nanocrystalline thermoelectric materials based on Si have long been of interest because Si is earth-abundant, inexpensive, and non-toxic. However, a poor understanding of phonon grain boundary scattering and its effect on thermal conductivity has impeded efforts to improve the thermoelectric figure of merit. Here, we report an ab-initio based computational study of thermal transport in nanocrystalline Si-based materials using a variance-reduced Monte Carlo method with the full phonon dispersion and intrinsic lifetimes from first-principles as input. By fitting the transmission profile of grain boundaries, we obtain excellent agreement with experimental thermal conductivity of nanocrystalline Si [Wang et al. Nano Letters 11, 2206 (2011)]. Based on these calculations, we examine phonon transport in nanocrystalline SiGe alloys with ab-initio electron-phonon scattering rates. Our calculations show that low energy phonons still transport substantial amounts of heat in these materials, despite scattering by electron-phonon interactions, due to the high transmission of phonons at grain boundaries, and thus improvements in ZT are still possible by disrupting these modes. This work demonstrates the important insights into phonon transport that can be obtained using ab-initio based Monte Carlo simulations in complex nanostructured materials.
Thermal transport in nanocrystalline Si and SiGe by ab initio based Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Yang, Lina; Minnich, Austin J.
2017-03-01
Nanocrystalline thermoelectric materials based on Si have long been of interest because Si is earth-abundant, inexpensive, and non-toxic. However, a poor understanding of phonon grain boundary scattering and its effect on thermal conductivity has impeded efforts to improve the thermoelectric figure of merit. Here, we report an ab-initio based computational study of thermal transport in nanocrystalline Si-based materials using a variance-reduced Monte Carlo method with the full phonon dispersion and intrinsic lifetimes from first-principles as input. By fitting the transmission profile of grain boundaries, we obtain excellent agreement with experimental thermal conductivity of nanocrystalline Si [Wang et al. Nano Letters 11, 2206 (2011)]. Based on these calculations, we examine phonon transport in nanocrystalline SiGe alloys with ab-initio electron-phonon scattering rates. Our calculations show that low energy phonons still transport substantial amounts of heat in these materials, despite scattering by electron-phonon interactions, due to the high transmission of phonons at grain boundaries, and thus improvements in ZT are still possible by disrupting these modes. This work demonstrates the important insights into phonon transport that can be obtained using ab-initio based Monte Carlo simulations in complex nanostructured materials.
Schreiber, Eric C; Chang, Sha X
2012-08-01
Microbeam radiation therapy (MRT) is an experimental radiotherapy technique that has shown potent antitumor effects with minimal damage to normal tissue in animal studies. This unique form of radiation is currently only produced in a few large synchrotron accelerator research facilities in the world. To promote widespread translational research on this promising treatment technology we have proposed and are in the initial development stages of a compact MRT system that is based on carbon nanotube field emission x-ray technology. We report on a Monte Carlo based feasibility study of the compact MRT system design. Monte Carlo calculations were performed using EGSnrc-based codes. The proposed small animal research MRT device design includes carbon nanotube cathodes shaped to match the corresponding MRT collimator apertures, a common reflection anode with filter, and a MRT collimator. Each collimator aperture is sized to deliver a beam width ranging from 30 to 200 μm at 18.6 cm source-to-axis distance. Design parameters studied with Monte Carlo include electron energy, cathode design, anode angle, filtration, and collimator design. Calculations were performed for single and multibeam configurations. Increasing the energy from 100 kVp to 160 kVp increased the photon fluence through the collimator by a factor of 1.7. Both energies produced a largely uniform fluence along the long dimension of the microbeam, with 5% decreases in intensity near the edges. The isocentric dose rate for 160 kVp was calculated to be 700 Gy∕min∕A in the center of a 3 cm diameter target. Scatter contributions resulting from collimator size were found to produce only small (<7%) changes in the dose rate for field widths greater than 50 μm. Dose vs depth was weakly dependent on filtration material. The peak-to-valley ratio varied from 10 to 100 as the separation between adjacent microbeams varies from 150 to 1000 μm. Monte Carlo simulations demonstrate that the proposed compact MRT system
Schreiber, Eric C.; Chang, Sha X.
2012-01-01
Purpose: Microbeam radiation therapy (MRT) is an experimental radiotherapy technique that has shown potent antitumor effects with minimal damage to normal tissue in animal studies. This unique form of radiation is currently only produced in a few large synchrotron accelerator research facilities in the world. To promote widespread translational research on this promising treatment technology we have proposed and are in the initial development stages of a compact MRT system that is based on carbon nanotube field emission x-ray technology. We report on a Monte Carlo based feasibility study of the compact MRT system design. Methods: Monte Carlo calculations were performed using EGSnrc-based codes. The proposed small animal research MRT device design includes carbon nanotube cathodes shaped to match the corresponding MRT collimator apertures, a common reflection anode with filter, and a MRT collimator. Each collimator aperture is sized to deliver a beam width ranging from 30 to 200 μm at 18.6 cm source-to-axis distance. Design parameters studied with Monte Carlo include electron energy, cathode design, anode angle, filtration, and collimator design. Calculations were performed for single and multibeam configurations. Results: Increasing the energy from 100 kVp to 160 kVp increased the photon fluence through the collimator by a factor of 1.7. Both energies produced a largely uniform fluence along the long dimension of the microbeam, with 5% decreases in intensity near the edges. The isocentric dose rate for 160 kVp was calculated to be 700 Gy/min/A in the center of a 3 cm diameter target. Scatter contributions resulting from collimator size were found to produce only small (<7%) changes in the dose rate for field widths greater than 50 μm. Dose vs depth was weakly dependent on filtration material. The peak-to-valley ratio varied from 10 to 100 as the separation between adjacent microbeams varies from 150 to 1000 μm. Conclusions: Monte Carlo simulations demonstrate
NASA Astrophysics Data System (ADS)
Boudreau, C.; Heath, E.; Seuntjens, J.; Ballivy, O.; Parker, W.
2005-03-01
The PEREGRINE Monte Carlo dose-calculation system (North American Scientific, Cranberry Township, PA) is the first commercially available Monte Carlo dose-calculation code intended specifically for intensity modulated radiotherapy (IMRT) treatment planning and quality assurance. In order to assess the impact of Monte Carlo based dose calculations for IMRT clinical cases, dose distributions for 11 head and neck patients were evaluated using both PEREGRINE and the CORVUS (North American Scientific, Cranberry Township, PA) finite size pencil beam (FSPB) algorithm with equivalent path-length (EPL) inhomogeneity correction. For the target volumes, PEREGRINE calculations predict, on average, a less than 2% difference in the calculated mean and maximum doses to the gross tumour volume (GTV) and clinical target volume (CTV). An average 16% ± 4% and 12% ± 2% reduction in the volume covered by the prescription isodose line was observed for the GTV and CTV, respectively. Overall, no significant differences were noted in the doses to the mandible and spinal cord. For the parotid glands, PEREGRINE predicted a 6% ± 1% increase in the volume of tissue receiving a dose greater than 25 Gy and an increase of 4% ± 1% in the mean dose. Similar results were noted for the brainstem where PEREGRINE predicted a 6% ± 2% increase in the mean dose. The observed differences between the PEREGRINE and CORVUS calculated dose distributions are attributed to secondary electron fluence perturbations, which are not modelled by the EPL correction, issues of organ outlining, particularly in the vicinity of air cavities, and differences in dose reporting (dose to water versus dose to tissue type).
SU-E-T-761: TOMOMC, A Monte Carlo-Based Planning VerificationTool for Helical Tomotherapy
Chibani, O; Ma, C
2015-06-15
Purpose: Present a new Monte Carlo code (TOMOMC) to calculate 3D dose distributions for patients undergoing helical tomotherapy treatments. TOMOMC performs CT-based dose calculations using the actual dynamic variables of the machine (couch motion, gantry rotation, and MLC sequences). Methods: TOMOMC is based on the GEPTS (Gama Electron and Positron Transport System) general-purpose Monte Carlo system (Chibani and Li, Med. Phys. 29, 2002, 835). First, beam models for the Hi-Art Tomotherpy machine were developed for the different beam widths (1, 2.5 and 5 cm). The beam model accounts for the exact geometry and composition of the different components of the linac head (target, primary collimator, jaws and MLCs). The beams models were benchmarked by comparing calculated Pdds and lateral/transversal dose profiles with ionization chamber measurements in water. See figures 1–3. The MLC model was tuned in such a way that tongue and groove effect, inter-leaf and intra-leaf transmission are modeled correctly. See figure 4. Results: By simulating the exact patient anatomy and the actual treatment delivery conditions (couch motion, gantry rotation and MLC sinogram), TOMOMC is able to calculate the 3D patient dose distribution which is in principal more accurate than the one from the treatment planning system (TPS) since it relies on the Monte Carlo method (gold standard). Dose volume parameters based on the Monte Carlo dose distribution can also be compared to those produced by the TPS. Attached figures show isodose lines for a H&N patient calculated by TOMOMC (transverse and sagittal views). Analysis of differences between TOMOMC and TPS is an ongoing work for different anatomic sites. Conclusion: A new Monte Carlo code (TOMOMC) was developed for Tomotherapy patient-specific QA. The next step in this project is implementing GPU computing to speed up Monte Carlo simulation and make Monte Carlo-based treatment verification a practical solution.
Monte Carlo calculation based on hydrogen composition of the tissue for MV photon radiotherapy.
Demol, Benjamin; Viard, Romain; Reynaert, Nick
2015-09-01
The purpose of this study was to demonstrate that Monte Carlo treatment planning systems require tissue characterization (density and composition) as a function of CT number. A discrete set of tissue classes with a specific composition is introduced. In the current work we demonstrate that, for megavoltage photon radiotherapy, only the hydrogen content of the different tissues is of interest. This conclusion might have an impact on MRI-based dose calculations and on MVCT calibration using tissue substitutes. A stoichiometric calibration was performed, grouping tissues with similar atomic composition into 15 dosimetrically equivalent subsets. To demonstrate the importance of hydrogen, a new scheme was derived, with correct hydrogen content, complemented by oxygen (all elements differing from hydrogen are replaced by oxygen). Mass attenuation coefficients and mass stopping powers for this scheme were calculated and compared to the original scheme. Twenty-five CyberKnife treatment plans were recalculated by an in-house developed Monte Carlo system using tissue density and hydrogen content derived from the CT images. The results were compared to Monte Carlo simulations using the original stoichiometric calibration. Between 300 keV and 3 MeV, the relative difference of mass attenuation coefficients is under 1% within all subsets. Between 10 keV and 20 MeV, the relative difference of mass stopping powers goes up to 5% in hard bone and remains below 2% for all other tissue subsets. Dose-volume histograms (DVHs) of the treatment plans present no visual difference between the two schemes. Relative differences of dose indexes D98, D95, D50, D05, D02, and Dmean were analyzed and a distribution centered around zero and of standard deviation below 2% (3σ) was established. On the other hand, once the hydrogen content is slightly modified, important dose differences are obtained. Monte Carlo dose planning in the field of megavoltage photon radiotherapy is fully achievable using
Monte Carlo calculation based on hydrogen composition of the tissue for MV photon radiotherapy.
Demol, Benjamin; Viard, Romain; Reynaert, Nick
2015-09-08
The purpose of this study was to demonstrate that Monte Carlo treatment planning systems require tissue characterization (density and composition) as a function of CT number. A discrete set of tissue classes with a specific composition is introduced. In the current work we demonstrate that, for megavoltage photon radiotherapy, only the hydrogen content of the different tissues is of interest. This conclusion might have an impact on MRI-based dose calculations and on MVCT calibration using tissue substitutes. A stoichiometric calibration was performed, grouping tissues with similar atomic composition into 15 dosimetrically equivalent subsets. To demonstrate the importance of hydrogen, a new scheme was derived, with correct hydrogen content, complemented by oxygen (all elements differing from hydrogen are replaced by oxygen). Mass attenuation coefficients and mass stopping powers for this scheme were calculated and compared to the original scheme. Twenty-five CyberKnife treatment plans were recalculated by an in-house developed Monte Carlo system using tissue density and hydrogen content derived from the CT images. The results were compared to Monte Carlo simulations using the original stoichiometric calibration. Between 300 keV and 3 MeV, the relative difference of mass attenuation coefficients is under 1% within all subsets. Between 10 keV and 20 MeV, the relative difference of mass stopping powers goes up to 5% in hard bone and remains below 2% for all other tissue subsets. Dose-volume histograms (DVHs) of the treatment plans present no visual difference between the two schemes. Relative differences of dose indexes D98, D95, D50, D05, D02, and Dmean were analyzed and a distribution centered around zero and of standard deviation below 2% (3 σ) was established. On the other hand, once the hydrogen content is slightly modified, important dose differences are obtained. Monte Carlo dose planning in the field of megavoltage photon radiotherapy is fully achievable using
Comment on “A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation”
Fang, Qianqian
2011-01-01
The Monte Carlo (MC) method is a popular approach to modeling photon propagation inside general turbid media, such as human tissue. Progress had been made in the past year with the independent proposals of two mesh-based Monte Carlo methods employing ray-tracing techniques. Both methods have shown improvements in accuracy and efficiency in modeling complex domains. A recent paper by Shen and Wang [Biomed. Opt. Express 2, 44 (2011)] reported preliminary results towards the cross-validation of the two mesh-based MC algorithms and software implementations, showing a 3–6 fold speed difference between the two software packages. In this comment, we share our views on unbiased software comparisons and discuss additional issues such as the use of pre-computed data, interpolation strategies, impact of compiler settings, use of Russian roulette, memory cost and potential pitfalls in measuring algorithm performance. Despite key differences between the two algorithms in handling of non-tetrahedral meshes, we found that they share similar structure and performance for tetrahedral meshes. A significant fraction of the observed speed differences in the mentioned article was the result of inconsistent use of compilers and libraries. PMID:21559136
Stochastic modeling of polarized light scattering using a Monte Carlo based stencil method.
Sormaz, Milos; Stamm, Tobias; Jenny, Patrick
2010-05-01
This paper deals with an efficient and accurate simulation algorithm to solve the vector Boltzmann equation for polarized light transport in scattering media. The approach is based on a stencil method, which was previously developed for unpolarized light scattering and proved to be much more efficient (speedup factors of up to 10 were reported) than the classical Monte Carlo while being equally accurate. To validate what we believe to be the new stencil method, a substrate composed of spherical non-absorbing particles embedded in a non-absorbing medium was considered. The corresponding single scattering Mueller matrix, which is required to model scattering of polarized light, was determined based on the Lorenz-Mie theory. From simulations of a reflected polarized laser beam, the Mueller matrix of the substrate was computed and compared with an established reference. The agreement is excellent, and it could be demonstrated that a significant speedup of the simulations is achieved due to the stencil approach compared with the classical Monte Carlo.
Comment on "A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation".
Fang, Qianqian
2011-04-19
The Monte Carlo (MC) method is a popular approach to modeling photon propagation inside general turbid media, such as human tissue. Progress had been made in the past year with the independent proposals of two mesh-based Monte Carlo methods employing ray-tracing techniques. Both methods have shown improvements in accuracy and efficiency in modeling complex domains. A recent paper by Shen and Wang [Biomed. Opt. Express 2, 44 (2011)] reported preliminary results towards the cross-validation of the two mesh-based MC algorithms and software implementations, showing a 3-6 fold speed difference between the two software packages. In this comment, we share our views on unbiased software comparisons and discuss additional issues such as the use of pre-computed data, interpolation strategies, impact of compiler settings, use of Russian roulette, memory cost and potential pitfalls in measuring algorithm performance. Despite key differences between the two algorithms in handling of non-tetrahedral meshes, we found that they share similar structure and performance for tetrahedral meshes. A significant fraction of the observed speed differences in the mentioned article was the result of inconsistent use of compilers and libraries.
Monte Carlo simulation as a tool to predict blasting fragmentation based on the Kuz Ram model
NASA Astrophysics Data System (ADS)
Morin, Mario A.; Ficarazzo, Francesco
2006-04-01
Rock fragmentation is considered the most important aspect of production blasting because of its direct effects on the costs of drilling and blasting and on the economics of the subsequent operations of loading, hauling and crushing. Over the past three decades, significant progress has been made in the development of new technologies for blasting applications. These technologies include increasingly sophisticated computer models for blast design and blast performance prediction. Rock fragmentation depends on many variables such as rock mass properties, site geology, in situ fracturing and blasting parameters and as such has no complete theoretical solution for its prediction. However, empirical models for the estimation of size distribution of rock fragments have been developed. In this study, a blast fragmentation Monte Carlo-based simulator, based on the Kuz-Ram fragmentation model, has been developed to predict the entire fragmentation size distribution, taking into account intact and joints rock properties, the type and properties of explosives and the drilling pattern. Results produced by this simulator were quite favorable when compared with real fragmentation data obtained from a blast quarry. It is anticipated that the use of Monte Carlo simulation will increase our understanding of the effects of rock mass and explosive properties on the rock fragmentation by blasting, as well as increase our confidence in these empirical models. This understanding will translate into improvements in blasting operations, its corresponding costs and the overall economics of open pit mines and rock quarries.
Generalized mesh-based Monte Carlo for wide-field illumination and detection via mesh retessellation
Yao, Ruoyang; Intes, Xavier; Fang, Qianqian
2015-01-01
Monte Carlo methods are commonly used as the gold standard in modeling photon transport through turbid media. With the rapid development of structured light applications, an accurate and efficient method capable of simulating arbitrary illumination patterns and complex detection schemes over large surface area is in great need. Here we report a generalized mesh-based Monte Carlo algorithm to support a variety of wide-field illumination methods, including spatial-frequency-domain imaging (SFDI) patterns and arbitrary 2-D patterns. The extended algorithm can also model wide-field detectors such as a free-space CCD camera. The significantly enhanced flexibility of source and detector modeling is achieved via a fast mesh retessellation process that combines the target domain and the source/detector space in a single tetrahedral mesh. Both simulations of complex domains and comparisons with phantom measurements are included to demonstrate the flexibility, efficiency and accuracy of the extended algorithm. Our updated open-source software is provided at http://mcx.space/mmc. PMID:26819826
Fission yield calculation using toy model based on Monte Carlo simulation
Jubaidah; Kurniadi, Rizal
2015-09-30
Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (R{sub c}), mean of left curve (μ{sub L}) and mean of right curve (μ{sub R}), deviation of left curve (σ{sub L}) and deviation of right curve (σ{sub R}). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90
A method based on Monte Carlo simulation for the determination of the G(E) function.
Chen, Wei; Feng, Tiancheng; Liu, Jun; Su, Chuanying; Tian, Yanjie
2015-02-01
The G(E) function method is a spectrometric method for the exposure dose estimation; this paper describes a method based on Monte Carlo method to determine the G(E) function of a 4″ × 4″ × 16″ NaI(Tl) detector. Simulated spectrums of various monoenergetic gamma rays in the region of 40 -3200 keV and the corresponding deposited energy in an air ball in the energy region of full-energy peak were obtained using Monte Carlo N-particle Transport Code. Absorbed dose rate in air was obtained according to the deposited energy and divided by counts of corresponding full-energy peak to get the G(E) function value at energy E in spectra. Curve-fitting software 1st0pt was used to determine coefficients of the G(E) function. Experimental results show that the calculated dose rates using the G(E) function determined by the authors' method are accordant well with those values obtained by ionisation chamber, with a maximum deviation of 6.31 %.
A fast Monte Carlo code for proton transport in radiation therapy based on MCNPX.
Jabbari, Keyvan; Seuntjens, Jan
2014-07-01
An important requirement for proton therapy is a software for dose calculation. Monte Carlo is the most accurate method for dose calculation, but it is very slow. In this work, a method is developed to improve the speed of dose calculation. The method is based on pre-generated tracks for particle transport. The MCNPX code has been used for generation of tracks. A set of data including the track of the particle was produced in each particular material (water, air, lung tissue, bone, and soft tissue). This code can transport protons in wide range of energies (up to 200 MeV for proton). The validity of the fast Monte Carlo (MC) code is evaluated with data MCNPX as a reference code. While analytical pencil beam algorithm transport shows great errors (up to 10%) near small high density heterogeneities, there was less than 2% deviation of MCNPX results in our dose calculation and isodose distribution. In terms of speed, the code runs 200 times faster than MCNPX. In the Fast MC code which is developed in this work, it takes the system less than 2 minutes to calculate dose for 10(6) particles in an Intel Core 2 Duo 2.66 GHZ desktop computer.
A fast Monte Carlo code for proton transport in radiation therapy based on MCNPX
Jabbari, Keyvan; Seuntjens, Jan
2014-01-01
An important requirement for proton therapy is a software for dose calculation. Monte Carlo is the most accurate method for dose calculation, but it is very slow. In this work, a method is developed to improve the speed of dose calculation. The method is based on pre-generated tracks for particle transport. The MCNPX code has been used for generation of tracks. A set of data including the track of the particle was produced in each particular material (water, air, lung tissue, bone, and soft tissue). This code can transport protons in wide range of energies (up to 200 MeV for proton). The validity of the fast Monte Carlo (MC) code is evaluated with data MCNPX as a reference code. While analytical pencil beam algorithm transport shows great errors (up to 10%) near small high density heterogeneities, there was less than 2% deviation of MCNPX results in our dose calculation and isodose distribution. In terms of speed, the code runs 200 times faster than MCNPX. In the Fast MC code which is developed in this work, it takes the system less than 2 minutes to calculate dose for 106 particles in an Intel Core 2 Duo 2.66 GHZ desktop computer. PMID:25190994
CAD-based Monte Carlo Program for Integrated Simulation of Nuclear System SuperMC
NASA Astrophysics Data System (ADS)
Wu, Yican; Song, Jing; Zheng, Huaqing; Sun, Guangyao; Hao, Lijuan; Long, Pengcheng; Hu, Liqin
2014-06-01
Monte Carlo (MC) method has distinct advantages to simulate complicated nuclear systems and is envisioned as routine method for nuclear design and analysis in the future. High fidelity simulation with MC method coupled with multi-physical phenomenon simulation has significant impact on safety, economy and sustainability of nuclear systems. However, great challenges to current MC methods and codes prevent its application in real engineering project. SuperMC is a CAD-based Monte Carlo program for integrated simulation of nuclear system developed by FDS Team, China, making use of hybrid MC-deterministic method and advanced computer technologies. The design aim, architecture and main methodology of SuperMC were presented in this paper. SuperMC2.1, the latest version for neutron, photon and coupled neutron and photon transport calculation, has been developed and validated by using a series of benchmarking cases such as the fusion reactor ITER model and the fast reactor BN-600 model. SuperMC is still in its evolution process toward a general and routine tool for nuclear system. Warning, no authors found for 2014snam.conf06023.
Monte Carlo-based energy response studies of diode dosimeters in radiotherapy photon beams.
Arun, C; Palani Selvam, T; Dinkar, Verma; Munshi, Prabhat; Kalra, Manjit Singh
2013-01-01
This study presents Monte Carlo-calculated absolute and normalized (relative to a (60)Co beam) sensitivity values of silicon diode dosimeters for a variety of commercially available silicon diode dosimeters for radiotherapy photon beams in the energy range of (60)Co-24 MV. These values were obtained at 5 cm depth along the central axis of a water-equivalent phantom of 10 cm × 10 cm field size. The Monte Carlo calculations were based on the EGSnrc code system. The diode dosimeters considered in the calculations have different buildup materials such as aluminum, brass, copper, and stainless steel + epoxy. The calculated normalized sensitivity values of the diode dosimeters were then compared to previously published measured values for photon beams at (60)Co-20 MV. The comparison showed reasonable agreement for some diode dosimeters and deviations of 5-17 % (17 % for the 3.4 mm brass buildup case for a 10 MV beam) for some diode dosimeters. Larger deviations of the measurements reflect that these models of the diode dosimeter were too simple. The effect of wall materials on the absorbed dose to the diode was studied and the results are presented. Spencer-Attix and Bragg-Gray stopping power ratios (SPRs) of water-to-diode were calculated at 5 cm depth in water. The Bragg-Gray SPRs of water-to-diode compare well with Spencer-Attix SPRs for ∆ = 100 keV and above at all beam qualities.
Adaptation of GEANT4 to Monte Carlo dose calculations based on CT data.
Jiang, H; Paganetti, H
2004-10-01
The GEANT4 Monte Carlo code provides many powerful functions for conducting particle transport simulations with great reliability and flexibility. However, as a general purpose Monte Carlo code, not all the functions were specifically designed and fully optimized for applications in radiation therapy. One of the primary issues is the computational efficiency, which is especially critical when patient CT data have to be imported into the simulation model. In this paper we summarize the relevant aspects of the GEANT4 tracking and geometry algorithms and introduce our work on using the code to conduct dose calculations based on CT data. The emphasis is focused on modifications of the GEANT4 source code to meet the requirements for fast dose calculations. The major features include a quick voxel search algorithm, fast volume optimization, and the dynamic assignment of material density. These features are ready to be used for tracking the primary types of particles employed in radiation therapy such as photons, electrons, and heavy charged particles. Recalculation of a proton therapy treatment plan generated by a commercial treatment planning program for a paranasal sinus case is presented as an example.
Fission yield calculation using toy model based on Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Jubaidah, Kurniadi, Rizal
2015-09-01
Toy model is a new approximation in predicting fission yield distribution. Toy model assumes nucleus as an elastic toy consist of marbles. The number of marbles represents the number of nucleons, A. This toy nucleus is able to imitate the real nucleus properties. In this research, the toy nucleons are only influenced by central force. A heavy toy nucleus induced by a toy nucleon will be split into two fragments. These two fission fragments are called fission yield. In this research, energy entanglement is neglected. Fission process in toy model is illustrated by two Gaussian curves intersecting each other. There are five Gaussian parameters used in this research. They are scission point of the two curves (Rc), mean of left curve (μL) and mean of right curve (μR), deviation of left curve (σL) and deviation of right curve (σR). The fission yields distribution is analyses based on Monte Carlo simulation. The result shows that variation in σ or µ can significanly move the average frequency of asymmetry fission yields. This also varies the range of fission yields distribution probability. In addition, variation in iteration coefficient only change the frequency of fission yields. Monte Carlo simulation for fission yield calculation using toy model successfully indicates the same tendency with experiment results, where average of light fission yield is in the range of 90
Optical skin assessment based on spectral reflectance estimation and Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Bauer, Jacob R.; Hardeberg, Jon Y.; Verdaasdonk, Rudolf
2017-02-01
Optical non-contact measurements in general, and chromophore concentration estimation in particular, have been identified to be useful tools for skin assessment. Spectral estimation using a low cost hand held device has not been studied adequately as a basis for skin assessment. Spectral measurements on the one hand, which require bulky, expensive and complex devices and direct channel approaches on the other hand, which operate with simple optical devices have been considered and applied for skin assessment. In this study, we analyse the capabilities of spectral estimation for skin assessment in form of chromophore concentration estimation using a prototypical low cost optical non-contact device. A spectral estimation work flow is implemented and combined with pre-simulated Monte Carlo spectra to use estimated spectra based on conventional image sensors for chromophore concentrations estimation and obtain health metrics. To evaluate the proposed approach, we performed a series of occlusion experiments and examined the capabilities of the proposed process. Additionally, the method has been applied to more general skin assessment tasks. The proposed process provides a more general representation in form of a spectral image cube which can be used for more advanced analysis and the comparisons show good agreement with expectations and conventional skin assessment methods. Utilising spectral estimation in conjunction with Monte Carlo simulation could lead to low cost, easy to use, hand held and multifunctional optical skin assessment with the possibility to improve skin assessment and the diagnosis of diseases.
Monte Carlo simulations for external neutron dosimetry based on the visible Chinese human phantom
NASA Astrophysics Data System (ADS)
Zhang, Guozhi; Liu, Qian; Luo, Qingming
2007-12-01
A group of Monte Carlo simulations has been performed for external neutron dosimetry calculation based on a whole-body anatomical model, the visible Chinese human (VCH) phantom, which was newly developed from high-resolution cryosectional color photographic images of a healthy Chinese adult male cadaver. Physical characteristics of the VCH computational phantom that consists of 230 × 120 × 892 voxels corresponding to an element volume of 2 × 2 × 2 mm3 are evaluated through comparison against a variety of other anthropomorphic models. Organ-absorbed doses and the effective doses for monoenergic neutron beams ranging from 10-9 MeV to 10 GeV under six idealized irradiation geometries (AP, PA, LLAT, RLAT, ROT and ISO) were calculated using the Monte Carlo code MCNPX2.5. Absorbed dose results for selected organs and the effective doses are presented in the form of tables. Dose results are also compared with currently available neutron data form ICRP Publication 74 and those of VIP-Man. Anatomical variations between different models, as well as their influence on dose distributions, are explored. Detailed information derived from the VCH phantom is able to lend quantitative references to the widespread application of human computational models in radiology.
A strategy for finding the optimal scale of plant core collection based on Monte Carlo simulation.
Wang, Jiancheng; Guan, Yajing; Wang, Yang; Zhu, Liwei; Wang, Qitian; Hu, Qijuan; Hu, Jin
2014-01-01
Core collection is an ideal resource for genome-wide association studies (GWAS). A subcore collection is a subset of a core collection. A strategy was proposed for finding the optimal sampling percentage on plant subcore collection based on Monte Carlo simulation. A cotton germplasm group of 168 accessions with 20 quantitative traits was used to construct subcore collections. Mixed linear model approach was used to eliminate environment effect and GE (genotype × environment) effect. Least distance stepwise sampling (LDSS) method combining 6 commonly used genetic distances and unweighted pair-group average (UPGMA) cluster method was adopted to construct subcore collections. Homogeneous population assessing method was adopted to assess the validity of 7 evaluating parameters of subcore collection. Monte Carlo simulation was conducted on the sampling percentage, the number of traits, and the evaluating parameters. A new method for "distilling free-form natural laws from experimental data" was adopted to find the best formula to determine the optimal sampling percentages. The results showed that coincidence rate of range (CR) was the most valid evaluating parameter and was suitable to serve as a threshold to find the optimal sampling percentage. The principal component analysis showed that subcore collections constructed by the optimal sampling percentages calculated by present strategy were well representative.
CAD-Based Monte Carlo Neutron Transport KSTAR Analysis for KSTAR
NASA Astrophysics Data System (ADS)
Seo, Geon Ho; Choi, Sung Hoon; Shim, Hyung Jin
2017-09-01
The Monte Carlo (MC) neutron transport analysis for a complex nuclear system such as fusion facility may require accurate modeling of its complicated geometry. In order to take advantage of modeling capability of the computer aided design (CAD) system for the MC neutronics analysis, the Seoul National University MC code, McCARD, has been augmented with a CAD-based geometry processing module by imbedding the OpenCASCADE CAD kernel. In the developed module, the CAD geometry data are internally converted to the constructive solid geometry model with help of the CAD kernel. An efficient cell-searching algorithm is devised for the void space treatment. The performance of the CAD-based McCARD calculations are tested for the Korea Superconducting Tokamak Advanced Research device by comparing with results of the conventional MC calculations using a text-based geometry input.
Huang, Guanghui; Wan, Jianping; Chen, Hui
2013-02-01
Nonlinear stochastic differential equation models with unobservable state variables are now widely used in analysis of PK/PD data. Unobservable state variables are usually estimated with extended Kalman filter (EKF), and the unknown pharmacokinetic parameters are usually estimated by maximum likelihood estimator. However, EKF is inadequate for nonlinear PK/PD models, and MLE is known to be biased downwards. A density-based Monte Carlo filter (DMF) is proposed to estimate the unobservable state variables, and a simulation-based M estimator is proposed to estimate the unknown parameters in this paper, where a genetic algorithm is designed to search the optimal values of pharmacokinetic parameters. The performances of EKF and DMF are compared through simulations for discrete time and continuous time systems respectively, and it is found that the results based on DMF are more accurate than those given by EKF with respect to mean absolute error. Copyright © 2012 Elsevier Ltd. All rights reserved.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h_{L}. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levels ${\\infty}$ >h_{0}>h_{1 }...>h_{L}. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; ...
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level hL. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levelsmore » $${\\infty}$$ >h0>h1 ...>hL. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.« less
Multilevel sequential Monte Carlo samplers
Beskos, Alexandros; Jasra, Ajay; Law, Kody; Tempone, Raul; Zhou, Yan
2016-08-24
Here, we study the approximation of expectations w.r.t. probability distributions associated to the solution of partial differential equations (PDEs); this scenario appears routinely in Bayesian inverse problems. In practice, one often has to solve the associated PDE numerically, using, for instance finite element methods and leading to a discretisation bias, with the step-size level h_{L}. In addition, the expectation cannot be computed analytically and one often resorts to Monte Carlo methods. In the context of this problem, it is known that the introduction of the multilevel Monte Carlo (MLMC) method can reduce the amount of computational effort to estimate expectations, for a given level of error. This is achieved via a telescoping identity associated to a Monte Carlo approximation of a sequence of probability distributions with discretisation levels ${\\infty}$ >h_{0}>h_{1 }...>h_{L}. In many practical problems of interest, one cannot achieve an i.i.d. sampling of the associated sequence of probability distributions. A sequential Monte Carlo (SMC) version of the MLMC method is introduced to deal with this problem. In conclusion, it is shown that under appropriate assumptions, the attractive property of a reduction of the amount of computational effort to estimate expectations, for a given level of error, can be maintained within the SMC context.
Monte Carlo Particle Lists: MCPL
NASA Astrophysics Data System (ADS)
Kittelmann, T.; Klinkby, E.; Knudsen, E. B.; Willendrup, P.; Cai, X. X.; Kanaki, K.
2017-09-01
A binary format with lists of particle state information, for interchanging particles between various Monte Carlo simulation applications, is presented. Portable C code for file manipulation is made available to the scientific community, along with converters and plugins for several popular simulation packages.
GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources.
Townson, Reid W; Jia, Xun; Tian, Zhen; Graves, Yan Jiang; Zavgorodni, Sergei; Jiang, Steve B
2013-06-21
A novel phase-space source implementation has been designed for graphics processing unit (GPU)-based Monte Carlo dose calculation engines. Short of full simulation of the linac head, using a phase-space source is the most accurate method to model a clinical radiation beam in dose calculations. However, in GPU-based Monte Carlo dose calculations where the computation efficiency is very high, the time required to read and process a large phase-space file becomes comparable to the particle transport time. Moreover, due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel source implementation utilizing pre-processed patient-independent phase-spaces that are sorted by particle type, energy and position. Position bins located outside a rectangular region of interest enclosing the treatment field are ignored, substantially decreasing simulation time with little effect on the final dose distribution. The three methods were validated in absolute dose against BEAMnrc/DOSXYZnrc and compared using gamma-index tests (2%/2 mm above the 10% isodose). It was found that the PSL method has the optimal balance between accuracy and efficiency and thus is used as the default method in gDPM v3.0. Using the PSL method, open fields of 4 × 4, 10 × 10 and 30 × 30 cm
GPU-based Monte Carlo radiotherapy dose calculation using phase-space sources
NASA Astrophysics Data System (ADS)
Townson, Reid W.; Jia, Xun; Tian, Zhen; Jiang Graves, Yan; Zavgorodni, Sergei; Jiang, Steve B.
2013-06-01
A novel phase-space source implementation has been designed for graphics processing unit (GPU)-based Monte Carlo dose calculation engines. Short of full simulation of the linac head, using a phase-space source is the most accurate method to model a clinical radiation beam in dose calculations. However, in GPU-based Monte Carlo dose calculations where the computation efficiency is very high, the time required to read and process a large phase-space file becomes comparable to the particle transport time. Moreover, due to the parallelized nature of GPU hardware, it is essential to simultaneously transport particles of the same type and similar energies but separated spatially to yield a high efficiency. We present three methods for phase-space implementation that have been integrated into the most recent version of the GPU-based Monte Carlo radiotherapy dose calculation package gDPM v3.0. The first method is to sequentially read particles from a patient-dependent phase-space and sort them on-the-fly based on particle type and energy. The second method supplements this with a simple secondary collimator model and fluence map implementation so that patient-independent phase-space sources can be used. Finally, as the third method (called the phase-space-let, or PSL, method) we introduce a novel source implementation utilizing pre-processed patient-independent phase-spaces that are sorted by particle type, energy and position. Position bins located outside a rectangular region of interest enclosing the treatment field are ignored, substantially decreasing simulation time with little effect on the final dose distribution. The three methods were validated in absolute dose against BEAMnrc/DOSXYZnrc and compared using gamma-index tests (2%/2 mm above the 10% isodose). It was found that the PSL method has the optimal balance between accuracy and efficiency and thus is used as the default method in gDPM v3.0. Using the PSL method, open fields of 4 × 4, 10 × 10 and 30 × 30 cm
Suitable Candidates for Monte Carlo Solutions.
ERIC Educational Resources Information Center
Lewis, Jerome L.
1998-01-01
Discusses Monte Carlo methods, powerful and useful techniques that rely on random numbers to solve deterministic problems whose solutions may be too difficult to obtain using conventional mathematics. Reviews two excellent candidates for the application of Monte Carlo methods. (ASK)
A Classroom Note on Monte Carlo Integration.
ERIC Educational Resources Information Center
Kolpas, Sid
1998-01-01
The Monte Carlo method provides approximate solutions to a variety of mathematical problems by performing random sampling simulations with a computer. Presents a program written in Quick BASIC simulating the steps of the Monte Carlo method. (ASK)
Applications of Monte Carlo Methods in Calculus.
ERIC Educational Resources Information Center
Gordon, Sheldon P.; Gordon, Florence S.
1990-01-01
Discusses the application of probabilistic ideas, especially Monte Carlo simulation, to calculus. Describes some applications using the Monte Carlo method: Riemann sums; maximizing and minimizing a function; mean value theorems; and testing conjectures. (YP)
A Markov-Chain Monte-Carlo Based Method for Flaw Detection in Beams
Glaser, R E; Lee, C L; Nitao, J J; Hickling, T L; Hanley, W G
2006-09-28
A Bayesian inference methodology using a Markov Chain Monte Carlo (MCMC) sampling procedure is presented for estimating the parameters of computational structural models. This methodology combines prior information, measured data, and forward models to produce a posterior distribution for the system parameters of structural models that is most consistent with all available data. The MCMC procedure is based upon a Metropolis-Hastings algorithm that is shown to function effectively with noisy data, incomplete data sets, and mismatched computational nodes/measurement points. A series of numerical test cases based upon a cantilever beam is presented. The results demonstrate that the algorithm is able to estimate model parameters utilizing experimental data for the nodal displacements resulting from specified forces.
A Monte Carlo template based analysis for air-Cherenkov arrays
NASA Astrophysics Data System (ADS)
Parsons, R. D.; Hinton, J. A.
2014-04-01
We present a high-performance event reconstruction algorithm: an Image Pixel-wise fit for Atmospheric Cherenkov Telescopes (ImPACT). The reconstruction algorithm is based around the likelihood fitting of camera pixel amplitudes to an expected image template. A maximum likelihood fit is performed to find the best-fit shower parameters. A related reconstruction algorithm has already been shown to provide significant improvements over traditional reconstruction for both the CAT and H.E.S.S. experiments. We demonstrate a significant improvement to the template generation step of the procedure, by the use of a full Monte Carlo air shower simulation in combination with a ray-tracing optics simulation to more accurately model the expected camera images. This reconstruction step is combined with an MVA-based background rejection.
Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems
Ma, Xiaoyao; Hall, Randall W.; Löffler, Frank; Kowalski, Karol; Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana
2016-01-07
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H{sub 2}O, N{sub 2}, and F{sub 2} molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.
Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems
Ma, Xiaoyao; Hall, Randall W.; Löffler, Frank; Kowalski, Karol; Bhaskaran-Nair, Kiran; Jarrell, Mark; Moreno, Juana
2016-01-07
The Sign Learning Kink (SiLK) based Quantum Monte Carlo (QMC) method is used to calculate the ab initio ground state energies for multiple geometries of the H2O, N2, and F2 molecules. The method is based on Feynman’s path integral formulation of quantum mechanics and has two stages. The first stage is called the learning stage and reduces the well-known QMC minus sign problem by optimizing the linear combinations of Slater determinants which are used in the second stage, a conventional QMC simulation. The method is tested using different vector spaces and compared to the results of other quantum chemical methods and to exact diagonalization. Our findings demonstrate that the SiLK method is accurate and reduces or eliminates the minus sign problem.
Monte-Carlo-based inversion scheme for 3D quantitative photoacoustic tomography
NASA Astrophysics Data System (ADS)
Kaplan, Bernhard A.; Buchmann, Jens; Prohaska, Steffen; Laufer, Jan
2017-03-01
The goal of quantitative photoacoustic tomography (qPAT) is to recover maps of the chromophore distributions from multiwavelength images of the initial pressure. Model-based inversions that incorporate the physical processes underlying the photoacoustic (PA) signal generation represent a promising approach. Monte-Carlo models of the light transport are computationally expensive, but provide accurate fluence distributions predictions, especially in the ballistic and quasi-ballistic regimes. Here, we focus on the inverse problem of 3D qPAT of blood oxygenation and investigate the application of the Monte-Carlo method in a model-based inversion scheme. A forward model of the light transport based on the MCX simulator and acoustic propagation modeled by the k-Wave toolbox was used to generate a PA image data set acquired in a tissue phantom over a planar detection geometry. The combination of the optical and acoustic models is shown to account for limited-view artifacts. In addition, the errors in the fluence due to, for example, partial volume artifacts and absorbers immediately adjacent to the region of interest are investigated. To accomplish large-scale inversions in 3D, the number of degrees of freedom is reduced by applying image segmentation to the initial pressure distribution to extract a limited number of regions with homogeneous optical parameters. The absorber concentration in the tissue phantom was estimated using a coordinate descent parameter search based on the comparison between measured and modeled PA spectra. The estimated relative concentrations using this approach lie within 5 % compared to the known concentrations. Finally, we discuss the feasibility of this approach to recover the blood oxygenation from experimental data.
GGEMS-Brachy: GPU GEant4-based Monte Carlo simulation for brachytherapy applications
NASA Astrophysics Data System (ADS)
Lemaréchal, Yannick; Bert, Julien; Falconnet, Claire; Després, Philippe; Valeri, Antoine; Schick, Ulrike; Pradier, Olivier; Garcia, Marie-Paule; Boussion, Nicolas; Visvikis, Dimitris
2015-07-01
In brachytherapy, plans are routinely calculated using the AAPM TG43 formalism which considers the patient as a simple water object. An accurate modeling of the physical processes considering patient heterogeneity using Monte Carlo simulation (MCS) methods is currently too time-consuming and computationally demanding to be routinely used. In this work we implemented and evaluated an accurate and fast MCS on Graphics Processing Units (GPU) for brachytherapy low dose rate (LDR) applications. A previously proposed Geant4 based MCS framework implemented on GPU (GGEMS) was extended to include a hybrid GPU navigator, allowing navigation within voxelized patient specific images and analytically modeled 125I seeds used in LDR brachytherapy. In addition, dose scoring based on track length estimator including uncertainty calculations was incorporated. The implemented GGEMS-brachy platform was validated using a comparison with Geant4 simulations and reference datasets. Finally, a comparative dosimetry study based on the current clinical standard (TG43) and the proposed platform was performed on twelve prostate cancer patients undergoing LDR brachytherapy. Considering patient 3D CT volumes of 400 × 250 × 65 voxels and an average of 58 implanted seeds, the mean patient dosimetry study run time for a 2% dose uncertainty was 9.35 s (≈500 ms 10-6 simulated particles) and 2.5 s when using one and four GPUs, respectively. The performance of the proposed GGEMS-brachy platform allows envisaging the use of Monte Carlo simulation based dosimetry studies in brachytherapy compatible with clinical practice. Although the proposed platform was evaluated for prostate cancer, it is equally applicable to other LDR brachytherapy clinical applications. Future extensions will allow its application in high dose rate brachytherapy applications.
NASA Astrophysics Data System (ADS)
Lima, Ivan T., Jr.; Kalra, Anshul; Hernández-Figueroa, Hugo E.; Sherif, Sherif S.
2012-03-01
Computer simulations of light transport in multi-layered turbid media are an effective way to theoretically investigate light transport in tissue, which can be applied to the analysis, design and optimization of optical coherence tomography (OCT) systems. We present a computationally efficient method to calculate the diffuse reflectance due to ballistic and quasi-ballistic components of photons scattered in turbid media, which represents the signal in optical coherence tomography systems. Our importance sampling based Monte Carlo method enables the calculation of the OCT signal with less than one hundredth of the computational time required by the conventional Monte Carlo method. It also does not produce a systematic bias in the statistical result that is typically observed in existing methods to speed up Monte Carlo simulations of light transport in tissue. This method can be used to assess and optimize the performance of existing OCT systems, and it can also be used to design novel OCT systems.
Monte Carlo Simulation for Perusal and Practice.
ERIC Educational Resources Information Center
Brooks, Gordon P.; Barcikowski, Robert S.; Robey, Randall R.
The meaningful investigation of many problems in statistics can be solved through Monte Carlo methods. Monte Carlo studies can help solve problems that are mathematically intractable through the analysis of random samples from populations whose characteristics are known to the researcher. Using Monte Carlo simulation, the values of a statistic are…
Full modelling of the MOSAIC animal PET system based on the GATE Monte Carlo simulation code
NASA Astrophysics Data System (ADS)
Merheb, C.; Petegnief, Y.; Talbot, J. N.
2007-02-01
within 9%. For a 410-665 keV energy window, the measured sensitivity for a centred point source was 1.53% and mouse and rat scatter fractions were respectively 12.0% and 18.3%. The scattered photons produced outside the rat and mouse phantoms contributed to 24% and 36% of total simulated scattered coincidences. Simulated and measured single and prompt count rates agreed well for activities up to the electronic saturation at 110 MBq for the mouse and rat phantoms. Volumetric spatial resolution was 17.6 µL at the centre of the FOV with differences less than 6% between experimental and simulated spatial resolution values. The comprehensive evaluation of the Monte Carlo modelling of the Mosaic™ system demonstrates that the GATE package is adequately versatile and appropriate to accurately describe the response of an Anger logic based animal PET system.
A Monte Carlo simulation based inverse propagation method for stochastic model updating
NASA Astrophysics Data System (ADS)
Bao, Nuo; Wang, Chunjie
2015-08-01
This paper presents an efficient stochastic model updating method based on statistical theory. Significant parameters have been selected implementing the F-test evaluation and design of experiments, and then the incomplete fourth-order polynomial response surface model (RSM) has been developed. Exploiting of the RSM combined with Monte Carlo simulation (MCS), reduces the calculation amount and the rapid random sampling becomes possible. The inverse uncertainty propagation is given by the equally weighted sum of mean and covariance matrix objective functions. The mean and covariance of parameters are estimated synchronously by minimizing the weighted objective function through hybrid of particle-swarm and Nelder-Mead simplex optimization method, thus the better correlation between simulation and test is achieved. Numerical examples of a three degree-of-freedom mass-spring system under different conditions and GARTEUR assembly structure validated the feasibility and effectiveness of the proposed method.
NASA Astrophysics Data System (ADS)
Ma, X. B.; Qiu, R. M.; Chen, Y. X.
2017-02-01
Uncertainties regarding fission fractions are essential in understanding antineutrino flux predictions in reactor antineutrino experiments. A new Monte Carlo-based method to evaluate the covariance coefficients between isotopes is proposed. The covariance coefficients are found to vary with reactor burnup and may change from positive to negative because of balance effects in fissioning. For example, between 235U and 239Pu, the covariance coefficient changes from 0.15 to -0.13. Using the equation relating fission fraction and atomic density, consistent uncertainties in the fission fraction and covariance matrix were obtained. The antineutrino flux uncertainty is 0.55%, which does not vary with reactor burnup. The new value is about 8.3% smaller.
Prediction of gas chromatographic retention indices based on Monte Carlo method.
Veselinović, Aleksandar M; Velimorović, Dragan; Kaličanin, Biljana; Toropova, Alla; Toropov, Andrey; Veselinović, Jovana
2017-06-01
A new method for the prediction of retention indices using Monte Carlo method and based on local graph invariants and SMILES notation of studied compounds has been presented. Very satisfactory results were obtained with the proposed method, since robust model with good statistical quality was developed. The predictive potential of the applied approach was tested and the robustness of the model was proven with different methods. The best calculated QSPR model had following statistical parameters: r(2)=0.8097 for the training set and r(2)=0.9372 for the test set. Structural indicators defined responsible for the increases and decreases of gas chromatographic retention indices activity have been calculated. Copyright © 2017 Elsevier B.V. All rights reserved.
Monte Carlo tests of the Rasch model based on scalability coefficients.
Christensen, Karl Bang; Kreiner, Svend
2010-02-01
For item responses fitting the Rasch model, the assumptions underlying the Mokken model of double monotonicity are met. This makes non-parametric item response theory a natural starting-point for Rasch item analysis. This paper studies scalability coefficients based on Loevinger's H coefficient that summarizes the number of Guttman errors in the data matrix. These coefficients are shown to yield efficient tests of the Rasch model using p-values computed using Markov chain Monte Carlo methods. The power of the tests of unequal item discrimination, and their ability to distinguish between local dependence and unequal item discrimination, are discussed. The methods are illustrated and motivated using a simulation study and a real data example.
EUPDF: An Eulerian-Based Monte Carlo Probability Density Function (PDF) Solver. User's Manual
NASA Technical Reports Server (NTRS)
Raju, M. S.
1998-01-01
EUPDF is an Eulerian-based Monte Carlo PDF solver developed for application with sprays, combustion, parallel computing and unstructured grids. It is designed to be massively parallel and could easily be coupled with any existing gas-phase flow and spray solvers. The solver accommodates the use of an unstructured mesh with mixed elements of either triangular, quadrilateral, and/or tetrahedral type. The manual provides the user with the coding required to couple the PDF code to any given flow code and a basic understanding of the EUPDF code structure as well as the models involved in the PDF formulation. The source code of EUPDF will be available with the release of the National Combustion Code (NCC) as a complete package.
Monte Carlo based statistical power analysis for mediation models: methods and software.
Zhang, Zhiyong
2014-12-01
The existing literature on statistical power analysis for mediation models often assumes data normality and is based on a less powerful Sobel test instead of the more powerful bootstrap test. This study proposes to estimate statistical power to detect mediation effects on the basis of the bootstrap method through Monte Carlo simulation. Nonnormal data with excessive skewness and kurtosis are allowed in the proposed method. A free R package called bmem is developed to conduct the power analysis discussed in this study. Four examples, including a simple mediation model, a multiple-mediator model with a latent mediator, a multiple-group mediation model, and a longitudinal mediation model, are provided to illustrate the proposed method.
Wavelength selection of bidirectional laser transmission based on Monte Carlo method
NASA Astrophysics Data System (ADS)
Zhang, Chuanxin; Zhang, Xusheng; Yuan, Yuan; Ai, Qing; Tan, Heping
2017-06-01
The laser detection technology in uncertain and dynamic environments is of utmost importance in many fields. A model of transient radiative transfer of bidirectional path laser based on Monte Carlo method is developed to investigate the optimum wavelength of active detector at complex atmospheric conditions. The radiative parameters of atmosphere are calculated by HITRAN database and Mie theory at several typical atmospheric conditions including the standard atmosphere, urban aerosol, and radiation fog. Transmission characteristics for five spectral bands at the above atmospheric conditions are calculated by this model. The optimal transmission ability occurred in bands 0.2-0.5, 1.4-1.6, and 0.75-1.25 μm on the condition of standard atmosphere, urban aerosol, and radiation fog, respectively. All results provide effective reference and basic support for choosing the optimal spectral band for active detection.
Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator.
Bol, G H; Hissoiny, S; Lagendijk, J J W; Raaymakers, B W
2012-03-07
The MRI accelerator, a combination of a 6 MV linear accelerator with a 1.5 T MRI, facilitates continuous patient anatomy updates regarding translations, rotations and deformations of targets and organs at risk. Accounting for these demands high speed, online intensity-modulated radiotherapy (IMRT) re-optimization. In this paper, a fast IMRT optimization system is described which combines a GPU-based Monte Carlo dose calculation engine for online beamlet generation and a fast inverse dose optimization algorithm. Tightly conformal IMRT plans are generated for four phantom cases and two clinical cases (cervix and kidney) in the presence of the magnetic fields of 0 and 1.5 T. We show that for the presented cases the beamlet generation and optimization routines are fast enough for online IMRT planning. Furthermore, there is no influence of the magnetic field on plan quality and complexity, and equal optimization constraints at 0 and 1.5 T lead to almost identical dose distributions.
Monte Carlo simulation of non-invasive glucose measurement based on FMCW LIDAR
NASA Astrophysics Data System (ADS)
Xiong, Bing; Wei, Wenxiong; Liu, Nan; He, Jian-Jun
2010-11-01
Continuous non-invasive glucose monitoring is a powerful tool for the treatment and management of diabetes. A glucose measurement method, with the potential advantage of miniaturizability with no moving parts, based on the frequency modulated continuous wave (FMCW) LIDAR technology is proposed and investigated. The system mainly consists of an integrated near-infrared tunable semiconductor laser and a detector, using heterodyne technology to convert the signal from time-domain to frequency-domain. To investigate the feasibility of the method, Monte Carlo simulations have been performed on tissue phantoms with optical parameters similar to those of human interstitial fluid. The simulation showed that the sensitivity of the FMCW LIDAR system to glucose concentration can reach 0.2mM. Our analysis suggests that the FMCW LIDAR technique has good potential for noninvasive blood glucose monitoring.
Fast online Monte Carlo-based IMRT planning for the MRI linear accelerator
NASA Astrophysics Data System (ADS)
Bol, G. H.; Hissoiny, S.; Lagendijk, J. J. W.; Raaymakers, B. W.
2012-03-01
The MRI accelerator, a combination of a 6 MV linear accelerator with a 1.5 T MRI, facilitates continuous patient anatomy updates regarding translations, rotations and deformations of targets and organs at risk. Accounting for these demands high speed, online intensity-modulated radiotherapy (IMRT) re-optimization. In this paper, a fast IMRT optimization system is described which combines a GPU-based Monte Carlo dose calculation engine for online beamlet generation and a fast inverse dose optimization algorithm. Tightly conformal IMRT plans are generated for four phantom cases and two clinical cases (cervix and kidney) in the presence of the magnetic fields of 0 and 1.5 T. We show that for the presented cases the beamlet generation and optimization routines are fast enough for online IMRT planning. Furthermore, there is no influence of the magnetic field on plan quality and complexity, and equal optimization constraints at 0 and 1.5 T lead to almost identical dose distributions.
Giuseppe Palmiotti
2015-05-01
In this work, the implementation of a collision history-based approach to sensitivity/perturbation calculations in the Monte Carlo code SERPENT is discussed. The proposed methods allow the calculation of the eects of nuclear data perturbation on several response functions: the eective multiplication factor, reaction rate ratios and bilinear ratios (e.g., eective kinetics parameters). SERPENT results are compared to ERANOS and TSUNAMI Generalized Perturbation Theory calculations for two fast metallic systems and for a PWR pin-cell benchmark. New methods for the calculation of sensitivities to angular scattering distributions are also presented, which adopts fully continuous (in energy and angle) Monte Carlo estimators.
Adiabatic optimization versus diffusion Monte Carlo methods
NASA Astrophysics Data System (ADS)
Jarret, Michael; Jordan, Stephen P.; Lackey, Brad
2016-10-01
Most experimental and theoretical studies of adiabatic optimization use stoquastic Hamiltonians, whose ground states are expressible using only real nonnegative amplitudes. This raises a question as to whether classical Monte Carlo methods can simulate stoquastic adiabatic algorithms with polynomial overhead. Here we analyze diffusion Monte Carlo algorithms. We argue that, based on differences between L1 and L2 normalized states, these algorithms suffer from certain obstructions preventing them from efficiently simulating stoquastic adiabatic evolution in generality. In practice however, we obtain good performance by introducing a method that we call Substochastic Monte Carlo. In fact, our simulations are good classical optimization algorithms in their own right, competitive with the best previously known heuristic solvers for MAX-k -SAT at k =2 ,3 ,4 .
Shell model the Monte Carlo way
Ormand, W.E.
1995-03-01
The formalism for the auxiliary-field Monte Carlo approach to the nuclear shell model is presented. The method is based on a linearization of the two-body part of the Hamiltonian in an imaginary-time propagator using the Hubbard-Stratonovich transformation. The foundation of the method, as applied to the nuclear many-body problem, is discussed. Topics presented in detail include: (1) the density-density formulation of the method, (2) computation of the overlaps, (3) the sign of the Monte Carlo weight function, (4) techniques for performing Monte Carlo sampling, and (5) the reconstruction of response functions from an imaginary-time auto-correlation function using MaxEnt techniques. Results obtained using schematic interactions, which have no sign problem, are presented to demonstrate the feasibility of the method, while an extrapolation method for realistic Hamiltonians is presented. In addition, applications at finite temperature are outlined.
Geodesic Monte Carlo on Embedded Manifolds
Byrne, Simon; Girolami, Mark
2013-01-01
Markov chain Monte Carlo methods explicitly defined on the manifold of probability distributions have recently been established. These methods are constructed from diffusions across the manifold and the solution of the equations describing geodesic flows in the Hamilton–Jacobi representation. This paper takes the differential geometric basis of Markov chain Monte Carlo further by considering methods to simulate from probability distributions that themselves are defined on a manifold, with common examples being classes of distributions describing directional statistics. Proposal mechanisms are developed based on the geodesic flows over the manifolds of support for the distributions, and illustrative examples are provided for the hypersphere and Stiefel manifold of orthonormal matrices. PMID:25309024
Monte Carlo simulation of neutron scattering instruments
Seeger, P.A.
1995-12-31
A library of Monte Carlo subroutines has been developed for the purpose of design of neutron scattering instruments. Using small-angle scattering as an example, the philosophy and structure of the library are described and the programs are used to compare instruments at continuous wave (CW) and long-pulse spallation source (LPSS) neutron facilities. The Monte Carlo results give a count-rate gain of a factor between 2 and 4 using time-of-flight analysis. This is comparable to scaling arguments based on the ratio of wavelength bandwidth to resolution width.
Effects of Hounsfield number conversion on CT based proton Monte Carlo dose calculations
Jiang Hongyu; Seco, Joao; Paganetti, Harald
2007-04-15
The Monte Carlo method provides the most accurate dose calculations on a patient computed tomography (CT) geometry. The increase in accuracy is, at least in part, due to the fact that instead of treating human tissues as water of various densities as in analytical algorithms, the Monte Carlo method allows human tissues to be characterized by elemental composition and mass density, and hence allows the accurate consideration of all relevant electromagnetic and nuclear interactions. On the other hand, the algorithm to convert CT Hounsfield numbers to tissue materials for Monte Carlo dose calculation introduces uncertainties. There is not a simple one to one correspondence between Hounsfield numbers and tissue materials. To investigate the effects of Hounsfield number conversion for proton Monte Carlo dose calculations, clinical proton treatment plans were simulated using the Geant4 Monte Carlo code. Three Hounsfield number to material conversion methods were studied. The results were compared in forms of dose volume histograms of gross tumor volume and clinical target volume. The differences found are generally small but can be dosimetrically significant. Further, different methods may cause deviations in the predicted proton beam range in particular for deep proton fields. Typically, slight discrepancies in mass density assignments play only a minor role in the target region, whereas more significant effects are caused by different assignments in elemental compositions. In the presence of large tissue inhomogeneities, for head and neck treatments, treatment planning decisions could be affected by these differences because of deviations in the predicted tumor coverage. Outside the target area, differences in elemental composition and mass density assignments both may play a role. This can lead to pronounced effects for organs at risk, in particular in the spread-out Bragg peak penumbra or distal regions. In addition, the significance of the elemental composition
Effects of Hounsfield number conversion on CT based proton Monte Carlo dose calculations
Jiang, Hongyu; Seco, Joao; Paganetti, Harald
2008-01-01
The Monte Carlo method provides the most accurate dose calculations on a patient computed tomography (CT) geometry. The increase in accuracy is, at least in part, due to the fact that instead of treating human tissues as water of various densities as in analytical algorithms, the Monte Carlo method allows human tissues to be characterized by elemental composition and mass density, and hence allows the accurate consideration of all relevant electromagnetic and nuclear interactions. On the other hand, the algorithm to convert CT Hounsfield numbers to tissue materials for Monte Carlo dose calculation introduces uncertainties. There is not a simple one to one correspondence between Hounsfield numbers and tissue materials. To investigate the effects of Hounsfield number conversion for proton Monte Carlo dose calculations, clinical proton treatment plans were simulated using the Geant4 Monte Carlo code. Three Hounsfield number to material conversion methods were studied. The results were compared in forms of dose volume histograms of gross tumor volume and clinical target volume. The differences found are generally small but can be dosimetrically significant. Further, different methods may cause deviations in the predicted proton beam range in particular for deep proton fields. Typically, slight discrepancies in mass density assignments play only a minor role in the target region, whereas more significant effects are caused by different assignments in elemental compositions. In the presence of large tissue inhomogeneities, for head and neck treatments, treatment planning decisions could be affected by these differences because of deviations in the predicted tumor coverage. Outside the target area, differences in elemental composition and mass density assignments both may play a role. This can lead to pronounced effects for organs at risk, in particular in the spread-out Bragg peak penumbra or distal regions. In addition, the significance of the elemental composition
Effects of Hounsfield number conversion on CT based proton Monte Carlo dose calculations.
Jiang, Hongyu; Seco, Joao; Paganetti, Harald
2007-04-01
The Monte Carlo method provides the most accurate dose calculations on a patient computed tomography (CT) geometry. The increase in accuracy is, at least in part, due to the fact that instead of treating human tissues as water of various densities as in analytical algorithms, the Monte Carlo method allows human tissues to be characterized by elemental composition and mass density, and hence allows the accurate consideration of all relevant electromagnetic and nuclear interactions. On the other hand, the algorithm to convert CT Hounsfield numbers to tissue materials for Monte Carlo dose calculation introduces uncertainties. There is not a simple one to one correspondence between Hounsfield numbers and tissue materials. To investigate the effects of Hounsfield number conversion for proton Monte Carlo dose calculations, clinical proton treatment plans were simulated using the Geant4 Monte Carlo code. Three Hounsfield number to material conversion methods were studied. The results were compared in forms of dose volume histograms of gross tumor volume and clinical target volume. The differences found are generally small but can be dosimetrically significant. Further, different methods may cause deviations in the predicted proton beam range in particular for deep proton fields. Typically, slight discrepancies in mass density assignments play only a minor role in the target region, whereas more significant effects are caused by different assignments in elemental compositions. In the presence of large tissue inhomogeneities, for head and neck treatments, treatment planning decisions could be affected by these differences because of deviations in the predicted tumor coverage. Outside the target area, differences in elemental composition and mass density assignments both may play a role. This can lead to pronounced effects for organs at risk, in particular in the spread-out Bragg peak penumbra or distal regions. In addition, the significance of the elemental composition
Zimmerman, G.B.
1997-06-24
Monte Carlo methods appropriate to simulate the transport of x-rays, neutrons, ion and electrons in Inertial Confinement Fusion targets are described and analyzed. The Implicit Monte Carlo method of x-ray transport handles symmetry within indirect drive ICF hohlraums well, but can be improved 50X in efficiency by angular biasing the x-rays towards the fuel capsule. Accurate simulation of thermonuclear burns nd burn diagnostics involves detailed particle source spectra, charged particle ranges, inflight reaction kinematics, corrections for bulk and thermal Doppler effects and variance reduction to obtain adequate statistics for rare events. It is found that the effects of angular Coulomb scattering must be included in models of charged particle transport through heterogeneous materials.
To help address the Food Quality Protection Act of 1996, a physically-based, two-stage Monte Carlo probabilistic model has been developed to quantify and analyze aggregate exposure and dose to pesticides via multiple routes and pathways. To illustrate model capabilities and ide...
To help address the Food Quality Protection Act of 1996, a physically-based, two-stage Monte Carlo probabilistic model has been developed to quantify and analyze aggregate exposure and dose to pesticides via multiple routes and pathways. To illustrate model capabilities and ide...
Monte Carlo methods on advanced computer architectures
Martin, W.R.
1991-12-31
Monte Carlo methods describe a wide class of computational methods that utilize random numbers to perform a statistical simulation of a physical problem, which itself need not be a stochastic process. For example, Monte Carlo can be used to evaluate definite integrals, which are not stochastic processes, or may be used to simulate the transport of electrons in a space vehicle, which is a stochastic process. The name Monte Carlo came about during the Manhattan Project to describe the new mathematical methods being developed which had some similarity to the games of chance played in the casinos of Monte Carlo. Particle transport Monte Carlo is just one application of Monte Carlo methods, and will be the subject of this review paper. Other applications of Monte Carlo, such as reliability studies, classical queueing theory, molecular structure, the study of phase transitions, or quantum chromodynamics calculations for basic research in particle physics, are not included in this review. The reference by Kalos is an introduction to general Monte Carlo methods and references to other applications of Monte Carlo can be found in this excellent book. For the remainder of this paper, the term Monte Carlo will be synonymous to particle transport Monte Carlo, unless otherwise noted. 60 refs., 14 figs., 4 tabs.
Monte Carlo Simulation of Counting Experiments.
ERIC Educational Resources Information Center
Ogden, Philip M.
A computer program to perform a Monte Carlo simulation of counting experiments was written. The program was based on a mathematical derivation which started with counts in a time interval. The time interval was subdivided to form a binomial distribution with no two counts in the same subinterval. Then the number of subintervals was extended to…
A Monte Carlo exploration of threefold base geometries for 4d F-theory vacua
Taylor, Washington; Wang, Yi-Nan
2016-01-22
Here, we use Monte Carlo methods to explore the set of toric threefold bases that support elliptic Calabi-Yau fourfolds for F-theory compactifications to four dimensions, and study the distribution of geometrically non-Higgsable gauge groups, matter, and quiver structure. We estimate the number of distinct threefold bases in the connected set studied to be ~ 1048. Moreover, the distribution of bases peaks around h1,1 ~ 82. All bases encountered after "thermalization" have some geometric non-Higgsable structure. We also find that the number of non-Higgsable gauge group factors grows roughly linearly in h1,1 of the threefold base. Typical bases have ~ 6more » isolated gauge factors as well as several larger connected clusters of gauge factors with jointly charged matter. Approximately 76% of the bases sampled contain connected two-factor gauge group products of the form SU(3) x SU(2), which may act as the non-Abelian part of the standard model gauge group. SU(3) x SU(2) is the third most common connected two-factor product group, following SU(2) x SU(2) and G2 x SU(2), which arise more frequently.« less
A Monte Carlo exploration of threefold base geometries for 4d F-theory vacua
NASA Astrophysics Data System (ADS)
Taylor, Washington; Wang, Yi-Nan
2016-01-01
We use Monte Carlo methods to explore the set of toric threefold bases that support elliptic Calabi-Yau fourfolds for F-theory compactifications to four dimensions, and study the distribution of geometrically non-Higgsable gauge groups, matter, and quiver structure. We estimate the number of distinct threefold bases in the connected set studied to be ˜ 1048. The distribution of bases peaks around h 1,1 ˜ 82. All bases encountered after "thermalization" have some geometric non-Higgsable structure. We find that the number of non-Higgsable gauge group factors grows roughly linearly in h 1,1 of the threefold base. Typical bases have ˜ 6 isolated gauge factors as well as several larger connected clusters of gauge factors with jointly charged matter. Approximately 76% of the bases sampled contain connected two-factor gauge group products of the form SU(3) × SU(2), which may act as the non-Abelian part of the standard model gauge group. SU(3) × SU(2) is the third most common connected two-factor product group, following SU(2) × SU(2) and G 2 × SU(2), which arise more frequently.
A Monte Carlo exploration of threefold base geometries for 4d F-theory vacua
Taylor, Washington; Wang, Yi-Nan
2016-01-22
Here, we use Monte Carlo methods to explore the set of toric threefold bases that support elliptic Calabi-Yau fourfolds for F-theory compactifications to four dimensions, and study the distribution of geometrically non-Higgsable gauge groups, matter, and quiver structure. We estimate the number of distinct threefold bases in the connected set studied to be ~ 10^{48}. Moreover, the distribution of bases peaks around h^{1,1} ~ 82. All bases encountered after "thermalization" have some geometric non-Higgsable structure. We also find that the number of non-Higgsable gauge group factors grows roughly linearly in h^{1,1} of the threefold base. Typical bases have ~ 6 isolated gauge factors as well as several larger connected clusters of gauge factors with jointly charged matter. Approximately 76% of the bases sampled contain connected two-factor gauge group products of the form SU(3) x SU(2), which may act as the non-Abelian part of the standard model gauge group. SU(3) x SU(2) is the third most common connected two-factor product group, following SU(2) x SU(2) and G2 x SU(2), which arise more frequently.
Monte Carlo simulation of grating-based neutron phase contrast imaging at CPHS
NASA Astrophysics Data System (ADS)
Zhang, Ran; Chen, Zhiqiang; Huang, Zhifeng; Xiao, Yongshun; Wang, Xuewu; Wie, Jie; Loong, C.-K.
2011-09-01
Since the launching of the Compact Pulsed Hadron Source (CPHS) project of Tsinghua University in 2009, works have begun on the design and engineering of an imaging/radiography instrument for the neutron source provided by CPHS. The instrument will perform basic tasks such as transmission imaging and computerized tomography. Additionally, we include in the design the utilization of coded-aperture and grating-based phase contrast methodology, as well as the options of prompt gamma-ray analysis and neutron-energy selective imaging. Previously, we had implemented the hardware and data-analysis software for grating-based X-ray phase contrast imaging. Here, we investigate Geant4-based Monte Carlo simulations of neutron refraction phenomena and then model the grating-based neutron phase contrast imaging system according to the classic-optics-based method. The simulated experimental results of the retrieving phase shift gradient information by five-step phase-stepping approach indicate the feasibility of grating-based neutron phase contrast imaging as an option for the cold neutron imaging instrument at the CPHS.
Uncertainties in Monte Carlo-based absorbed dose calculations for an experimental benchmark
NASA Astrophysics Data System (ADS)
Renner, F.; Wulff, J.; Kapsch, R.-P.; Zink, K.
2015-10-01
There is a need to verify the accuracy of general purpose Monte Carlo codes like EGSnrc, which are commonly employed for investigations of dosimetric problems in radiation therapy. A number of experimental benchmarks have been published to compare calculated values of absorbed dose to experimentally determined values. However, there is a lack of absolute benchmarks, i.e. benchmarks without involved normalization which may cause some quantities to be cancelled. Therefore, at the Physikalisch-Technische Bundesanstalt a benchmark experiment was performed, which aimed at the absolute verification of radiation transport calculations for dosimetry in radiation therapy. A thimble-type ionization chamber in a solid phantom was irradiated by high-energy bremsstrahlung and the mean absorbed dose in the sensitive volume was measured per incident electron of the target. The characteristics of the accelerator and experimental setup were precisely determined and the results of a corresponding Monte Carlo simulation with EGSnrc are presented within this study. For a meaningful comparison, an analysis of the uncertainty of the Monte Carlo simulation is necessary. In this study uncertainties with regard to the simulation geometry, the radiation source, transport options of the Monte Carlo code and specific interaction cross sections are investigated, applying the general methodology of the Guide to the expression of uncertainty in measurement. Besides studying the general influence of changes in transport options of the EGSnrc code, uncertainties are analyzed by estimating the sensitivity coefficients of various input quantities in a first step. Secondly, standard uncertainties are assigned to each quantity which are known from the experiment, e.g. uncertainties for geometric dimensions. Data for more fundamental quantities such as photon cross sections and the I-value of electron stopping powers are taken from literature. The significant uncertainty contributions are identified as
Uncertainties in Monte Carlo-based absorbed dose calculations for an experimental benchmark.
Renner, F; Wulff, J; Kapsch, R-P; Zink, K
2015-10-07
There is a need to verify the accuracy of general purpose Monte Carlo codes like EGSnrc, which are commonly employed for investigations of dosimetric problems in radiation therapy. A number of experimental benchmarks have been published to compare calculated values of absorbed dose to experimentally determined values. However, there is a lack of absolute benchmarks, i.e. benchmarks without involved normalization which may cause some quantities to be cancelled. Therefore, at the Physikalisch-Technische Bundesanstalt a benchmark experiment was performed, which aimed at the absolute verification of radiation transport calculations for dosimetry in radiation therapy. A thimble-type ionization chamber in a solid phantom was irradiated by high-energy bremsstrahlung and the mean absorbed dose in the sensitive volume was measured per incident electron of the target. The characteristics of the accelerator and experimental setup were precisely determined and the results of a corresponding Monte Carlo simulation with EGSnrc are presented within this study. For a meaningful comparison, an analysis of the uncertainty of the Monte Carlo simulation is necessary. In this study uncertainties with regard to the simulation geometry, the radiation source, transport options of the Monte Carlo code and specific interaction cross sections are investigated, applying the general methodology of the Guide to the expression of uncertainty in measurement. Besides studying the general influence of changes in transport options of the EGSnrc code, uncertainties are analyzed by estimating the sensitivity coefficients of various input quantities in a first step. Secondly, standard uncertainties are assigned to each quantity which are known from the experiment, e.g. uncertainties for geometric dimensions. Data for more fundamental quantities such as photon cross sections and the I-value of electron stopping powers are taken from literature. The significant uncertainty contributions are identified as
Discrete diffusion Monte Carlo for frequency-dependent radiative transfer
Densmore, Jeffrey D; Kelly, Thompson G; Urbatish, Todd J
2010-11-17
Discrete Diffusion Monte Carlo (DDMC) is a technique for increasing the efficiency of Implicit Monte Carlo radiative-transfer simulations. In this paper, we develop an extension of DDMC for frequency-dependent radiative transfer. We base our new DDMC method on a frequency-integrated diffusion equation for frequencies below a specified threshold. Above this threshold we employ standard Monte Carlo. With a frequency-dependent test problem, we confirm the increased efficiency of our new DDMC technique.
NASA Astrophysics Data System (ADS)
Kanjilal, Oindrila; Manohar, C. S.
2017-07-01
The study considers the problem of simulation based time variant reliability analysis of nonlinear randomly excited dynamical systems. Attention is focused on importance sampling strategies based on the application of Girsanov's transformation method. Controls which minimize the distance function, as in the first order reliability method (FORM), are shown to minimize a bound on the sampling variance of the estimator for the probability of failure. Two schemes based on the application of calculus of variations for selecting control signals are proposed: the first obtains the control force as the solution of a two-point nonlinear boundary value problem, and, the second explores the application of the Volterra series in characterizing the controls. The relative merits of these schemes, vis-à-vis the method based on ideas from the FORM, are discussed. Illustrative examples, involving archetypal single degree of freedom (dof) nonlinear oscillators, and a multi-degree of freedom nonlinear dynamical system, are presented. The credentials of the proposed procedures are established by comparing the solutions with pertinent results from direct Monte Carlo simulations.
Comparison of adjoint and forward Monte Carlo based treatment planning for a realistic head phantom.
Nievaart, S; Moss, R; Wittig, A
2009-07-01
BNCT treatment planning can be improved by having the adjoint technique available in the Monte Carlo transport code. In adjoint MC, the simulated particles travel backwards instead of 'forward'. By speeding up the calculations, more beam positions can be investigated and thus a better plan can be composed. In a realistic head phantom with 10 disseminated lesions in the brain, the adjoint method is more favourable than the forward calculations whenever larger beam diameters are applied.
Uncertainty Analysis of Power Grid Investment Capacity Based on Monte Carlo
NASA Astrophysics Data System (ADS)
Qin, Junsong; Liu, Bingyi; Niu, Dongxiao
By analyzing the influence factors of the investment capacity of power grid, to depreciation cost, sales price and sales quantity, net profit, financing and GDP of the second industry as the dependent variable to build the investment capacity analysis model. After carrying out Kolmogorov-Smirnov test, get the probability distribution of each influence factor. Finally, obtained the grid investment capacity uncertainty of analysis results by Monte Carlo simulation.
Density-of-states based Monte Carlo methods for simulation of biological systems
NASA Astrophysics Data System (ADS)
Rathore, Nitin; Knotts, Thomas A.; de Pablo, Juan J.
2004-03-01
We have developed density-of-states [1] based Monte Carlo techniques for simulation of biological molecules. Two such methods are discussed. The first, Configurational Temperature Density of States (CTDOS) [2], relies on computing the density of states of a peptide system from knowledge of its configurational temperature. The reciprocal of this intrinsic temperature, computed from instantaneous configurational information of the system, is integrated to arrive at the density of states. The method shows improved efficiency and accuracy over techniques that are based on histograms of random visits to distinct energy states. The second approach, Expanded Ensemble Density of States (EXEDOS), incorporates elements from both the random walk method and the expanded ensemble formalism. It is used in this work to study mechanical deformation of model peptides. Results are presented in the form of force-extension curves and the corresponding potentials of mean force. The application of this proposed technique is further generalized to other biological systems; results will be presented for ion transport through protein channels, base stacking in nucleic acids and hybridization of DNA strands. [1]. F. Wang and D. P. Landau, Phys. Rev. Lett., 86, 2050 (2001). [2]. N. Rathore, T. A. Knotts IV and J. J. de Pablo, Biophys. J., Dec. (2003).
NASA Astrophysics Data System (ADS)
Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; Savara, Aditya
2017-10-01
Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of "KMC stiffness" (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps/CPU time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order to achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events-allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm is designed for use in achieving and simulating steady-state conditions in KMC simulations. As shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.
IR imaging simulation and analysis for aeroengine exhaust system based on reverse Monte Carlo method
NASA Astrophysics Data System (ADS)
Chen, Shiguo; Chen, Lihai; Mo, Dongla; Shi, Jingcheng
2014-11-01
The IR radiation characteristics of aeroengine are the important basis for IR stealth design and anti-stealth detection of aircraft. With the development of IR imaging sensor technology, the importance of aircraft IR stealth increases. An effort is presented to explore target IR radiation imaging simulation based on Reverse Monte Carlo Method (RMCM), which combined with the commercial CFD software. Flow and IR radiation characteristics of an aeroengine exhaust system are investigated, which developing a full size geometry model based on the actual parameters, using a flow-IR integration structured mesh, obtaining the engine performance parameters as the inlet boundary conditions of mixer section, and constructing a numerical simulation model of engine exhaust system of IR radiation characteristics based on RMCM. With the above models, IR radiation characteristics of aeroengine exhaust system is given, and focuses on the typical detecting band of IR spectral radiance imaging at azimuth 20°. The result shows that: (1) in small azimuth angle, the IR radiation is mainly from the center cone of all hot parts; near the azimuth 15°, mixer has the biggest radiation contribution, while center cone, turbine and flame stabilizer equivalent; (2) the main radiation components and space distribution in different spectrum is different, CO2 at 4.18, 4.33 and 4.45 micron absorption and emission obviously, H2O at 3.0 and 5.0 micron absorption and emission obviously.
Danielson, Thomas; Sutton, Jonathan E.; Hin, Céline; ...
2017-06-09
Lattice based Kinetic Monte Carlo (KMC) simulations offer a powerful simulation technique for investigating large reaction networks while retaining spatial configuration information, unlike ordinary differential equations. However, large chemical reaction networks can contain reaction processes with rates spanning multiple orders of magnitude. This can lead to the problem of “KMC stiffness” (similar to stiffness in differential equations), where the computational expense has the potential to be overwhelmed by very short time-steps during KMC simulations, with the simulation spending an inordinate amount of KMC steps / cpu-time simulating fast frivolous processes (FFPs) without progressing the system (reaction network). In order tomore » achieve simulation times that are experimentally relevant or desired for predictions, a dynamic throttling algorithm involving separation of the processes into speed-ranks based on event frequencies has been designed and implemented with the intent of decreasing the probability of FFP events, and increasing the probability of slow process events -- allowing rate limiting events to become more likely to be observed in KMC simulations. This Staggered Quasi-Equilibrium Rank-based Throttling for Steady-state (SQERTSS) algorithm designed for use in achieving and simulating steady-state conditions in KMC simulations. Lastly, as shown in this work, the SQERTSS algorithm also works for transient conditions: the correct configuration space and final state will still be achieved if the required assumptions are not violated, with the caveat that the sizes of the time-steps may be distorted during the transient period.« less
Seismic wavefield imaging based on the replica exchange Monte Carlo method
NASA Astrophysics Data System (ADS)
Kano, Masayuki; Nagao, Hiromichi; Ishikawa, Daichi; Ito, Shin-ichi; Sakai, Shin'ichi; Nakagawa, Shigeki; Hori, Muneo; Hirata, Naoshi
2016-11-01
Earthquakes sometimes cause serious disasters not only directly by ground motion itself but also secondarily by infrastructure damage, particularly in densely populated urban areas that have capital functions. To reduce the number and severity of secondary disasters, it is important to evaluate seismic hazards rapidly by analyzing the seismic responses of individual structures to input ground motions. We propose a method that integrates physics-based and data-driven approaches in order to obtain a seismic wavefield for use as input to a seismic response analysis. The new contribution of this study is the use of the replica exchange Monte Carlo (REMC) method, which is one of the Markov chain Monte Carlo (MCMC) methods, for estimation of a seismic wavefield, together with a one-dimensional (1-D) local subsurface structure and source information. Numerical tests were conducted to verify the proposed method, using synthetic observation data obtained from analytical solutions for two horizontally-layered subsurface structure models. The geometries of the observation sites were determined from the dense seismic observation array called the Metropolitan Seismic Observation network (MeSO-net), which has been in operation in the Tokyo metropolitan area in Japan since 2007. The results of the numerical tests show that the proposed method is able to search the parameters related to the source and the local subsurface structure in a broader parameter space than the Metropolis method, which is an ordinary MCMC method. The proposed method successfully reproduces a seismic wavefield consistent with a true wavefield. In contrast, ordinary kriging, which is a classical data-driven interpolation method for spatial data, is hardly able to reproduce a true wavefield, even in the low frequency bands. This suggests that it is essential to employ both physics-based and data-driven approaches in seismic wavefield imaging, utilizing seismograms from a dense seismic array. The REMC method
Seismic wavefield imaging based on the replica exchange Monte Carlo method
NASA Astrophysics Data System (ADS)
Kano, Masayuki; Nagao, Hiromichi; Ishikawa, Daichi; Ito, Shin-ichi; Sakai, Shin'ichi; Nakagawa, Shigeki; Hori, Muneo; Hirata, Naoshi
2017-01-01
Earthquakes sometimes cause serious disasters not only directly by ground motion itself but also secondarily by infrastructure damage, particularly in densely populated urban areas that have capital functions. To reduce the number and severity of secondary disasters, it is important to evaluate seismic hazards rapidly by analysing the seismic responses of individual structures to input ground motions. We propose a method that integrates physics-based and data-driven approaches in order to obtain a seismic wavefield for use as input to a seismic response analysis. The new contribution of this study is the use of the replica exchange Monte Carlo (REMC) method, which is one of the Markov chain Monte Carlo (MCMC) methods, for estimation of a seismic wavefield, together with a 1-D local subsurface structure and source information. Numerical tests were conducted to verify the proposed method, using synthetic observation data obtained from analytical solutions for two horizontally layered subsurface structure models. The geometries of the observation sites were determined from the dense seismic observation array called the Metropolitan Seismic Observation network, which has been in operation in the Tokyo metropolitan area in Japan since 2007. The results of the numerical tests show that the proposed method is able to search the parameters related to the source and the local subsurface structure in a broader parameter space than the Metropolis method, which is an ordinary MCMC method. The proposed method successfully reproduces a seismic wavefield consistent with a true wavefield. In contrast, ordinary kriging, which is a classical data-driven interpolation method for spatial data, is hardly able to reproduce a true wavefield, even in the low frequency bands. This suggests that it is essential to employ both physics-based and data-driven approaches in seismic wavefield imaging, utilizing seismograms from a dense seismic array. The REMC method, which provides not only
NASA Astrophysics Data System (ADS)
Nievaart, V. A.; Daquino, G. G.; Moss, R. L.
2007-06-01
Boron Neutron Capture Therapy (BNCT) is a bimodal form of radiotherapy for the treatment of tumour lesions. Since the cancer cells in the treatment volume are targeted with 10B, a higher dose is given to these cancer cells due to the 10B(n,α)7Li reaction, in comparison with the surrounding healthy cells. In Petten (The Netherlands), at the High Flux Reactor, a specially tailored neutron beam has been designed and installed. Over 30 patients have been treated with BNCT in 2 clinical protocols: a phase I study for the treatment of glioblastoma multiforme and a phase II study on the treatment of malignant melanoma. Furthermore, activities concerning the extra-corporal treatment of metastasis in the liver (from colorectal cancer) are in progress. The irradiation beam at the HFR contains both neutrons and gammas that, together with the complex geometries of both patient and beam set-up, demands for very detailed treatment planning calculations. A well designed Treatment Planning System (TPS) should obey the following general scheme: (1) a pre-processing phase (CT and/or MRI scans to create the geometric solid model, cross-section files for neutrons and/or gammas); (2) calculations (3D radiation transport, estimation of neutron and gamma fluences, macroscopic and microscopic dose); (3) post-processing phase (displaying of the results, iso-doses and -fluences). Treatment planning in BNCT is performed making use of Monte Carlo codes incorporated in a framework, which includes also the pre- and post-processing phases. In particular, the glioblastoma multiforme protocol used BNCT_rtpe, while the melanoma metastases protocol uses NCTPlan. In addition, an ad hoc Positron Emission Tomography (PET) based treatment planning system (BDTPS) has been implemented in order to integrate the real macroscopic boron distribution obtained from PET scanning. BDTPS is patented and uses MCNP as the calculation engine. The precision obtained by the Monte Carlo based TPSs exploited at Petten
Design and evaluation of a Monte Carlo based model of an orthovoltage treatment system.
Penchev, Petar; Mäder, Ulf; Fiebich, Martin; Zink, Klemens
2015-12-01
The aim of this study was to develop a flexible framework of an orthovoltage treatment system capable of calculating and visualizing dose distributions in different phantoms and CT datasets. The framework provides a complete set of various filters, applicators and x-ray energies and therefore can be adapted to varying studies or be used for educational purposes. A dedicated user friendly graphical interface was developed allowing for easy setup of the simulation parameters and visualization of the results. For the Monte Carlo simulations the EGSnrc Monte Carlo code package was used. Building the geometry was accomplished with the help of the EGSnrc C++ class library. The deposited dose was calculated according to the KERMA approximation using the track-length estimator. The validation against measurements showed a good agreement within 4-5% deviation, down to depths of 20% of the depth dose maximum. Furthermore, to show its capabilities, the validated model was used to calculate the dose distribution on two CT datasets. Typical Monte Carlo calculation time for these simulations was about 10 minutes achieving an average statistical uncertainty of 2% on a standard PC. However, this calculation time depends strongly on the used CT dataset, tube potential, filter material/thickness and applicator size.
Development and validation of MCNPX-based Monte Carlo treatment plan verification system
Jabbari, Iraj; Monadi, Shahram
2015-01-01
A Monte Carlo treatment plan verification (MCTPV) system was developed for clinical treatment plan verification (TPV), especially for the conformal and intensity-modulated radiotherapy (IMRT) plans. In the MCTPV, the MCNPX code was used for particle transport through the accelerator head and the patient body. MCTPV has an interface with TiGRT planning system and reads the information which is needed for Monte Carlo calculation transferred in digital image communications in medicine-radiation therapy (DICOM-RT) format. In MCTPV several methods were applied in order to reduce the simulation time. The relative dose distribution of a clinical prostate conformal plan calculated by the MCTPV was compared with that of TiGRT planning system. The results showed well implementation of the beams configuration and patient information in this system. For quantitative evaluation of MCTPV a two-dimensional (2D) diode array (MapCHECK2) and gamma index analysis were used. The gamma passing rate (3%/3 mm) of an IMRT plan was found to be 98.5% for total beams. Also, comparison of the measured and Monte Carlo calculated doses at several points inside an inhomogeneous phantom for 6- and 18-MV photon beams showed a good agreement (within 1.5%). The accuracy and timing results of MCTPV showed that MCTPV could be used very efficiently for additional assessment of complicated plans such as IMRT plan. PMID:26170554
Development and validation of MCNPX-based Monte Carlo treatment plan verification system.
Jabbari, Iraj; Monadi, Shahram
2015-01-01
A Monte Carlo treatment plan verification (MCTPV) system was developed for clinical treatment plan verification (TPV), especially for the conformal and intensity-modulated radiotherapy (IMRT) plans. In the MCTPV, the MCNPX code was used for particle transport through the accelerator head and the patient body. MCTPV has an interface with TiGRT planning system and reads the information which is needed for Monte Carlo calculation transferred in digital image communications in medicine-radiation therapy (DICOM-RT) format. In MCTPV several methods were applied in order to reduce the simulation time. The relative dose distribution of a clinical prostate conformal plan calculated by the MCTPV was compared with that of TiGRT planning system. The results showed well implementation of the beams configuration and patient information in this system. For quantitative evaluation of MCTPV a two-dimensional (2D) diode array (MapCHECK2) and gamma index analysis were used. The gamma passing rate (3%/3 mm) of an IMRT plan was found to be 98.5% for total beams. Also, comparison of the measured and Monte Carlo calculated doses at several points inside an inhomogeneous phantom for 6- and 18-MV photon beams showed a good agreement (within 1.5%). The accuracy and timing results of MCTPV showed that MCTPV could be used very efficiently for additional assessment of complicated plans such as IMRT plan.
Baba, Justin S; John, Dwayne O; Koju, Vijay
2015-01-01
The propagation of light in turbid media is an active area of research with relevance to numerous investigational fields, e.g., biomedical diagnostics and therapeutics. The statistical random-walk nature of photon propagation through turbid media is ideal for computational based modeling and simulation. Ready access to super computing resources provide a means for attaining brute force solutions to stochastic light-matter interactions entailing scattering by facilitating timely propagation of sufficient (>10million) photons while tracking characteristic parameters based on the incorporated physics of the problem. One such model that works well for isotropic but fails for anisotropic scatter, which is the case for many biomedical sample scattering problems, is the diffusion approximation. In this report, we address this by utilizing Berry phase (BP) evolution as a means for capturing anisotropic scattering characteristics of samples in the preceding depth where the diffusion approximation fails. We extend the polarization sensitive Monte Carlo method of Ramella-Roman, et al.,1 to include the computationally intensive tracking of photon trajectory in addition to polarization state at every scattering event. To speed-up the computations, which entail the appropriate rotations of reference frames, the code was parallelized using OpenMP. The results presented reveal that BP is strongly correlated to the photon penetration depth, thus potentiating the possibility of polarimetric depth resolved characterization of highly scattering samples, e.g., biological tissues.
Monte carlo method-based QSAR modeling of penicillins binding to human serum proteins.
Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M; Veselinović, Aleksandar M
2015-01-01
The binding of penicillins to human serum proteins was modeled with optimal descriptors based on the Simplified Molecular Input-Line Entry System (SMILES). The concentrations of protein-bound drug for 87 penicillins expressed as percentage of the total plasma concentration were used as experimental data. The Monte Carlo method was used as a computational tool to build up the quantitative structure-activity relationship (QSAR) model for penicillins binding to plasma proteins. One random data split into training, test and validation set was examined. The calculated QSAR model had the following statistical parameters: r(2) = 0.8760, q(2) = 0.8665, s = 8.94 for the training set and r(2) = 0.9812, q(2) = 0.9753, s = 7.31 for the test set. For the validation set, the statistical parameters were r(2) = 0.727 and s = 12.52, but after removing the three worst outliers, the statistical parameters improved to r(2) = 0.921 and s = 7.18. SMILES-based molecular fragments (structural indicators) responsible for the increase and decrease of penicillins binding to plasma proteins were identified. The possibility of using these results for the computer-aided design of new penicillins with desired binding properties is presented. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
A Monte Carlo-based treatment planning tool for proton therapy
NASA Astrophysics Data System (ADS)
Mairani, A.; Böhlen, T. T.; Schiavi, A.; Tessonnier, T.; Molinelli, S.; Brons, S.; Battistoni, G.; Parodi, K.; Patera, V.
2013-04-01
In the field of radiotherapy, Monte Carlo (MC) particle transport calculations are recognized for their superior accuracy in predicting dose and fluence distributions in patient geometries compared to analytical algorithms which are generally used for treatment planning due to their shorter execution times. In this work, a newly developed MC-based treatment planning (MCTP) tool for proton therapy is proposed to support treatment planning studies and research applications. It allows for single-field and simultaneous multiple-field optimization in realistic treatment scenarios and is based on the MC code FLUKA. Relative biological effectiveness (RBE)-weighted dose is optimized either with the common approach using a constant RBE of 1.1 or using a variable RBE according to radiobiological input tables. A validated reimplementation of the local effect model was used in this work to generate radiobiological input tables. Examples of treatment plans in water phantoms and in patient-CT geometries together with an experimental dosimetric validation of the plans are presented for clinical treatment parameters as used at the Italian National Center for Oncological Hadron Therapy. To conclude, a versatile MCTP tool for proton therapy was developed and validated for realistic patient treatment scenarios against dosimetric measurements and commercial analytical TP calculations. It is aimed to be used in future for research and to support treatment planning at state-of-the-art ion beam therapy facilities.
The development of GPU-based parallel PRNG for Monte Carlo applications in CUDA Fortran
NASA Astrophysics Data System (ADS)
Kargaran, Hamed; Minuchehr, Abdolhamid; Zolfaghari, Ahmad
2016-04-01
The implementation of Monte Carlo simulation on the CUDA Fortran requires a fast random number generation with good statistical properties on GPU. In this study, a GPU-based parallel pseudo random number generator (GPPRNG) have been proposed to use in high performance computing systems. According to the type of GPU memory usage, GPU scheme is divided into two work modes including GLOBAL_MODE and SHARED_MODE. To generate parallel random numbers based on the independent sequence method, the combination of middle-square method and chaotic map along with the Xorshift PRNG have been employed. Implementation of our developed PPRNG on a single GPU showed a speedup of 150x and 470x (with respect to the speed of PRNG on a single CPU core) for GLOBAL_MODE and SHARED_MODE, respectively. To evaluate the accuracy of our developed GPPRNG, its performance was compared to that of some other commercially available PPRNGs such as MATLAB, FORTRAN and Miller-Park algorithm through employing the specific standard tests. The results of this comparison showed that the developed GPPRNG in this study can be used as a fast and accurate tool for computational science applications.
Saha, Krishnendu; Straus, Kenneth J.; Glick, Stephen J.; Chen, Yu.
2014-08-28
To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.
NASA Astrophysics Data System (ADS)
Baba, J. S.; Koju, V.; John, D.
2015-03-01
The propagation of light in turbid media is an active area of research with relevance to numerous investigational fields, e.g., biomedical diagnostics and therapeutics. The statistical random-walk nature of photon propagation through turbid media is ideal for computational based modeling and simulation. Ready access to super computing resources provide a means for attaining brute force solutions to stochastic light-matter interactions entailing scattering by facilitating timely propagation of sufficient (>107) photons while tracking characteristic parameters based on the incorporated physics of the problem. One such model that works well for isotropic but fails for anisotropic scatter, which is the case for many biomedical sample scattering problems, is the diffusion approximation. In this report, we address this by utilizing Berry phase (BP) evolution as a means for capturing anisotropic scattering characteristics of samples in the preceding depth where the diffusion approximation fails. We extend the polarization sensitive Monte Carlo method of Ramella-Roman, et al., to include the computationally intensive tracking of photon trajectory in addition to polarization state at every scattering event. To speed-up the computations, which entail the appropriate rotations of reference frames, the code was parallelized using OpenMP. The results presented reveal that BP is strongly correlated to the photon penetration depth, thus potentiating the possibility of polarimetric depth resolved characterization of highly scattering samples, e.g., biological tissues.
NASA Astrophysics Data System (ADS)
Saha, Krishnendu; Straus, Kenneth J.; Chen, Yu.; Glick, Stephen J.
2014-08-01
To maximize sensitivity, it is desirable that ring Positron Emission Tomography (PET) systems dedicated for imaging the breast have a small bore. Unfortunately, due to parallax error this causes substantial degradation in spatial resolution for objects near the periphery of the breast. In this work, a framework for computing and incorporating an accurate system matrix into iterative reconstruction is presented in an effort to reduce spatial resolution degradation towards the periphery of the breast. The GATE Monte Carlo Simulation software was utilized to accurately model the system matrix for a breast PET system. A strategy for increasing the count statistics in the system matrix computation and for reducing the system element storage space was used by calculating only a subset of matrix elements and then estimating the rest of the elements by using the geometric symmetry of the cylindrical scanner. To implement this strategy, polar voxel basis functions were used to represent the object, resulting in a block-circulant system matrix. Simulation studies using a breast PET scanner model with ring geometry demonstrated improved contrast at 45% reduced noise level and 1.5 to 3 times resolution performance improvement when compared to MLEM reconstruction using a simple line-integral model. The GATE based system matrix reconstruction technique promises to improve resolution and noise performance and reduce image distortion at FOV periphery compared to line-integral based system matrix reconstruction.
NASA Astrophysics Data System (ADS)
Zhai, Xue; Fei, Cheng-Wei; Choy, Yat-Sze; Wang, Jian-Jun
2017-01-01
To improve the accuracy and efficiency of computation model for complex structures, the stochastic model updating (SMU) strategy was proposed by combining the improved response surface model (IRSM) and the advanced Monte Carlo (MC) method based on experimental static test, prior information and uncertainties. Firstly, the IRSM and its mathematical model were developed with the emphasis on moving least-square method, and the advanced MC simulation method is studied based on Latin hypercube sampling method as well. And then the SMU procedure was presented with experimental static test for complex structure. The SMUs of simply-supported beam and aeroengine stator system (casings) were implemented to validate the proposed IRSM and advanced MC simulation method. The results show that (1) the SMU strategy hold high computational precision and efficiency for the SMUs of complex structural system; (2) the IRSM is demonstrated to be an effective model due to its SMU time is far less than that of traditional response surface method, which is promising to improve the computational speed and accuracy of SMU; (3) the advanced MC method observably decrease the samples from finite element simulations and the elapsed time of SMU. The efforts of this paper provide a promising SMU strategy for complex structure and enrich the theory of model updating.
The development of GPU-based parallel PRNG for Monte Carlo applications in CUDA Fortran
Kargaran, Hamed Minuchehr, Abdolhamid; Zolfaghari, Ahmad
2016-04-15
The implementation of Monte Carlo simulation on the CUDA Fortran requires a fast random number generation with good statistical properties on GPU. In this study, a GPU-based parallel pseudo random number generator (GPPRNG) have been proposed to use in high performance computing systems. According to the type of GPU memory usage, GPU scheme is divided into two work modes including GLOBAL-MODE and SHARED-MODE. To generate parallel random numbers based on the independent sequence method, the combination of middle-square method and chaotic map along with the Xorshift PRNG have been employed. Implementation of our developed PPRNG on a single GPU showed a speedup of 150x and 470x (with respect to the speed of PRNG on a single CPU core) for GLOBAL-MODE and SHARED-MODE, respectively. To evaluate the accuracy of our developed GPPRNG, its performance was compared to that of some other commercially available PPRNGs such as MATLAB, FORTRAN and Miller-Park algorithm through employing the specific standard tests. The results of this comparison showed that the developed GPPRNG in this study can be used as a fast and accurate tool for computational science applications.
Status of the Space Radiation Monte Carlos Simulation Based on FLUKA and ROOT
NASA Technical Reports Server (NTRS)
Andersen, Victor; Carminati, Federico; Empl, Anton; Ferrari, Alfredo; Pinsky, Lawrence; Sala, Paola; Wilson, Thomas L.
2002-01-01
The NASA-funded project reported on at the first IWSSRR in Arona to develop a Monte-Carlo simulation program for use in simulating the space radiation environment based on the FLUKA and ROOT codes is well into its second year of development, and considerable progress has been made. The general tasks required to achieve the final goals include the addition of heavy-ion interactions into the FLUKA code and the provision of a ROOT-based interface to FLUKA. The most significant progress to date includes the incorporation of the DPMJET event generator code within FLUKA to handle heavy-ion interactions for incident projectile energies greater than 3GeV/A. The ongoing effort intends to extend the treatment of these interactions down to 10 MeV, and at present two alternative approaches are being explored. The ROOT interface is being pursued in conjunction with the CERN LHC ALICE software team through an adaptation of their existing AliROOT software. As a check on the validity of the code, a simulation of the recent data taken by the ATIC experiment is underway.
Qin, Nan; Botas, Pablo; Giantsoudi, Drosoula; Schuemann, Jan; Tian, Zhen; Jiang, Steve B; Paganetti, Harald; Jia, Xun
2016-10-03
Monte Carlo (MC) simulation is commonly considered as the most accurate dose calculation method for proton therapy. Aiming at achieving fast MC dose calculations for clinical applications, we have previously developed a graphics-processing unit (GPU)-based MC tool, gPMC. In this paper, we report our recent updates on gPMC in terms of its accuracy, portability, and functionality, as well as comprehensive tests on this tool. The new version, gPMC v2.0, was developed under the OpenCL environment to enable portability across different computational platforms. Physics models of nuclear interactions were refined to improve calculation accuracy. Scoring functions of gPMC were expanded to enable tallying particle fluence, dose deposited by different particle types, and dose-averaged linear energy transfer (LETd). A multiple counter approach was employed to improve efficiency by reducing the frequency of memory writing conflict at scoring. For dose calculation, accuracy improvements over gPMC v1.0 were observed in both water phantom cases and a patient case. For a prostate cancer case planned using high-energy proton beams, dose discrepancies in beam entrance and target region seen in gPMC v1.0 with respect to the gold standard tool for proton Monte Carlo simulations (TOPAS) results were substantially reduced and gamma test passing rate (1%/1 mm) was improved from 82.7%-93.1%. The average relative difference in LETd between gPMC and TOPAS was 1.7%. The average relative differences in the dose deposited by primary, secondary, and other heavier particles were within 2.3%, 0.4%, and 0.2%. Depending on source proton energy and phantom complexity, it took 8-17 s on an AMD Radeon R9 290x GPU to simulate [Formula: see text] source protons, achieving less than [Formula: see text] average statistical uncertainty. As the beam size was reduced from 10 × 10 cm(2) to 1 × 1 cm(2), the time on scoring was only increased by 4.8% with eight counters, in
NASA Astrophysics Data System (ADS)
Kudrolli, Haris A.
2001-04-01
A three dimensional (3D) reconstruction procedure for Positron Emission Tomography (PET) based on inverse Monte Carlo analysis is presented. PET is a medical imaging modality which employs a positron emitting radio-tracer to give functional images of an organ's metabolic activity. This makes PET an invaluable tool in the detection of cancer and for in-vivo biochemical measurements. There are a number of analytical and iterative algorithms for image reconstruction of PET data. Analytical algorithms are computationally fast, but the assumptions intrinsic in the line integral model limit their accuracy. Iterative algorithms can apply accurate models for reconstruction and give improvements in image quality, but at an increased computational cost. These algorithms require the explicit calculation of the system response matrix, which may not be easy to calculate. This matrix gives the probability that a photon emitted from a certain source element will be detected in a particular detector line of response. The ``Three Dimensional Stochastic Sampling'' (SS3D) procedure implements iterative algorithms in a manner that does not require the explicit calculation of the system response matrix. It uses Monte Carlo techniques to simulate the process of photon emission from a source distribution and interaction with the detector. This technique has the advantage of being able to model complex detector systems and also take into account the physics of gamma ray interaction within the source and detector systems, which leads to an accurate image estimate. A series of simulation studies was conducted to validate the method using the Maximum Likelihood - Expectation Maximization (ML-EM) algorithm. The accuracy of the reconstructed images was improved by using an algorithm that required a priori knowledge of the source distribution. Means to reduce the computational time for reconstruction were explored by using parallel processors and algorithms that had faster convergence rates
NASA Astrophysics Data System (ADS)
Qin, Nan; Botas, Pablo; Giantsoudi, Drosoula; Schuemann, Jan; Tian, Zhen; Jiang, Steve B.; Paganetti, Harald; Jia, Xun
2016-10-01
Monte Carlo (MC) simulation is commonly considered as the most accurate dose calculation method for proton therapy. Aiming at achieving fast MC dose calculations for clinical applications, we have previously developed a graphics-processing unit (GPU)-based MC tool, gPMC. In this paper, we report our recent updates on gPMC in terms of its accuracy, portability, and functionality, as well as comprehensive tests on this tool. The new version, gPMC v2.0, was developed under the OpenCL environment to enable portability across different computational platforms. Physics models of nuclear interactions were refined to improve calculation accuracy. Scoring functions of gPMC were expanded to enable tallying particle fluence, dose deposited by different particle types, and dose-averaged linear energy transfer (LETd). A multiple counter approach was employed to improve efficiency by reducing the frequency of memory writing conflict at scoring. For dose calculation, accuracy improvements over gPMC v1.0 were observed in both water phantom cases and a patient case. For a prostate cancer case planned using high-energy proton beams, dose discrepancies in beam entrance and target region seen in gPMC v1.0 with respect to the gold standard tool for proton Monte Carlo simulations (TOPAS) results were substantially reduced and gamma test passing rate (1%/1 mm) was improved from 82.7%-93.1%. The average relative difference in LETd between gPMC and TOPAS was 1.7%. The average relative differences in the dose deposited by primary, secondary, and other heavier particles were within 2.3%, 0.4%, and 0.2%. Depending on source proton energy and phantom complexity, it took 8-17 s on an AMD Radeon R9 290x GPU to simulate {{10}7} source protons, achieving less than 1% average statistical uncertainty. As the beam size was reduced from 10 × 10 cm2 to 1 × 1 cm2, the time on scoring was only increased by 4.8% with eight counters, in contrast to a 40% increase using only
Semistochastic Projector Monte Carlo Method
NASA Astrophysics Data System (ADS)
Petruzielo, F. R.; Holmes, A. A.; Changlani, Hitesh J.; Nightingale, M. P.; Umrigar, C. J.
2012-12-01
We introduce a semistochastic implementation of the power method to compute, for very large matrices, the dominant eigenvalue and expectation values involving the corresponding eigenvector. The method is semistochastic in that the matrix multiplication is partially implemented numerically exactly and partially stochastically with respect to expectation values only. Compared to a fully stochastic method, the semistochastic approach significantly reduces the computational time required to obtain the eigenvalue to a specified statistical uncertainty. This is demonstrated by the application of the semistochastic quantum Monte Carlo method to systems with a sign problem: the fermion Hubbard model and the carbon dimer.
Mesh-based Monte Carlo code for fluorescence modeling in complex tissues with irregular boundaries
NASA Astrophysics Data System (ADS)
Wilson, Robert H.; Chen, Leng-Chun; Lloyd, William; Kuo, Shiuhyang; Marcelo, Cynthia; Feinberg, Stephen E.; Mycek, Mary-Ann
2011-07-01
There is a growing need for the development of computational models that can account for complex tissue morphology in simulations of photon propagation. We describe the development and validation of a user-friendly, MATLAB-based Monte Carlo code that uses analytically-defined surface meshes to model heterogeneous tissue geometry. The code can use information from non-linear optical microscopy images to discriminate the fluorescence photons (from endogenous or exogenous fluorophores) detected from different layers of complex turbid media. We present a specific application of modeling a layered human tissue-engineered construct (Ex Vivo Produced Oral Mucosa Equivalent, EVPOME) designed for use in repair of oral tissue following surgery. Second-harmonic generation microscopic imaging of an EVPOME construct (oral keratinocytes atop a scaffold coated with human type IV collagen) was employed to determine an approximate analytical expression for the complex shape of the interface between the two layers. This expression can then be inserted into the code to correct the simulated fluorescence for the effect of the irregular tissue geometry.
Absorbed Dose Calculations Using Mesh-based Human Phantoms And Monte Carlo Methods
NASA Astrophysics Data System (ADS)
Kramer, Richard
2011-08-01
Health risks attributable to the exposure to ionizing radiation are considered to be a function of the absorbed or equivalent dose to radiosensitive organs and tissues. However, as human tissue cannot express itself in terms of equivalent dose, exposure models have to be used to determine the distribution of equivalent dose throughout the human body. An exposure model, be it physical or computational, consists of a representation of the human body, called phantom, plus a method for transporting ionizing radiation through the phantom and measuring or calculating the equivalent dose to organ and tissues of interest. The FASH2 (Female Adult meSH) and the MASH2 (Male Adult meSH) computational phantoms have been developed at the University of Pernambuco in Recife/Brazil based on polygon mesh surfaces using open source software tools and anatomical atlases. Representing standing adults, FASH2 and MASH2 have organ and tissue masses, body height and body mass adjusted to the anatomical data published by the International Commission on Radiological Protection for the reference male and female adult. For the purposes of absorbed dose calculations the phantoms have been coupled to the EGSnrc Monte Carlo code, which can transport photons, electrons and positrons through arbitrary media. This paper reviews the development of the FASH2 and the MASH2 phantoms and presents dosimetric applications for X-ray diagnosis and for prostate brachytherapy.
A comprehensive revisit of the ρ meson with improved Monte-Carlo based QCD sum rules
NASA Astrophysics Data System (ADS)
Wang, Qi-Nan; Zhang, Zhu-Feng; Steele, T. G.; Jin, Hong-Ying; Huang, Zhuo-Ran
2017-07-01
We improve the Monte-Carlo based QCD sum rules by introducing the rigorous Hölder-inequality-determined sum rule window and a Breit-Wigner type parametrization for the phenomenological spectral function. In this improved sum rule analysis methodology, the sum rule analysis window can be determined without any assumptions on OPE convergence or the QCD continuum. Therefore, an unbiased prediction can be obtained for the phenomenological parameters (the hadronic mass and width etc.). We test the new approach in the ρ meson channel with re-examination and inclusion of α s corrections to dimension-4 condensates in the OPE. We obtain results highly consistent with experimental values. We also discuss the possible extension of this method to some other channels. Supported by NSFC (11175153, 11205093, 11347020), Open Foundation of the Most Important Subjects of Zhejiang Province, and K. C. Wong Magna Fund in Ningbo University, TGS is Supported by the Natural Sciences and Engineering Research Council of Canada (NSERC), Z. F. Zhang and Z. R. Huang are Grateful to the University of Saskatchewan for its Warm Hospitality
Hydrogenated amorphous silicon (a-Si:H) based gamma camera--Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Lee, Hyoung-Koo; Drewery, John S.; Hong, Wan S.; Jing, Tao; Kaplan, Selig N.; Mireshghi, Ali; Perez-Mendez, Victor
1994-05-01
A new gamma camera using a-Si:H photodetectors has been designed for the imaging of heart and other small organs. In this new design the photomultiplier tubes and the position sensing circuitry are replaced by 2D array of a-Si:H p-i-n pixel photodetectors and readout circuitry which are built on a substrate. Without the photomultiplier tubes this camera is light weight, hence can be made portable. To predict the characteristics and the performance of this new gamma camera we did Monte Carlo simulations. In the simulations 128 X 128 imaging array of various pixel sizes were used. 99mTc (140 keV) and 201Tl (70 keV) were used as radiation sources. From the simulations we could obtain the resolution of the camera and the overall system, and the blurring effects due to scattering in the phantom. Using the Wiener filter for image processing, restoration of the blurred image could be achieved. Simulation results of a-Si:H based gamma camera were compared with those of a conventional gamma camera.
A Monte Carlo-based treatment-planning tool for ion beam therapy
Böhlen, T.T.; Bauer, J.; Dosanjh, M.; Ferrari, A.; Haberer, T.; Parodi, K.; Patera, V.; Mairani, A.
2013-01-01
Ion beam therapy, as an emerging radiation therapy modality, requires continuous efforts to develop and improve tools for patient treatment planning (TP) and research applications. Dose and fluence computation algorithms using the Monte Carlo (MC) technique have served for decades as reference tools for accurate dose computations for radiotherapy. In this work, a novel MC-based treatment-planning (MCTP) tool for ion beam therapy using the pencil beam scanning technique is presented. It allows single-field and simultaneous multiple-fields optimization for realistic patient treatment conditions and for dosimetric quality assurance for irradiation conditions at state-of-the-art ion beam therapy facilities. It employs iterative procedures that allow for the optimization of absorbed dose and relative biological effectiveness (RBE)-weighted dose using radiobiological input tables generated by external RBE models. Using a re-implementation of the local effect model (LEM), the MCTP tool is able to perform TP studies using ions with atomic numbers Z ≤ 8. Example treatment plans created with the MCTP tool are presented for carbon ions in comparison with a certified analytical treatment-planning system. Furthermore, the usage of the tool to compute and optimize mixed-ion treatment plans, i.e. plans including pencil beams of ions with different atomic numbers, is demonstrated. The tool is aimed for future use in research applications and to support treatment planning at ion beam facilities. PMID:23824131
IVF cycle cost estimation using Activity Based Costing and Monte Carlo simulation.
Cassettari, Lucia; Mosca, Marco; Mosca, Roberto; Rolando, Fabio; Costa, Mauro; Pisaturo, Valerio
2016-03-01
The Authors present a new methodological approach in stochastic regime to determine the actual costs of an healthcare process. The paper specifically shows the application of the methodology for the determination of the cost of an Assisted reproductive technology (ART) treatment in Italy. The reason of this research comes from the fact that deterministic regime is inadequate to implement an accurate estimate of the cost of this particular treatment. In fact the durations of the different activities involved are unfixed and described by means of frequency distributions. Hence the need to determine in addition to the mean value of the cost, the interval within which it is intended to vary with a known confidence level. Consequently the cost obtained for each type of cycle investigated (in vitro fertilization and embryo transfer with or without intracytoplasmic sperm injection), shows tolerance intervals around the mean value sufficiently restricted as to make the data obtained statistically robust and therefore usable also as reference for any benchmark with other Countries. It should be noted that under a methodological point of view the approach was rigorous. In fact it was used both the technique of Activity Based Costing for determining the cost of individual activities of the process both the Monte Carlo simulation, with control of experimental error, for the construction of the tolerance intervals on the final result.
Auxiliary-field-based trial wave functions in quantum Monte Carlo calculations
NASA Astrophysics Data System (ADS)
Chang, Chia-Chen; Rubenstein, Brenda M.; Morales, Miguel A.
2016-12-01
Quantum Monte Carlo (QMC) algorithms have long relied on Jastrow factors to incorporate dynamic correlation into trial wave functions. While Jastrow-type wave functions have been widely employed in real-space algorithms, they have seen limited use in second-quantized QMC methods, particularly in projection methods that involve a stochastic evolution of the wave function in imaginary time. Here we propose a scheme for generating Jastrow-type correlated trial wave functions for auxiliary-field QMC methods. The method is based on decoupling the two-body Jastrow into one-body projectors coupled to auxiliary fields, which then operate on a single determinant to produce a multideterminant trial wave function. We demonstrate that intelligent sampling of the most significant determinants in this expansion can produce compact trial wave functions that reduce errors in the calculated energies. Our technique may be readily generalized to accommodate a wide range of two-body Jastrow factors and applied to a variety of model and chemical systems.
NASA Astrophysics Data System (ADS)
Ma, Yang-Bin; Albe, Karsten; Xu, Bai-Xiang
2015-05-01
Canonical and microcanonical Monte Carlo simulations are carried out to study the electrocaloric effect (ECE) in ferroelectrics and relaxor ferroelectrics (RFEs) by direct computation of field-induced temperature variations at the ferroelectric-to-paraelectric phase transition and the nonergodic-to-ergodic state transformation. A lattice-based Hamiltonian is introduced, which includes a thermal energy, a Landau-type term, a dipole-dipole interaction energy, a gradient term representing the domain-wall energy, and an electrostatic energy contribution describing the coupling to external and random fields. The model is first parametrized and studied for the case of BaTiO3. Then, the ECE in RFEs is investigated, with particular focus on the influence of random fields and domain-wall energies. If the strength or the density of the random fields increases, the ECE peak shifts to a lower temperature but the temperature variation is reduced. On the contrary, if the domain-wall energy increases, the peak shifts to a higher temperature and the ECE becomes stronger. In RFEs, the ECE is maximum at the freezing temperature where the nonergodic-to-ergodic transition takes place. Our results imply that the presence of random fields reduces the entropy variation in an ECE cycle by pinning local polarization.
Monte Carlo based verification of a beam model used in a treatment planning system
NASA Astrophysics Data System (ADS)
Wieslander, E.; Knöös, T.
2008-02-01
Modern treatment planning systems (TPSs) usually separate the dose modelling into a beam modelling phase, describing the beam exiting the accelerator, followed by a subsequent dose calculation in the patient. The aim of this work is to use the Monte Carlo code system EGSnrc to study the modelling of head scatter as well as the transmission through multi-leaf collimator (MLC) and diaphragms in the beam model used in a commercial TPS (MasterPlan, Nucletron B.V.). An Elekta Precise linear accelerator equipped with an MLC has been modelled in BEAMnrc, based on available information from the vendor regarding the material and geometry of the treatment head. The collimation in the MLC direction consists of leafs which are complemented with a backup diaphragm. The characteristics of the electron beam, i.e., energy and spot size, impinging on the target have been tuned to match measured data. Phase spaces from simulations of the treatment head are used to extract the scatter from, e.g., the flattening filter and the collimating structures. Similar data for the source models used in the TPS are extracted from the treatment planning system, thus a comprehensive analysis is possible. Simulations in a water phantom, with DOSXYZnrc, are also used to study the modelling of the MLC and the diaphragms by the TPS. The results from this study will be helpful to understand the limitations of the model in the TPS and provide knowledge for further improvements of the TPS source modelling.
Geant4-based Monte Carlo simulations on GPU for medical applications.
Bert, Julien; Perez-Ponce, Hector; El Bitar, Ziad; Jan, Sébastien; Boursier, Yannick; Vintache, Damien; Bonissent, Alain; Morel, Christian; Brasse, David; Visvikis, Dimitris
2013-08-21
Monte Carlo simulation (MCS) plays a key role in medical applications, especially for emission tomography and radiotherapy. However MCS is also associated with long calculation times that prevent its use in routine clinical practice. Recently, graphics processing units (GPU) became in many domains a low cost alternative for the acquisition of high computational power. The objective of this work was to develop an efficient framework for the implementation of MCS on GPU architectures. Geant4 was chosen as the MCS engine given the large variety of physics processes available for targeting different medical imaging and radiotherapy applications. In addition, Geant4 is the MCS engine behind GATE which is actually the most popular medical applications' simulation platform. We propose the definition of a global strategy and associated structures for such a GPU based simulation implementation. Different photon and electron physics effects are resolved on the fly directly on GPU without any approximations with respect to Geant4. Validations have shown equivalence in the underlying photon and electron physics processes between the Geant4 and the GPU codes with a speedup factor of 80-90. More clinically realistic simulations in emission and transmission imaging led to acceleration factors of 400-800 respectively compared to corresponding GATE simulations.
Geant4-based Monte Carlo simulations on GPU for medical applications
NASA Astrophysics Data System (ADS)
Bert, Julien; Perez-Ponce, Hector; El Bitar, Ziad; Jan, Sébastien; Boursier, Yannick; Vintache, Damien; Bonissent, Alain; Morel, Christian; Brasse, David; Visvikis, Dimitris
2013-08-01
Monte Carlo simulation (MCS) plays a key role in medical applications, especially for emission tomography and radiotherapy. However MCS is also associated with long calculation times that prevent its use in routine clinical practice. Recently, graphics processing units (GPU) became in many domains a low cost alternative for the acquisition of high computational power. The objective of this work was to develop an efficient framework for the implementation of MCS on GPU architectures. Geant4 was chosen as the MCS engine given the large variety of physics processes available for targeting different medical imaging and radiotherapy applications. In addition, Geant4 is the MCS engine behind GATE which is actually the most popular medical applications' simulation platform. We propose the definition of a global strategy and associated structures for such a GPU based simulation implementation. Different photon and electron physics effects are resolved on the fly directly on GPU without any approximations with respect to Geant4. Validations have shown equivalence in the underlying photon and electron physics processes between the Geant4 and the GPU codes with a speedup factor of 80-90. More clinically realistic simulations in emission and transmission imaging led to acceleration factors of 400-800 respectively compared to corresponding GATE simulations.
Stationarity Modeling and Informatics-Based Diagnostics in Monte Carlo Criticality Calculations
Ueki, Taro; Brown, Forrest B.
2005-01-15
In Monte Carlo criticality calculations, source error propagation through the stationary (active) cycles and source convergence in the settling (inactive) cycles are both dominated by the dominance ratio (DR) of fission kernels. For symmetric two-fissile-component systems with the DR close to unity, the extinction of fission source sites can occur in one of the components even when the initial source is symmetric and the number of histories per cycle is more than 1000. When such a system is made slightly asymmetric, the neutron effective multiplication factor at the inactive cycles does not reflect the convergence to stationary source distribution. To overcome this problem, relative entropy has been applied to a slightly asymmetric two-fissile-component problem with a DR of 0.993. The numerical results are mostly satisfactory but also show the possibility of the occasional occurrence of unnecessarily strict stationarity diagnostics. Therefore, a criterion is defined based on the concept of data compression limit in information theory. Numerical results for a pressurized water reactor fuel storage facility with a DR of 0.994 strongly support the efficacy of relative entropy in both the posterior and progressive stationarity diagnostics.
Auxiliary-field-based trial wave functions in quantum Monte Carlo calculations
Chang, Chia -Chen; Rubenstein, Brenda M.; Morales, Miguel A.
2016-12-19
Quantum Monte Carlo (QMC) algorithms have long relied on Jastrow factors to incorporate dynamic correlation into trial wave functions. While Jastrow-type wave functions have been widely employed in real-space algorithms, they have seen limited use in second-quantized QMC methods, particularly in projection methods that involve a stochastic evolution of the wave function in imaginary time. Here we propose a scheme for generating Jastrow-type correlated trial wave functions for auxiliary-field QMC methods. The method is based on decoupling the two-body Jastrow into one-body projectors coupled to auxiliary fields, which then operate on a single determinant to produce a multideterminant trial wave function. We demonstrate that intelligent sampling of the most significant determinants in this expansion can produce compact trial wave functions that reduce errors in the calculated energies. Lastly, our technique may be readily generalized to accommodate a wide range of two-body Jastrow factors and applied to a variety of model and chemical systems.
Auxiliary-field-based trial wave functions in quantum Monte Carlo calculations
Chang, Chia -Chen; Rubenstein, Brenda M.; Morales, Miguel A.
2016-12-19
Quantum Monte Carlo (QMC) algorithms have long relied on Jastrow factors to incorporate dynamic correlation into trial wave functions. While Jastrow-type wave functions have been widely employed in real-space algorithms, they have seen limited use in second-quantized QMC methods, particularly in projection methods that involve a stochastic evolution of the wave function in imaginary time. Here we propose a scheme for generating Jastrow-type correlated trial wave functions for auxiliary-field QMC methods. The method is based on decoupling the two-body Jastrow into one-body projectors coupled to auxiliary fields, which then operate on a single determinant to produce a multideterminant trial wavemore » function. We demonstrate that intelligent sampling of the most significant determinants in this expansion can produce compact trial wave functions that reduce errors in the calculated energies. Lastly, our technique may be readily generalized to accommodate a wide range of two-body Jastrow factors and applied to a variety of model and chemical systems.« less
Monte Carlo docking with ubiquitin.
Cummings, M. D.; Hart, T. N.; Read, R. J.
1995-01-01
The development of general strategies for the performance of docking simulations is prerequisite to the exploitation of this powerful computational method. Comprehensive strategies can only be derived from docking experiences with a diverse array of biological systems, and we have chosen the ubiquitin/diubiquitin system as a learning tool for this process. Using our multiple-start Monte Carlo docking method, we have reconstructed the known structure of diubiquitin from its two halves as well as from two copies of the uncomplexed monomer. For both of these cases, our relatively simple potential function ranked the correct solution among the lowest energy configurations. In the experiments involving the ubiquitin monomer, various structural modifications were made to compensate for the lack of flexibility and for the lack of a covalent bond in the modeled interaction. Potentially flexible regions could be identified using available biochemical and structural information. A systematic conformational search ruled out the possibility that the required covalent bond could be formed in one family of low-energy configurations, which was distant from the observed dimer configuration. A variety of analyses was performed on the low-energy dockings obtained in the experiment involving structurally modified ubiquitin. Characterization of the size and chemical nature of the interface surfaces was a powerful adjunct to our potential function, enabling us to distinguish more accurately between correct and incorrect dockings. Calculations with the structure of tetraubiquitin indicated that the dimer configuration in this molecule is much less favorable than that observed in the diubiquitin structure, for a simple monomer-monomer pair. Based on the analysis of our results, we draw conclusions regarding some of the approximations involved in our simulations, the use of diverse chemical and biochemical information in experimental design and the analysis of docking results, as well as
Multidimensional stochastic approximation Monte Carlo
NASA Astrophysics Data System (ADS)
Zablotskiy, Sergey V.; Ivanov, Victor A.; Paul, Wolfgang
2016-06-01
Stochastic Approximation Monte Carlo (SAMC) has been established as a mathematically founded powerful flat-histogram Monte Carlo method, used to determine the density of states, g (E ) , of a model system. We show here how it can be generalized for the determination of multidimensional probability distributions (or equivalently densities of states) of macroscopic or mesoscopic variables defined on the space of microstates of a statistical mechanical system. This establishes this method as a systematic way for coarse graining a model system, or, in other words, for performing a renormalization group step on a model. We discuss the formulation of the Kadanoff block spin transformation and the coarse-graining procedure for polymer models in this language. We also apply it to a standard case in the literature of two-dimensional densities of states, where two competing energetic effects are present g (E1,E2) . We show when and why care has to be exercised when obtaining the microcanonical density of states g (E1+E2) from g (E1,E2) .
Single scatter electron Monte Carlo
Svatos, M.M.
1997-03-01
A single scatter electron Monte Carlo code (SSMC), CREEP, has been written which bridges the gap between existing transport methods and modeling real physical processes. CREEP simulates ionization, elastic and bremsstrahlung events individually. Excitation events are treated with an excitation-only stopping power. The detailed nature of these simulations allows for calculation of backscatter and transmission coefficients, backscattered energy spectra, stopping powers, energy deposits, depth dose, and a variety of other associated quantities. Although computationally intense, the code relies on relatively few mathematical assumptions, unlike other charged particle Monte Carlo methods such as the commonly-used condensed history method. CREEP relies on sampling the Lawrence Livermore Evaluated Electron Data Library (EEDL) which has data for all elements with an atomic number between 1 and 100, over an energy range from approximately several eV (or the binding energy of the material) to 100 GeV. Compounds and mixtures may also be used by combining the appropriate element data via Bragg additivity.
TH-E-BRE-08: GPU-Monte Carlo Based Fast IMRT Plan Optimization
Li, Y; Tian, Z; Shi, F; Jiang, S; Jia, X
2014-06-15
Purpose: Intensity-modulated radiation treatment (IMRT) plan optimization needs pre-calculated beamlet dose distribution. Pencil-beam or superposition/convolution type algorithms are typically used because of high computation speed. However, inaccurate beamlet dose distributions, particularly in cases with high levels of inhomogeneity, may mislead optimization, hindering the resulting plan quality. It is desire to use Monte Carlo (MC) methods for beamlet dose calculations. Yet, the long computational time from repeated dose calculations for a number of beamlets prevents this application. It is our objective to integrate a GPU-based MC dose engine in lung IMRT optimization using a novel two-steps workflow. Methods: A GPU-based MC code gDPM is used. Each particle is tagged with an index of a beamlet where the source particle is from. Deposit dose are stored separately for beamlets based on the index. Due to limited GPU memory size, a pyramid space is allocated for each beamlet, and dose outside the space is neglected. A two-steps optimization workflow is proposed for fast MC-based optimization. At first step, rough beamlet dose calculations is conducted with only a small number of particles per beamlet. Plan optimization is followed to get an approximated fluence map. In the second step, more accurate beamlet doses are calculated, where sampled number of particles for a beamlet is proportional to the intensity determined previously. A second-round optimization is conducted, yielding the final Result. Results: For a lung case with 5317 beamlets, 10{sup 5} particles per beamlet in the first round, and 10{sup 8} particles per beam in the second round are enough to get a good plan quality. The total simulation time is 96.4 sec. Conclusion: A fast GPU-based MC dose calculation method along with a novel two-step optimization workflow are developed. The high efficiency allows the use of MC for IMRT optimizations.
Monte-Carlo Opening Books for Amazons
NASA Astrophysics Data System (ADS)
Kloetzer, Julien
Automatically creating opening books is a natural step towards the building of strong game-playing programs, especially when there is little available knowledge about the game. However, while recent popular Monte-Carlo Tree-Search programs showed strong results for various games, we show here that programs based on such methods cannot efficiently use opening books created using algorithms based on minimax. To overcome this issue, we propose to use an MCTS-based technique, Meta-MCTS, to create such opening books. This method, while requiring some tuning to arrive at the best opening book possible, shows promising results to create an opening book for the game of the Amazons, even if this is at the cost of removing its Monte-Carlo part.
Chiavassa, S; Aubineau-Lanièce, I; Bitar, A; Lisbona, A; Barbet, J; Franck, D; Jourdain, J R; Bardiès, M
2006-02-07
Dosimetric studies are necessary for all patients treated with targeted radiotherapy. In order to attain the precision required, we have developed Oedipe, a dosimetric tool based on the MCNPX Monte Carlo code. The anatomy of each patient is considered in the form of a voxel-based geometry created using computed tomography (CT) images or magnetic resonance imaging (MRI). Oedipe enables dosimetry studies to be carried out at the voxel scale. Validation of the results obtained by comparison with existing methods is complex because there are multiple sources of variation: calculation methods (different Monte Carlo codes, point kernel), patient representations (model or specific) and geometry definitions (mathematical or voxel-based). In this paper, we validate Oedipe by taking each of these parameters into account independently. Monte Carlo methodology requires long calculation times, particularly in the case of voxel-based geometries, and this is one of the limits of personalized dosimetric methods. However, our results show that the use of voxel-based geometry as opposed to a mathematically defined geometry decreases the calculation time two-fold, due to an optimization of the MCNPX2.5e code. It is therefore possible to envisage the use of Oedipe for personalized dosimetry in the clinical context of targeted radiotherapy.
Monte Carlo Test Assembly for Item Pool Analysis and Extension
ERIC Educational Resources Information Center
Belov, Dmitry I.; Armstrong, Ronald D.
2005-01-01
A new test assembly algorithm based on a Monte Carlo random search is presented in this article. A major advantage of the Monte Carlo test assembly over other approaches (integer programming or enumerative heuristics) is that it performs a uniform sampling from the item pool, which provides every feasible item combination (test) with an equal…
Li, Pu; Chen, Bing; Li, Zelin; Zheng, Xiao; Wu, Hongjing; Jing, Liang; Lee, Kenneth
2014-09-15
In this paper, a Monte Carlo simulation based two-stage adaptive resonance theory mapping (MC-TSAM) model was developed to classify a given site into distinguished zones representing different levels of offshore Oil Spill Vulnerability Index (OSVI). It consisted of an adaptive resonance theory (ART) module, an ART Mapping module, and a centroid determination module. Monte Carlo simulation was integrated with the TSAM approach to address uncertainties that widely exist in site conditions. The applicability of the proposed model was validated by classifying a large coastal area, which was surrounded by potential oil spill sources, based on 12 features. Statistical analysis of the results indicated that the classification process was affected by multiple features instead of one single feature. The classification results also provided the least or desired number of zones which can sufficiently represent the levels of offshore OSVI in an area under uncertainty and complexity, saving time and budget in spill monitoring and response.
1993-09-01
This study refines risk analysis procedures for trichloroethylene (TCE) using a physiologically based pharmacokinetic (PBPK) model in conjunction...promulgate, and better present, more realistic standards.... Risk analysis , Physiologically based pharmacokinetics, Pbpk, Trichloroethylene, Monte carlo method.
Liu, Shaoying; King, Michael A.; Brill, Aaron B.; Stabin, Michael G.; Farncombe, Troy H.
2010-01-01
Monte Carlo (MC) is a well-utilized tool for simulating photon transport in single photon emission computed tomography (SPECT) due to its ability to accurately model physical processes of photon transport. As a consequence of this accuracy, it suffers from a relatively low detection efficiency and long computation time. One technique used to improve the speed of MC modeling is the effective and well-established variance reduction technique (VRT) known as forced detection (FD). With this method, photons are followed as they traverse the object under study but are then forced to travel in the direction of the detector surface, whereby they are detected at a single detector location. Another method, called convolution-based forced detection (CFD), is based on the fundamental idea of FD with the exception that detected photons are detected at multiple detector locations and determined with a distance-dependent blurring kernel. In order to further increase the speed of MC, a method named multiple projection convolution-based forced detection (MP-CFD) is presented. Rather than forcing photons to hit a single detector, the MP-CFD method follows the photon transport through the object but then, at each scatter site, forces the photon to interact with a number of detectors at a variety of angles surrounding the object. This way, it is possible to simulate all the projection images of a SPECT simulation in parallel, rather than as independent projections. The result of this is vastly improved simulation time as much of the computation load of simulating photon transport through the object is done only once for all projection angles. The results of the proposed MP-CFD method agrees well with the experimental data in measurements of point spread function (PSF), producing a correlation coefficient (r2) of 0.99 compared to experimental data. The speed of MP-CFD is shown to be about 60 times faster than a regular forced detection MC program with similar results. PMID:20811587
Chi, Yujie; Tian, Zhen; Jia, Xun
2016-08-07
Monte Carlo (MC) particle transport simulation on a graphics-processing unit (GPU) platform has been extensively studied recently due to the efficiency advantage achieved via massive parallelization. Almost all of the existing GPU-based MC packages were developed for voxelized geometry. This limited application scope of these packages. The purpose of this paper is to develop a module to model parametric geometry and integrate it in GPU-based MC simulations. In our module, each continuous region was defined by its bounding surfaces that were parameterized by quadratic functions. Particle navigation functions in this geometry were developed. The module was incorporated to two previously developed GPU-based MC packages and was tested in two example problems: (1) low energy photon transport simulation in a brachytherapy case with a shielded cylinder applicator and (2) MeV coupled photon/electron transport simulation in a phantom containing several inserts of different shapes. In both cases, the calculated dose distributions agreed well with those calculated in the corresponding voxelized geometry. The averaged dose differences were 1.03% and 0.29%, respectively. We also used the developed package to perform simulations of a Varian VS 2000 brachytherapy source and generated a phase-space file. The computation time under the parameterized geometry depended on the memory location storing the geometry data. When the data was stored in GPU's shared memory, the highest computational speed was achieved. Incorporation of parameterized geometry yielded a computation time that was ~3 times of that in the corresponding voxelized geometry. We also developed a strategy to use an auxiliary index array to reduce frequency of geometry calculations and hence improve efficiency. With this strategy, the computational time ranged in 1.75-2.03 times of the voxelized geometry for coupled photon/electron transport depending on the voxel dimension of the auxiliary index array, and in 0
Monte-Carlo simulation of an ultra small-angle neutron scattering instrument based on Soller slits
Rieker, T.; Hubbard, P.
1997-09-01
Monte Carlo simulations are used to investigate an ultra small-angle neutron scattering instrument for use at a pulsed source based on a Soller slit collimator and analyzer. The simulations show that for a q{sub min} of {approximately}le-4 {angstrom}{sup -1} (15 {angstrom} neutrons) a few tenths of a percent of the incident flux is transmitted through both collimators at q=0.
The simulation of the recharging method of active medical implant based on Monte Carlo method
NASA Astrophysics Data System (ADS)
Kong, Xianyue; Song, Yong; Hao, Qun; Cao, Jie; Zhang, Xiaoyu; Dai, Pantao; Li, Wansong
2014-11-01
The recharging of Active Medical Implant (AMI) is an important issue for its future application. In this paper, a method for recharging active medical implant using wearable incoherent light source has been proposed. Firstly, the models of the recharging method are developed. Secondly, the recharging processes of the proposed method have been simulated by using Monte Carlo (MC) method. Finally, some important conclusions have been reached. The results indicate that the proposed method will help to result in a convenient, safe and low-cost recharging method of AMI, which will promote the application of this kind of implantable device.
A study of potential numerical pitfalls in GPU-based Monte Carlo dose calculation
NASA Astrophysics Data System (ADS)
Magnoux, Vincent; Ozell, Benoît; Bonenfant, Éric; Després, Philippe
2015-07-01
The purpose of this study was to evaluate the impact of numerical errors caused by the floating point representation of real numbers in a GPU-based Monte Carlo code used for dose calculation in radiation oncology, and to identify situations where this type of error arises. The program used as a benchmark was bGPUMCD. Three tests were performed on the code, which was divided into three functional components: energy accumulation, particle tracking and physical interactions. First, the impact of single-precision calculations was assessed for each functional component. Second, a GPU-specific compilation option that reduces execution time as well as precision was examined. Third, a specific function used for tracking and potentially more sensitive to precision errors was tested by comparing it to a very high-precision implementation. Numerical errors were found in two components of the program. Because of the energy accumulation process, a few voxels surrounding a radiation source end up with a lower computed dose than they should. The tracking system contained a series of operations that abnormally amplify rounding errors in some situations. This resulted in some rare instances (less than 0.1%) of computed distances that are exceedingly far from what they should have been. Most errors detected had no significant effects on the result of a simulation due to its random nature, either because they cancel each other out or because they only affect a small fraction of particles. The results of this work can be extended to other types of GPU-based programs and be used as guidelines to avoid numerical errors on the GPU computing platform.
A voxel-based mouse for internal dose calculations using Monte Carlo simulations (MCNP)
NASA Astrophysics Data System (ADS)
Bitar, A.; Lisbona, A.; Thedrez, P.; Sai Maurel, C.; LeForestier, D.; Barbet, J.; Bardies, M.
2007-02-01
Murine models are useful for targeted radiotherapy pre-clinical experiments. These models can help to assess the potential interest of new radiopharmaceuticals. In this study, we developed a voxel-based mouse for dosimetric estimates. A female nude mouse (30 g) was frozen and cut into slices. High-resolution digital photographs were taken directly on the frozen block after each section. Images were segmented manually. Monoenergetic photon or electron sources were simulated using the MCNP4c2 Monte Carlo code for each source organ, in order to give tables of S-factors (in Gy Bq-1 s-1) for all target organs. Results obtained from monoenergetic particles were then used to generate S-factors for several radionuclides of potential interest in targeted radiotherapy. Thirteen source and 25 target regions were considered in this study. For each source region, 16 photon and 16 electron energies were simulated. Absorbed fractions, specific absorbed fractions and S-factors were calculated for 16 radionuclides of interest for targeted radiotherapy. The results obtained generally agree well with data published previously. For electron energies ranging from 0.1 to 2.5 MeV, the self-absorbed fraction varies from 0.98 to 0.376 for the liver, and from 0.89 to 0.04 for the thyroid. Electrons cannot be considered as 'non-penetrating' radiation for energies above 0.5 MeV for mouse organs. This observation can be generalized to radionuclides: for example, the beta self-absorbed fraction for the thyroid was 0.616 for I-131; absorbed fractions for Y-90 for left kidney-to-left kidney and for left kidney-to-spleen were 0.486 and 0.058, respectively. Our voxel-based mouse allowed us to generate a dosimetric database for use in preclinical targeted radiotherapy experiments.
A study of potential numerical pitfalls in GPU-based Monte Carlo dose calculation.
Magnoux, Vincent; Ozell, Benoît; Bonenfant, Éric; Després, Philippe
2015-07-07
The purpose of this study was to evaluate the impact of numerical errors caused by the floating point representation of real numbers in a GPU-based Monte Carlo code used for dose calculation in radiation oncology, and to identify situations where this type of error arises. The program used as a benchmark was bGPUMCD. Three tests were performed on the code, which was divided into three functional components: energy accumulation, particle tracking and physical interactions. First, the impact of single-precision calculations was assessed for each functional component. Second, a GPU-specific compilation option that reduces execution time as well as precision was examined. Third, a specific function used for tracking and potentially more sensitive to precision errors was tested by comparing it to a very high-precision implementation. Numerical errors were found in two components of the program. Because of the energy accumulation process, a few voxels surrounding a radiation source end up with a lower computed dose than they should. The tracking system contained a series of operations that abnormally amplify rounding errors in some situations. This resulted in some rare instances (less than 0.1%) of computed distances that are exceedingly far from what they should have been. Most errors detected had no significant effects on the result of a simulation due to its random nature, either because they cancel each other out or because they only affect a small fraction of particles. The results of this work can be extended to other types of GPU-based programs and be used as guidelines to avoid numerical errors on the GPU computing platform.
Recovering intrinsic fluorescence by Monte Carlo modeling.
Müller, Manfred; Hendriks, Benno H W
2013-02-01
We present a novel way to recover intrinsic fluorescence in turbid media based on Monte Carlo generated look-up tables and making use of a diffuse reflectance measurement taken at the same location. The method has been validated on various phantoms with known intrinsic fluorescence and is benchmarked against photon-migration methods. This new method combines more flexibility in the probe design with fast reconstruction and showed similar reconstruction accuracy as found in other reconstruction methods.
Accelerated Monte Carlo by Embedded Cluster Dynamics
NASA Astrophysics Data System (ADS)
Brower, R. C.; Gross, N. A.; Moriarty, K. J. M.
1991-07-01
We present an overview of the new methods for embedding Ising spins in continuous fields to achieve accelerated cluster Monte Carlo algorithms. The methods of Brower and Tamayo and Wolff are summarized and variations are suggested for the O( N) models based on multiple embedded Z2 spin components and/or correlated projections. Topological features are discussed for the XY model and numerical simulations presented for d=2, d=3 and mean field theory lattices.
NASA Astrophysics Data System (ADS)
Du, Zhengchun; Zhu, Mengrui; Wu, Zhaoyong; Yang, Jianguo
2016-12-01
The uncertainty determination of the geometrical feature measurement for coordinate measuring machines (CMMs) is an essential part in the reliable quality control process. However, the most commonly-used methods for uncertainty assessment are difficult and require not only a large number of repeated measurements but also rich operation experience. Based on the error ellipse theory and the Monte Carlo simulation method, an uncertainty evaluation method for CMM measurements is presented. For circular features, the uncertainty evaluation model was established and extended into the use of an application of two holes’ central distance measurement through Monte Carlo Simulation. The verification experiment of the new method was conducted and results were compared with the traditional ones and they fit reasonably well, which proved the validity of the proposed method.
Effect of statistical uncertainties on Monte Carlo treatment planning
NASA Astrophysics Data System (ADS)
Ma, C.-M.; Li, J. S.; Jiang, S. B.; Pawlicki, T.; Xiong, W.; Qin, L. H.; Yang, J.
2005-03-01
This paper reviews the effect of statistical uncertainties on radiotherapy treatment planning using Monte Carlo simulations. We discuss issues related to the statistical analysis of Monte Carlo dose calculations for realistic clinical beams using various variance reduction or time saving techniques. We discuss the effect of statistical uncertainties on dose prescription and monitor unit calculation for conventional treatment and intensity-modulated radiotherapy (IMRT) based on Monte Carlo simulations. We show the effect of statistical uncertainties on beamlet dose calculation and plan optimization for IMRT and other advanced treatment techniques such as modulated electron radiotherapy (MERT). We provide practical guidelines for the clinical implementation of Monte Carlo treatment planning and show realistic examples of Monte Carlo based IMRT and MERT plans.
Keall, Paul J; Siebers, Jeffrey V; Libby, Bruce; Mohan, Radhe
2003-04-01
An accurate dose calculation in phantom and patient geometries requires an accurate description of the radiation source. Errors in the radiation source description are propagated through the dose calculation. With the emergence of linear accelerators whose dosimetric characteristics are similar to within measurement uncertainty, the same radiation source description can be used as the input to dose calculation for treatment planning at many institutions with the same linear accelerator model. Our goal in the current research was to determine the initial electron fluence above the linear accelerator target for such an accelerator to allow a dose calculation in water to within 1% or 1 mm of the measured data supplied by the manufacturer. The method used for both the radiation source description and the patient transport was Monte Carlo. The linac geometry was input into the Monte Carlo code using the accelerator's manufacturer's specifications. Assumptions about the initial electron source above the target were made based on previous studies. The free parameters derived for the calculations were the mean energy and radial Gaussian width of the initial electron fluence and the target density. A combination of the free parameters yielded an initial electron fluence that, when transported through the linear accelerator and into the phantom, allowed a dose-calculation agreement to the experimental ion chamber data to within the specified criteria at both 6 and 18 MV nominal beam energies, except near the surface, particularly for the 18 MV beam. To save time during Monte Carlo treatment planning, the initial electron fluence was transported through part of the treatment head to a plane between the monitor chambers and the jaws and saved as phase-space files. These files are used for clinical Monte Carlo-based treatment planning and are freely available from the authors.
NASA Astrophysics Data System (ADS)
Parodi, K.; Ferrari, A.; Sommerer, F.; Paganetti, H.
2007-07-01
Clinical investigations on post-irradiation PET/CT (positron emission tomography/computed tomography) imaging for in vivo verification of treatment delivery and, in particular, beam range in proton therapy are underway at Massachusetts General Hospital (MGH). Within this project, we have developed a Monte Carlo framework for CT-based calculation of dose and irradiation-induced positron emitter distributions. Initial proton beam information is provided by a separate Geant4 Monte Carlo simulation modelling the treatment head. Particle transport in the patient is performed in the CT voxel geometry using the FLUKA Monte Carlo code. The implementation uses a discrete number of different tissue types with composition and mean density deduced from the CT scan. Scaling factors are introduced to account for the continuous Hounsfield unit dependence of the mass density and of the relative stopping power ratio to water used by the treatment planning system (XiO (Computerized Medical Systems Inc.)). Resulting Monte Carlo dose distributions are generally found in good correspondence with calculations of the treatment planning program, except a few cases (e.g. in the presence of air/tissue interfaces). Whereas dose is computed using standard FLUKA utilities, positron emitter distributions are calculated by internally combining proton fluence with experimental and evaluated cross-sections yielding 11C, 15O, 14O, 13N, 38K and 30P. Simulated positron emitter distributions yield PET images in good agreement with measurements. In this paper, we describe in detail the specific implementation of the FLUKA calculation framework, which may be easily adapted to handle arbitrary phase spaces of proton beams delivered by other facilities or include more reaction channels based on additional cross-section data. Further, we demonstrate the effects of different acquisition time regimes (e.g., PET imaging during or after irradiation) on the intensity and spatial distribution of the irradiation
Chen, Xueli; Gao, Xinbo; Qu, Xiaochao; Chen, Duofang; Ma, Bin; Wang, Lin; Peng, Kuan; Liang, Jimin; Tian, Jie
2010-01-01
During the past decade, Monte Carlo method has obtained wide applications in optical imaging to simulate photon transport process inside tissues. However, this method has not been effectively extended to the simulation of free-space photon transport at present. In this paper, a uniform framework for noncontact optical imaging is proposed based on Monte Carlo method, which consists of the simulation of photon transport both in tissues and in free space. Specifically, the simplification theory of lens system is utilized to model the camera lens equipped in the optical imaging system, and Monte Carlo method is employed to describe the energy transformation from the tissue surface to the CCD camera. Also, the focusing effect of camera lens is considered to establish the relationship of corresponding points between tissue surface and CCD camera. Furthermore, a parallel version of the framework is realized, making the simulation much more convenient and effective. The feasibility of the uniform framework and the effectiveness of the parallel version are demonstrated with a cylindrical phantom based on real experimental results. PMID:20689705
Monte Carlo N-particle simulation of neutron-based sterilisation of anthrax contamination.
Liu, B; Xu, J; Liu, T; Ouyang, X
2012-10-01
To simulate the neutron-based sterilisation of anthrax contamination by Monte Carlo N-particle (MCNP) 4C code. Neutrons are elementary particles that have no charge. They are 20 times more effective than electrons or γ-rays in killing anthrax spores on surfaces and inside closed containers. Neutrons emitted from a (252)Cf neutron source are in the 100 keV to 2 MeV energy range. A 2.5 MeV D-D neutron generator can create neutrons at up to 10(13) n s(-1) with current technology. All these enable an effective and low-cost method of killing anthrax spores. There is no effect on neutron energy deposition on the anthrax sample when using a reflector that is thicker than its saturation thickness. Among all three reflecting materials tested in the MCNP simulation, paraffin is the best because it has the thinnest saturation thickness and is easy to machine. The MCNP radiation dose and fluence simulation calculation also showed that the MCNP-simulated neutron fluence that is needed to kill the anthrax spores agrees with previous analytical estimations very well. The MCNP simulation indicates that a 10 min neutron irradiation from a 0.5 g (252)Cf neutron source or a 1 min neutron irradiation from a 2.5 MeV D-D neutron generator may kill all anthrax spores in a sample. This is a promising result because a 2.5 MeV D-D neutron generator output >10(13) n s(-1) should be attainable in the near future. This indicates that we could use a D-D neutron generator to sterilise anthrax contamination within several seconds.
Monte Carlo N-particle simulation of neutron-based sterilisation of anthrax contamination
Liu, B; Xu, J; Liu, T; Ouyang, X
2012-01-01
Objective To simulate the neutron-based sterilisation of anthrax contamination by Monte Carlo N-particle (MCNP) 4C code. Methods Neutrons are elementary particles that have no charge. They are 20 times more effective than electrons or γ-rays in killing anthrax spores on surfaces and inside closed containers. Neutrons emitted from a 252Cf neutron source are in the 100 keV to 2 MeV energy range. A 2.5 MeV D–D neutron generator can create neutrons at up to 1013 n s−1 with current technology. All these enable an effective and low-cost method of killing anthrax spores. Results There is no effect on neutron energy deposition on the anthrax sample when using a reflector that is thicker than its saturation thickness. Among all three reflecting materials tested in the MCNP simulation, paraffin is the best because it has the thinnest saturation thickness and is easy to machine. The MCNP radiation dose and fluence simulation calculation also showed that the MCNP-simulated neutron fluence that is needed to kill the anthrax spores agrees with previous analytical estimations very well. Conclusion The MCNP simulation indicates that a 10 min neutron irradiation from a 0.5 g 252Cf neutron source or a 1 min neutron irradiation from a 2.5 MeV D–D neutron generator may kill all anthrax spores in a sample. This is a promising result because a 2.5 MeV D–D neutron generator output >1013 n s−1 should be attainable in the near future. This indicates that we could use a D–D neutron generator to sterilise anthrax contamination within several seconds. PMID:22573293
GPU-based fast Monte Carlo dose calculation for proton therapy.
Jia, Xun; Schümann, Jan; Paganetti, Harald; Jiang, Steve B
2012-12-07
Accurate radiation dose calculation is essential for successful proton radiotherapy. Monte Carlo (MC) simulation is considered to be the most accurate method. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. We have developed a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. In gPMC, proton transport is modeled by the class II condensed history simulation scheme with a continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons are not transported and their energies are locally deposited. After an inelastic nuclear interaction event, a variety of products are generated using an empirical model. Among them, charged nuclear fragments are terminated with energy locally deposited. Secondary protons are stored in a stack and transported after finishing transport of the primary protons, while secondary neutral particles are neglected. gPMC is implemented on the GPU under the CUDA platform. We have validated gPMC using the TOPAS/Geant4 MC code as the gold standard. For various cases including homogeneous and inhomogeneous phantoms as well as a patient case, good agreements between gPMC and TOPAS/Geant4 are observed. The gamma passing rate for the 2%/2 mm criterion is over 98.7% in the region with dose greater than 10% maximum dose in all cases, excluding low-density air regions. With gPMC it takes only 6-22 s to simulate 10 million source protons to achieve ∼1% relative statistical uncertainty, depending on the phantoms and energy. This is an extremely high efficiency compared to the computational time of tens of CPU hours for TOPAS/Geant4. Our fast GPU-based code can thus facilitate the routine use of MC dose calculation in proton therapy.
Monte Carlo based NMR simulations of open fractures in porous media
NASA Astrophysics Data System (ADS)
Lukács, Tamás; Balázs, László
2014-05-01
According to the basic principles of nuclear magnetic resonance (NMR), a measurement's free induction decay curve has an exponential characteristic and its parameter is the transversal relaxation time, T2, given by the Bloch equations in rotating frame. In our simulations we are observing that particular case when the bulk's volume is neglectable to the whole system, the vertical movement is basically zero, hence the diffusion part of the T2 relation can be editted out. This small-apertured situations are common in sedimentary layers, and the smallness of the observed volume enable us to calculate with just the bulk relaxation and the surface relaxation. The simulation uses the Monte-Carlo method, so it is based on a random-walk generator which provides the brownian motions of the particles by uniformly distributed, pseudorandom generated numbers. An attached differential equation assures the bulk relaxation, the initial and the iterated conditions guarantee the simulation's replicability and enable having consistent estimations. We generate an initial geometry of a plain segment with known height, with given number of particles, the spatial distribution is set to equal to each simulation, and the surface-volume ratio remains at a constant value. It follows that to the given thickness of the open fracture, from the fitted curve's parameter, the surface relaxivity is determinable. The calculated T2 distribution curves are also indicating the inconstancy in the observed fracture situations. The effect of varying the height of the lamina at a constant diffusion coefficient also produces characteristic anomaly and for comparison we have run the simulation with the same initial volume, number of particles and conditions in spherical bulks, their profiles are clear and easily to understand. The surface relaxation enables us to estimate the interaction beetwen the materials of boundary with this two geometrically well-defined bulks, therefore the distribution takes as a
NASA Astrophysics Data System (ADS)
Karamat, Muhammad I.; Farncombe, Troy H.
2015-10-01
Simultaneous multi-isotope Single Photon Emission Computed Tomography (SPECT) imaging has a number of applications in cardiac, brain, and cancer imaging. The major concern however, is the significant crosstalk contamination due to photon scatter between the different isotopes. The current study focuses on a method of crosstalk compensation between two isotopes in simultaneous dual isotope SPECT acquisition applied to cancer imaging using 99mTc and 111In. We have developed an iterative image reconstruction technique that simulates the photon down-scatter from one isotope into the acquisition window of a second isotope. Our approach uses an accelerated Monte Carlo (MC) technique for the forward projection step in an iterative reconstruction algorithm. The MC estimated scatter contamination of a radionuclide contained in a given projection view is then used to compensate for the photon contamination in the acquisition window of other nuclide. We use a modified ordered subset-expectation maximization (OS-EM) algorithm named simultaneous ordered subset-expectation maximization (Sim-OSEM), to perform this step. We have undertaken a number of simulation tests and phantom studies to verify this approach. The proposed reconstruction technique was also evaluated by reconstruction of experimentally acquired phantom data. Reconstruction using Sim-OSEM showed very promising results in terms of contrast recovery and uniformity of object background compared to alternative reconstruction methods implementing alternative scatter correction schemes (i.e., triple energy window or separately acquired projection data). In this study the evaluation is based on the quality of reconstructed images and activity estimated using Sim-OSEM. In order to quantitate the possible improvement in spatial resolution and signal to noise ratio (SNR) observed in this study, further simulation and experimental studies are required.
Monte Carlo-based noise compensation in coil intensity corrected endorectal MRI.
Lui, Dorothy; Modhafar, Amen; Haider, Masoom A; Wong, Alexander
2015-10-12
Prostate cancer is one of the most common forms of cancer found in males making early diagnosis important. Magnetic resonance imaging (MRI) has been useful in visualizing and localizing tumor candidates and with the use of endorectal coils (ERC), the signal-to-noise ratio (SNR) can be improved. The coils introduce intensity inhomogeneities and the surface coil intensity correction built into MRI scanners is used to reduce these inhomogeneities. However, the correction typically performed at the MRI scanner level leads to noise amplification and noise level variations. In this study, we introduce a new Monte Carlo-based noise compensation approach for coil intensity corrected endorectal MRI which allows for effective noise compensation and preservation of details within the prostate. The approach accounts for the ERC SNR profile via a spatially-adaptive noise model for correcting non-stationary noise variations. Such a method is useful particularly for improving the image quality of coil intensity corrected endorectal MRI data performed at the MRI scanner level and when the original raw data is not available. SNR and contrast-to-noise ratio (CNR) analysis in patient experiments demonstrate an average improvement of 11.7 and 11.2 dB respectively over uncorrected endorectal MRI, and provides strong performance when compared to existing approaches. Experimental results using both phantom and patient data showed that ACER provided strong performance in terms of SNR, CNR, edge preservation, subjective scoring when compared to a number of existing approaches. A new noise compensation method was developed for the purpose of improving the quality of coil intensity corrected endorectal MRI data performed at the MRI scanner level. We illustrate that promising noise compensation performance can be achieved for the proposed approach, which is particularly important for processing coil intensity corrected endorectal MRI data performed at the MRI scanner level and when the
TH-C-17A-08: Monte Carlo Based Design of Efficient Scintillating Fiber Dosimeters
Wiles, A; Loyalka, S; Rangaraj, D; Izaguirre, E
2014-06-15
Purpose: To accurately predict Cherenkov radiation generation in scintillating fiber dosimeters. Quantifying Cherenkov radiation provides a method for optimizing fiber dimensions, orientation, optical filters, and photodiode spectral sensitivity to achieve efficient real time imaging dosimeter designs. Methods: We develop in-house Monte Carlo simulation software to model polymer scintillation fibers' fluorescence and Cherenkov emission in megavoltage clinical beams. The model computes emissions using generation probabilities, wavelength sampling, fiber photon capture, and fiber transport efficiency and incorporates the fiber's index of refraction, optical attenuation in the Cherenkov and visible spectrum and fiber dimensions. Detector component selection based on parameters such as silicon photomultiplier efficiency and optical coupling filters separates Cherenkov radiation from the dose-proportional scintillating emissions. The computation uses spectral and geometrical separation of Cherenkov radiation, however other filtering techniques can expand the model. Results: We compute Cherenkov generation per electron and fiber capture and transmission of those photons toward the detector with incident electron beam angle dependence. The model accounts for beam obliquity and nonperpendicular electron fiber impingement, which increases Cherenkov emission and trapping. The rotational angle around square fibers shows trapping efficiency variation from the normally incident minimum to a maximum at 45 degrees rotation. For rotation in the plane formed by the fiber axis and its surface normal, trapping efficiency increases with angle from the normal. The Cherenkov spectrum follows the theoretical curve from 300nm to 800nm, the wavelength range of interest defined by silicon photomultiplier and photodiode spectral efficiency. Conclusion: We are able to compute Cherenkov generation in realistic real time scintillating fiber dosimeter geometries. Design parameters incorporate
Canopy polarized BRDF simulation based on non-stationary Monte Carlo 3-D vector RT modeling
NASA Astrophysics Data System (ADS)
Kallel, Abdelaziz; Gastellu-Etchegorry, Jean Philippe
2017-03-01
Vector radiative transfer (VRT) has been largely used to simulate polarized reflectance of atmosphere and ocean. However it is still not properly used to describe vegetation cover polarized reflectance. In this study, we try to propose a 3-D VRT model based on a modified Monte Carlo (MC) forward ray tracing simulation to analyze vegetation canopy reflectance. Two kinds of leaf scattering are taken into account: (i) Lambertian diffuse reflectance and transmittance and (ii) specular reflection. A new method to estimate the condition on leaf orientation to produce reflection is proposed, and its probability to occur, Pl,max, is computed. It is then shown that Pl,max is low, but when reflection happens, the corresponding radiance Stokes vector, Io, is very high. Such a phenomenon dramatically increases the MC variance and yields to an irregular reflectance distribution function. For better regularization, we propose a non-stationary MC approach that simulates reflection for each sunny leaf assuming that its orientation is randomly chosen according to its angular distribution. It is shown in this case that the average canopy reflection is proportional to Pl,max ·Io which produces a smooth distribution. Two experiments are conducted: (i) assuming leaf light polarization is only due to the Fresnel reflection and (ii) the general polarization case. In the former experiment, our results confirm that in the forward direction, canopy polarizes horizontally light. In addition, they show that in inclined forward direction, diagonal polarization can be observed. In the latter experiment, polarization is produced in all orientations. It is particularly pointed out that specular polarization explains just a part of the forward polarization. Diffuse scattering polarizes light horizontally and vertically in forward and backward directions, respectively. Weak circular polarization signal is also observed near the backscattering direction. Finally, validation of the non
GPU-based fast Monte Carlo dose calculation for proton therapy
NASA Astrophysics Data System (ADS)
Jia, Xun; Schümann, Jan; Paganetti, Harald; Jiang, Steve B.
2012-12-01
Accurate radiation dose calculation is essential for successful proton radiotherapy. Monte Carlo (MC) simulation is considered to be the most accurate method. However, the long computation time limits it from routine clinical applications. Recently, graphics processing units (GPUs) have been widely used to accelerate computationally intensive tasks in radiotherapy. We have developed a fast MC dose calculation package, gPMC, for proton dose calculation on a GPU. In gPMC, proton transport is modeled by the class II condensed history simulation scheme with a continuous slowing down approximation. Ionization, elastic and inelastic proton nucleus interactions are considered. Energy straggling and multiple scattering are modeled. Secondary electrons are not transported and their energies are locally deposited. After an inelastic nuclear interaction event, a variety of products are generated using an empirical model. Among them, charged nuclear fragments are terminated with energy locally deposited. Secondary protons are stored in a stack and transported after finishing transport of the primary protons, while secondary neutral particles are neglected. gPMC is implemented on the GPU under the CUDA platform. We have validated gPMC using the TOPAS/Geant4 MC code as the gold standard. For various cases including homogeneous and inhomogeneous phantoms as well as a patient case, good agreements between gPMC and TOPAS/Geant4 are observed. The gamma passing rate for the 2%/2 mm criterion is over 98.7% in the region with dose greater than 10% maximum dose in all cases, excluding low-density air regions. With gPMC it takes only 6-22 s to simulate 10 million source protons to achieve ˜1% relative statistical uncertainty, depending on the phantoms and energy. This is an extremely high efficiency compared to the computational time of tens of CPU hours for TOPAS/Geant4. Our fast GPU-based code can thus facilitate the routine use of MC dose calculation in proton therapy.
NASA Astrophysics Data System (ADS)
Paiva Fonseca, Gabriel; Landry, Guillaume; White, Shane; D'Amours, Michel; Yoriyaz, Hélio; Beaulieu, Luc; Reniers, Brigitte; Verhaegen, Frank
2014-10-01
Accounting for brachytherapy applicator attenuation is part of the recommendations from the recent report of AAPM Task Group 186. To do so, model based dose calculation algorithms require accurate modelling of the applicator geometry. This can be non-trivial in the case of irregularly shaped applicators such as the Fletcher Williamson gynaecological applicator or balloon applicators with possibly irregular shapes employed in accelerated partial breast irradiation (APBI) performed using electronic brachytherapy sources (EBS). While many of these applicators can be modelled using constructive solid geometry (CSG), the latter may be difficult and time-consuming. Alternatively, these complex geometries can be modelled using tessellated geometries such as tetrahedral meshes (mesh geometries (MG)). Recent versions of Monte Carlo (MC) codes Geant4 and MCNP6 allow for the use of MG. The goal of this work was to model a series of applicators relevant to brachytherapy using MG. Applicators designed for 192Ir sources and 50 kV EBS were studied; a shielded vaginal applicator, a shielded Fletcher Williamson applicator and an APBI balloon applicator. All applicators were modelled in Geant4 and MCNP6 using MG and CSG for dose calculations. CSG derived dose distributions were considered as reference and used to validate MG models by comparing dose distribution ratios. In general agreement within 1% for the dose calculations was observed for all applicators between MG and CSG and between codes when considering volumes inside the 25% isodose surface. When compared to CSG, MG required longer computation times by a factor of at least 2 for MC simulations using the same code. MCNP6 calculation times were more than ten times shorter than Geant4 in some cases. In conclusion we presented methods allowing for high fidelity modelling with results equivalent to CSG. To the best of our knowledge MG offers the most accurate representation of an irregular APBI balloon applicator.
Test Population Selection from Weibull-Based, Monte Carlo Simulations of Fatigue Life
NASA Technical Reports Server (NTRS)
Vlcek, Brian L.; Zaretsky, Erwin V.; Hendricks, Robert C.
2012-01-01
Fatigue life is probabilistic and not deterministic. Experimentally establishing the fatigue life of materials, components, and systems is both time consuming and costly. As a result, conclusions regarding fatigue life are often inferred from a statistically insufficient number of physical tests. A proposed methodology for comparing life results as a function of variability due to Weibull parameters, variability between successive trials, and variability due to size of the experimental population is presented. Using Monte Carlo simulation of randomly selected lives from a large Weibull distribution, the variation in the L10 fatigue life of aluminum alloy AL6061 rotating rod fatigue tests was determined as a function of population size. These results were compared to the L10 fatigue lives of small (10 each) populations from AL2024, AL7075 and AL6061. For aluminum alloy AL6061, a simple algebraic relationship was established for the upper and lower L10 fatigue life limits as a function of the number of specimens failed. For most engineering applications where less than 30 percent variability can be tolerated in the maximum and minimum values, at least 30 to 35 test samples are necessary. The variability of test results based on small sample sizes can be greater than actual differences, if any, that exists between materials and can result in erroneous conclusions. The fatigue life of AL2024 is statistically longer than AL6061 and AL7075. However, there is no statistical difference between the fatigue lives of AL6061 and AL7075 even though AL7075 had a fatigue life 30 percent greater than AL6061.
Test Population Selection from Weibull-Based, Monte Carlo Simulations of Fatigue Life
NASA Technical Reports Server (NTRS)
Vlcek, Brian L.; Zaretsky, Erwin V.; Hendricks, Robert C.
2008-01-01
Fatigue life is probabilistic and not deterministic. Experimentally establishing the fatigue life of materials, components, and systems is both time consuming and costly. As a result, conclusions regarding fatigue life are often inferred from a statistically insufficient number of physical tests. A proposed methodology for comparing life results as a function of variability due to Weibull parameters, variability between successive trials, and variability due to size of the experimental population is presented. Using Monte Carlo simulation of randomly selected lives from a large Weibull distribution, the variation in the L10 fatigue life of aluminum alloy AL6061 rotating rod fatigue tests was determined as a function of population size. These results were compared to the L10 fatigue lives of small (10 each) populations from AL2024, AL7075 and AL6061. For aluminum alloy AL6061, a simple algebraic relationship was established for the upper and lower L10 fatigue life limits as a function of the number of specimens failed. For most engineering applications where less than 30 percent variability can be tolerated in the maximum and minimum values, at least 30 to 35 test samples are necessary. The variability of test results based on small sample sizes can be greater than actual differences, if any, that exists between materials and can result in erroneous conclusions. The fatigue life of AL2024 is statistically longer than AL6061 and AL7075. However, there is no statistical difference between the fatigue lives of AL6061 and AL7075 even though AL7075 had a fatigue life 30 percent greater than AL6061.
GPU-based fast Monte Carlo simulation for radiotherapy dose calculation.
Jia, Xun; Gu, Xuejun; Graves, Yan Jiang; Folkerts, Michael; Jiang, Steve B
2011-11-21
Monte Carlo (MC) simulation is commonly considered to be the most accurate dose calculation method in radiotherapy. However, its efficiency still requires improvement for many routine clinical applications. In this paper, we present our recent progress toward the development of a graphics processing unit (GPU)-based MC dose calculation package, gDPM v2.0. It utilizes the parallel computation ability of a GPU to achieve high efficiency, while maintaining the same particle transport physics as in the original dose planning method (DPM) code and hence the same level of simulation accuracy. In GPU computing, divergence of execution paths between threads can considerably reduce the efficiency. Since photons and electrons undergo different physics and hence attain different execution paths, we use a simulation scheme where photon transport and electron transport are separated to partially relieve the thread divergence issue. A high-performance random number generator and a hardware linear interpolation are also utilized. We have also developed various components to handle the fluence map and linac geometry, so that gDPM can be used to compute dose distributions for realistic IMRT or VMAT treatment plans. Our gDPM package is tested for its accuracy and efficiency in both phantoms and realistic patient cases. In all cases, the average relative uncertainties are less than 1%. A statistical t-test is performed and the dose difference between the CPU and the GPU results is not found to be statistically significant in over 96% of the high dose region and over 97% of the entire region. Speed-up factors of 69.1 ∼ 87.2 have been observed using an NVIDIA Tesla C2050 GPU card against a 2.27 GHz Intel Xeon CPU processor. For realistic IMRT and VMAT plans, MC dose calculation can be completed with less than 1% standard deviation in 36.1 ∼ 39.6 s using gDPM.
An enhanced Monte Carlo outlier detection method.
Zhang, Liangxiao; Li, Peiwu; Mao, Jin; Ma, Fei; Ding, Xiaoxia; Zhang, Qi
2015-09-30
Outlier detection is crucial in building a highly predictive model. In this study, we proposed an enhanced Monte Carlo outlier detection method by establishing cross-prediction models based on determinate normal samples and analyzing the distribution of prediction errors individually for dubious samples. One simulated and three real datasets were used to illustrate and validate the performance of our method, and the results indicated that this method outperformed Monte Carlo outlier detection in outlier diagnosis. After these outliers were removed, the value of validation by Kovats retention indices and the root mean square error of prediction decreased from 3.195 to 1.655, and the average cross-validation prediction error decreased from 2.0341 to 1.2780. This method helps establish a good model by eliminating outliers. © 2015 Wiley Periodicals, Inc.
Monte Carlo results for the hydrogen Hugoniot.
Bezkrovniy, V; Filinov, V S; Kremp, D; Bonitz, M; Schlanges, M; Kraeft, W D; Levashov, P R; Fortov, V E
2004-11-01
We propose a theoretical Hugoniot relation obtained by combining results for the equation of state from the direct path integral Monte Carlo technique (DPIMC) and those from reaction ensemble Monte Carlo (REMC) simulations. The main idea of this proposal is based on the fact that the DPMIC technique provides first-principle results for a wide range of densities and temperatures including the region of partially ionized plasmas. On the other hand, for lower temperatures where the formation of molecules becomes dominant, DPIMC simulations become cumbersome and inefficient. For this region it is possible to use accurate REMC simulations where bound states (molecules) are treated on the Born-Oppenheimer level. The remaining interaction is then reduced to the scattering between neutral particles which is reliably treated classically by applying effective potentials. The resulting Hugoniot is located between the experimental values of Knudson et al. [Phys. Rev. Lett. 87, 225501 (2001)] and Collins et al. [Science 281, 1178 (1998)].
Quantum Monte Carlo applied to solids
Shulenburger, Luke; Mattsson, Thomas R.
2013-12-01
We apply diffusion quantum Monte Carlo to a broad set of solids, benchmarking the method by comparing bulk structural properties (equilibrium volume and bulk modulus) to experiment and density functional theory (DFT) based theories. The test set includes materials with many different types of binding including ionic, metallic, covalent, and van der Waals. We show that, on average, the accuracy is comparable to or better than that of DFT when using the new generation of functionals, including one hybrid functional and two dispersion corrected functionals. The excellent performance of quantum Monte Carlo on solids is promising for its application to heterogeneous systems and high-pressure/high-density conditions. Important to the results here is the application of a consistent procedure with regards to the several approximations that are made, such as finite-size corrections and pseudopotential approximations. This test set allows for any improvements in these methods to be judged in a systematic way.
Nature of time in Monte Carlo processes
NASA Astrophysics Data System (ADS)
Choi, M. Y.; Huberman, B. A.
1984-03-01
We show that the asymptotic behavior of Monte Carlo simulations of many-body systems is much more complex than that produced by continuous dynamics regardless of the updating process. Therefore the nature of time in Monte Carlo processes is discrete enough so as to produce dynamics which is different from that generated by the familiar master equation.
Challenges of Monte Carlo Transport
Long, Alex Roberts
2016-06-10
These are slides from a presentation for Parallel Summer School at Los Alamos National Laboratory. Solving discretized partial differential equations (PDEs) of interest can require a large number of computations. We can identify concurrency to allow parallel solution of discrete PDEs. Simulated particles histories can be used to solve the Boltzmann transport equation. Particle histories are independent in neutral particle transport, making them amenable to parallel computation. Physical parameters and method type determine the data dependencies of particle histories. Data requirements shape parallel algorithms for Monte Carlo. Then, Parallel Computational Physics and Parallel Monte Carlo are discussed and, finally, the results are given. The mesh passing method greatly simplifies the IMC implementation and allows simple load-balancing. Using MPI windows and passive, one-sided RMA further simplifies the implementation by removing target synchronization. The author is very interested in implementations of PGAS that may allow further optimization for one-sided, read-only memory access (e.g. Open SHMEM). The MPICH_RMA_OVER_DMAPP option and library is required to make one-sided messaging scale on Trinitite - Moonlight scales poorly. Interconnect specific libraries or functions are likely necessary to ensure performance. BRANSON has been used to directly compare the current standard method to a proposed method on idealized problems. The mesh passing algorithm performs well on problems that are designed to show the scalability of the particle passing method. BRANSON can now run load-imbalanced, dynamic problems. Potential avenues of improvement in the mesh passing algorithm will be implemented and explored. A suite of test problems that stress DD methods will elucidate a possible path forward for production codes.
Quantitative analyses of spectral measurement error based on Monte-Carlo simulation
NASA Astrophysics Data System (ADS)
Jiang, Jingying; Ma, Congcong; Zhang, Qi; Lu, Junsheng; Xu, Kexin
2015-03-01
The spectral measurement error is controlled by the resolution and the sensitivity of the spectroscopic instrument and the instability of involved environment. In this talk, the spectral measurement error has been analyzed quantitatively by using the Monte Carlo (MC) simulation. Take the floating reference point measurement for example, unavoidably there is a deviation between the measuring position and the theoretical position due to various influence factors. In order to determine the error caused by the positioning accuracy of the measuring device, Monte Carlo simulation has been carried out at the wavelength of 1310nm, simulating Intralipid solution of 2%. MC simulation was performed with the number of 1010 photons and the sampling interval of the ring at 1μm. The data from MC simulation will be analyzed on the basis of thinning and calculating method (TCM) proposed in this talk. The results indicate that TCM could be used to quantitatively analyze the spectral measurement error brought by the positioning inaccuracy.
Yuan, L G; Tang, Y Z; Zhang, Y X; Sun, J; Luo, X Y; Zhu, L X; Zhang, Z; Wang, R; Liu, Y H
2015-08-01
To estimate the valnemulin pharmacokinetic profile in a swine population and to assess a dosage regimen for increasing the likelihood of optimization. This study was, respectively, performed in 22 sows culled by p.o. administration and in 80 growing-finishing pigs by i.v. administration at a single dose of 10 mg/kg to develop a population pharmacokinetic model and Monte Carlo simulation. The relationships among the plasma concentration, dose, and time of valnemulin in pigs were illustrated as C(i,v) = X(0 )(8.4191 × 10(-4) × e(-0.2371t) + 1.2788 × 10(-5) × e(-0.0069t)) after i.v. and C(p.o) = X(0) (-8.4964 × 10(-4) × e(-0.5840t) + 8.4195 × e(-0.2371t) + 7.6869 × 10(-6) × e(-0.0069t)) after p.o. Monte Carlo simulation showed that T(>MIC) was more than 24 h when a single daily dosage at 13.5 mg/kg BW in pigs was administrated by p.o., and MIC was 0.031 mg/L. It was concluded that the current dosage regimen at 10-12 mg/kg BW led to valnemulin underexposure if the MIC was more than 0.031 mg/L and could increase the risk of treatment failure and/or drug resistance.
Density-of-States Based Monte Carlo Techniques for Simulation of Proteins and Polymers
NASA Astrophysics Data System (ADS)
Rathore, Nitin; Knotts, Thomas Allen; de Pablo, Juan José
2003-11-01
Monte Carlo methods are reaching a level of sophistication that permits study of relatively complex fluids or materials. Over the past few years our research group at the University of Wisconsin has concentrated its efforts on the development and application of these methods for the study of biological macromolecules, liquid crystalline suspensions and polymeric glasses. Much of our recent simulation work relies on the use of parallel tempering (or replica exchange) methods, and the use of expanded ensemble formalisms. Both of these approaches, however, face severe limitations in terms of the size of the systems that can be handled. Multicanonical or entropic sampling techniques can be used to overcome some of these limitations, but the challenge then resides in identifying appropriate weighting functions capable of leading to uniform sampling of phase space. In this regard, knowledge of the density of states would be particularly useful because it would permit perfectly uniform sampling of phase space. Recently, Wang and Landau have introduced a new technique that facilitates considerably the direct calculation of the density of states in Monte Carlo simulations. This paper discusses several variants of this technique, including its implementation in parallel, a Configurational Temperature Density of States, and an Expanded Ensemble Density of States. The implementation of these variants is discussed in the context of simulations of the folding behavior of several proteins.
NASA Astrophysics Data System (ADS)
Jedrychowski, M.; Bacroix, B.; Salman, O. U.; Tarasiuk, J.; Wronski, S.
2015-08-01
The work focuses on the influence of moderate plastic deformation on subsequent partial recrystallization of hexagonal zirconium (Zr702). In the considered case, strain induced boundary migration (SIBM) is assumed to be the dominating recrystallization mechanism. This hypothesis is analyzed and tested in detail using experimental EBSD-OIM data and Monte Carlo computer simulations. An EBSD investigation is performed on zirconium samples, which were channel-die compressed in two perpendicular directions: normal direction (ND) and transverse direction (TD) of the initial material sheet. The maximal applied strain was below 17%. Then, samples were briefly annealed in order to achieve a partly recrystallized state. Obtained EBSD data were analyzed in terms of texture evolution associated with a microstructural characterization, including: kernel average misorientation (KAM), grain orientation spread (GOS), twinning, grain size distributions, description of grain boundary regions. In parallel, Monte Carlo Potts model combined with experimental microstructures was employed in order to verify two main recrystallization scenarios: SIBM driven growth from deformed sub-grains and classical growth of recrystallization nuclei. It is concluded that simulation results provided by the SIBM model are in a good agreement with experimental data in terms of texture as well as microstructural evolution.
Burke, TImothy P.; Kiedrowski, Brian C.; Martin, William R.; Brown, Forrest B.
2015-11-19
Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics for one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.
Electronic structure quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Bajdich, Michal; Mitas, Lubos
2009-04-01
Quantum Monte Carlo (QMC) is an advanced simulation methodology for studies of manybody quantum systems. The QMC approaches combine analytical insights with stochastic computational techniques for efficient solution of several classes of important many-body problems such as the stationary Schrödinger equation. QMC methods of various flavors have been applied to a great variety of systems spanning continuous and lattice quantum models, molecular and condensed systems, BEC-BCS ultracold condensates, nuclei, etc. In this review, we focus on the electronic structure QMC, i.e., methods relevant for systems described by the electron-ion Hamiltonians. Some of the key QMC achievements include direct treatment of electron correlation, accuracy in predicting energy differences and favorable scaling in the system size. Calculations of atoms, molecules, clusters and solids have demonstrated QMC applicability to real systems with hundreds of electrons while providing 90-95% of the correlation energy and energy differences typically within a few percent of experiments. Advances in accuracy beyond these limits are hampered by the so-called fixed-node approximation which is used to circumvent the notorious fermion sign problem. Many-body nodes of fermion states and their properties have therefore become one of the important topics for further progress in predictive power and efficiency of QMC calculations. Some of our recent results on the wave function nodes and related nodal domain topologies will be briefly reviewed. This includes analysis of few-electron systems and descriptions of exact and approximate nodes using transformations and projections of the highly-dimensional nodal hypersurfaces into the 3D space. Studies of fermion nodes offer new insights into topological properties of eigenstates such as explicit demonstrations that generic fermionic ground states exhibit the minimal number of two nodal domains. Recently proposed trial wave functions based on Pfaffians with
Quantum Monte Carlo using a Stochastic Poisson Solver
Das, D; Martin, R M; Kalos, M H
2005-05-06
Quantum Monte Carlo (QMC) is an extremely powerful method to treat many-body systems. Usually quantum Monte Carlo has been applied in cases where the interaction potential has a simple analytic form, like the 1/r Coulomb potential. However, in a complicated environment as in a semiconductor heterostructure, the evaluation of the interaction itself becomes a non-trivial problem. Obtaining the potential from any grid-based finite-difference method, for every walker and every step is unfeasible. We demonstrate an alternative approach of solving the Poisson equation by a classical Monte Carlo within the overall quantum Monte Carlo scheme. We have developed a modified ''Walk On Spheres'' algorithm using Green's function techniques, which can efficiently account for the interaction energy of walker configurations, typical of quantum Monte Carlo algorithms. This stochastically obtained potential can be easily incorporated within popular quantum Monte Carlo techniques like variational Monte Carlo (VMC) or diffusion Monte Carlo (DMC). We demonstrate the validity of this method by studying a simple problem, the polarization of a helium atom in the electric field of an infinite capacitor.
Reconstruction of Monte Carlo replicas from Hessian parton distributions
NASA Astrophysics Data System (ADS)
Hou, Tie-Jiun; Gao, Jun; Huston, Joey; Nadolsky, Pavel; Schmidt, Carl; Stump, Daniel; Wang, Bo-Ting; Xie, Ke Ping; Dulat, Sayipjamal; Pumplin, Jon; Yuan, C. P.
2017-03-01
We explore connections between two common methods for quantifying the uncertainty in parton distribution functions (PDFs), based on the Hessian error matrix and Monte-Carlo sampling. CT14 parton distributions in the Hessian representation are converted into Monte-Carlo replicas by a numerical method that reproduces important properties of CT14 Hessian PDFs: the asymmetry of CT14 uncertainties and positivity of individual parton distributions. The ensembles of CT14 Monte-Carlo replicas constructed this way at NNLO and NLO are suitable for various collider applications, such as cross section reweighting. Master formulas for computation of asymmetric standard deviations in the Monte-Carlo representation are derived. A correction is proposed to address a bias in asymmetric uncertainties introduced by the Taylor series approximation. A numerical program is made available for conversion of Hessian PDFs into Monte-Carlo replicas according to normal, log-normal, and Watt-Thorne sampling procedures.
New approach based on tetrahedral-mesh geometry for accurate 4D Monte Carlo patient-dose calculation
NASA Astrophysics Data System (ADS)
Han, Min Cheol; Yeom, Yeon Soo; Kim, Chan Hyeong; Kim, Seonghoon; Sohn, Jason W.
2015-02-01
In the present study, to achieve accurate 4D Monte Carlo dose calculation in radiation therapy, we devised a new approach that combines (1) modeling of the patient body using tetrahedral-mesh geometry based on the patient’s 4D CT data, (2) continuous movement/deformation of the tetrahedral patient model by interpolation of deformation vector fields acquired through deformable image registration, and (3) direct transportation of radiation particles during the movement and deformation of the tetrahedral patient model. The results of our feasibility study show that it is certainly possible to construct 4D patient models (= phantoms) with sufficient accuracy using the tetrahedral-mesh geometry and to directly transport radiation particles during continuous movement and deformation of the tetrahedral patient model. This new approach not only produces more accurate dose distribution in the patient but also replaces the current practice of using multiple 3D voxel phantoms and combining multiple dose distributions after Monte Carlo simulations. For routine clinical application of our new approach, the use of fast automatic segmentation algorithms is a must. In order to achieve, simultaneously, both dose accuracy and computation speed, the number of tetrahedrons for the lungs should be optimized. Although the current computation speed of our new 4D Monte Carlo simulation approach is slow (i.e. ~40 times slower than that of the conventional dose accumulation approach), this problem is resolvable by developing, in Geant4, a dedicated navigation class optimized for particle transportation in tetrahedral-mesh geometry.
Periyasamy, Vijitha; Pramanik, Manojit
2016-04-10
Monte Carlo simulation for light propagation in biological tissue is widely used to study light-tissue interaction. Simulation for optical coherence tomography (OCT) studies requires handling of embedded objects of various shapes. In this work, time-domain OCT simulations for multilayered tissue with embedded objects (such as sphere, cylinder, ellipsoid, and cuboid) was done. Improved importance sampling (IS) was implemented for the proposed OCT simulation for faster speed. At first, IS was validated against standard and angular biased Monte Carlo methods for OCT. Both class I and class II photons were in agreement in all the three methods. However, the IS method had more than tenfold improvement in terms of simulation time. Next, B-scan images were obtained for four types of embedded objects. All the four shapes are clearly visible from the B-scan OCT images. With the improved IS B-scan OCT images of embedded objects can be obtained with reasonable simulation time using a standard desktop computer. User-friendly, C-based, Monte Carlo simulation for tissue layers with embedded objects for OCT (MCEO-OCT) will be very useful for time-domain OCT simulations in many biological applications.
Han, Min Cheol; Yeom, Yeon Soo; Kim, Chan Hyeong; Kim, Seonghoon; Sohn, Jason W
2015-02-21
In the present study, to achieve accurate 4D Monte Carlo dose calculation in radiation therapy, we devised a new approach that combines (1) modeling of the patient body using tetrahedral-mesh geometry based on the patient's 4D CT data, (2) continuous movement/deformation of the tetrahedral patient model by interpolation of deformation vector fields acquired through deformable image registration, and (3) direct transportation of radiation particles during the movement and deformation of the tetrahedral patient model. The results of our feasibility study show that it is certainly possible to construct 4D patient models (= phantoms) with sufficient accuracy using the tetrahedral-mesh geometry and to directly transport radiation particles during continuous movement and deformation of the tetrahedral patient model. This new approach not only produces more accurate dose distribution in the patient but also replaces the current practice of using multiple 3D voxel phantoms and combining multiple dose distributions after Monte Carlo simulations. For routine clinical application of our new approach, the use of fast automatic segmentation algorithms is a must. In order to achieve, simultaneously, both dose accuracy and computation speed, the number of tetrahedrons for the lungs should be optimized. Although the current computation speed of our new 4D Monte Carlo simulation approach is slow (i.e. ~40 times slower than that of the conventional dose accumulation approach), this problem is resolvable by developing, in Geant4, a dedicated navigation class optimized for particle transportation in tetrahedral-mesh geometry.
Zaikin, Alexey; Míguez, Joaquín
2017-01-01
We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency. PMID:28797087
Mariño, Inés P; Zaikin, Alexey; Míguez, Joaquín
2017-01-01
We compare three state-of-the-art Bayesian inference methods for the estimation of the unknown parameters in a stochastic model of a genetic network. In particular, we introduce a stochastic version of the paradigmatic synthetic multicellular clock model proposed by Ullner et al., 2007. By introducing dynamical noise in the model and assuming that the partial observations of the system are contaminated by additive noise, we enable a principled mechanism to represent experimental uncertainties in the synthesis of the multicellular system and pave the way for the design of probabilistic methods for the estimation of any unknowns in the model. Within this setup, we tackle the Bayesian estimation of a subset of the model parameters. Specifically, we compare three Monte Carlo based numerical methods for the approximation of the posterior probability density function of the unknown parameters given a set of partial and noisy observations of the system. The schemes we assess are the particle Metropolis-Hastings (PMH) algorithm, the nonlinear population Monte Carlo (NPMC) method and the approximate Bayesian computation sequential Monte Carlo (ABC-SMC) scheme. We present an extensive numerical simulation study, which shows that while the three techniques can effectively solve the problem there are significant differences both in estimation accuracy and computational efficiency.
A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system.
Ma, Jiasen; Beltran, Chris; Seum Wan Chan Tseung, Hok; Herman, Michael G
2014-12-01
Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. For relatively large and complex three-field head and neck cases, i.e., >100,000 spots with a target volume of ∼ 1000 cm(3) and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45,000 dollars. The fast calculation and
NASA Astrophysics Data System (ADS)
Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun
2015-04-01
Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 106 particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 105 particles per beamlet. Correspondingly, the computation time
A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system
Ma, Jiasen Beltran, Chris; Seum Wan Chan Tseung, Hok; Herman, Michael G.
2014-12-15
Purpose: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. Methods: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. Results: For relatively large and complex three-field head and neck cases, i.e., >100 000 spots with a target volume of ∼1000 cm{sup 3} and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. Conclusions: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45
Li, Yongbao; Tian, Zhen; Shi, Feng; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun
2015-04-07
Intensity-modulated radiation treatment (IMRT) plan optimization needs beamlet dose distributions. Pencil-beam or superposition/convolution type algorithms are typically used because of their high computational speed. However, inaccurate beamlet dose distributions may mislead the optimization process and hinder the resulting plan quality. To solve this problem, the Monte Carlo (MC) simulation method has been used to compute all beamlet doses prior to the optimization step. The conventional approach samples the same number of particles from each beamlet. Yet this is not the optimal use of MC in this problem. In fact, there are beamlets that have very small intensities after solving the plan optimization problem. For those beamlets, it may be possible to use fewer particles in dose calculations to increase efficiency. Based on this idea, we have developed a new MC-based IMRT plan optimization framework that iteratively performs MC dose calculation and plan optimization. At each dose calculation step, the particle numbers for beamlets were adjusted based on the beamlet intensities obtained through solving the plan optimization problem in the last iteration step. We modified a GPU-based MC dose engine to allow simultaneous computations of a large number of beamlet doses. To test the accuracy of our modified dose engine, we compared the dose from a broad beam and the summed beamlet doses in this beam in an inhomogeneous phantom. Agreement within 1% for the maximum difference and 0.55% for the average difference was observed. We then validated the proposed MC-based optimization schemes in one lung IMRT case. It was found that the conventional scheme required 10(6) particles from each beamlet to achieve an optimization result that was 3% difference in fluence map and 1% difference in dose from the ground truth. In contrast, the proposed scheme achieved the same level of accuracy with on average 1.2 × 10(5) particles per beamlet. Correspondingly, the computation
Monte Carlo simulations of compact gamma cameras based on avalanche photodiodes.
Després, Philippe; Funk, Tobias; Shah, Kanai S; Hasegawa, Bruce H
2007-06-07
Avalanche photodiodes (APDs), and in particular position-sensitive avalanche photodiodes (PSAPDs), are an attractive alternative to photomultiplier tubes (PMTs) for reading out scintillators for PET and SPECT. These solid-state devices offer high gain and quantum efficiency, and can potentially lead to more compact and robust imaging systems with improved spatial and energy resolution. In order to evaluate this performance improvement, we have conducted Monte Carlo simulations of gamma cameras based on avalanche photodiodes. Specifically, we investigated the relative merit of discrete and PSAPDs in a simple continuous crystal gamma camera. The simulated camera was composed of either a 4 x 4 array of four channels 8 x 8 mm2 PSAPDs or an 8 x 8 array of 4 x 4 mm2 discrete APDs. These configurations, requiring 64 channels readout each, were used to read the scintillation light from a 6 mm thick continuous CsI:Tl crystal covering the entire 3.6 x 3.6 cm2 photodiode array. The simulations, conducted with GEANT4, accounted for the optical properties of the materials, the noise characteristics of the photodiodes and the nonlinear charge division in PSAPDs. The performance of the simulated camera was evaluated in terms of spatial resolution, energy resolution and spatial uniformity at 99mTc (140 keV) and 125I ( approximately 30 keV) energies. Intrinsic spatial resolutions of 1.0 and 0.9 mm were obtained for the APD- and PSAPD-based cameras respectively for 99mTc, and corresponding values of 1.2 and 1.3 mm FWHM for 125I. The simulations yielded maximal energy resolutions of 7% and 23% for 99mTc and 125I, respectively. PSAPDs also provided better spatial uniformity than APDs in the simple system studied. These results suggest that APDs constitute an attractive technology especially suitable to build compact, small field of view gamma cameras dedicated, for example, to small animal or organ imaging.
van der Graaf, E R; Limburg, J; Koomans, R L; Tijs, M
2011-03-01
The calibration of scintillation detectors for gamma radiation in a well characterized setup can be transferred to other geometries using Monte Carlo simulations to account for the differences between the calibration and the other geometry. In this study a calibration facility was used that is constructed from bricks of well-known activity concentrations of ⁴⁰K and of radionuclides from the ²³⁸U- and ²³²Th-series. Transfer of the calibration was attempted to a Marinelli beaker geometry with the detector inside a lead shield and to an in situ application with the detector positioned on a sand bed. In general this resulted in good correspondence (within 5-10%) between the activity concentrations derived using the transferred calibration and activities that were derived by independent measurements. Some discrepancies were identified that were attributed to coincident summing in the natural decay series and interference of radon. Copyright © 2010 Elsevier Ltd. All rights reserved.
Experimental validation of a rapid Monte Carlo based micro-CT simulator
NASA Astrophysics Data System (ADS)
Colijn, A. P.; Zbijewski, W.; Sasov, A.; Beekman, F. J.
2004-09-01
We describe a newly developed, accelerated Monte Carlo simulator of a small animal micro-CT scanner. Transmission measurements using aluminium slabs are employed to estimate the spectrum of the x-ray source. The simulator incorporating this spectrum is validated with micro-CT scans of physical water phantoms of various diameters, some containing stainless steel and Teflon rods. Good agreement is found between simulated and real data: normalized error of simulated projections, as compared to the real ones, is typically smaller than 0.05. Also the reconstructions obtained from simulated and real data are found to be similar. Thereafter, effects of scatter are studied using a voxelized software phantom representing a rat body. It is shown that the scatter fraction can reach tens of per cents in specific areas of the body and therefore scatter can significantly affect quantitative accuracy in small animal CT imaging.
Using Monte Carlo/Gaussian Based Small Area Estimates to Predict Where Medicaid Patients Reside
Behrens, Jess J.; Wen, Xuejin; Goel, Satyender; Zhou, Jing; Fu, Lina; Kho, Abel N.
2016-01-01
Electronic Health Records (EHR) are rapidly becoming accepted as tools for planning and population health1,2. With the national dialogue around Medicaid expansion12, the role of EHR data has become even more important. For their potential to be fully realized and contribute to these discussions, techniques for creating accurate small area estimates is vital. As such, we examined the efficacy of developing small area estimates for Medicaid patients in two locations, Albuquerque and Chicago, by using a Monte Carlo/Gaussian technique that has worked in accurately locating registered voters in North Carolina11. The Albuquerque data, which includes patient address, will first be used to assess the accuracy of the methodology. Subsequently, it will be combined with the EHR data from Chicago to develop a regression that predicts Medicaid patients by US Block Group. We seek to create a tool that is effective in translating EHR data’s potential for population health studies. PMID:28269824
Monte Carlo based geometrical model for efficiency calculation of an n-type HPGe detector.
Cabal, Fatima Padilla; Lopez-Pino, Neivy; Bernal-Castillo, Jose Luis; Martinez-Palenzuela, Yisel; Aguilar-Mena, Jimmy; D'Alessandro, Katia; Arbelo, Yuniesky; Corrales, Yasser; Diaz, Oscar
2010-12-01
A procedure to optimize the geometrical model of an n-type detector is described. Sixteen lines from seven point sources ((241)Am, (133)Ba, (22)Na, (60)Co, (57)Co, (137)Cs and (152)Eu) placed at three different source-to-detector distances (10, 20 and 30 cm) were used to calibrate a low-background gamma spectrometer between 26 and 1408 keV. Direct Monte Carlo techniques using the MCNPX 2.6 and GEANT 4 9.2 codes, and a semi-empirical procedure were performed to obtain theoretical efficiency curves. Since discrepancies were found between experimental and calculated data using the manufacturer parameters of the detector, a detail study of the crystal dimensions and the geometrical configuration is carried out. The relative deviation with experimental data decreases from a mean value of 18-4%, after the parameters were optimized.
Monte Carlo based dosimetry for neutron capture therapy of brain tumors
NASA Astrophysics Data System (ADS)
Zaidi, Lilia; Belgaid, Mohamed; Khelifi, Rachid
2016-11-01
Boron Neutron Capture Therapy (BNCT) is a biologically targeted, radiation therapy for cancer which combines neutron irradiation with a tumor targeting agent labeled with a boron10 having a high thermal neutron capture cross section. The tumor area is subjected to the neutron irradiation. After a thermal neutron capture, the excited 11B nucleus fissions into an alpha particle and lithium recoil nucleus. The high Linear Energy Transfer (LET) emitted particles deposit their energy in a range of about 10μm, which is of the same order of cell diameter [1], at the same time other reactions due to neutron activation with body component are produced. In-phantom measurement of physical dose distribution is very important for BNCT planning validation. Determination of total absorbed dose requires complex calculations which were carried out using the Monte Carlo MCNP code [2].
Monte Carlo calculations and validation of a gold foil-based Bonner sphere system.
Fernández, F; Bouassoule, T; Amgarou, K; Domingo, C; Garcia, M J; Lacoste, V; Gressier, V; Muller, H
2007-01-01
The Grup de Física de les Radiacions (GFR) of the Universitat Autònoma de Barcelona (UAB), in collaboration with the Institute for Radiological Protection and Nuclear Safety (IRSN), has developed a passive Bonner sphere system (UAB-BSS), with gold foils as thermal neutron detectors, for application in pulsed neutron fields or in mixed neutron-photon fields with high photon intensities. In such fields, active devices suffer from saturation and dead-time effects. The MCNPX Monte-Carlo code has been used to determine the response to neutrons of different energies of each polyethylene sphere belonging to the BSS. The passive UAB-BSS system was characterised with the ISO (252)Cf reference source at the IRSN facilities. The energy distribution of the reference source neutron fluence was folded with the response functions for comparison with the experimental data. A good agreement between the experimental and calculated count rates was found.
PC-Based Process Distribution to Solve Iterative Monte Carlo Simulations in Physical Dosimetry
NASA Astrophysics Data System (ADS)
Leal, A.; Sánchez-Doblado, F.; Perucha, M.; Rincón, M.; Arrans, R.; Bernal, C.; Carrasco, E.
A distribution model to simulate physical dosimetry measurements with Monte Carlo (MC) techniques has been developed. This approach is indicated to solve the simulations where there are continuous changes of measurement conditions (and hence of the input parameters) such as a TPR curve or the estimation of the resolution limit of an optical densitometer in the case of small field profiles. As a comparison, a high resolution scan for narrow beams with no iterative process is presented. The model has been installed on a network PCs without any resident software. The only requirement for these PCs has been a small and temporal Linux partition in the hard disks and to be connecting by the net with our server PC.
Sun, Guojian; Luan, Bin; Zhao, Ruiying; Li, Zhanbiao; Xing, Zhangmin
2016-12-01
The purpose of this study was to introduce a new method to elucidating the molecular mechanisms in ischemic stroke. Genes from microarray data were performed enrichment to biological pathways. Dysregulated pathways and dysregulated pathway pairs were identified and constructed into networks. After Random Forest classification was performed, area under the curve (AUC) value of main network was calculated. After 50 bootstraps of Monte Carlo Cross-Validation, six pairs of pathways were found for >40 times. The best main network with AUC value = 0.735 was identified, including 14 pairs of pathways. Compared with the traditional method (gene set enrichment analysis), although a small part of pathways were shared, most of the pathways were closely related with ischemic stroke. The best network may give new insights into the underlying molecular mechanisms in ischemic stroke. It may play pivotal roles in the progression of ischemic stroke and particular attention should be focused on them for further research.
Monte Carlo based modeling of indocyanine green bolus tracking in the adult human head
NASA Astrophysics Data System (ADS)
Elliott, Jonathan T.; Diop, Mamadou; Tichauer, Kenneth M.; Lee, Ting-Yim; St. Lawrence, Keith
2011-02-01
The use of near-infrared spectroscopy (NIRS) is increasingly being investigated in critical care settings to assess cerebral hemodynamics, because of its potential for guiding therapy during the recovery period following brain injury. Cerebral blood flow (CBF) can be quantified by NIRS using indocyanine green (ICG) as an intravascular tracer. However, extracting accurate measurements from complex tissue geometries, such as the human head, is challenging and has hindered the clinical applications. With the development of fast Monte Carlo simulations that can take into account a priori anatomical information (e.g. near-infrared light propagation in tissue from MRI or CT imaging data), it is now possible to investigate signal contamination arising from the extracerebral layers, which can confound NIRS-CBF measurements. Here, we present a theoretical model that combines Monte Carlo simulations of broadband time-resolved near-infrared measurements with indicator-dilution theory to model time-dependent changes in light propagation following ICG bolus injection. Broadband, time-resolved near-infrared spectroscopy measurements were simulated for three source-detector positions. Individual simulations required 56 seconds for 5x108 photons, and a set of simulations consisting of baseline measurements at 40 wavelengths, and single-wavelength measurements at 160 time-points required on average 3.4 hours. To demonstrate the usefulness of our model, the propagation of errors associated with varying both the scalp blood flow and the scalp thickness was investigated. For each simulation the data were analyzed using four independent approaches-simple-subtraction blood flow index (ΔBFISS), time-resolved variance time-to-peak (ΔTTPTR), and absolute and relative CBF with depth-resolved NIRS (CBFDR and ΔCBFDR)-to assess cerebral hemodynamics.
[Study of Determination of Oil Mixture Components Content Based on Quasi-Monte Carlo Method].
Wang, Yu-tian; Xu, Jing; Liu, Xiao-fei; Chen, Meng-han; Wang, Shi-tao
2015-05-01
Gasoline, kerosene, diesel is processed by crude oil with different distillation range. The boiling range of gasoline is 35 ~205 °C. The boiling range of kerosene is 140~250 °C. And the boiling range of diesel is 180~370 °C. At the same time, the carbon chain length of differentmineral oil is different. The carbon chain-length of gasoline is within the scope of C7 to C11. The carbon chain length of kerosene is within the scope of C12 to C15. And the carbon chain length of diesel is within the scope of C15 to C18. The recognition and quantitative measurement of three kinds of mineral oil is based on different fluorescence spectrum formed in their different carbon number distribution characteristics. Mineral oil pollution occurs frequently, so monitoring mineral oil content in the ocean is very important. A new method of components content determination of spectra overlapping mineral oil mixture is proposed, with calculation of characteristic peak power integrationof three-dimensional fluorescence spectrum by using Quasi-Monte Carlo Method, combined with optimal algorithm solving optimum number of characteristic peak and range of integral region, solving nonlinear equations by using BFGS(a rank to two update method named after its inventor surname first letter, Boyden, Fletcher, Goldfarb and Shanno) method. Peak power accumulation of determined points in selected area is sensitive to small changes of fluorescence spectral line, so the measurement of small changes of component content is sensitive. At the same time, compared with the single point measurement, measurement sensitivity is improved by the decrease influence of random error due to the selection of points. Three-dimensional fluorescence spectra and fluorescence contour spectra of single mineral oil and the mixture are measured by taking kerosene, diesel and gasoline as research objects, with a single mineral oil regarded whole, not considered each mineral oil components. Six characteristic peaks are
NASA Astrophysics Data System (ADS)
Doronin, Alexander; Rushmeier, Holly E.; Meglinski, Igor; Bykov, Alexander V.
2016-03-01
We present a new Monte Carlo based approach for the modelling of Bidirectional Scattering-Surface Reflectance Distribution Function (BSSRDF) for accurate rendering of human skin appearance. The variations of both skin tissues structure and the major chromophores are taken into account correspondingly to the different ethnic and age groups. The computational solution utilizes HTML5, accelerated by the graphics processing units (GPUs), and therefore is convenient for the practical use at the most of modern computer-based devices and operating systems. The results of imitation of human skin reflectance spectra, corresponding skin colours and examples of 3D faces rendering are presented and compared with the results of phantom studies.
Monte Carlo Shower Counter Studies
NASA Technical Reports Server (NTRS)
Snyder, H. David
1991-01-01
Activities and accomplishments related to the Monte Carlo shower counter studies are summarized. A tape of the VMS version of the GEANT software was obtained and installed on the central computer at Gallaudet University. Due to difficulties encountered in updating this VMS version, a decision was made to switch to the UNIX version of the package. This version was installed and used to generate the set of data files currently accessed by various analysis programs. The GEANT software was used to write files of data for positron and proton showers. Showers were simulated for a detector consisting of 50 alternating layers of lead and scintillator. Each file consisted of 1000 events at each of the following energies: 0.1, 0.5, 2.0, 10, 44, and 200 GeV. Data analysis activities related to clustering, chi square, and likelihood analyses are summarized. Source code for the GEANT user subprograms and data analysis programs are provided along with example data plots.
TU-F-CAMPUS-T-05: A Cloud-Based Monte Carlo Dose Calculation for Electron Cutout Factors
Mitchell, T; Bush, K
2015-06-15
Purpose: For electron cutouts of smaller sizes, it is necessary to verify electron cutout factors due to perturbations in electron scattering. Often, this requires a physical measurement using a small ion chamber, diode, or film. The purpose of this study is to develop a fast Monte Carlo based dose calculation framework that requires only a smart phone photograph of the cutout and specification of the SSD and energy to determine the electron cutout factor, with the ultimate goal of making this cloud-based calculation widely available to the medical physics community. Methods: The algorithm uses a pattern recognition technique to identify the corners of the cutout in the photograph as shown in Figure 1. It then corrects for variations in perspective, scaling, and translation of the photograph introduced by the user’s positioning of the camera. Blob detection is used to identify the portions of the cutout which comprise the aperture and the portions which are cutout material. This information is then used define physical densities of the voxels used in the Monte Carlo dose calculation algorithm as shown in Figure 2, and select a particle source from a pre-computed library of phase-spaces scored above the cutout. The electron cutout factor is obtained by taking a ratio of the maximum dose delivered with the cutout in place to the dose delivered under calibration/reference conditions. Results: The algorithm has been shown to successfully identify all necessary features of the electron cutout to perform the calculation. Subsequent testing will be performed to compare the Monte Carlo results with a physical measurement. Conclusion: A simple, cloud-based method of calculating electron cutout factors could eliminate the need for physical measurements and substantially reduce the time required to properly assure accurate dose delivery.
Al-Subeihi, Ala A A; Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert; van Bladeren, Peter J; Rietjens, Ivonne M C M; Punt, Ans
2015-03-01
The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1'-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1'-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1'-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1'-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1'-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1'-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment.
Zhu, Changfang; Palmer, Gregory M.; Breslin, Tara M.; Harter, Josephine; Ramanujam, Nirmala
2009-01-01
We explore the use of Monte-Carlo-model-based approaches for the analysis of fluorescence and diffuse reflectance spectra measured ex vivo from breast tissues. These models are used to extract the absorption, scattering, and fluorescence properties of malignant and nonmalignant tissues and to diagnose breast cancer based on these intrinsic tissue properties. Absorption and scattering properties, including β-carotene concentration, total hemoglobin concentration, hemoglobin saturation, and the mean reduced scattering coefficient are derived from diffuse reflectance spectra using a previously developed Monte Carlo model of diffuse reflectance. A Monte Carlo model of fluorescence described in an earlier manuscript was employed to retrieve the intrinsic fluorescence spectra. The intrinsic fluorescence spectra were decomposed into several contributing components, which we attribute to endogenous fluorophores that may present in breast tissues including collagen, NADH, and retinol/vitamin A. The model-based approaches removes any dependency on the instrument and probe geometry. The relative fluorescence contributions of individual fluorescing components, as well as β-carotene concentration, hemoglobin saturation, and the mean reduced scattering coefficient display statistically significant differences between malignant and adipose breast tissues. The hemoglobin saturation and the reduced scattering coefficient display statistically significant differences between malignant and fibrous/benign breast tissues. A linear support vector machine classification using (1) fluorescence properties alone, (2) absorption and scattering properties alone, and (3) the combination of all tissue properties achieves comparable classification accuracies of 81 to 84% in sensitivity and 75 to 89% in specificity for discriminating malignant from nonmalignant breast tissues, suggesting each set of tissue properties are diagnostically useful for the discrimination of breast malignancy. PMID
Recommender engine for continuous-time quantum Monte Carlo methods.
Huang, Li; Yang, Yi-Feng; Wang, Lei
2017-03-01
Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.
Recommender engine for continuous-time quantum Monte Carlo methods
NASA Astrophysics Data System (ADS)
Huang, Li; Yang, Yi-feng; Wang, Lei
2017-03-01
Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.
Yuan, Jiankui; Zheng, Yiran; Wessels, Barry; Lo, Simon S; Ellis, Rodney; Machtay, Mitchell; Yao, Min
2016-12-01
A virtual source model for Monte Carlo simulations of helical TomoTherapy has been developed previously by the authors. The purpose of this work is to perform experiments in an anthropomorphic (RANDO) phantom with the same order of complexity as in clinical treatments to validate the virtual source model to be used for quality assurance secondary check on TomoTherapy patient planning dose. Helical TomoTherapy involves complex delivery pattern with irregular beam apertures and couch movement during irradiation. Monte Carlo simulation, as the most accurate dose algorithm, is desirable in radiation dosimetry. Current Monte Carlo simulations for helical TomoTherapy adopt the full Monte Carlo model, which includes detailed modeling of individual machine component, and thus, large phase space files are required at different scoring planes. As an alternative approach, we developed a virtual source model without using the large phase space files for the patient dose calculations previously. In this work, we apply the simulation system to recompute the patient doses, which were generated by the treatment planning system in an anthropomorphic phantom to mimic the real patient treatments. We performed thermoluminescence dosimeter point dose and film measurements to compare with Monte Carlo results. Thermoluminescence dosimeter measurements show that the relative difference in both Monte Carlo and treatment planning system is within 3%, with the largest difference less than 5% for both the test plans. The film measurements demonstrated 85.7% and 98.4% passing rate using the 3 mm/3% acceptance criterion for the head and neck and lung cases, respectively. Over 95% passing rate is achieved if 4 mm/4% criterion is applied. For the dose-volume histograms, very good agreement is obtained between the Monte Carlo and treatment planning system method for both cases. The experimental results demonstrate that the virtual source model Monte Carlo system can be a viable option for the
Sieh, Weiva; Basu, Saonli; Fu, Audrey Q; Rothstein, Joseph H; Scheet, Paul A; Stewart, William C L; Sung, Yun J; Thompson, Elizabeth A; Wijsman, Ellen M
2005-12-30
We performed multipoint linkage analysis of the electrophysiological trait ECB21 on chromosome 4 in the full pedigrees provided by the Collaborative Study on the Genetics of Alcoholism (COGA). Three Markov chain Monte Carlo (MCMC)-based approaches were applied to the provided and re-estimated genetic maps and to five different marker panels consisting of microsatellite (STRP) and/or SNP markers at various densities. We found evidence of linkage near the GABRB1 STRP using all methods, maps, and marker panels. Difficulties encountered with SNP panels included convergence problems and demanding computations.
[A study of brain inner tissue water molecule self-diffusion model based on Monte Carlo simulation].
Wu, Zhanxiong; Zhu, Shanan; Bin, He
2010-06-01
The study of water molecule self-diffusion process is of importance not only for getting anatomical information of brain inner tissue, but also for shedding light on the diffusion process of some medicine in brain tissue. In this paper, we summarized the self-diffusion model of water molecule in brain inner tissue, and calculated the self-diffusion coefficient based on Monte Carlo simulation under different conditions. The comparison between this result and that of Latour model showed that the two self-diffusion coefficients were getting closer when the diffusion time became longer, and that the Latour model was a long time-depended self-diffusion model.
Analytical Applications of Monte Carlo Techniques.
ERIC Educational Resources Information Center
Guell, Oscar A.; Holcombe, James A.
1990-01-01
Described are analytical applications of the theory of random processes, in particular solutions obtained by using statistical procedures known as Monte Carlo techniques. Supercomputer simulations, sampling, integration, ensemble, annealing, and explicit simulation are discussed. (CW)
Improved Monte Carlo Renormalization Group Method
DOE R&D Accomplishments Database
Gupta, R.; Wilson, K. G.; Umrigar, C.
1985-01-01
An extensive program to analyze critical systems using an Improved Monte Carlo Renormalization Group Method (IMCRG) being undertaken at LANL and Cornell is described. Here we first briefly review the method and then list some of the topics being investigated.
An analytic linear accelerator source model for GPU-based Monte Carlo dose calculations.
Tian, Zhen; Li, Yongbao; Folkerts, Michael; Shi, Feng; Jiang, Steve B; Jia, Xun
2015-10-21
Recently, there has been a lot of research interest in developing fast Monte Carlo (MC) dose calculation methods on graphics processing unit (GPU) platforms. A good linear accelerator (linac) source model is critical for both accuracy and efficiency considerations. In principle, an analytical source model should be more preferred for GPU-based MC dose engines than a phase-space file-based model, in that data loading and CPU-GPU data transfer can be avoided. In this paper, we presented an analytical field-independent source model specifically developed for GPU-based MC dose calculations, associated with a GPU-friendly sampling scheme. A key concept called phase-space-ring (PSR) was proposed. Each PSR contained a group of particles that were of the same type, close in energy and reside in a narrow ring on the phase-space plane located just above the upper jaws. The model parameterized the probability densities of particle location, direction and energy for each primary photon PSR, scattered photon PSR and electron PSR. Models of one 2D Gaussian distribution or multiple Gaussian components were employed to represent the particle direction distributions of these PSRs. A method was developed to analyze a reference phase-space file and derive corresponding model parameters. To efficiently use our model in MC dose calculations on GPU, we proposed a GPU-friendly sampling strategy, which ensured that the particles sampled and transported simultaneously are of the same type and close in energy to alleviate GPU thread divergences. To test the accuracy of our model, dose distributions of a set of open fields in a water phantom were calculated using our source model and compared to those calculated using the reference phase-space files. For the high dose gradient regions, the average distance-to-agreement (DTA) was within 1 mm and the maximum DTA within 2 mm. For relatively low dose gradient regions, the root-mean-square (RMS) dose difference was within 1.1% and the maximum
NASA Astrophysics Data System (ADS)
Houska, Tobias; Multsch, Sebastian; Kraft, Philipp; Frede, Hans-Georg; Breuer, Lutz
2014-05-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the Van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 x 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The shape
NASA Astrophysics Data System (ADS)
Houska, T.; Multsch, S.; Kraft, P.; Frede, H.-G.; Breuer, L.
2013-12-01
Computer simulations are widely used to support decision making and planning in the agriculture sector. On the one hand, many plant growth models use simplified hydrological processes and structures, e.g. by the use of a small number of soil layers or by the application of simple water flow approaches. On the other hand, in many hydrological models plant growth processes are poorly represented. Hence, fully coupled models with a high degree of process representation would allow a more detailed analysis of the dynamic behaviour of the soil-plant interface. We used the Python programming language to couple two of such high process oriented independent models and to calibrate both models simultaneously. The Catchment Modelling Framework (CMF) simulated soil hydrology based on the Richards equation and the van-Genuchten-Mualem retention curve. CMF was coupled with the Plant growth Modelling Framework (PMF), which predicts plant growth on the basis of radiation use efficiency, degree days, water shortage and dynamic root biomass allocation. The Monte Carlo based Generalised Likelihood Uncertainty Estimation (GLUE) method was applied to parameterize the coupled model and to investigate the related uncertainty of model predictions to it. Overall, 19 model parameters (4 for CMF and 15 for PMF) were analysed through 2 × 106 model runs randomly drawn from an equally distributed parameter space. Three objective functions were used to evaluate the model performance, i.e. coefficient of determination (R2), bias and model efficiency according to Nash Sutcliffe (NSE). The model was applied to three sites with different management in Muencheberg (Germany) for the simulation of winter wheat (Triticum aestivum L.) in a cross-validation experiment. Field observations for model evaluation included soil water content and the dry matters of roots, storages, stems and leaves. Best parameter sets resulted in NSE of 0.57 for the simulation of soil moisture across all three sites. The
Al-Subeihi, Ala' A.A.; Alhusainy, Wasma; Kiwamoto, Reiko; Spenkelink, Bert; Bladeren, Peter J. van; Rietjens, Ivonne M.C.M.; Punt, Ans
2015-03-01
The present study aims at predicting the level of formation of the ultimate carcinogenic metabolite of methyleugenol, 1′-sulfooxymethyleugenol, in the human population by taking variability in key bioactivation and detoxification reactions into account using Monte Carlo simulations. Depending on the metabolic route, variation was simulated based on kinetic constants obtained from incubations with a range of individual human liver fractions or by combining kinetic constants obtained for specific isoenzymes with literature reported human variation in the activity of these enzymes. The results of the study indicate that formation of 1′-sulfooxymethyleugenol is predominantly affected by variation in i) P450 1A2-catalyzed bioactivation of methyleugenol to 1′-hydroxymethyleugenol, ii) P450 2B6-catalyzed epoxidation of methyleugenol, iii) the apparent kinetic constants for oxidation of 1′-hydroxymethyleugenol, and iv) the apparent kinetic constants for sulfation of 1′-hydroxymethyleugenol. Based on the Monte Carlo simulations a so-called chemical-specific adjustment factor (CSAF) for intraspecies variation could be derived by dividing different percentiles by the 50th percentile of the predicted population distribution for 1′-sulfooxymethyleugenol formation. The obtained CSAF value at the 90th percentile was 3.2, indicating that the default uncertainty factor of 3.16 for human variability in kinetics may adequately cover the variation within 90% of the population. Covering 99% of the population requires a larger uncertainty factor of 6.4. In conclusion, the results showed that adequate predictions on interindividual human variation can be made with Monte Carlo-based PBK modeling. For methyleugenol this variation was observed to be in line with the default variation generally assumed in risk assessment. - Highlights: • Interindividual human differences in methyleugenol bioactivation were simulated. • This was done using in vitro incubations, PBK modeling
Extra Chance Generalized Hybrid Monte Carlo
NASA Astrophysics Data System (ADS)
Campos, Cédric M.; Sanz-Serna, J. M.
2015-01-01
We study a method, Extra Chance Generalized Hybrid Monte Carlo, to avoid rejections in the Hybrid Monte Carlo method and related algorithms. In the spirit of delayed rejection, whenever a rejection would occur, extra work is done to find a fresh proposal that, hopefully, may be accepted. We present experiments that clearly indicate that the additional work per sample carried out in the extra chance approach clearly pays in terms of the quality of the samples generated.
NASA Astrophysics Data System (ADS)
Tian, Zhen; Jiang Graves, Yan; Jia, Xun; Jiang, Steve B.
2014-10-01
Monte Carlo (MC) simulation is commonly considered as the most accurate method for radiation dose calculations. Commissioning of a beam model in the MC code against a clinical linear accelerator beam is of crucial importance for its clinical implementation. In this paper, we propose an automatic commissioning method for our GPU-based MC dose engine, gDPM. gDPM utilizes a beam model based on a concept of phase-space-let (PSL). A PSL contains a group of particles that are of the same type and close in space and energy. A set of generic PSLs was generated by splitting a reference phase-space file. Each PSL was associated with a weighting factor, and in dose calculations the particle carried a weight corresponding to the PSL where it was from. Dose for each PSL in water was pre-computed, and hence the dose in water for a whole beam under a given set of PSL weighting factors was the weighted sum of the PSL doses. At the commissioning stage, an optimization problem was solved to adjust the PSL weights in order to minimize the difference between the calculated dose and measured one. Symmetry and smoothness regularizations were utilized to uniquely determine the solution. An augmented Lagrangian method was employed to solve the optimization problem. To validate our method, a phase-space file of a Varian TrueBeam 6 MV beam was used to generate the PSLs for 6 MV beams. In a simulation study, we commissioned a Siemens 6 MV beam on which a set of field-dependent phase-space files was available. The dose data of this desired beam for different open fields and a small off-axis open field were obtained by calculating doses using these phase-space files. The 3D γ-index test passing rate within the regions with dose above 10% of dmax dose for those open fields tested was improved averagely from 70.56 to 99.36% for 2%/2 mm criteria and from 32.22 to 89.65% for 1%/1 mm criteria. We also tested our commissioning method on a six-field head-and-neck cancer IMRT plan. The
Monte Carlo-based treatment planning system calculation engine for microbeam radiation therapy
Martinez-Rovira, I.; Sempau, J.; Prezado, Y.
2012-05-15
Purpose: Microbeam radiation therapy (MRT) is a synchrotron radiotherapy technique that explores the limits of the dose-volume effect. Preclinical studies have shown that MRT irradiations (arrays of 25-75-{mu}m-wide microbeams spaced by 200-400 {mu}m) are able to eradicate highly aggressive animal tumor models while healthy tissue is preserved. These promising results have provided the basis for the forthcoming clinical trials at the ID17 Biomedical Beamline of the European Synchrotron Radiation Facility (ESRF). The first step includes irradiation of pets (cats and dogs) as a milestone before treatment of human patients. Within this context, accurate dose calculations are required. The distinct features of both beam generation and irradiation geometry in MRT with respect to conventional techniques require the development of a specific MRT treatment planning system (TPS). In particular, a Monte Carlo (MC)-based calculation engine for the MRT TPS has been developed in this work. Experimental verification in heterogeneous phantoms and optimization of the computation time have also been performed. Methods: The penelope/penEasy MC code was used to compute dose distributions from a realistic beam source model. Experimental verification was carried out by means of radiochromic films placed within heterogeneous slab-phantoms. Once validation was completed, dose computations in a virtual model of a patient, reconstructed from computed tomography (CT) images, were performed. To this end, decoupling of the CT image voxel grid (a few cubic millimeter volume) to the dose bin grid, which has micrometer dimensions in the transversal direction of the microbeams, was performed. Optimization of the simulation parameters, the use of variance-reduction (VR) techniques, and other methods, such as the parallelization of the simulations, were applied in order to speed up the dose computation. Results: Good agreement between MC simulations and experimental results was achieved, even at
Monte Carlo simulation based study of a proposed multileaf collimator for a telecobalt machine
Sahani, G.; Dash Sharma, P. K.; Hussain, S. A.; Dutt Sharma, Sunil; Sharma, D. N.
2013-02-15
Purpose: The objective of the present work was to propose a design of a secondary multileaf collimator (MLC) for a telecobalt machine and optimize its design features through Monte Carlo simulation. Methods: The proposed MLC design consists of 72 leaves (36 leaf pairs) with additional jaws perpendicular to leaf motion having the capability of shaping a maximum square field size of 35 Multiplication-Sign 35 cm{sup 2}. The projected widths at isocenter of each of the central 34 leaf pairs and 2 peripheral leaf pairs are 10 and 5 mm, respectively. The ends of the leaves and the x-jaws were optimized to obtain acceptable values of dosimetric and leakage parameters. Monte Carlo N-Particle code was used for generating beam profiles and depth dose curves and estimating the leakage radiation through the MLC. A water phantom of dimension 50 Multiplication-Sign 50 Multiplication-Sign 40 cm{sup 3} with an array of voxels (4 Multiplication-Sign 0.3 Multiplication-Sign 0.6 cm{sup 3}= 0.72 cm{sup 3}) was used for the study of dosimetric and leakage characteristics of the MLC. Output files generated for beam profiles were exported to the PTW radiation field analyzer software through locally developed software for analysis of beam profiles in order to evaluate radiation field width, beam flatness, symmetry, and beam penumbra. Results: The optimized version of the MLC can define radiation fields of up to 35 Multiplication-Sign 35 cm{sup 2} within the prescribed tolerance values of 2 mm. The flatness and symmetry were found to be well within the acceptable tolerance value of 3%. The penumbra for a 10 Multiplication-Sign 10 cm{sup 2} field size is 10.7 mm which is less than the generally acceptable value of 12 mm for a telecobalt machine. The maximum and average radiation leakage through the MLC were found to be 0.74% and 0.41% which are well below the International Electrotechnical Commission recommended tolerance values of 2% and 0.75%, respectively. The maximum leakage through the
Marcus, Ryan C.
2012-07-24
Overview of this presentation is (1) Exascale computing - different technologies, getting there; (2) high-performance proof-of-concept MCMini - features and results; and (3) OpenCL toolkit - Oatmeal (OpenCL Automatic Memory Allocation Library) - purpose and features. Despite driver issues, OpenCL seems like a good, hardware agnostic tool. MCMini demonstrates the possibility for GPGPU-based Monte Carlo methods - it shows great scaling for HPC application and algorithmic equivalence. Oatmeal provides a flexible framework to aid in the development of scientific OpenCL codes.
MBR Monte Carlo Simulation in PYTHIA8
NASA Astrophysics Data System (ADS)
Ciesielski, R.
We present the MBR (Minimum Bias Rockefeller) Monte Carlo simulation of (anti)proton-proton interactions and its implementation in the PYTHIA8 event generator. We discuss the total, elastic, and total-inelastic cross sections, and three contributions from diffraction dissociation processes that contribute to the latter: single diffraction, double diffraction, and central diffraction or double-Pomeron exchange. The event generation follows a renormalized-Regge-theory model, successfully tested using CDF data. Based on the MBR-enhanced PYTHIA8 simulation, we present cross-section predictions for the LHC and beyond, up to collision energies of 50 TeV.
Monte Carlo procedure for protein design
NASA Astrophysics Data System (ADS)
Irbäck, Anders; Peterson, Carsten; Potthast, Frank; Sandelin, Erik
1998-11-01
A method for sequence optimization in protein models is presented. The approach, which has inherited its basic philosophy from recent work by Deutsch and Kurosky [Phys. Rev. Lett. 76, 323 (1996)] by maximizing conditional probabilities rather than minimizing energy functions, is based upon a different and very efficient multisequence Monte Carlo scheme. By construction, the method ensures that the designed sequences represent good folders thermodynamically. A bootstrap procedure for the sequence space search is devised making very large chains feasible. The algorithm is successfully explored on the two-dimensional HP model [K. F. Lau and K. A. Dill, Macromolecules 32, 3986 (1989)] with chain lengths N=16, 18, and 32.
Monte Carlo algorithm for free energy calculation.
Bi, Sheng; Tong, Ning-Hua
2015-07-01
We propose a Monte Carlo algorithm for the free energy calculation based on configuration space sampling. An upward or downward temperature scan can be used to produce F(T). We implement this algorithm for the Ising model on a square lattice and triangular lattice. Comparison with the exact free energy shows an excellent agreement. We analyze the properties of this algorithm and compare it with the Wang-Landau algorithm, which samples in energy space. This method is applicable to general classical statistical models. The possibility of extending it to quantum systems is discussed.
Monte Carlo simulation for the transport beamline
NASA Astrophysics Data System (ADS)
Romano, F.; Attili, A.; Cirrone, G. A. P.; Carpinelli, M.; Cuttone, G.; Jia, S. B.; Marchetto, F.; Russo, G.; Schillaci, F.; Scuderi, V.; Tramontana, A.; Varisano, A.
2013-07-01
In the framework of the ELIMED project, Monte Carlo (MC) simulations are widely used to study the physical transport of charged particles generated by laser-target interactions and to preliminarily evaluate fluence and dose distributions. An energy selection system and the experimental setup for the TARANIS laser facility in Belfast (UK) have been already simulated with the GEANT4 (GEometry ANd Tracking) MC toolkit. Preliminary results are reported here. Future developments are planned to implement a MC based 3D treatment planning in order to optimize shots number and dose delivery.
Evaluation of a commercial MRI Linac based Monte Carlo dose calculation algorithm with GEANT 4
Ahmad, Syed Bilal; Sarfehnia, Arman; Kim, Anthony; Sahgal, Arjun; Keller, Brian; Paudel, Moti Raj; Hissoiny, Sami
2016-02-15
Purpose: This paper provides a comparison between a fast, commercial, in-patient Monte Carlo dose calculation algorithm (GPUMCD) and GEANT4. It also evaluates the dosimetric impact of the application of an external 1.5 T magnetic field. Methods: A stand-alone version of the Elekta™ GPUMCD algorithm, to be used within the Monaco treatment planning system to model dose for the Elekta™ magnetic resonance imaging (MRI) Linac, was compared against GEANT4 (v10.1). This was done in the presence or absence of a 1.5 T static magnetic field directed orthogonally to the radiation beam axis. Phantoms with material compositions of water, ICRU lung, ICRU compact-bone, and titanium were used for this purpose. Beams with 2 MeV monoenergetic photons as well as a 7 MV histogrammed spectrum representing the MRI Linac spectrum were emitted from a point source using a nominal source-to-surface distance of 142.5 cm. Field sizes ranged from 1.5 × 1.5 to 10 × 10 cm{sup 2}. Dose scoring was performed using a 3D grid comprising 1 mm{sup 3} voxels. The production thresholds were equivalent for both codes. Results were analyzed based upon a voxel by voxel dose difference between the two codes and also using a volumetric gamma analysis. Results: Comparisons were drawn from central axis depth doses, cross beam profiles, and isodose contours. Both in the presence and absence of a 1.5 T static magnetic field the relative differences in doses scored along the beam central axis were less than 1% for the homogeneous water phantom and all results matched within a maximum of ±2% for heterogeneous phantoms. Volumetric gamma analysis indicated that more than 99% of the examined volume passed gamma criteria of 2%—2 mm (dose difference and distance to agreement, respectively). These criteria were chosen because the minimum primary statistical uncertainty in dose scoring voxels was 0.5%. The presence of the magnetic field affects the dose at the interface depending upon the density of the material
Evaluation of a commercial MRI Linac based Monte Carlo dose calculation algorithm with GEANT4.
Ahmad, Syed Bilal; Sarfehnia, Arman; Paudel, Moti Raj; Kim, Anthony; Hissoiny, Sami; Sahgal, Arjun; Keller, Brian
2016-02-01
This paper provides a comparison between a fast, commercial, in-patient Monte Carlo dose calculation algorithm (GPUMCD) and geant4. It also evaluates the dosimetric impact of the application of an external 1.5 T magnetic field. A stand-alone version of the Elekta™ GPUMCD algorithm, to be used within the Monaco treatment planning system to model dose for the Elekta™ magnetic resonance imaging (MRI) Linac, was compared against GEANT4 (v10.1). This was done in the presence or absence of a 1.5 T static magnetic field directed orthogonally to the radiation beam axis. Phantoms with material compositions of water, ICRU lung, ICRU compact-bone, and titanium were used for this purpose. Beams with 2 MeV monoenergetic photons as well as a 7 MV histogrammed spectrum representing the MRI Linac spectrum were emitted from a point source using a nominal source-to-surface distance of 142.5 cm. Field sizes ranged from 1.5 × 1.5 to 10 × 10 cm(2). Dose scoring was performed using a 3D grid comprising 1 mm(3) voxels. The production thresholds were equivalent for both codes. Results were analyzed based upon a voxel by voxel dose difference between the two codes and also using a volumetric gamma analysis. Comparisons were drawn from central axis depth doses, cross beam profiles, and isodose contours. Both in the presence and absence of a 1.5 T static magnetic field the relative differences in doses scored along the beam central axis were less than 1% for the homogeneous water phantom and all results matched within a maximum of ±2% for heterogeneous phantoms. Volumetric gamma analysis indicated that more than 99% of the examined volume passed gamma criteria of 2%-2 mm (dose difference and distance to agreement, respectively). These criteria were chosen because the minimum primary statistical uncertainty in dose scoring voxels was 0.5%. The presence of the magnetic field affects the dose at the interface depending upon the density of the material on either sides of the interface
NASA Astrophysics Data System (ADS)
Pande, S.; Shafiei, M.
2016-12-01
Markov chain Monte Carlo (MCMC) methods have been applied in many hydrologic studies to explore posterior parameter distributions within a Bayesian framework. Accurate estimation of posterior parameter distributions is key to reliably estimate marginal likelihood functions and hence to reliably estimate measures of Bayesian complexity. This paper introduces an alternative to well-known random walk based MCMC samplers. An Adaptive Kernel Density Independence Sampling based Monte Carlo Sampling (A-KISMCS) is proposed. A-KISMCS uses an independence sampler with Metropolis-Hastings (M-H) updates which ensures that candidate observations are drawn independently of the current state of a chain. This ensures efficient exploration of the target distribution. The bandwidth of the kernel density estimator is also adapted online in order to increase its accuracy and ensure fast convergence to a target distribution. The performance of A-KISMCS is tested on one several case studies, including synthetic and real world case studies of hydrological modelling and compared with Differential Evolution Adaptive Metropolis (DREAM-zs), which is fundamentally based on random walk sampling with differential evolution. Results show that while DREAM-zs converges to slightly sharper posterior densities, A-KISMCS is slightly more efficient in tracking the mode of the posteriors.
NASA Astrophysics Data System (ADS)
Zhang, Jun; Guo, Fan
2015-11-01
Tooth modification technique is widely used in gear industry to improve the meshing performance of gearings. However, few of the present studies on tooth modification considers the influence of inevitable random errors on gear modification effects. In order to investigate the uncertainties of tooth modification amount variations on system's dynamic behaviors of a helical planetary gears, an analytical dynamic model including tooth modification parameters is proposed to carry out a deterministic analysis on the dynamics of a helical planetary gear. The dynamic meshing forces as well as the dynamic transmission errors of the sun-planet 1 gear pair with and without tooth modifications are computed and compared to show the effectiveness of tooth modifications on gear dynamics enhancement. By using response surface method, a fitted regression model for the dynamic transmission error(DTE) fluctuations is established to quantify the relationship between modification amounts and DTE fluctuations. By shifting the inevitable random errors arousing from manufacturing and installing process to tooth modification amount variations, a statistical tooth modification model is developed and a methodology combining Monte Carlo simulation and response surface method is presented for uncertainty analysis of tooth modifications. The uncertainly analysis reveals that the system's dynamic behaviors do not obey the normal distribution rule even though the design variables are normally distributed. In addition, a deterministic modification amount will not definitely achieve an optimal result for both static and dynamic transmission error fluctuation reduction simultaneously.
Performance evaluation of Biograph PET/CT system based on Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Wang, Bing; Gao, Fei; Liu, Hua-Feng
2010-10-01
Combined lutetium oxyorthosilicate (LSO) Biograph PET/CT is developed by Siemens Company and has been introduced into medical practice. There is no septa between the scintillator rings, the acquisition mode is full 3D mode. The PET components incorporate three rings of 48 detector blocks which comprises a 13×13 matrix of 4×4×20mm3 elements. The patient aperture is 70cm, the transversal field of view (FOV) is 58.5cm, and the axial field of view is 16.2cm. The CT components adopt 16 slices spiral CT scanner. The physical performance of this PET/CT scanner has been evaluated using Monte Carlo simulation method according to latest NEMA NU 2-2007 standard and the results have been compared with real experiment results. For PET part, in the center FOV the average transversal resolution is 3.67mm, the average axial resolution is 3.94mm, and the 3D-reconstructed scatter fraction is 31.7%. The sensitivities of the PET scanner are 4.21kcps/MBq and 4.26kcps/MBq at 0cm and 10cm off the center of the transversal FOV. The peak NEC is 95.6kcps at a concentration of 39.2kBq/ml. The spatial resolution of CT part is up to 1.12mm at 10mm off the center. The errors between simulated and real results are permitted.
QSAR models for HEPT derivates as NNRTI inhibitors based on Monte Carlo method.
Toropova, Alla P; Toropov, Andrey A; Veselinović, Jovana B; Miljković, Filip N; Veselinović, Aleksandar M
2014-04-22
A series of 107 1-[(2-hydroxyethoxy)-methyl]-6-(phenylthio) thymine (HEPT) with anti-HIV-1 activity as a non-nucleoside reverse transcriptase inhibitor (NNRTI) has been studied. Monte Carlo method has been used as a tool to build up the quantitative structure-activity relationships (QSAR) for anti-HIV-1 activity. The QSAR models were calculated with the representation of the molecular structure by simplified molecular input-line entry system and by the molecular graph. Three various splits into training and test set were examined. Statistical quality of all build models is very good. Best calculated model had following statistical parameters: for training set r(2) = 0.8818, q(2) = 0.8774 and r(2) = 0.9360, q(2) = 0.9243 for test set. Structural indicators (alerts) for increase and decrease of the IC50 are defined. Using defined structural alerts computer aided design of new potential anti-HIV-1 HEPT derivates is presented. Copyright © 2014 Elsevier Masson SAS. All rights reserved.
Abdel-Khalik, Hany S.; Zhang, Qiong
2014-05-20
The development of hybrid Monte-Carlo-Deterministic (MC-DT) approaches, taking place over the past few decades, have primarily focused on shielding and detection applications where the analysis requires a small number of responses, i.e. at the detector locations(s). This work further develops a recently introduced global variance reduction approach, denoted by the SUBSPACE approach is designed to allow the use of MC simulation, currently limited to benchmarking calculations, for routine engineering calculations. By way of demonstration, the SUBSPACE approach is applied to assembly level calculations used to generate the few-group homogenized cross-sections. These models are typically expensive and need to be executed in the order of 10^{3} - 10^{5} times to properly characterize the few-group cross-sections for downstream core-wide calculations. Applicability to k-eigenvalue core-wide models is also demonstrated in this work. Given the favorable results obtained in this work, we believe the applicability of the MC method for reactor analysis calculations could be realized in the near future.
Kumar, A; Chauhan, S
2017-03-08
Obesity is one of the most provoking health burdens in the developed countries. One of the strategies to prevent obesity is the inhibition of pancreatic lipase enzyme. The aim of this study was to build QSAR models for natural lipase inhibitors by using the Monte Carlo method. The molecular structures were represented by the simplified molecular input line entry system (SMILES) notation and molecular graphs. Three sets - training, calibration and test set of three splits - were examined and validated. Statistical quality of all the described models was very good. The best QSAR model showed the following statistical parameters: r(2) = 0.864 and Q(2) = 0.836 for the test set and r(2) = 0.824 and Q(2) = 0.819 for the validation set. Structural attributes for increasing and decreasing the activity (expressed as pIC50) were also defined. Using defined structural attributes, the design of new potential lipase inhibitors is also presented. Additionally, a molecular docking study was performed for the determination of binding modes of designed molecules.
Lattice based Kinetic Monte Carlo Simulations of a complex chemical reaction network
NASA Astrophysics Data System (ADS)
Danielson, Thomas; Savara, Aditya; Hin, Celine
Lattice Kinetic Monte Carlo (KMC) simulations offer a powerful alternative to using ordinary differential equations for the simulation of complex chemical reaction networks. Lattice KMC provides the ability to account for local spatial configurations of species in the reaction network, resulting in a more detailed description of the reaction pathway. In KMC simulations with a large number of reactions, the range of transition probabilities can span many orders of magnitude, creating subsets of processes that occur more frequently or more rarely. Consequently, processes that have a high probability of occurring may be selected repeatedly without actually progressing the system (i.e. the forward and reverse process for the same reaction). In order to avoid the repeated occurrence of fast frivolous processes, it is necessary to throttle the transition probabilities in such a way that avoids altering the overall selectivity. Likewise, as the reaction progresses, new frequently occurring species and reactions may be introduced, making a dynamic throttling algorithm a necessity. We present a dynamic steady-state detection scheme with the goal of accurately throttling rate constants in order to optimize the KMC run time without compromising the selectivity of the reaction network. The algorithm has been applied to a large catalytic chemical reaction network, specifically that of methanol oxidative dehydrogenation, as well as additional pathways on CeO2(111) resulting in formaldehyde, CO, methanol, CO2, H2 and H2O as gas products.
Dosimetric investigation of proton therapy on CT-based patient data using Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Chongsan, T.; Liamsuwan, T.; Tangboonduangjit, P.
2016-03-01
The aim of radiotherapy is to deliver high radiation dose to the tumor with low radiation dose to healthy tissues. Protons have Bragg peaks that give high radiation dose to the tumor but low exit dose or dose tail. Therefore, proton therapy is promising for treating deep- seated tumors and tumors locating close to organs at risk. Moreover, the physical characteristic of protons is suitable for treating cancer in pediatric patients. This work developed a computational platform for calculating proton dose distribution using the Monte Carlo (MC) technique and patient's anatomical data. The studied case is a pediatric patient with a primary brain tumor. PHITS will be used for MC simulation. Therefore, patient-specific CT-DICOM files were converted to the PHITS input. A MATLAB optimization program was developed to create a beam delivery control file for this study. The optimization program requires the proton beam data. All these data were calculated in this work using analytical formulas and the calculation accuracy was tested, before the beam delivery control file is used for MC simulation. This study will be useful for researchers aiming to investigate proton dose distribution in patients but do not have access to proton therapy machines.
NASA Astrophysics Data System (ADS)
Waseda, O.; Goldenstein, H.; Silva, G. F. B. Lenz e.; Neiva, A.; Chantrenne, P.; Morthomas, J.; Perez, M.; Becquart, C. S.; Veiga, R. G. A.
2017-10-01
The thermal stability of nanocrystalline Ni due to small additions of Mo or W (up to 1 at%) was investigated in computer simulations by means of a combined Monte Carlo (MC)/molecular dynamics (MD) two-steps approach. In the first step, energy-biased on-lattice MC revealed segregation of the alloying elements to grain boundaries. However, the condition for the thermodynamic stability of these nanocrystalline Ni alloys (zero grain boundary energy) was not fulfilled. Subsequently, MD simulations were carried out for up to 0.5 μs at 1000 K. At this temperature, grain growth was hindered for minimum global concentrations of 0.5 at% W and 0.7 at% Mo, thus preserving most of the nanocrystalline structure. This is in clear contrast to a pure Ni model system, for which the transformation into a monocrystal was observed in MD simulations within 0.2 μs at the same temperature. These results suggest that grain boundary segregation of low-soluble alloying elements in low-alloyed systems can produce high-temperature metastable nanocrystalline materials. MD simulations carried out at 1200 K for 1 at% Mo/W showed significant grain boundary migration accompanied by some degree of solute diffusion, thus providing additional evidence that solute drag mostly contributed to the nanostructure stability observed at lower temperature.
Živković, Jelena V; Trutić, Nataša V; Veselinović, Jovana B; Nikolić, Goran M; Veselinović, Aleksandar M
2015-09-01
The Monte Carlo method was used for QSAR modeling of maleimide derivatives as glycogen synthase kinase-3β inhibitors. The first QSAR model was developed for a series of 74 3-anilino-4-arylmaleimide derivatives. The second QSAR model was developed for a series of 177 maleimide derivatives. QSAR models were calculated with the representation of the molecular structure by the simplified molecular input-line entry system. Two splits have been examined: one split into the training and test set for the first QSAR model, and one split into the training, test and validation set for the second. The statistical quality of the developed model is very good. The calculated model for 3-anilino-4-arylmaleimide derivatives had following statistical parameters: r(2)=0.8617 for the training set; r(2)=0.8659, and r(m)(2)=0.7361 for the test set. The calculated model for maleimide derivatives had following statistical parameters: r(2)=0.9435, for the training, r(2)=0.9262 and r(m)(2)=0.8199 for the test and r(2)=0.8418, r(av)(m)(2)=0.7469 and ∆r(m)(2)=0.1476 for the validation set. Structural indicators considered as molecular fragments responsible for the increase and decrease in the inhibition activity have been defined. The computer-aided design of new potential glycogen synthase kinase-3β inhibitors has been presented by using defined structural alerts.
Thermodynamic response functions of fluids: A microscopic approach based on NpT Monte Carlo
NASA Astrophysics Data System (ADS)
Piñeiro, Manuel M.; Cerdeiriña, Claudio A.; Medeiros, Milton
2008-07-01
On the basis of NpT Monte Carlo simulations, a detailed analysis on the microscopic origins of some specific features of thermodynamic response functions of fluids is performed. Specifically, the residual isobaric heat capacity Cpres, the isobaric thermal expansivity αp, and the isothermal compressibility κT for Lennard-Jones methane and optimized potential for liquid simulations (OPLS) methanol have been determined via standard techniques. For the former, data along the liquid, gas, and supercritical regions are presented, while a wide temperature range at a single supercritical pressure is covered for the latter. They have been obtained by computing the various pairwise fluctuations contributing to each property. Attention is mainly focused on isothermal and isobaric maxima found for both Cpres and αp, which have been rationalized at a molecular level using qualitative arguments. It is encountered that maxima emerge as a natural consequence of the destruction of fluid structure as temperature is increased or as pressure is decreased. The results for Lennard-Jones methane reveal the competition of energetic and volumetric effects, while those for OPLS methanol evidence that hydrogen-bonding is dominant as energetic effects are concerned. Further discussion on previous results and alternative approaches using equations of state as well as on closely related topics such as "maxima and critical phenomena" is included.
Beam steering uncertainty analysis for Risley prisms based on Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Zhang, Hao; Yuan, Yan; Su, Lijuan; Huang, Fengzhen
2017-01-01
The Risley-prism system is applied in imaging LADAR to achieve precision directing of laser beams. The image quality of LADAR is affected deeply by the laser beam steering quality of Risley prisms. The ray-tracing method was used to predict the pointing error. The beam steering uncertainty of Risley prisms was investigated through Monte Carlo simulation under the effects of rotation axis jitter and prism rotation error. Case examples were given to elucidate the probability distribution of pointing error. Furthermore, the effect of scan pattern on the beam steering uncertainty was also studied. It is found that the demand for the bearing rotational accuracy of the second prism is much more stringent than that of the first prism. Under the effect of rotation axis jitter, the pointing uncertainty in the field of regard is related to the altitude angle of the emerging beam, but it has no relationship with the azimuth angle. The beam steering uncertainty will be affected by the original phase if the scan pattern is a circle. The proposed method can be used to estimate the beam steering uncertainty of Risley prisms, and the conclusions will be helpful in the design and manufacture of this system.
Monte Carlo simulation of x-ray scatter based on patient model from digital breast tomosynthesis
NASA Astrophysics Data System (ADS)
Liu, Bob; Wu, Tao; Moore, Richard H.; Kopans, Daniel B.
2006-03-01
We are developing a breast specific scatter correction method for digital beast tomosynthesis (DBT). The 3D breast volume was initially reconstructed from 15 projection images acquired from a GE prototype tomosynthesis system without correction of scatter. The voxel values were mapped to the tissue compositions using various segmentation schemes. This voxelized digital breast model was entered into a Monte Carlo package simulating the prototype tomosynthesis system. One billion photons were generated from the x-ray source for each projection in the simulation and images of scattered photons were obtained. A primary only projection image was then produced by subtracting the scatter image from the corresponding original projection image which contains contributions from the both primary photons and scatter photons. The scatter free projection images were then used to reconstruct the 3D breast using the same algorithm. Compared with the uncorrected 3D image, the x-ray attenuation coefficients represented by the scatter-corrected 3D image are closer to those derived from the measurement data.
McMillan, Kyle; McNitt-Gray, Michael; Ruan, Dan
2013-01-01
underestimated measurements by 1.35%–5.31% (mean difference = −3.42%, SD = 1.09%). Conclusions: This work demonstrates the feasibility of using a measurement-based kV CBCT source model to facilitate dose calculations with Monte Carlo methods for both the radiographic and CBCT mode of operation. While this initial work validates simulations against measurements for simple geometries, future work will involve utilizing the source model to investigate kV CBCT dosimetry with more complex anthropomorphic phantoms and patient specific models. PMID:24320440
Monte Carlo simulation of intercalated carbon nanotubes.
Mykhailenko, Oleksiy; Matsui, Denis; Prylutskyy, Yuriy; Le Normand, Francois; Eklund, Peter; Scharff, Peter
2007-01-01
Monte Carlo simulations of the single- and double-walled carbon nanotubes (CNT) intercalated with different metals have been carried out. The interrelation between the length of a CNT, the number and type of metal atoms has also been established. This research is aimed at studying intercalated systems based on CNTs and d-metals such as Fe and Co. Factors influencing the stability of these composites have been determined theoretically by the Monte Carlo method with the Tersoff potential. The modeling of CNTs intercalated with metals by the Monte Carlo method has proved that there is a correlation between the length of a CNT and the number of endo-atoms of specific type. Thus, in the case of a metallic CNT (9,0) with length 17 bands (3.60 nm), in contrast to Co atoms, Fe atoms are extruded out of the CNT if the number of atoms in the CNT is not less than eight. Thus, this paper shows that a CNT of a certain size can be intercalated with no more than eight Fe atoms. The systems investigated are stabilized by coordination of 3d-atoms close to the CNT wall with a radius-vector of (0.18-0.20) nm. Another characteristic feature is that, within the temperature range of (400-700) K, small systems exhibit ground-state stabilization which is not characteristic of the higher ones. The behavior of Fe and Co endo-atoms between the walls of a double-walled carbon nanotube (DW CNT) is explained by a dominating van der Waals interaction between the Co atoms themselves, which is not true for the Fe atoms.
de Finetti Priors using Markov chain Monte Carlo computations.
Bacallado, Sergio; Diaconis, Persi; Holmes, Susan
2015-07-01
Recent advances in Monte Carlo methods allow us to revisit work by de Finetti who suggested the use of approximate exchangeability in the analyses of contingency tables. This paper gives examples of computational implementations using Metropolis Hastings, Langevin and Hamiltonian Monte Carlo to compute posterior distributions for test statistics relevant for testing independence, reversible or three way models for discrete exponential families using polynomial priors and Gröbner bases.
de Finetti Priors using Markov chain Monte Carlo computations
Bacallado, Sergio; Diaconis, Persi; Holmes, Susan
2015-01-01
Recent advances in Monte Carlo methods allow us to revisit work by de Finetti who suggested the use of approximate exchangeability in the analyses of contingency tables. This paper gives examples of computational implementations using Metropolis Hastings, Langevin and Hamiltonian Monte Carlo to compute posterior distributions for test statistics relevant for testing independence, reversible or three way models for discrete exponential families using polynomial priors and Gröbner bases. PMID:26412947
Confidence and efficiency scaling in variational quantum Monte Carlo calculations
NASA Astrophysics Data System (ADS)
Delyon, F.; Bernu, B.; Holzmann, Markus
2017-02-01
Based on the central limit theorem, we discuss the problem of evaluation of the statistical error of Monte Carlo calculations using a time-discretized diffusion process. We present a robust and practical method to determine the effective variance of general observables and show how to verify the equilibrium hypothesis by the Kolmogorov-Smirnov test. We then derive scaling laws of the efficiency illustrated by variational Monte Carlo calculations on the two-dimensional electron gas.
Monte Carlo simulations within avalanche rescue
NASA Astrophysics Data System (ADS)
Reiweger, Ingrid; Genswein, Manuel; Schweizer, Jürg
2016-04-01
Refining concepts for avalanche rescue involves calculating suitable settings for rescue strategies such as an adequate probing depth for probe line searches or an optimal time for performing resuscitation for a recovered avalanche victim in case of additional burials. In the latter case, treatment decisions have to be made in the context of triage. However, given the low number of incidents it is rarely possible to derive quantitative criteria based on historical statistics in the context of evidence-based medicine. For these rare, but complex rescue scenarios, most of the associated concepts, theories, and processes involve a number of unknown "random" parameters which have to be estimated in order to calculate anything quantitatively. An obvious approach for incorporating a number of random variables and their distributions into a calculation is to perform a Monte Carlo (MC) simulation. We here present Monte Carlo simulations for calculating the most suitable probing depth for probe line searches depending on search area and an optimal resuscitation time in case of multiple avalanche burials. The MC approach reveals, e.g., new optimized values for the duration of resuscitation that differ from previous, mainly case-based assumptions.
Monte Carlo variance reduction approaches for non-Boltzmann tallies
Booth, T.E.
1992-12-01
Quantities that depend on the collective effects of groups of particles cannot be obtained from the standard Boltzmann transport equation. Monte Carlo estimates of these quantities are called non-Boltzmann tallies and have become increasingly important recently. Standard Monte Carlo variance reduction techniques were designed for tallies based on individual particles rather than groups of particles. Experience with non-Boltzmann tallies and analog Monte Carlo has demonstrated the severe limitations of analog Monte Carlo for many non-Boltzmann tallies. In fact, many calculations absolutely require variance reduction methods to achieve practical computation times. Three different approaches to variance reduction for non-Boltzmann tallies are described and shown to be unbiased. The advantages and disadvantages of each of the approaches are discussed.
Combinatorial geometry domain decomposition strategies for Monte Carlo simulations
Li, G.; Zhang, B.; Deng, L.; Mo, Z.; Liu, Z.; Shangguan, D.; Ma, Y.; Li, S.; Hu, Z.
2013-07-01
Analysis and modeling of nuclear reactors can lead to memory overload for a single core processor when it comes to refined modeling. A method to solve this problem is called 'domain decomposition'. In the current work, domain decomposition algorithms for a combinatorial geometry Monte Carlo transport code are developed on the JCOGIN (J Combinatorial Geometry Monte Carlo transport INfrastructure). Tree-based decomposition and asynchronous communication of particle information between domains are described in the paper. Combination of domain decomposition and domain replication (particle parallelism) is demonstrated and compared with that of MERCURY code. A full-core reactor model is simulated to verify the domain decomposition algorithms using the Monte Carlo particle transport code JMCT (J Monte Carlo Transport Code), which has being developed on the JCOGIN infrastructure. Besides, influences of the domain decomposition algorithms to tally variances are discussed. (authors)
NASA Astrophysics Data System (ADS)
Jenkins, C. M.; Godang, R.; Cavaglia, M.; Cremaldi, L.; Summers, D.
2008-10-01
The 14 TeV center of mass proton-proton collisions at the LHC opens the possibility for new Physics, including the possible formation of microscopic black holes. A Fortran-based Monte Carlo event generator program called CATFISH (Collider grAviTational FIeld Simulator for black Holes) has been developed at the University of Mississippi to study signatures of microscopic black hole production (http://www.phy.olemiss.edu/GR/catfish). This black hole event generator includes many of the currently accepted theoretical results for microscopic black hole formation. High energy physics data analysis is shifting from Fortran to C++ as the CERN data analysis packages HBOOK and PAW are no longer supported. The C++ based root is replacing these packages. Work done at the University of South Alabama has resulted in a successful inclusion of CATFISH into root. The methods used to interface the Fortran-based CATFISH into the C++ based root will be presented. Benchmark histograms will be presented demonstrating the conversion. Preliminary results will be presented for selecting black hole candidate events in 14 TeV/ center of mass proton-proton collisions.
THE MCNPX MONTE CARLO RADIATION TRANSPORT CODE
WATERS, LAURIE S.; MCKINNEY, GREGG W.; DURKEE, JOE W.; FENSIN, MICHAEL L.; JAMES, MICHAEL R.; JOHNS, RUSSELL C.; PELOWITZ, DENISE B.
2007-01-10
MCNPX (Monte Carlo N-Particle eXtended) is a general-purpose Monte Carlo radiation transport code with three-dimensional geometry and continuous-energy transport of 34 particles and light ions. It contains flexible source and tally options, interactive graphics, and support for both sequential and multi-processing computer platforms. MCNPX is based on MCNP4B, and has been upgraded to most MCNP5 capabilities. MCNP is a highly stable code tracking neutrons, photons and electrons, and using evaluated nuclear data libraries for low-energy interaction probabilities. MCNPX has extended this base to a comprehensive set of particles and light ions, with heavy ion transport in development. Models have been included to calculate interaction probabilities when libraries are not available. Recent additions focus on the time evolution of residual nuclei decay, allowing calculation of transmutation and delayed particle emission. MCNPX is now a code of great dynamic range, and the excellent neutronics capabilities allow new opportunities to simulate devices of interest to experimental particle physics; particularly calorimetry. This paper describes the capabilities of the current MCNPX version 2.6.C, and also discusses ongoing code development.
Optimization of a photoneutron source based on 10 MeV electron beam using Geant4 Monte Carlo code
NASA Astrophysics Data System (ADS)
Askri, Boubaker
2015-10-01
Geant4 Monte Carlo code has been used to conceive and optimize a simple and compact neutron source based on a 10 MeV electron beam impinging on a tungsten target adjoined to a beryllium target. For this purpose, a precise photonuclear reaction cross-section model issued from the International Atomic Energy Agency (IAEA) database was linked to Geant4 to accurately simulate the interaction of low energy bremsstrahlung photons with beryllium material. A benchmark test showed that a good agreement was achieved when comparing the emitted neutron flux spectra predicted by Geant4 and Fluka codes for a beryllium cylinder bombarded with a 5 MeV photon beam. The source optimization was achieved through a two stage Monte Carlo simulation. In the first stage, the distributions of the seven phase space coordinates of the bremsstrahlung photons at the boundaries of the tungsten target were determined. In the second stage events corresponding to photons emitted according to these distributions were tracked. A neutron yield of 4.8 × 1010 neutrons/mA/s was obtained at 20 cm from the beryllium target. A thermal neutron yield of 1.5 × 109 neutrons/mA/s was obtained after introducing a spherical shell of polyethylene as a neutron moderator.
Geng, Changran; Tang, Xiaobin; Gong, Chunhui; Guan, Fada; Johns, Jesse; Shu, Diyun; Chen, Da
2015-12-01
The active shielding technique has great potential for radiation protection in space exploration because it has the advantage of a significant mass saving compared with the passive shielding technique. This paper demonstrates a Monte Carlo-based approach to evaluating the shielding effectiveness of the active shielding technique using confined magnetic fields (CMFs). The International Commission on Radiological Protection reference anthropomorphic phantom, as well as the toroidal CMF, was modeled using the Monte Carlo toolkit Geant4. The penetrating primary particle fluence, organ-specific dose equivalent, and male effective dose were calculated for particles in galactic cosmic radiation (GCR) and solar particle events (SPEs). Results show that the SPE protons can be easily shielded against, even almost completely deflected, by the toroidal magnetic field. GCR particles can also be more effectively shielded against by increasing the magnetic field strength. Our results also show that the introduction of a structural Al wall in the CMF did not provide additional shielding for GCR; in fact it can weaken the total shielding effect of the CMF. This study demonstrated the feasibility of accurately determining the radiation field inside the environment and evaluating the organ dose equivalents for astronauts under active shielding using the CMF.
NASA Astrophysics Data System (ADS)
Ding, Chizhu
2016-10-01
Diffuse reflectance spectroscopy in the near-infrared (NIR) spectral ranges is a widely used technique for nondestructive inspection of biological tissues. The optical properties, such as absorption and scattering coefficients, can be inversely deduced from the measured quantities and then be used to speculate on some related chemical and physical properties of the tissue. Most studies consider biological tissues as homogeneous semi-infinite turbid media or infinitelywide planar layered turbid media. However, the biological tissues have various geometries, and nearly all of them have curved surfaces. The position and direction of the incident light relative to the tissue surface affect the diffuse reflectance. In this work, we study the influence of incident light offset on the measured diffuse reflectance signals based on the Monte Carlo (MC) simulation. The MC method are regarded as golden standard for light propagation in turbid media and can be used without the limitations of complex tissue geometries. A model for diffuse reflectance spectroscopy measurement using optic fiber probe is built. The incident light is assumed to be an infinitely narrow photon beam. The tissue under detection is assumed to be spherical described by its curvature radius. A series of Monte Carlo simulation are carried out with varying incident directions. Simulation results are analyzed and discussed to assess the influence on the measurements for tissues with different curvature radii. This study may aid in achieving more accurate and effective measurement without extensive experiments.
Monte Carlo simulation of nitrogen dissociation based on state-resolved cross sections
Kim, Jae Gang Boyd, Iain D.
2014-01-15
State-resolved analyses of N + N{sub 2} are performed using the direct simulation Monte Carlo (DSMC) method. In describing the elastic collisions by a state-resolved method, a state-specific total cross section is proposed. The state-resolved method is constructed from the state-specific total cross section and the rovibrational state-to-state transition cross sections for bound-bound and bound-free transitions taken from a NASA database. This approach makes it possible to analyze the rotational-to-translational, vibrational-to-translational, and rotational-to-vibrational energy transfers and the chemical reactions without relying on macroscopic properties and phenomenological models. In nonequilibrium heat bath calculations, the results of present state-resolved DSMC calculations are validated with those of the master equation calculations and the existing shock-tube experimental data for bound-bound and bound-free transitions. In various equilibrium and nonequilibrium heat bath conditions and 2D cylindrical flows, the DSMC calculations by the state-resolved method are compared with those obtained with previous phenomenological DSMC models. In these previous DSMC models, the variable soft sphere, phenomenological Larsen-Borgnakke, quantum kinetic, and total collision energy models are considered. From these studies, it is concluded that the state-resolved method can accurately describe the rotational-to-translational, vibrational-to-translational, and rotational-to-vibrational transfers and quasi-steady state of rotational and vibrational energies in nonequilibrium chemical reactions by state-to-state kinetics.
NASA Astrophysics Data System (ADS)
Messina, Luca; Castin, Nicolas; Domain, Christophe; Olsson, Pär
2017-02-01
The quality of kinetic Monte Carlo (KMC) simulations of microstructure evolution in alloys relies on the parametrization of point-defect migration rates, which are complex functions of the local chemical composition and can be calculated accurately with ab initio methods. However, constructing reliable models that ensure the best possible transfer of physical information from ab initio to KMC is a challenging task. This work presents an innovative approach, where the transition rates are predicted by artificial neural networks trained on a database of 2000 migration barriers, obtained with density functional theory (DFT) in place of interatomic potentials. The method is tested on copper precipitation in thermally aged iron alloys, by means of a hybrid atomistic-object KMC model. For the object part of the model, the stability and mobility properties of copper-vacancy clusters are analyzed by means of independent atomistic KMC simulations, driven by the same neural networks. The cluster diffusion coefficients and mean free paths are found to increase with size, confirming the dominant role of coarsening of medium- and large-sized clusters in the precipitation kinetics. The evolution under thermal aging is in better agreement with experiments with respect to a previous interatomic-potential model, especially concerning the experiment time scales. However, the model underestimates the solubility of copper in iron due to the excessively high solution energy predicted by the chosen DFT method. Nevertheless, this work proves the capability of neural networks to transfer complex ab initio physical properties to higher-scale models, and facilitates the extension to systems with increasing chemical complexity, setting the ground for reliable microstructure evolution simulations in a wide range of alloys and applications.
GPU-BASED MONTE CARLO DUST RADIATIVE TRANSFER SCHEME APPLIED TO ACTIVE GALACTIC NUCLEI
Heymann, Frank; Siebenmorgen, Ralf
2012-05-20
A three-dimensional parallel Monte Carlo (MC) dust radiative transfer code is presented. To overcome the huge computing-time requirements of MC treatments, the computational power of vectorized hardware is used, utilizing either multi-core computer power or graphics processing units. The approach is a self-consistent way to solve the radiative transfer equation in arbitrary dust configurations. The code calculates the equilibrium temperatures of two populations of large grains and stochastic heated polycyclic aromatic hydrocarbons. Anisotropic scattering is treated applying the Heney-Greenstein phase function. The spectral energy distribution (SED) of the object is derived at low spatial resolution by a photon counting procedure and at high spatial resolution by a vectorized ray tracer. The latter allows computation of high signal-to-noise images of the objects at any frequencies and arbitrary viewing angles. We test the robustness of our approach against other radiative transfer codes. The SED and dust temperatures of one- and two-dimensional benchmarks are reproduced at high precision. The parallelization capability of various MC algorithms is analyzed and included in our treatment. We utilize the Lucy algorithm for the optical thin case where the Poisson noise is high, the iteration-free Bjorkman and Wood method to reduce the calculation time, and the Fleck and Canfield diffusion approximation for extreme optical thick cells. The code is applied to model the appearance of active galactic nuclei (AGNs) at optical and infrared wavelengths. The AGN torus is clumpy and includes fluffy composite grains of various sizes made up of silicates and carbon. The dependence of the SED on the number of clumps in the torus and the viewing angle is studied. The appearance of the 10 {mu}m silicate features in absorption or emission is discussed. The SED of the radio-loud quasar 3C 249.1 is fit by the AGN model and a cirrus component to account for the far-infrared emission.
Monte-Carlo based Uncertainty Analysis For CO2 Laser Microchanneling Model
NASA Astrophysics Data System (ADS)
Prakash, Shashi; Kumar, Nitish; Kumar, Subrata
2016-09-01
CO2 laser microchanneling has emerged as a potential technique for the fabrication of microfluidic devices on PMMA (Poly-methyl-meth-acrylate). PMMA directly vaporizes when subjected to high intensity focused CO2 laser beam. This process results in clean cut and acceptable surface finish on microchannel walls. Overall, CO2 laser microchanneling process is cost effective and easy to implement. While fabricating microchannels on PMMA using a CO2 laser, the maximum depth of the fabricated microchannel is the key feature. There are few analytical models available to predict the maximum depth of the microchannels and cut channel profile on PMMA substrate using a CO2 laser. These models depend upon the values of thermophysical properties of PMMA and laser beam parameters. There are a number of variants of transparent PMMA available in the market with different values of thermophysical properties. Therefore, for applying such analytical models, the values of these thermophysical properties are required to be known exactly. Although, the values of laser beam parameters are readily available, extensive experiments are required to be conducted to determine the value of thermophysical properties of PMMA. The unavailability of exact values of these property parameters restrict the proper control over the microchannel dimension for given power and scanning speed of the laser beam. In order to have dimensional control over the maximum depth of fabricated microchannels, it is necessary to have an idea of uncertainty associated with the predicted microchannel depth. In this research work, the uncertainty associated with the maximum depth dimension has been determined using Monte Carlo method (MCM). The propagation of uncertainty with different power and scanning speed has been predicted. The relative impact of each thermophysical property has been determined using sensitivity analysis.
Quantum Monte Carlo methods for nuclear physics
NASA Astrophysics Data System (ADS)
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-07-01
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; ...
2015-09-09
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit,more » and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less
CosmoMC: Cosmological MonteCarlo
NASA Astrophysics Data System (ADS)
Lewis, Antony; Bridle, Sarah
2011-06-01
We present a fast Markov Chain Monte-Carlo exploration of cosmological parameter space. We perform a joint analysis of results from recent CMB experiments and provide parameter constraints, including sigma_8, from the CMB independent of other data. We next combine data from the CMB, HST Key Project, 2dF galaxy redshift survey, supernovae Ia and big-bang nucleosynthesis. The Monte Carlo method allows the rapid investigation of a large number of parameters, and we present results from 6 and 9 parameter analyses of flat models, and an 11 parameter analysis of non-flat models. Our results include constraints on the neutrino mass (m_nu < 0.3eV), equation of state of the dark energy, and the tensor amplitude, as well as demonstrating the effect of additional parameters on the base parameter constraints. In a series of appendices we describe the many uses of importance sampling, including computing results from new data and accuracy correction of results generated from an approximate method. We also discuss the different ways of converting parameter samples to parameter constraints, the effect of the prior, assess the goodness of fit and consistency, and describe the use of analytic marginalization over normalization parameters.
Quantum Monte Carlo methods for nuclear physics
Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; ...
2014-10-19
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-bodymore » interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.« less
Quantum Monte Carlo methods for nuclear physics
Carlson, J.; Gandolfi, S.; Pederiva, F.; Pieper, Steven C.; Schiavilla, R.; Schmidt, K. E.; Wiringa, R. B.
2015-09-09
Quantum Monte Carlo methods have proved valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments, and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. The nuclear interactions and currents are reviewed along with a description of the continuum quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. A variety of results are presented, including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. Low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars are also described. Furthermore, a coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Scalable Domain Decomposed Monte Carlo Particle Transport
NASA Astrophysics Data System (ADS)
O'Brien, Matthew Joseph
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation. The main algorithms we consider are: • Domain decomposition of constructive solid geometry: enables extremely large calculations in which the background geometry is too large to fit in the memory of a single computational node. • Load Balancing: keeps the workload per processor as even as possible so the calculation runs efficiently. • Global Particle Find: if particles are on the wrong processor, globally resolve their locations to the correct processor based on particle coordinate and background domain. • Visualizing constructive solid geometry, sourcing particles, deciding that particle streaming communication is completed and spatial redecomposition. These algorithms are some of the most important parallel algorithms required for domain decomposed Monte Carlo particle transport. We demonstrate that our previous algorithms were not scalable, prove that our new algorithms are scalable, and run some of the algorithms up to 2 million MPI processes on the Sequoia supercomputer.
Quantum Monte Carlo methods for nuclear physics
Carlson, Joseph A.; Gandolfi, Stefano; Pederiva, Francesco; Pieper, Steven C.; Schiavilla, Rocco; Schmidt, K. E,; Wiringa, Robert B.
2014-10-19
Quantum Monte Carlo methods have proved very valuable to study the structure and reactions of light nuclei and nucleonic matter starting from realistic nuclear interactions and currents. These ab-initio calculations reproduce many low-lying states, moments and transitions in light nuclei, and simultaneously predict many properties of light nuclei and neutron matter over a rather wide range of energy and momenta. We review the nuclear interactions and currents, and describe the continuum Quantum Monte Carlo methods used in nuclear physics. These methods are similar to those used in condensed matter and electronic structure but naturally include spin-isospin, tensor, spin-orbit, and three-body interactions. We present a variety of results including the low-lying spectra of light nuclei, nuclear form factors, and transition matrix elements. We also describe low-energy scattering techniques, studies of the electroweak response of nuclei relevant in electron and neutrino scattering, and the properties of dense nucleonic matter as found in neutron stars. A coherent picture of nuclear structure and dynamics emerges based upon rather simple but realistic interactions and currents.
Development of Monte Carlo Capability for Orion Parachute Simulations
NASA Technical Reports Server (NTRS)
Moore, James W.
2011-01-01
Parachute test programs employ Monte Carlo simulation techniques to plan testing and make critical decisions related to parachute loads, rate-of-descent, or other parameters. This paper describes the development and use of a MATLAB-based Monte Carlo tool for three parachute drop test simulations currently used by NASA. The Decelerator System Simulation (DSS) is a legacy 6 Degree-of-Freedom (DOF) simulation used to predict parachute loads and descent trajectories. The Decelerator System Simulation Application (DSSA) is a 6-DOF simulation that is well suited for modeling aircraft extraction and descent of pallet-like test vehicles. The Drop Test Vehicle Simulation (DTVSim) is a 2-DOF trajectory simulation that is convenient for quick turn-around analysis tasks. These three tools have significantly different software architectures and do not share common input files or output data structures. Separate Monte Carlo tools were initially developed for each simulation. A recently-developed simulation output structure enables the use of the more sophisticated DSSA Monte Carlo tool with any of the core-simulations. The task of configuring the inputs for the nominal simulation is left to the existing tools. Once the nominal simulation is configured, the Monte Carlo tool perturbs the input set according to dispersion rules created by the analyst. These rules define the statistical distribution and parameters to be applied to each simulation input. Individual dispersed parameters are combined to create a dispersed set of simulation inputs. The Monte Carlo tool repeatedly executes the core-simulation with the dispersed inputs and stores the results for analysis. The analyst may define conditions on one or more output parameters at which to collect data slices. The tool provides a versatile interface for reviewing output of large Monte Carlo data sets while preserving the capability for detailed examination of individual dispersed trajectories. The Monte Carlo tool described in
An improved method for treating Monte Carlo-diffusion interfaces
Densmore, J. D.
2004-01-01
Discrete Diffusion Monte Carlo (DDMC) has been suggested as a technique for increasing the efficiency of Monte Carlo simulations in diffusive media. In this technique, Monte Carlo particles travel discrete steps between spatial cells according to a discretized diffusion equation. An important part of the DDMC method is the treatment of the interface between a transport region, where standard Monte Carlo is used, and a diffusive region, where DDMC is employed. Previously developed DDMC methods use the Marshak boundary condition at transport diffusion-interfaces, and thus produce incorrect results if the Monte Carlo-calculated angular flux incident on the interface surface is anisotropic. In this summary we present a new interface method based on the asymptotic diffusion-limit boundary condition, which is able to produce accurate solutions if the incident angular flux is anisotropic. We show that this new interface technique has a simple Monte Carlo interpretation, and can be used in conjunction with the existing DDMC method. With a set of numerical simulations, we demonstrate that this asymptotic interface method is much more accurate than the previously developed Marshak interface method.
Hong Enriquez, Rolando Pablo; Santambrogio, Carlo; Grandori, Rita; Marasco, Daniela; Giordano, Antonio; Scoles, Giacinto; Fortuna, Sara
2015-01-01
Short peptides can be designed in silico and synthesized through automated techniques, making them advantageous and versatile protein binders. A number of docking-based algorithms allow for a computational screening of peptides as binders. Here we developed ex-novo peptides targeting the maltose site of the Maltose Binding Protein, the prototypical system for the study of protein ligand recognition. We used a Monte Carlo based protocol, to computationally evolve a set of octapeptides starting from a polialanine sequence. We screened in silico the candidate peptides and characterized their binding abilities by surface plasmon resonance, fluorescence and electrospray ionization mass spectrometry assays. These experiments showed the designed binders to recognize their target with micromolar affinity. We finally discuss the obtained results in the light of further improvement in the ex-novo optimization of peptide based binders. PMID:26252476
Verleker, Akshay Prabhu; Shaffer, Michael; Fang, Qianqian; Choi, Mi-Ran; Clare, Susan; Stantz, Keith M
2016-12-01
A three-dimensional photon dosimetry in tissues is critical in designing optical therapeutic protocols to trigger light-activated drug release. The objective of this study is to investigate the feasibility of a Monte Carlo-based optical therapy planning software by developing dosimetry tools to characterize and cross-validate the local photon fluence in brain tissue, as part of a long-term strategy to quantify the effects of photoactivated drug release in brain tumors. An existing GPU-based 3D Monte Carlo (MC) code was modified to simulate near-infrared photon transport with differing laser beam profiles within phantoms of skull bone (B), white matter (WM), and gray matter (GM). A novel titanium-based optical dosimetry probe with isotropic acceptance was used to validate the local photon fluence, and an empirical model of photon transport was developed to significantly decrease execution time for clinical application. Comparisons between the MC and the dosimetry probe measurements were on an average 11.27%, 13.25%, and 11.81% along the illumination beam axis, and 9.4%, 12.06%, 8.91% perpendicular to the beam axis for WM, GM, and B phantoms, respectively. For a heterogeneous head phantom, the measured % errors were 17.71% and 18.04% along and perpendicular to beam axis. The empirical algorithm was validated by probe measurements and matched the MC results (R^{2}0.99), with average % error of 10.1%, 45.2%, and 22.1% relative to probe measurements, and 22.6%, 35.8%, and 21.9% relative to the MC, for WM, GM, and B phantoms, respectively. The simulation time for the empirical model was 6 s versus 8 h for the GPU-based Monte Carlo for a head phantom simulation. These tools provide the capability to develop and optimize treatment plans for optimal release of pharmaceuticals in the treatment of cancer. Future work will test and validate these novel delivery and release mechanisms in vivo.
Commissioning of 6 MV medical linac for dynamic MLC-based IMRT on Monte Carlo code GEANT4.
Okamoto, Hiroyuki; Fujita, Yukio; Sakama, Kyoko; Saitoh, Hidetoshi; Kanai, Tatsuaki; Itami, Jun; Kohno, Toshiyuki
2014-07-01
Monte Carlo simulation is the most accurate tool for calculating dose distributions. In particular, the Electron Gamma shower computer code has been widely used for multi-purpose research in radiotherapy, but Monte Carlo GEANT4 (GEometry ANd Tracking) is rare for radiotherapy with photon beams and needs to be verified further under various irradiation conditions, particularly multi-leaf collimator-based intensity-modulated radiation therapy (MLC-based IMRT). In this study, GEANT4 was used for modeling of a 6 MV linac for dynamic MLC-based IMRT. To verify the modeling of our linac, we compared the calculated data with the measured depth-dose for a 10 × 10 cm(2) field and the measured dose profile for a 35 × 35 cm(2) field. Moreover, 120 MLCs were modeled on the GEANT4. Five tests of MLC modeling were performed: (I) MLC transmission, (II) MLC transmission profile including intra- and inter-leaf leakage, (III) tongue-and-groove leakage, (IV) a simple field with different field sizes by use of MLC and (V) a dynamic MLC-based IMRT field. For all tests, the calculations were compared with measurements of an ionization chamber and radiographic film. The calculations agreed with the measurements: MLC transmissions by calculations and measurements were 1.76 ± 0.01 and 1.87 ± 0.01 %, respectively. In gamma evaluation method (3 %/3 mm), the pass rates of the (IV) and (V) tests were 98.5 and 97.0 %, respectively. Furthermore, tongue-and-groove leakage could be calculated by GEANT4, and it agreed with the film measurements. The procedure of commissioning of dynamic MLC-based IMRT for GEANT4 is proposed in this study.
NASA Astrophysics Data System (ADS)
Le Bao, V.; Kim, G.
2017-03-01
The Rotational Modulation Collimator (RMC) is a simple and versatile tool for the radiation imaging system with low cost, makes it a reasonable selection for locating and tracking nuclear materials and radiation sources. In this paper, Monte Carlo simulation-based design studies for an alternative RMC which has an extended field-of-view will be presented. Modulation patterns for 5 different hemispherical RMC (H-RMC) designs were simulated for various source locations, and fundamental characteristics of rotational modulation patterns were investigated. Obtained patterns showed variations depending on the source location for most of the H-RMC designs, exhibiting promises for the future development of an omni-directional radiation imager based on a non-position sensitive radiation detector.
Densmore, J.D.; Park, H.; Wollaber, A.B.; Rauenzahn, R.M.; Knoll, D.A.
2015-03-01
We present a moment-based acceleration algorithm applied to Monte Carlo simulation of thermal radiative-transfer problems. Our acceleration algorithm employs a continuum system of moments to accelerate convergence of stiff absorption–emission physics. The combination of energy-conserving tallies and the use of an asymptotic approximation in optically thick regions remedy the difficulties of local energy conservation and mitigation of statistical noise in such regions. We demonstrate the efficiency and accuracy of the developed method. We also compare directly to the standard linearization-based method of Fleck and Cummings [1]. A factor of 40 reduction in total computational time is achieved with the new algorithm for an equivalent (or more accurate) solution as compared with the Fleck–Cummings algorithm.
Zhong, Xiewei; Wen, Xiang; Zhu, Dan
2014-01-27
Fiber reflectance spectroscopy is a non-invasive method for diagnosing skin diseases or evaluating aesthetic efficacy, but it is dependent on the inverse model validity. In this work, a lookup-table-based inverse model is developed using two-layered Monte Carlo simulations in order to extract the physiological and optical properties of skin. The melanin volume fraction and blood oxygen parameters are extracted from fiber reflectance spectra of in vivo human skin. The former indicates good coincidence with a commercial skin-melanin probe, and the latter (based on forearm venous occlusion and ischemia, and hot compress experiment) shows that the measurements are in agreement with physiological changes. These results verify the potential of this spectroscopy technique for evaluating the physiological characteristics of human skin.
Quantum speedup of Monte Carlo methods
Montanaro, Ashley
2015-01-01
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently. PMID:26528079
Self-learning Monte Carlo method
NASA Astrophysics Data System (ADS)
Liu, Junwei; Qi, Yang; Meng, Zi Yang; Fu, Liang
2017-01-01
Monte Carlo simulation is an unbiased numerical tool for studying classical and quantum many-body systems. One of its bottlenecks is the lack of a general and efficient update algorithm for large size systems close to the phase transition, for which local updates perform badly. In this Rapid Communication, we propose a general-purpose Monte Carlo method, dubbed self-learning Monte Carlo (SLMC), in which an efficient update algorithm is first learned from the training data generated in trial simulations and then used to speed up the actual simulation. We demonstrate the efficiency of SLMC in a spin model at the phase transition point, achieving a 10-20 times speedup.
Quantum speedup of Monte Carlo methods.
Montanaro, Ashley
2015-09-08
Monte Carlo methods use random sampling to estimate numerical quantities which are hard to compute deterministically. One important example is the use in statistical physics of rapidly mixing Markov chains to approximately compute partition functions. In this work, we describe a quantum algorithm which can accelerate Monte Carlo methods in a very general setting. The algorithm estimates the expected output value of an arbitrary randomized or quantum subroutine with bounded variance, achieving a near-quadratic speedup over the best possible classical algorithm. Combining the algorithm with the use of quantum walks gives a quantum speedup of the fastest known classical algorithms with rigorous performance bounds for computing partition functions, which use multiple-stage Markov chain Monte Carlo techniques. The quantum algorithm can also be used to estimate the total variation distance between probability distributions efficiently.
Monte Carlo-based diode design for correction-less small field dosimetry
NASA Astrophysics Data System (ADS)
Charles, P. H.; Crowe, S. B.; Kairn, T.; Knight, R. T.; Hill, B.; Kenny, J.; Langton, C. M.; Trapp, J. V.
2013-07-01
Due to their small collecting volume, diodes are commonly used in small field dosimetry. However, the relative sensitivity of a diode increases with decreasing small field size. Conversely, small air gaps have been shown to cause a significant decrease in the sensitivity of a detector as the field size is decreased. Therefore, this study uses Monte Carlo simulations to look at introducing air upstream to diodes such that they measure with a constant sensitivity across all field sizes in small field dosimetry. Varying thicknesses of air were introduced onto the upstream end of two commercial diodes (PTW 60016 photon diode and PTW 60017 electron diode), as well as a theoretical unenclosed silicon chip using field sizes as small as 5 mm × 5 mm. The metric \\frac{{D_{w,Q} }}{{D_{Det,Q} }} used in this study represents the ratio of the dose to a point of water to the dose to the diode active volume, for a particular field size and location. The optimal thickness of air required to provide a constant sensitivity across all small field sizes was found by plotting \\frac{{D_{w,Q} }}{{D_{Det,Q} }} as a function of introduced air gap size for various field sizes, and finding the intersection point of these plots. That is, the point at which \\frac{{D_{w,Q} }}{{D_{Det,Q} }} was constant for all field sizes was found. The optimal thickness of air was calculated to be 3.3, 1.15 and 0.10 mm for the photon diode, electron diode and unenclosed silicon chip, respectively. The variation in these results was due to the different design of each detector. When calculated with the new diode design incorporating the upstream air gap, k_{Q_{clin} ,Q_{msr} }^{f_{clin} ,f_{msr} } was equal to unity to within statistical uncertainty (0.5%) for all three diodes. Cross-axis profile measurements were also improved with the new detector design. The upstream air gap could be implanted on the commercial diodes via a cap consisting of the air cavity surrounded by water equivalent material. The
Monte Carlo-based diode design for correction-less small field dosimetry.
Charles, P H; Crowe, S B; Kairn, T; Knight, R T; Hill, B; Kenny, J; Langton, C M; Trapp, J V
2013-07-07
Due to their small collecting volume, diodes are commonly used in small field dosimetry. However, the relative sensitivity of a diode increases with decreasing small field size. Conversely, small air gaps have been shown to cause a significant decrease in the sensitivity of a detector as the field size is decreased. Therefore, this study uses Monte Carlo simulations to look at introducing air upstream to diodes such that they measure with a constant sensitivity across all field sizes in small field dosimetry. Varying thicknesses of air were introduced onto the upstream end of two commercial diodes (PTW 60016 photon diode and PTW 60017 electron diode), as well as a theoretical unenclosed silicon chip using field sizes as small as 5 mm × 5 mm. The metric D(w,Q)/D(Det,Q) used in this study represents the ratio of the dose to a point of water to the dose to the diode active volume, for a particular field size and location. The optimal thickness of air required to provide a constant sensitivity across all small field sizes was found by plotting D(w,Q)/D(Det,Q) as a function of introduced air gap size for various field sizes, and finding the intersection point of these plots. That is, the point at which D(w,Q)/D(Det,Q) was constant for all field sizes was found. The optimal thickness of air was calculated to be 3.3, 1.15 and 0.10 mm for the photon diode, electron diode and unenclosed silicon chip, respectively. The variation in these results was due to the different design of each detector. When calculated with the new diode design incorporating the upstream air gap, k(f(clin),f(msr))(Q(clin),Q(msr)) was equal to unity to within statistical uncertainty (0.5%) for all three diodes. Cross-axis profile measurements were also improved with the new detector design. The upstream air gap could be implanted on the commercial diodes via a cap consisting of the air cavity surrounded by water equivalent material. The results for the unclosed silicon chip show that an ideal small
Evaluation of a commercial electron treatment planning system based on Monte Carlo techniques (eMC).
Pemler, Peter; Besserer, Jürgen; Schneider, Uwe; Neuenschwander, Hans
2006-01-01
A commercial electron beam treatment planning system on the basis of a Monte Carlo algorithm (Varian Eclipse, eMC V7.2.35) was evaluated. Measured dose distributions were used for comparison with dose distributions predicted by eMC calculations. Tests were carried out for various applicators and field sizes, irregular shaped cut outs and an inhomogeneity phantom for energies between 6 Me V and 22 MeV Monitor units were calculated for all applicator/energy combinations and field sizes down to 3 cm diameter and source-to-surface distances of 100 cm and 110 cm. A mass-density-to-Hounsfield-Units calibration was performed to compare dose distributions calculated with a default and an individual calibration. The relationship between calculation parameters of the eMC and the resulting dose distribution was studied in detail. Finally, the algorithm was also applied to a clinical case (boost treatment of the breast) to reveal possible problems in the implementation. For standard geometries there was a good agreement between measurements and calculations, except for profiles for low energies (6 MeV) and high energies (18 Me V 22 MeV), in which cases the algorithm overestimated the dose off-axis in the high-dose region. For energies of 12 MeV and higher there were oscillations in the plateau region of the corresponding depth dose curves calculated with a grid size of 1 mm. With irregular cut outs, an overestimation of the dose was observed for small slits and low energies (4% for 6 MeV), as well as for asymmetric cases and extended source-to-surface distances (12% for SSD = 120 cm). While all monitor unit calculations for SSD = 100 cm were within 3% compared to measure-ments, there were large deviations for small cut outs and source-to-surface distances larger than 100 cm (7%for a 3 cm diameter cut-out and a source-to-surface distance of 10 cm).
Parallel Markov chain Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Ren, Ruichao; Orkoulas, G.
2007-06-01
With strict detailed balance, parallel Monte Carlo simulation through domain decomposition cannot be validated with conventional Markov chain theory, which describes an intrinsically serial stochastic process. In this work, the parallel version of Markov chain theory and its role in accelerating Monte Carlo simulations via cluster computing is explored. It is shown that sequential updating is the key to improving efficiency in parallel simulations through domain decomposition. A parallel scheme is proposed to reduce interprocessor communication or synchronization, which slows down parallel simulation with increasing number of processors. Parallel simulation results for the two-dimensional lattice gas model show substantial reduction of simulation time for systems of moderate and large size.
Parallel Markov chain Monte Carlo simulations.
Ren, Ruichao; Orkoulas, G
2007-06-07
With strict detailed balance, parallel Monte Carlo simulation through domain decomposition cannot be validated with conventional Markov chain theory, which describes an intrinsically serial stochastic process. In this work, the parallel version of Markov chain theory and its role in accelerating Monte Carlo simulations via cluster computing is explored. It is shown that sequential updating is the key to improving efficiency in parallel simulations through domain decomposition. A parallel scheme is proposed to reduce interprocessor communication or synchronization, which slows down parallel simulation with increasing number of processors. Parallel simulation results for the two-dimensional lattice gas model show substantial reduction of simulation time for systems of moderate and large size.
Interaction picture density matrix quantum Monte Carlo
Malone, Fionn D. Lee, D. K. K.; Foulkes, W. M. C.; Blunt, N. S.; Shepherd, James J.; Spencer, J. S.
2015-07-28
The recently developed density matrix quantum Monte Carlo (DMQMC) algorithm stochastically samples the N-body thermal density matrix and hence provides access to exact properties of many-particle quantum systems at arbitrary temperatures. We demonstrate that moving to the interaction picture provides substantial benefits when applying DMQMC to interacting fermions. In this first study, we focus on a system of much recent interest: the uniform electron gas in the warm dense regime. The basis set incompleteness error at finite temperature is investigated and extrapolated via a simple Monte Carlo sampling procedure. Finally, we provide benchmark calculations for a four-electron system, comparing our results to previous work where possible.
Monte Carlo inversion of seismic data
NASA Technical Reports Server (NTRS)
Wiggins, R. A.
1972-01-01
The analytic solution to the linear inverse problem provides estimates of the uncertainty of the solution in terms of standard deviations of corrections to a particular solution, resolution of parameter adjustments, and information distribution among the observations. It is shown that Monte Carlo inversion, when properly executed, can provide all the same kinds of information for nonlinear problems. Proper execution requires a relatively uniform sampling of all possible models. The expense of performing Monte Carlo inversion generally requires strategies to improve the probability of finding passing models. Such strategies can lead to a very strong bias in the distribution of models examined unless great care is taken in their application.
The Rational Hybrid Monte Carlo algorithm
NASA Astrophysics Data System (ADS)
Clark, Michael
2006-12-01
The past few years have seen considerable progress in algorithmic development for the generation of gauge fields including the effects of dynamical fermions. The Rational Hybrid Monte Carlo (RHMC) algorithm, where Hybrid Monte Carlo is performed using a rational approximation in place the usual inverse quark matrix kernel is one of these developments. This algorithm has been found to be extremely beneficial in many areas of lattice QCD (chiral fermions, finite temperature, Wilson fermions etc.). We review the algorithm and some of these benefits, and we compare against other recent algorithm developements. We conclude with an update of the Berlin wall plot comparing costs of all popular fermion formulations.
NASA Astrophysics Data System (ADS)
Chen, Y.; Fischer, U.
2005-10-01
A program system for three-dimensional coupled Monte Carlo-deterministic shielding analysis has been developed to solve problems with complex geometry and bulk shield by integrating the Monte Carlo transport code MCNP, the three-dimensional discrete ordinates code TORT and a coupling interface program. A newly-proposed mapping approach is implemented in the interface program to calculate the angular flux distribution from the scored Monte Carlo particle tracks and generate the boundary source file for the use of TORT. Test calculations were performed with comparison to MCNP solutions. Satisfactory agreements were obtained between the results calculated by these two approaches. The program system has been chosen to treat the complicated shielding problem of the accelerator-based IFMIF neutron source. The successful application demonstrates that coupling scheme with the program system is a useful computational tool for the shielding analysis of complex and large nuclear facilities.
NASA Astrophysics Data System (ADS)
Idiri, Z.; Mazrou, H.; Beddek, S.; Amokrane, A.; Azbouche, A.
2007-07-01
The present paper describes the optimization of sample dimensions of a 241Am-Be neutron source-based Prompt gamma neutron activation analysis (PGNAA) setup devoted for in situ environmental water rejects analysis. The optimal dimensions have been achieved following extensive Monte Carlo neutron flux calculations using MCNP5 computer code. A validation process has been performed for the proposed preliminary setup with measurements of thermal neutron flux by activation technique of indium foils, bare and with cadmium covered sheet. Sensitive calculations were subsequently performed to simulate real conditions of in situ analysis by determining thermal neutron flux perturbations in samples according to chlorine and organic matter concentrations changes. The desired optimal sample dimensions were finally achieved once established constraints regarding neutron damage to semi-conductor gamma detector, pulse pile-up, dead time and radiation hazards were fully met.
NASA Astrophysics Data System (ADS)
Gong, Y.; Yu, Y. J.; Zhang, W. Y.
2016-08-01
This study has established a set of methodological systems by simulating loads and analyzing optimization strategy integrity for the optimization of watershed non-point source pollution control. First, the source of watershed agricultural non-point source pollution is divided into four aspects, including agricultural land, natural land, livestock breeding, and rural residential land. Secondly, different pollution control measures at the source, midway and ending stages are chosen. Thirdly, the optimization effect of pollution load control in three stages are simulated, based on the Monte Carlo simulation. The method described above is applied to the Ashi River watershed in Heilongjiang Province of China. Case study results indicate that the combined three types of control measures can be implemented only if the government promotes the optimized plan and gradually improves implementation efficiency. This method for the optimization strategy integrity for watershed non-point source pollution control has significant reference value.
Xiang Wen; Xiewei Zhong; Tingting Yu; Dan Zhu
2014-07-31
Fibre-optic diffuse reflectance spectroscopy offers a method for characterising phantoms of biotissue with specified optical properties. For a commercial reflectance probe (six source fibres surrounding a central collection fibre with an inter-fibre spacing of 480 μm; R400-7, Ocean Optics, USA) we have constructed a Monte Carlo based lookup table to create a function called getR(μ{sub a}, μ'{sub s}), where μ{sub a} is the absorption coefficient and μ'{sub s} is the reduced scattering coefficient. Experimental measurements of reflectance from homogeneous calibrated phantoms with given optical properties are compared with the predicted reflectance from the lookup table. The deviation between experiment and prediction is on average 12.1%. (laser biophotonics)
NASA Astrophysics Data System (ADS)
Panzeri, M.; Riva, M.; Guadagnini, A.; Neuman, S. P.
2014-04-01
Traditional Ensemble Kalman Filter (EnKF) data assimilation requires computationally intensive Monte Carlo (MC) sampling, which suffers from filter inbreeding unless the number of simulations is large. Recently we proposed an alternative EnKF groundwater-data assimilation method that obviates the need for sampling and is free of inbreeding issues. In our new approach, theoretical ensemble moments are approximated directly by solving a system of corresponding stochastic groundwater flow equations. Like MC-based EnKF, our moment equations (ME) approach allows Bayesian updating of system states and parameters in real-time as new data become available. Here we compare the performances and accuracies of the two approaches on two-dimensional transient groundwater flow toward a well pumping water in a synthetic, randomly heterogeneous confined aquifer subject to prescribed head and flux boundary conditions.
Monte Carlo based approach to the LS-NaI 4πβ-γ anticoincidence extrapolation and uncertainty
Fitzgerald, R.
2016-01-01
The 4πβ-γ anticoincidence method is used for the primary standardization of β−, β+, electron capture (EC), α, and mixed-mode radionuclides. Efficiency extrapolation using one or more γ ray coincidence gates is typically carried out by a low-order polynomial fit. The approach presented here is to use a Geant4-based Monte Carlo simulation of the detector system to analyze the efficiency extrapolation. New code was developed to account for detector resolution, direct γ ray interaction with the PMT, and implementation of experimental β-decay shape factors. The simulation was tuned to 57Co and 60Co data, then tested with 99mTc data, and used in measurements of 18F, 129I, and 124I. The analysis method described here offers a more realistic activity value and uncertainty than those indicated from a least-squares fit alone. PMID:27358944
TH-A-19A-06: Site-Specific Comparison of Analytical and Monte Carlo Based Dose Calculations
Schuemann, J; Grassberger, C; Paganetti, H; Dowdell, S
2014-06-15
Purpose: To investigate the impact of complex patient geometries on the capability of analytical dose calculation algorithms to accurately predict dose distributions and to verify currently used uncertainty margins in proton therapy. Methods: Dose distributions predicted by an analytical pencilbeam algorithm were compared with Monte Carlo simulations (MCS) using TOPAS. 79 complete patient treatment plans were investigated for 7 disease sites (liver, prostate, breast, medulloblastoma spine and whole brain, lung and head and neck). A total of 508 individual passively scattered treatment fields were analyzed for field specific properties. Comparisons based on target coverage indices (EUD, D95, D90 and D50) were performed. Range differences were estimated for the distal position of the 90% dose level (R90) and the 50% dose level (R50). Two-dimensional distal dose surfaces were calculated and the root mean square differences (RMSD), average range difference (ARD) and average distal dose degradation (ADD), the distance between the distal position of the 80% and 20% dose levels (R80- R20), were analyzed. Results: We found target coverage indices calculated by TOPAS to generally be around 1–2% lower than predicted by the analytical algorithm. Differences in R90 predicted by TOPAS and the planning system can be larger than currently applied range margins in proton therapy for small regions distal to the target volume. We estimate new site-specific range margins (R90) for analytical dose calculations considering total range uncertainties and uncertainties from dose calculation alone based on the RMSD. Our results demonstrate that a reduction of currently used uncertainty margins is feasible for liver, prostate and whole brain fields even without introducing MC dose calculations. Conclusion: Analytical dose calculation algorithms predict dose distributions within clinical limits for more homogeneous patients sites (liver, prostate, whole brain). However, we recommend
Seo, Deoknam; Han, Seonggyu; Kim, Kie Hwan; Kim, Jungsu; Park, Kyung; Lim, Hyunjong; Kim, Jungmin
2015-11-01
At present, concern regarding radiation exposure is increasing with the prevalence of radiologic examination. As radiation damages the human body, we have evaluated medical radiation dose values and studied the importance of optimizing radiation exposure. We measured entrance surface dose (ESD) values using a RANDO(®) phantom (neck) in 94 randomly selected locations in the central region of Korea. Thyroid and organ doses were calculated using Monte Carlo simulations (PCXMC 2.0.1) based on measured values. In addition, the lifetime attributable risk (LAR) of cancer was calculated for the thyroid, using the method proposed in the biological effects of ionizing radiation VII report. The average measured ESD values obtained using the RANDO(®) phantom (neck) were antero-posterior 1.33 mGy and lateral 1.23 mGy, for a total of 2.56 mGy. Based on the ESD values measured using the phantom, the organ doses were obtained using a Monte Carlo simulation (PCXMC 2.0.1). The thyroid dose was 1.48 mSv on average. In evaluating the LAR of thyroid cancer incidence, a frequency of 0.02 per 100,000 from 2.94 per 100,000 males and a frequency of 0.10 per 100,000 from 16.23 per 100,000 females were found. The risk of cancer was found to be higher when the patient's age was lower, and was also higher in females than in males. It was concluded that beneficial exams in the medical field should not be prohibited because of a statistically small risk, although acknowledgement of the dangers of ionizing radiation is necessary.
NASA Astrophysics Data System (ADS)
Townson, Reid W.; Zavgorodni, Sergei
2014-12-01
In GPU-based Monte Carlo simulations for radiotherapy dose calculation, source modelling from a phase-space source can be an efficiency bottleneck. Previously, this has been addressed using phase-space-let (PSL) sources, which provided significant efficiency enhancement. We propose that additional speed-up can be achieved through the use of a hybrid primary photon point source model combined with a secondary PSL source. A novel phase-space derived and histogram-based implementation of this model has been integrated into gDPM v3.0. Additionally, a simple method for approximately deriving target photon source characteristics from a phase-space that does not contain inheritable particle history variables (LATCH) has been demonstrated to succeed in selecting over 99% of the true target photons with only ~0.3% contamination (for a Varian 21EX 18 MV machine). The hybrid source model was tested using an array of open fields for various Varian 21EX and TrueBeam energies, and all cases achieved greater than 97% chi-test agreement (the mean was 99%) above the 2% isodose with 1% / 1 mm criteria. The root mean square deviations (RMSDs) were less than 1%, with a mean of 0.5%, and the source generation time was 4-5 times faster. A seven-field intensity modulated radiation therapy patient treatment achieved 95% chi-test agreement above the 10% isodose with 1% / 1 mm criteria, 99.8% for 2% / 2 mm, a RMSD of 0.8%, and source generation speed-up factor of 2.5. Presented as part of the International Workshop on Monte Carlo Techniques in Medical Physics
Boylan, Christopher J; Aitkenhead, Adam H; Rowbottom, Carl G; Mackay, Ranald I
2013-12-01
To investigate the use of a software-based pre-treatment QA system for VMAT, which incorporates realistic linac motion during delivery. A beam model was produced using the GATE platform for GEANT4 Monte Carlo dose calculations. Initially validated against static measurements, the model was then integrated with a VMAT delivery emulator, which reads plan files and generates a set of dynamic delivery instructions analogous to the linac control system. Monte Carlo simulations were compared to measurements on dosimetric phantoms for prostate and head and neck VMAT plans. Comparisons were made between calculations using fixed control points, and simulations of continuous motion utilising the emulator. For routine use, the model was incorporated into an automated pre-treatment QA system. The model showed better agreement with measurements when incorporating linac motion: mean gamma pass (Γ<1) over 5 prostate plans was 100.0% at 3%/3mm and 97.4% at 2%/2mm when compared to measurement. For the head and neck plans, delivered to the anatomical phantom, gamma passes were 99.4% at 4%/4mm and 94.94% at 3%/3mm. For example simulations within patient CT data, gamma passes were observed which are within our centre's tolerance for pre-treatment QA. Through comparison to phantom measurements, it was found that the incorporation of a realistic linac motion improves the accuracy of the model compared to the simulation of fixed control points. The ability to accurately calculate dose as a second check of the planning system, and determine realistic delivery characteristics, may allow for the reduction of machine-based pre-treatment plan QA for VMAT. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Monte Carlo scatter correction for SPECT
NASA Astrophysics Data System (ADS)
Liu, Zemei
The goal of this dissertation is to present a quantitatively accurate and computationally fast scatter correction method that is robust and easily accessible for routine applications in SPECT imaging. A Monte Carlo based scatter estimation method is investigated and developed further. The Monte Carlo simulation program SIMIND (Simulating Medical Imaging Nuclear Detectors), was specifically developed to simulate clinical SPECT systems. The SIMIND scatter estimation (SSE) method was developed further using a multithreading technique to distribute the scatter estimation task across multiple threads running concurrently on multi-core CPU's to accelerate the scatter estimation process. An analytical collimator that ensures less noise was used during SSE. The research includes the addition to SIMIND of charge transport modeling in cadmium zinc telluride (CZT) detectors. Phenomena associated with radiation-induced charge transport including charge trapping, charge diffusion, charge sharing between neighboring detector pixels, as well as uncertainties in the detection process are addressed. Experimental measurements and simulation studies were designed for scintillation crystal based SPECT and CZT based SPECT systems to verify and evaluate the expanded SSE method. Jaszczak Deluxe and Anthropomorphic Torso Phantoms (Data Spectrum Corporation, Hillsborough, NC, USA) were used for experimental measurements and digital versions of the same phantoms employed during simulations to mimic experimental acquisitions. This study design enabled easy comparison of experimental and simulated data. The results have consistently shown that the SSE method performed similarly or better than the triple energy window (TEW) and effective scatter source estimation (ESSE) methods for experiments on all the clinical SPECT systems. The SSE method is proven to be a viable method for scatter estimation for routine clinical use.
Parallel implicit Monte Carlo in C++
Urbatsch, T.J.; Evans, T.M.
1998-12-31
The authors are developing a parallel C++ Implicit Monte Carlo code in the Draco framework. As a background and motivation for the parallelization strategy, they first present three basic parallelization schemes. They use three hypothetical examples, mimicking the memory constraints of the real world, to examine characteristics of the basic schemes. Next, they present a two-step scheme proposed by Lawrence Livermore National Laboratory (LLNL). The two-step parallelization scheme they develop is based upon LLNL`s two-step scheme. The two-step scheme appears to have greater potential compared to the basic schemes and LLNL`s two-step scheme. Lastly, they explain the code design and describe how the functionality of C++ and the Draco framework assist the development of a parallel code.
Monte Carlo applications to acoustical field solutions
NASA Technical Reports Server (NTRS)
Haviland, J. K.; Thanedar, B. D.
1973-01-01
The Monte Carlo technique is proposed for the determination of the acoustical pressure-time history at chosen points in a partial enclosure, the central idea of this technique being the tracing of acoustical rays. A statistical model is formulated and an algorithm for pressure is developed, the conformity of which is examined by two approaches and is shown to give the known results. The concepts that are developed are applied to the determination of the transient field due to a sound source in a homogeneous medium in a rectangular enclosure with perfect reflecting walls, and the results are compared with those presented by Mintzer based on the Laplace transform approach, as well as with a normal mode solution.
Hybrid algorithms in quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Kim, Jeongnim; Esler, Kenneth P.; McMinis, Jeremy; Morales, Miguel A.; Clark, Bryan K.; Shulenburger, Luke; Ceperley, David M.
2012-12-01
With advances in algorithms and growing computing powers, quantum Monte Carlo (QMC) methods have become a leading contender for high accuracy calculations for the electronic structure of realistic systems. The performance gain on recent HPC systems is largely driven by increasing parallelism: the number of compute cores of a SMP and the number of SMPs have been going up, as the Top500 list attests. However, the available memory as well as the communication and memory bandwidth per element has not kept pace with the increasing parallelism. This severely limits the applicability of QMC and the problem size it can handle. OpenMP/MPI hybrid programming provides applications with simple but effective solutions to overcome efficiency and scalability bottlenecks on large-scale clusters based on multi/many-core SMPs. We discuss the design and implementation of hybrid methods in QMCPACK and analyze its performance on current HPC platforms characterized by various memory and communication hierarchies.
Noncovalent Interactions by Quantum Monte Carlo.
Dubecký, Matúš; Mitas, Lubos; Jurečka, Petr
2016-05-11
Quantum Monte Carlo (QMC) is a family of stochastic methods for solving quantum many-body problems such as the stationary Schrödinger equation. The review introduces basic notions of electronic structure QMC based on random walks in real space as well as its advances and adaptations to systems with noncovalent interactions. Specific issues such as fixed-node error cancellation, construction of trial wave functions, and efficiency considerations that allow for benchmark quality QMC energy differences are described in detail. Comprehensive overview of articles covers QMC applications to systems with noncovalent interactions over the last three decades. The current status of QMC with regard to efficiency, applicability, and usability by nonexperts together with further considerations about QMC developments, limitations, and unsolved challenges are discussed as well.
Monte Carlo Studies of Protein Aggregation
NASA Astrophysics Data System (ADS)
Jónsson, Sigurður Ægir; Staneva, Iskra; Mohanty, Sandipan; Irbäck, Anders
The disease-linked amyloid β (Aβ) and α-synuclein (αS) proteins are both fibril-forming and natively unfolded in free monomeric form. Here, we discuss two recent studies, where we used extensive implicit solvent all-atom Monte Carlo (MC) simulations to elucidate the conformational ensembles sampled by these proteins. For αS, we somewhat unexpectedly observed two distinct phases, separated by a clear free-energy barrier. The presence of the barrier makes αS, with 140 residues, a challenge to simulate. By using a two-step simulation procedure based on flat-histogram techniques, it was possible to alleviate this problem. The barrier may in part explain why fibril formation is much slower for αS than it is for Aβ
ERIC Educational Resources Information Center
MacDonald, Paul; Paunonen, Sampo V.
2002-01-01
Examined the behavior of item and person statistics from item response theory and classical test theory frameworks through Monte Carlo methods with simulated test data. Findings suggest that item difficulty and person ability estimates are highly comparable for both approaches. (SLD)
NASA Astrophysics Data System (ADS)
Jin, Shengye; Tamura, Masayuki
2013-10-01
Monte Carlo Ray Tracing (MCRT) method is a versatile application for simulating radiative transfer regime of the Solar - Atmosphere - Landscape system. Moreover, it can be used to compute the radiation distribution over a complex landscape configuration, as an example like a forest area. Due to its robustness to the complexity of the 3-D scene altering, MCRT method is also employed for simulating canopy radiative transfer regime as the validation source of other radiative transfer models. In MCRT modeling within vegetation, one basic step is the canopy scene set up. 3-D scanning application was used for representing canopy structure as accurately as possible, but it is time consuming. Botanical growth function can be used to model the single tree growth, but cannot be used to express the impaction among trees. L-System is also a functional controlled tree growth simulation model, but it costs large computing memory. Additionally, it only models the current tree patterns rather than tree growth during we simulate the radiative transfer regime. Therefore, it is much more constructive to use regular solid pattern like ellipsoidal, cone, cylinder etc. to indicate single canopy. Considering the allelopathy phenomenon in some open forest optical images, each tree in its own `domain' repels other trees. According to this assumption a stochastic circle packing algorithm is developed to generate the 3-D canopy scene in this study. The canopy coverage (%) and the tree amount (N) of the 3-D scene are declared at first, similar to the random open forest image. Accordingly, we randomly generate each canopy radius (rc). Then we set the circle central coordinate on XY-plane as well as to keep circles separate from each other by the circle packing algorithm. To model the individual tree, we employ the Ishikawa's tree growth regressive model to set the tree parameters including DBH (dt), tree height (H). However, the relationship between canopy height (Hc) and trunk height (Ht) is
Titt, U; Sahoo, N; Ding, X; Zheng, Y; Newhauser, W D; Zhu, X R; Polf, J C; Gillin, M T; Mohan, R
2008-08-21
In recent years, the Monte Carlo method has been used in a large number of research studies in radiation therapy. For applications such as treatment planning, it is essential to validate the dosimetric accuracy of the Monte Carlo simulations in heterogeneous media. The AAPM Report no 105 addresses issues concerning clinical implementation of Monte Carlo based treatment planning for photon and electron beams, however for proton-therapy planning, such guidance is not yet available. Here we present the results of our validation of the Monte Carlo model of the double scattering system used at our Proton Therapy Center in Houston. In this study, we compared Monte Carlo simulated depth doses and lateral profiles to measured data for a magnitude of beam parameters. We varied simulated proton energies and widths of the spread-out Bragg peaks, and compared them to measurements obtained during the commissioning phase of the Proton Therapy Center in Houston. Of 191 simulated data sets, 189 agreed with measured data sets to within 3% of the maximum dose difference and within 3 mm of the maximum range or penumbra size difference. The two simulated data sets that did not agree with the measured data sets were in the distal falloff of the measured dose distribution, where large dose gradients potentially produce large differences on the basis of minute changes in the beam steering. Hence, the Monte Carlo models of medium- and large-size double scattering proton-therapy nozzles were valid for proton beams in the 100 MeV-250 MeV interval.
Scalable Domain Decomposed Monte Carlo Particle Transport
O'Brien, Matthew Joseph
2013-12-05
In this dissertation, we present the parallel algorithms necessary to run domain decomposed Monte Carlo particle transport on large numbers of processors (millions of processors). Previous algorithms were not scalable, and the parallel overhead became more computationally costly than the numerical simulation.
Monte Carlo studies of uranium calorimetry
Brau, J.; Hargis, H.J.; Gabriel, T.A.; Bishop, B.L.
1985-01-01
Detailed Monte Carlo calculations of uranium calorimetry are presented which reveal a significant difference in the responses of liquid argon and plastic scintillator in uranium calorimeters. Due to saturation effects, neutrons from the uranium are found to contribute only weakly to the liquid argon signal. Electromagnetic sampling inefficiencies are significant and contribute substantially to compensation in both systems. 17 references.
A comparison of Monte Carlo generators
Golan, Tomasz
2015-05-15
A comparison of GENIE, NEUT, NUANCE, and NuWro Monte Carlo neutrino event generators is presented using a set of four observables: protons multiplicity, total visible energy, most energetic proton momentum, and π{sup +} two-dimensional energy vs cosine distribution.
Structural Reliability and Monte Carlo Simulation.
ERIC Educational Resources Information Center
Laumakis, P. J.; Harlow, G.
2002-01-01
Analyzes a simple boom structure and assesses its reliability using elementary engineering mechanics. Demonstrates the power and utility of Monte-Carlo simulation by showing that such a simulation can be implemented more readily with results that compare favorably to the theoretical calculations. (Author/MM)
Search and Rescue Monte Carlo Simulation.
1985-03-01
confidence interval ) of the number of lives saved. A single page output and computer graphic present the information to the user in an easily understood...format. The confidence interval can be reduced by making additional runs of this Monte Carlo model. (Author)
Monte Carlo methods in genetic analysis
Lin, Shili
1996-12-31
Many genetic analyses require computation of probabilities and likelihoods of pedigree data. With more and more genetic marker data deriving from new DNA technologies becoming available to researchers, exact computations are often formidable with standard statistical methods and computational algorithms. The desire to utilize as much available data as possible, coupled with complexities of realistic genetic models, push traditional approaches to their limits. These methods encounter severe methodological and computational challenges, even with the aid of advanced computing technology. Monte Carlo methods are therefore increasingly being explored as practical techniques for estimating these probabilities and likelihoods. This paper reviews the basic elements of the Markov chain Monte Carlo method and the method of sequential imputation, with an emphasis upon their applicability to genetic analysis. Three areas of applications are presented to demonstrate the versatility of Markov chain Monte Carlo for different types of genetic problems. A multilocus linkage analysis example is also presented to illustrate the sequential imputation method. Finally, important statistical issues of Markov chain Monte Carlo and sequential imputation, some of which are unique to genetic data, are discussed, and current solutions are outlined. 72 refs.
Monte Carlo algorithms for Brownian phylogenetic models.
Horvilleur, Benjamin; Lartillot, Nicolas
2014-11-01
Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates. A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision. The program is freely available at www.phylobayes.org. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Monte Carlo algorithms for Brownian phylogenetic models
Horvilleur, Benjamin; Lartillot, Nicolas
2014-01-01
Motivation: Brownian models have been introduced in phylogenetics for describing variation in substitution rates through time, with applications to molecular dating or to the comparative analysis of variation in substitution patterns among lineages. Thus far, however, the Monte Carlo implementations of these models have relied on crude approximations, in which the Brownian process is sampled only at the internal nodes of the phylogeny or at the midpoints along each branch, and the unknown trajectory between these sampled points is summarized by simple branchwise average substitution rates. Results: A more accurate Monte Carlo approach is introduced, explicitly sampling a fine-grained discretization of the trajectory of the (potentially multivariate) Brownian process along the phylogeny. Generic Monte Carlo resampling algorithms are proposed for updating the Brownian paths along and across branches. Specific computational strategies are developed for efficient integration of the finite-time substitution probabilities across branches induced by the Brownian trajectory. The mixing properties and the computational complexity of the resulting Markov chain Monte Carlo sampler scale reasonably with the discretization level, allowing practical applications with up to a few hundred discretization points along the entire depth of the tree. The method can be generalized to other Markovian stochastic processes, making it possible to implement a wide range of time-dependent substitution models with well-controlled computational precision. Availability: The program is freely available at www.phylobayes.org Contact: nicolas.lartillot@univ-lyon1.fr PMID:25053744
Monte Carlo studies of ARA detector optimization
NASA Astrophysics Data System (ADS)
Stockham, Jessica
2013-04-01
The Askaryan Radio Array (ARA) is a neutrino detector deployed in the Antarctic ice sheet near the South Pole. The array is designed to detect ultra high energy neutrinos in the range of 0.1-10 EeV. Detector optimization is studied using Monte Carlo simulations.
NASA Astrophysics Data System (ADS)
Grevillot, L.; Bertrand, D.; Dessy, F.; Freud, N.; Sarrut, D.
2012-07-01
Active scanning delivery systems take full advantage of ion beams to best conform to the tumor and to spare surrounding healthy tissues; however, it is also a challenging technique for quality assurance. In this perspective, we upgraded the GATE/GEANT4 Monte Carlo platform in order to recalculate the treatment planning system (TPS) dose distributions for active scanning systems. A method that allows evaluating the TPS dose distributions with the GATE Monte Carlo platform has been developed and applied to the XiO TPS (Elekta), for the IBA proton pencil beam scanning (PBS) system. First, we evaluated the specificities of each dose engine. A dose-conversion scheme that allows one to convert dose to medium into dose to water was implemented within GATE. Specific test cases in homogeneous and heterogeneous configurations allowed for the estimation of the differences between the beam models implemented in XiO and GATE. Finally, dose distributions of a prostate treatment plan were compared. In homogeneous media, a satisfactory agreement was generally obtained between XiO and GATE. The maximum stopping power difference of 3% occurred in a human tissue of 0.9 g cm-3 density and led to a significant range shift. Comparisons in heterogeneous configurations pointed out the limits of the TPS dose calculation accuracy and the superiority of Monte Carlo simulations. The necessity of computing dose to water in our Monte Carlo code for comparisons with TPSs is also presented. Finally, the new capabilities of the platform are applied to a prostate treatment plan and dose differences between both dose engines are analyzed in detail. This work presents a generic method to compare TPS dose distributions with the GATE Monte Carlo platform. It is noteworthy that GATE is also a convenient tool for imaging applications, therefore opening new research possibilities for the PBS modality.
Grevillot, L; Bertrand, D; Dessy, F; Freud, N; Sarrut, D
2012-07-07
Active scanning delivery systems take full advantage of ion beams to best conform to the tumor and to spare surrounding healthy tissues; however, it is also a challenging technique for quality assurance. In this perspective, we upgraded the GATE/GEANT4 Monte Carlo platform in order to recalculate the treatment planning system (TPS) dose distributions for active scanning systems. A method that allows evaluating the TPS dose distributions with the GATE Monte Carlo platform has been developed and applied to the XiO TPS (Elekta), for the IBA proton pencil beam scanning (PBS) system. First, we evaluated the specificities of each dose engine. A dose-conversion scheme that allows one to convert dose to medium into dose to water was implemented within GATE. Specific test cases in homogeneous and heterogeneous configurations allowed for the estimation of the differences between the beam models implemented in XiO and GATE. Finally, dose distributions of a prostate treatment plan were compared. In homogeneous media, a satisfactory agreement was generally obtained between XiO and GATE. The maximum stopping power difference of 3% occurred in a human tissue of 0.9 g cm(-3) density and led to a significant range shift. Comparisons in heterogeneous configurations pointed out the limits of the TPS dose calculation accuracy and the superiority of Monte Carlo simulations. The necessity of computing dose to water in our Monte Carlo code for comparisons with TPSs is also presented. Finally, the new capabilities of the platform are applied to a prostate treatment plan and dose differences between both dose engines are analyzed in detail. This work presents a generic method to compare TPS dose distributions with the GATE Monte Carlo platform. It is noteworthy that GATE is also a convenient tool for imaging applications, therefore opening new research possibilities for the PBS modality.
NASA Astrophysics Data System (ADS)
Kohno, R.; Hotta, K.; Nishioka, S.; Matsubara, K.; Tansho, R.; Suzuki, T.
2011-11-01
We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.
Kohno, R; Hotta, K; Nishioka, S; Matsubara, K; Tansho, R; Suzuki, T
2011-11-21
We implemented the simplified Monte Carlo (SMC) method on graphics processing unit (GPU) architecture under the computer-unified device architecture platform developed by NVIDIA. The GPU-based SMC was clinically applied for four patients with head and neck, lung, or prostate cancer. The results were compared to those obtained by a traditional CPU-based SMC with respect to the computation time and discrepancy. In the CPU- and GPU-based SMC calculations, the estimated mean statistical errors of the calculated doses in the planning target volume region were within 0.5% rms. The dose distributions calculated by the GPU- and CPU-based SMCs were similar, within statistical errors. The GPU-based SMC showed 12.30-16.00 times faster performance than the CPU-based SMC. The computation time per beam arrangement using the GPU-based SMC for the clinical cases ranged 9-67 s. The results demonstrate the successful application of the GPU-based SMC to a clinical proton treatment planning.
An unbiased Hessian representation for Monte Carlo PDFs.
Carrazza, Stefano; Forte, Stefano; Kassabov, Zahari; Latorre, José Ignacio; Rojo, Juan
We develop a methodology for the construction of a Hessian representation of Monte Carlo sets of parton distributions, based on the use of a subset of the Monte Carlo PDF replicas as an unbiased linear basis, and of a genetic algorithm for the determination of the optimal basis. We validate the methodology by first showing that it faithfully reproduces a native Monte Carlo PDF set (NNPDF3.0), and then, that if applied to Hessian PDF set (MMHT14) which was transformed into a Monte Carlo set, it gives back the starting PDFs with minimal information loss. We then show that, when applied to a large Monte Carlo PDF set obtained as combination of several underlying sets, the methodology leads to a Hessian representation in terms of a rather smaller set of parameters (MC-H PDFs), thereby providing an alternative implementation of the recently suggested Meta-PDF idea and a Hessian version of the recently suggested PDF compression algorithm (CMC-PDFs). The mc2hessian conversion code is made publicly available together with (through LHAPDF6) a Hessian representations of the NNPDF3.0 set, and the MC-H PDF set.
Fission Matrix Capability for MCNP Monte Carlo
Carney, Sean E.; Brown, Forrest B.; Kiedrowski, Brian C.; Martin, William R.
2012-09-05
spatially low-order kernel, the fundamental eigenvector of which should converge faster than that of continuous kernel. We can then redistribute the fission bank to match the fundamental fission matrix eigenvector, effectively eliminating all higher modes. For all computations here biasing is not used, with the intention of comparing the unaltered, conventional Monte Carlo process with the fission matrix results. The source convergence of standard Monte Carlo criticality calculations are, to some extent, always subject to the characteristics of the problem. This method seeks to partially eliminate this problem-dependence by directly calculating the spatial coupling. The primary cost of this, which has prevented widespread use since its inception [2,3,4], is the extra storage required. To account for the coupling of all N spatial regions to every other region requires storing N{sup 2} values. For realistic problems, where a fine resolution is required for the suppression of discretization error, the storage becomes inordinate. Two factors lead to a renewed interest here: the larger memory available on modern computers and the development of a better storage scheme based on physical intuition. When the distance between source and fission events is short compared with the size of the entire system, saving memory by accounting for only local coupling introduces little extra error. We can gain other information from directly tallying the fission kernel: higher eigenmodes and eigenvalues. Conventional Monte Carlo cannot calculate this data - here we have a way to get new information for multiplying systems. In Ref. [5], higher mode eigenfunctions are analyzed for a three-region 1-dimensional problem and 2-dimensional homogenous problem. We analyze higher modes for more realistic problems. There is also the question of practical use of this information; here we examine a way of using eigenmode information to address the negative confidence interval bias due to inter
MontePython: Implementing Quantum Monte Carlo using Python
NASA Astrophysics Data System (ADS)
Nilsen, Jon Kristian
2007-11-01
We present a cross-language C++/Python program for simulations of quantum mechanical systems with the use of Quantum Monte Carlo (QMC) methods. We describe a system for which to apply QMC, the algorithms of variational Monte Carlo and diffusion Monte Carlo and we describe how to implement theses methods in pure C++ and C++/Python. Furthermore we check the efficiency of the implementations in serial and parallel cases to show that the overhead using Python can be negligible. Program summaryProgram title: MontePython Catalogue identifier: ADZP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 49 519 No. of bytes in distributed program, including test data, etc.: 114 484 Distribution format: tar.gz Programming language: C++, Python Computer: PC, IBM RS6000/320, HP, ALPHA Operating system: LINUX Has the code been vectorised or parallelized?: Yes, parallelized with MPI Number of processors used: 1-96 RAM: Depends on physical system to be simulated Classification: 7.6; 16.1 Nature of problem: Investigating ab initio quantum mechanical systems, specifically Bose-Einstein condensation in dilute gases of 87Rb Solution method: Quantum Monte Carlo Running time: 225 min with 20 particles (with 4800 walkers moved in 1750 time steps) on 1 AMD Opteron TM Processor 2218 processor; Production run for, e.g., 200 particles takes around 24 hours on 32 such processors.
Complexity of Monte Carlo and deterministic dose-calculation methods.
Börgers, C
1998-03-01
Grid-based deterministic dose-calculation methods for radiotherapy planning require the use of six-dimensional phase space grids. Because of the large number of phase space dimensions, a growing number of medical physicists appear to believe that grid-based deterministic dose-calculation methods are not competitive with Monte Carlo methods. We argue that this conclusion may be premature. Our results do suggest, however, that finite difference or finite element schemes with orders of accuracy greater than one will probably be needed if such methods are to compete well with Monte Carlo methods for dose calculations.
Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates
Fang, Qianqian
2010-01-01
We describe a fast mesh-based Monte Carlo (MC) photon migration algorithm for static and time-resolved imaging in 3D complex media. Compared with previous works using voxel-based media discretization, a mesh-based approach can be more accurate in modeling targets with curved boundaries or locally refined structures. We implement an efficient ray-tracing technique using Plücker Coordinates. The Barycentric coordinates computed from Plücker-formed ray-tracing enables us to use linear Lagrange basis functions to model both media properties and fluence distribution, leading to further improvement in accuracy. The Plücker-coordinate ray-polygon intersection test can be extended to hexahedral or high-order elements. Excellent agreement is found when comparing mesh-based MC with the analytical diffusion model and 3D voxel-based MC code in both homogeneous and heterogeneous cases. Realistic time-resolved imaging results are observed for a complex human brain anatomy using mesh-based MC. We also include multi-threading support in the software and will port it to a graphics processing unit platform in the near future. PMID:21170299
Mesh-based Monte Carlo method using fast ray-tracing in Plücker coordinates.
Fang, Qianqian
2010-08-02
We describe a fast mesh-based Monte Carlo (MC) photon migration algorithm for static and time-resolved imaging in 3D complex media. Compared with previous works using voxel-based media discretization, a mesh-based approach can be more accurate in modeling targets with curved boundaries or locally refined structures. We implement an efficient ray-tracing technique using Plücker Coordinates. The Barycentric coordinates computed from Plücker-formed ray-tracing enables us to use linear Lagrange basis functions to model both media properties and fluence distribution, leading to further improvement in accuracy. The Plücker-coordinate ray-polygon intersection test can be extended to hexahedral or high-order elements. Excellent agreement is found when comparing mesh-based MC with the analytical diffusion model and 3D voxel-based MC code in both homogeneous and heterogeneous cases. Realistic time-resolved imaging results are observed for a complex human brain anatomy using mesh-based MC. We also include multi-threading support in the software and will port it to a graphics processing unit platform in the near future.
NASA Astrophysics Data System (ADS)
Kotalczyk, G.; Kruis, F. E.
2017-07-01
Monte Carlo simulations based on weighted simulation particles can solve a variety of population balance problems and allow thus to formulate a solution-framework for many chemical engineering processes. This study presents a novel concept for the calculation of coagulation rates of weighted Monte Carlo particles by introducing a family of transformations to non-weighted Monte Carlo particles. The tuning of the accuracy (named 'stochastic resolution' in this paper) of those transformations allows the construction of a constant-number coagulation scheme. Furthermore, a parallel algorithm for the inclusion of newly formed Monte Carlo particles due to nucleation is presented in the scope of a constant-number scheme: the low-weight merging. This technique is found to create significantly less statistical simulation noise than the conventional technique (named 'random removal' in this paper). Both concepts are combined into a single GPU-based simulation method which is validated by comparison with the discrete-sectional simulation technique. Two test models describing a constant-rate nucleation coupled to a simultaneous coagulation in 1) the free-molecular regime or 2) the continuum regime are simulated for this purpose.
Development of a Space Radiation Monte-Carlo Computer Simulation Based on the FLUKE and Root Codes
NASA Technical Reports Server (NTRS)
Pinsky, L. S.; Wilson, T. L.; Ferrari, A.; Sala, Paola; Carminati, F.; Brun, R.
2001-01-01
The radiation environment in space is a complex problem to model. Trying to extrapolate the projections of that environment into all areas of the internal spacecraft geometry is even more daunting. With the support of our CERN colleagues, our research group in Houston is embarking on a project to develop a radiation transport tool that is tailored to the problem of taking the external radiation flux incident on any particular spacecraft and simulating the evolution of that flux through a geometrically accurate model of the spacecraft material. The output will be a prediction of the detailed nature of the resulting internal radiation environment within the spacecraft as well as its secondary albedo. Beyond doing the physics transport of the incident flux, the software tool we are developing will provide a self-contained stand-alone object-oriented analysis and visualization infrastructure. It will also include a graphical user interface and a set of input tools to facilitate the simulation of space missions in terms of nominal radiation models and mission trajectory profiles. The goal of this project is to produce a code that is considerably more accurate and user-friendly than existing Monte-Carlo-based tools for the evaluation of the space radiation environment. Furthermore, the code will be an essential complement to the currently existing analytic codes in the BRYNTRN/HZETRN family for the evaluation of radiation shielding. The code will be directly applicable to the simulation of environments in low earth orbit, on the lunar surface, on planetary surfaces (including the Earth) and in the interplanetary medium such as on a transit to Mars (and even in the interstellar medium). The software will include modules whose underlying physics base can continue to be enhanced and updated for physics content, as future data become available beyond the timeframe of the initial development now foreseen. This future maintenance will be available from the authors of FLUKA as
Monte Carlo tests of the ELIPGRID-PC algorithm
Davidson, J.R.
1995-04-01
The standard tool for calculating the probability of detecting pockets of contamination called hot spots has been the ELIPGRID computer code of Singer and Wickman. The ELIPGRID-PC program has recently made this algorithm available for an IBM{reg_sign} PC. However, no known independent validation of the ELIPGRID algorithm exists. This document describes a Monte Carlo simulation-based validation of a modified version of the ELIPGRID-PC code. The modified ELIPGRID-PC code is shown to match Monte Carlo-calculated hot-spot detection probabilities to within {plus_minus}0.5% for 319 out of 320 test cases. The one exception, a very thin elliptical hot spot located within a rectangular sampling grid, differed from the Monte Carlo-calculated probability by about 1%. These results provide confidence in the ability of the modified ELIPGRID-PC code to accurately predict hot-spot detection probabilities within an acceptable range of error.
SPQR: a Monte Carlo reactor kinetics code. [LMFBR
Cramer, S.N.; Dodds, H.L.
1980-02-01
The SPQR Monte Carlo code has been developed to analyze fast reactor core accident problems where conventional methods are considered inadequate. The code is based on the adiabatic approximation of the quasi-static method. This initial version contains no automatic material motion or feedback. An existing Monte Carlo code is used to calculate the shape functions and the integral quantities needed in the kinetics module. Several sample problems have been devised and analyzed. Due to the large statistical uncertainty associated with the calculation of reactivity in accident simulations, the results, especially at later times, differ greatly from deterministic methods. It was also found that in large uncoupled systems, the Monte Carlo method has difficulty in handling asymmetric perturbations.
Monte Carlo simulation of laser attenuation characteristics in fog
NASA Astrophysics Data System (ADS)
Wang, Hong-Xia; Sun, Chao; Zhu, You-zhang; Sun, Hong-hui; Li, Pan-shi
2011-06-01
Based on the Mie scattering theory and the gamma size distribution model, the scattering extinction parameter of spherical fog-drop is calculated. For the transmission attenuation of the laser in the fog, a Monte Carlo simulation model is established, and the impact of attenuation ratio on visibility and field angle is computed and analysed using the program developed by MATLAB language. The results of the Monte Carlo method in this paper are compared with the results of single scattering method. The results show that the influence of multiple scattering need to be considered when the visibility is low, and single scattering calculations have larger errors. The phenomenon of multiple scattering can be interpreted more better when the Monte Carlo is used to calculate the attenuation ratio of the laser transmitting in the fog.
Liu, T; Lin, H; Xu, X; Stabin, M
2015-06-15
Purpose: To develop a nuclear medicine dosimetry module for the GPU-based Monte Carlo code ARCHER. Methods: We have developed a nuclear medicine dosimetry module for the fast Monte Carlo code ARCHER. The coupled electron-photon Monte Carlo transport kernel included in ARCHER is built upon the Dose Planning Method code (DPM). The developed module manages the radioactive decay simulation by consecutively tracking several types of radiation on a per disintegration basis using the statistical sampling method. Optimization techniques such as persistent threads and prefetching are studied and implemented. The developed module is verified against the VIDA code, which is based on Geant4 toolkit and has previously been verified against OLINDA/EXM. A voxelized geometry is used in the preliminary test: a sphere made of ICRP soft tissue is surrounded by a box filled with water. Uniform activity distribution of I-131 is assumed in the sphere. Results: The self-absorption dose factors (mGy/MBqs) of the sphere with varying diameters are calculated by ARCHER and VIDA respectively. ARCHER’s result is in agreement with VIDA’s that are obtained from a previous publication. VIDA takes hours of CPU time to finish the computation, while it takes ARCHER 4.31 seconds for the 12.4-cm uniform activity sphere case. For a fairer CPU-GPU comparison, more effort will be made to eliminate the algorithmic differences. Conclusion: The coupled electron-photon Monte Carlo code ARCHER has been extended to radioactive decay simulation for nuclear medicine dosimetry. The developed code exhibits good performance in our preliminary test. The GPU-based Monte Carlo code is developed with grant support from the National Institute of Biomedical Imaging and Bioengineering through an R01 grant (R01EB015478)
Bergaoui, K; Reguigui, N; Gary, C K; Brown, C; Cremer, J T; Vainionpaa, J H; Piestrup, M A
2014-12-01
An explosive detection system based on a Deuterium-Deuterium (D-D) neutron generator has been simulated using the Monte Carlo N-Particle Transport Code (MCNP5). Nuclear-based explosive detection methods can detect explosives by identifying their elemental components, especially nitrogen. Thermal neutron capture reactions have been used for detecting prompt gamma emission (10.82MeV) following radiative neutron capture by (14)N nuclei. The explosive detection system was built based on a fully high-voltage-shielded, axial D-D neutron generator with a radio frequency (RF) driven ion source and nominal yield of about 10(10) fast neutrons per second (E=2.5MeV). Polyethylene and paraffin were used as moderators with borated polyethylene and lead as neutron and gamma ray shielding, respectively. The shape and the thickness of the moderators and shields are optimized to produce the highest thermal neutron flux at the position of the explosive and the minimum total dose at the outer surfaces of the explosive detection system walls. In addition, simulation of the response functions of NaI, BGO, and LaBr3-based γ-ray detectors to different explosives is described.
NASA Astrophysics Data System (ADS)
Kano, Masayuki; Nagao, Hiromichi; Nagata, Kenji; Ito, Shin-ichi; Sakai, Shin'ichi; Nakagawa, Shigeki; Hori, Muneo; Hirata, Naoshi
2017-04-01
Earthquakes sometimes cause serious disasters not only directly by ground motion itself but also secondarily by infrastructure damage, particularly in densely populated urban areas. To reduce these secondary disasters, it is important to rapidly evaluate seismic hazards by analyzing the seismic responses of individual structures due to the input ground motions. Such input motions are estimated utilizing an array of seismometers that are distributed more sparsely than the structures. We propose a methodology that integrates physics-based and data-driven approaches in order to obtain the seismic wavefield to be input into seismic response analysis. This study adopts the replica exchange Monte Carlo (REMC) method, which is one of the Markov chain Monte Carlo (MCMC) methods, for the estimation of the seismic wavefield together with one-dimensional local subsurface structure and source information. Numerical tests show that the REMC method is able to search the parameters related to the source and the local subsurface structure in broader parameter space than the Metropolis method, which is an ordinary MCMC method. The REMC method well reproduces the seismic wavefield consistent with the true one. In contrast, the ordinary kriging, which is a classical data-driven interpolation method for spatial data, is hardly able to reproduce the true wavefield even at low frequencies. This indicates that it is essential to take both physics-based and data-driven approaches into consideration for seismic wavefield imaging. Then the REMC method is applied to the actual waveforms observed by a dense seismic array MeSO-net (Metropolitan Seismic Observation network), in which 296 accelerometers are continuously in operation with several kilometer intervals in the Tokyo metropolitan area, Japan. The estimated wavefield within a frequency band of 0.10-0.20 Hz is absolutely consistent with the observed waveforms. Further investigation suggests that the seismic wavefield is successfully
Implementation of Monte Carlo Simulations for the Gamma Knife System
NASA Astrophysics Data System (ADS)
Xiong, W.; Huang, D.; Lee, L.; Feng, J.; Morris, K.; Calugaru, E.; Burman, C.; Li, J.; Ma, C.-M.
2007-06-01
Currently the Gamma Knife system is accompanied with a treatment planning system, Leksell GammaPlan (LGP) which is a standard, computer-based treatment planning system for Gamma Knife radiosurgery. In LGP, the dose calculation algorithm does not consider the scatter dose contributions and the inhomogeneity effect due to the skull and air cavities. To improve the dose calculation accuracy, Monte Carlo simulations have been implemented for the Gamma Knife planning system. In this work, the 201 Cobalt-60 sources in the Gamma Knife unit are considered to have the same activity. Each Cobalt-60 source is contained in a cylindric stainless steel capsule. The particle phase space information is stored in four beam data files, which are collected in the inner sides of the 4 treatment helmets, after the Cobalt beam passes through the stationary and helmet collimators. Patient geometries are rebuilt from patient CT data. Twenty two Patients are included in the Monte Carlo simulation for this study. The dose is calculated using Monte Carlo in both homogenous and inhomogeneous geometries with identical beam parameters. To investigate the attenuation effect of the skull bone the dose in a 16cm diameter spherical QA phantom is measured with and without a 1.5mm Lead-covering and also simulated using Monte Carlo. The dose ratios with and without the 1.5mm Lead-covering are 89.8% based on measurements and 89.2% according to Monte Carlo for a 18mm-collimator Helmet. For patient geometries, the Monte Carlo results show that although the relative isodose lines remain almost the same with and without inhomogeneity corrections, the difference in the absolute dose is clinically significant. The average inhomogeneity correction is (3.9 ± 0.90) % for the 22 patients investigated. These results suggest that the inhomogeneity effect should be considered in the dose calculation for Gamma Knife treatment planning.
NASA Astrophysics Data System (ADS)
Lysak, Y. V.; Klimanov, V. A.; Narkevich, B. Ya
2017-01-01
One of the most difficult problems of modern radionuclide therapy (RNT) is control of the absorbed dose in pathological volume. This research presents new approach based on estimation of radiopharmaceutical (RP) accumulated activity value in tumor volume, based on planar scintigraphic images of the patient and calculated radiation transport using Monte Carlo method, including absorption and scattering in biological tissues of the patient, and elements of gamma camera itself. In our research, to obtain the data, we performed modeling scintigraphy of the vial with administered to the patient activity of RP in gamma camera, the vial was placed at the certain distance from the collimator, and the similar study was performed in identical geometry, with the same values of activity of radiopharmaceuticals in the pathological target in the body of the patient. For correct calculation results, adapted Fisher-Snyder human phantom was simulated in MCNP program. In the context of our technique, calculations were performed for different sizes of pathological targets and various tumors deeps inside patient’s body, using radiopharmaceuticals based on a mixed β-γ-radiating (131I, 177Lu), and clear β- emitting (89Sr, 90Y) therapeutic radionuclides. Presented method can be used for adequate implementing in clinical practice estimation of absorbed doses in the regions of interest on the basis of planar scintigraphy of the patient with sufficient accuracy.
NASA Astrophysics Data System (ADS)
Pan, J.; Durand, M. T.; Vanderjagt, B. J.
2015-12-01
Markov Chain Monte Carlo (MCMC) method is a retrieval algorithm based on Bayes' rule, which starts from an initial state of snow/soil parameters, and updates it to a series of new states by comparing the posterior probability of simulated snow microwave signals before and after each time of random walk. It is a realization of the Bayes' rule, which gives an approximation to the probability of the snow/soil parameters in condition of the measured microwave TB signals at different bands. Although this method could solve all snow parameters including depth, density, snow grain size and temperature at the same time, it still needs prior information of these parameters for posterior probability calculation. How the priors will influence the SWE retrieval is a big concern. Therefore, in this paper at first, a sensitivity test will be carried out to study how accurate the snow emission models and how explicit the snow priors need to be to maintain the SWE error within certain amount. The synthetic TB simulated from the measured snow properties plus a 2-K observation error will be used for this purpose. It aims to provide a guidance on the MCMC application under different circumstances. Later, the method will be used for the snowpits at different sites, including Sodankyla, Finland, Churchill, Canada and Colorado, USA, using the measured TB from ground-based radiometers at different bands. Based on the previous work, the error in these practical cases will be studied, and the error sources will be separated and quantified.
Shin, Younghoon; Kwon, Hyuk-Sang
2016-03-21
We propose a Monte Carlo (MC) method based on a direct photon flux recording strategy using inhomogeneous, meshed rodent brain atlas. This MC method was inspired by and dedicated to fibre-optics-based optogenetic neural stimulations, thus providing an accurate and direct solution for light intensity distributions in brain regions with different optical properties. Our model was used to estimate the 3D light intensity attenuation for close proximity between an implanted optical fibre source and neural target area for typical optogenetics applications. Interestingly, there are discrepancies with studies using a diffusion-based light intensity prediction model, perhaps due to use of improper light scattering models developed for far-field problems. Our solution was validated by comparison with the gold-standard MC model, and it enabled accurate calculations of internal intensity distributions in an inhomogeneous near light source domain. Thus our strategy can be applied to studying how illuminated light spreads through an inhomogeneous brain area, or for determining the amount of light required for optogenetic manipulation of a specific neural target area.
Kangasmaa, Tuija; Kuikka, Jyrki; Sohlberg, Antti
2012-01-01
Simultaneous Tl-201/Tc-99m dual isotope myocardial perfusion SPECT is seriously hampered by down-scatter from Tc-99m into the Tl-201 energy window. This paper presents and optimises the ordered-subsets-expectation-maximisation-(OS-EM-) based reconstruction algorithm, which corrects the down-scatter using an efficient Monte Carlo (MC) simulator. The algorithm starts by first reconstructing the Tc-99m image with attenuation, collimator response, and MC-based scatter correction. The reconstructed Tc-99m image is then used as an input for an efficient MC-based down-scatter simulation of Tc-99m photons into the Tl-201 window. This down-scatter estimate is finally used in the Tl-201 reconstruction to correct the crosstalk between the two isotopes. The mathematical 4D NCAT phantom and physical cardiac phantoms were used to optimise the number of OS-EM iterations where the scatter estimate is updated and the number of MC simulated photons. The results showed that two scatter update iterations and 10(5) simulated photons are enough for the Tc-99m and Tl-201 reconstructions, whereas 10(6) simulated photons are needed to generate good quality down-scatter estimates. With these parameters, the entire Tl-201/Tc-99m dual isotope reconstruction can be accomplished in less than 3 minutes.
Garcia, Marie-Paule Villoing, Daphnée; Ferrer, Ludovic; Cremonesi, Marta; Botta, Francesca; Ferrari, Mahila; Bardiès, Manuel
2015-12-15
Purpose: The TestDose platform was developed to generate scintigraphic imaging protocols and associated dosimetry by Monte Carlo modeling. TestDose is part of a broader project (www.dositest.com) whose aim is to identify the biases induced by different clinical dosimetry protocols. Methods: The TestDose software allows handling the whole pipeline from virtual patient generation to resulting planar and SPECT images and dosimetry calculations. The originality of their approach relies on the implementation of functional segmentation for the anthropomorphic model representing a virtual patient. Two anthropomorphic models are currently available: 4D XCAT and ICRP 110. A pharmacokinetic model describes the biodistribution of a given radiopharmaceutical in each defined compartment at various time-points. The Monte Carlo simulation toolkit GATE offers the possibility to accurately simulate scintigraphic images and absorbed doses in volumes of interest. The TestDose platform relies on GATE to reproduce precisely any imaging protocol and to provide reference dosimetry. For image generation, TestDose stores user’s imaging requirements and generates automatically command files used as input for GATE. Each compartment is simulated only once and the resulting output is weighted using pharmacokinetic data. Resulting compartment projections are aggregated to obtain the final image. For dosimetry computation, emission data are stored in the platform database and relevant GATE input files are generated for the virtual patient model and associated pharmacokinetics. Results: Two samples of software runs are given to demonstrate the potential of TestDose. A clinical imaging protocol for the Octreoscan™ therapeutical treatment was implemented using the 4D XCAT model. Whole-body “step and shoot” acquisitions at different times postinjection and one SPECT acquisition were generated within reasonable computation times. Based on the same Octreoscan™ kinetics, a dosimetry
Zhuang Guilin; Chen Wulin; Zheng Jun; Yu Huiyou; Wang Jianguo
2012-08-15
A series of lanthanide coordination polymers have been obtained through the hydrothermal reaction of N-(sulfoethyl) iminodiacetic acid (H{sub 3}SIDA) and Ln(NO{sub 3}){sub 3} (Ln=La, 1; Pr, 2; Nd, 3; Gd, 4). Crystal structure analysis exhibits that lanthanide ions affect the coordination number, bond length and dimension of compounds 1-4, which reveal that their structure diversity can be attributed to the effect of lanthanide contraction. Furthermore, the combination of magnetic measure with quantum Monte Carlo(QMC) studies exhibits that the coupling parameters between two adjacent Gd{sup 3+} ions for anti-anti and syn-anti carboxylate bridges are -1.0 Multiplication-Sign 10{sup -3} and -5.0 Multiplication-Sign 10{sup -3} cm{sup -1}, respectively, which reveals weak antiferromagnetic interaction in 4. - Graphical abstract: Four lanthanide coordination polymers with N-(sulfoethyl) iminodiacetic acid were obtained under hydrothermal condition and reveal the weak antiferromagnetic coupling between two Gd{sup 3+} ions by Quantum Monte Carlo studies. Highlights: Black-Right-Pointing-Pointer Four lanthanide coordination polymers of H{sub 3}SIDA ligand were obtained. Black-Right-Pointing-Pointer Lanthanide ions play an important role in their structural diversity. Black-Right-Pointing-Pointer Magnetic measure exhibits that compound 4 features antiferromagnetic property. Black-Right-Pointing-Pointer Quantum Monte Carlo studies reveal the coupling parameters of two Gd{sup 3+} ions.
Monte Carlo Particle Transport: Algorithm and Performance Overview
Gentile, N; Procassini, R; Scott, H
2005-06-02
Monte Carlo methods are frequently used for neutron and radiation transport. These methods have several advantages, such as relative ease of programming and dealing with complex meshes. Disadvantages include long run times and statistical noise. Monte Carlo photon transport calculations also often suffer from inaccuracies in matter temperature due to the lack of implicitness. In this paper we discuss the Monte Carlo algorithm as it is applied to neutron and photon transport, detail the differences between neutron and photon Monte Carlo, and give an overview of the ways the numerical method has been modified to deal with issues that arise in photon Monte Carlo simulations.
Status of Monte Carlo at Los Alamos
Thompson, W.L.; Cashwell, E.D.; Godfrey, T.N.K.; Schrandt, R.G.; Deutsch, O.L.; Booth, T.E.
1980-05-01
Four papers were presented by Group X-6 on April 22, 1980, at the Oak Ridge Radiation Shielding Information Center (RSIC) Seminar-Workshop on Theory and Applications of Monte Carlo Methods. These papers are combined into one report for convenience and because they are related to each other. The first paper (by Thompson and Cashwell) is a general survey about X-6 and MCNP and is an introduction to the other three papers. It can also serve as a resume of X-6. The second paper (by Godfrey) explains some of the details of geometry specification in MCNP. The third paper (by Cashwell and Schrandt) illustrates calculating flux at a point with MCNP; in particular, the once-more-collided flux estimator is demonstrated. Finally, the fourth paper (by Thompson, Deutsch, and Booth) is a tutorial on some variance-reduction techniques. It should be required for a fledging Monte Carlo practitioner.
Monte Carlo study of vibrational relaxation processes
NASA Technical Reports Server (NTRS)
Boyd, Iain D.
1991-01-01
A new model is proposed for the computation of vibrational nonequilibrium in the direct simulation Monte Carlo method (DSMC). This model permits level to level vibrational transitions for the first time in a Monte Carlo flowfield simulation. The model follows the Landau-Teller theory for a harmonic oscillator in which the rates of transition are related to an experimental correlation for the vibrational relaxation time. The usual method for simulating such processes in the DSMC technique applies a constant exchange probability to each collision and the vibrational energy is treated as a continuum. A comparison of these two methods is made for the flow of nitrogen over a wedge. Significant differences exist for the vibrational temperatures computed. These arise as a consequence of the incorrect application of a constant exchange probability in the old method. It is found that the numerical performances of the two vibrational relaxation models are equal.
Status of Monte Carlo at Los Alamos
Thompson, W.L.; Cashwell, E.D.
1980-01-01
At Los Alamos the early work of Fermi, von Neumann, and Ulam has been developed and supplemented by many followers, notably Cashwell and Everett, and the main product today is the continuous-energy, general-purpose, generalized-geometry, time-dependent, coupled neutron-photon transport code called MCNP. The Los Alamos Monte Carlo research and development effort is concentrated in Group X-6. MCNP treats an arbitrary three-dimensional configuration of arbitrary materials in geometric cells bounded by first- and second-degree surfaces and some fourth-degree surfaces (elliptical tori). Monte Carlo has evolved into perhaps the main method for radiation transport calculations at Los Alamos. MCNP is used in every technical division at the Laboratory by over 130 users about 600 times a month accounting for nearly 200 hours of CDC-7600 time.
Monte Carlo Methods in the Physical Sciences
Kalos, M H
2007-06-06
I will review the role that Monte Carlo methods play in the physical sciences. They are very widely used for a number of reasons: they permit the rapid and faithful transformation of a natural or model stochastic process into a computer code. They are powerful numerical methods for treating the many-dimensional problems that derive from important physical systems. Finally, many of the methods naturally permit the use of modern parallel computers in efficient ways. In the presentation, I will emphasize four aspects of the computations: whether or not the computation derives from a natural or model stochastic process; whether the system under study is highly idealized or realistic; whether the Monte Carlo methodology is straightforward or mathematically sophisticated; and finally, the scientific role of the computation.
Fission Matrix Capability for MCNP Monte Carlo
NASA Astrophysics Data System (ADS)
Brown, Forrest; Carney, Sean; Kiedrowski, Brian; Martin, William
2014-06-01
We describe recent experience and results from implementing a fission matrix capability into the MCNP Monte Carlo code. The fission matrix can be used to provide estimates of the fundamental mode fission distribution, the dominance ratio, the eigenvalue spectrum, and higher mode forward and adjoint eigenfunctions of the fission neutron source distribution. It can also be used to accelerate the convergence of the power method iterations and to provide basis functions for higher-order perturbation theory. The higher-mode fission sources can be used in MCNP to determine higher-mode forward fluxes and tallies, and work is underway to provide higher-mode adjoint-weighted fluxes and tallies. Past difficulties and limitations of the fission matrix approach are overcome with a new sparse representation of the matrix, permitting much larger and more accurate fission matrix representations. The new fission matrix capabilities provide a significant advance in the state-of-the-art for Monte Carlo criticality calculations.
Inhomogeneous Monte Carlo simulations of dermoscopic spectroscopy
NASA Astrophysics Data System (ADS)
Gareau, Daniel S.; Li, Ting; Jacques, Steven; Krueger, James
2012-03-01
Clinical skin-lesion diagnosis uses dermoscopy: 10X epiluminescence microscopy. Skin appearance ranges from black to white with shades of blue, red, gray and orange. Color is an important diagnostic criteria for diseases including melanoma. Melanin and blood content and distribution impact the diffuse spectral remittance (300-1000nm). Skin layers: immersion medium, stratum corneum, spinous epidermis, basal epidermis and dermis as well as laterally asymmetric features (eg. melanocytic invasion) were modeled in an inhomogeneous Monte Carlo model.
Monte Carlo simulation of Alaska wolf survival
NASA Astrophysics Data System (ADS)
Feingold, S. J.
1996-02-01
Alaskan wolves live in a harsh climate and are hunted intensively. Penna's biological aging code, using Monte Carlo methods, has been adapted to simulate wolf survival. It was run on the case in which hunting causes the disruption of wolves' social structure. Social disruption was shown to increase the number of deaths occurring at a given level of hunting. For high levels of social disruption, the population did not survive.
Monte Carlo Simulation of Plumes Spectral Emission
2005-06-07
Table 1 Calculatio n series phN , %ε Figure 1 105 11.0 2 2 106 4.9 3 3 107 0.6 5 The relative error ε was calculated with respect to the mean...is presented in Table 2. Table 2 Monte-Carlo Simulation of Plumes Spectral Emission 19 Calculatio n series phN , %ε Figure 1 5×103 0.475 6
Monte Carlo approach to Estrada index
NASA Astrophysics Data System (ADS)
Gutman, Ivan; Radenković, Slavko; Graovac, Ante; Plavšić, Dejan
2007-09-01
Let G be a graph on n vertices, and let λ1, λ2, …, λn be its eigenvalues. The Estrada index of G is a recently introduced molecular structure descriptor, defined as EE=∑i=1ne. Using a Monte Carlo approach, and treating the graph eigenvalues as random variables, we deduce approximate expressions for EE, in terms of the number of vertices and number of edges, of very high accuracy.
Monte Carlo simulation of Touschek effect.
Xiao, A.; Borland, M.; Accelerator Systems Division
2010-07-30
We present a Monte Carlo method implementation in the code elegant for simulating Touschek scattering effects in a linac beam. The local scattering rate and the distribution of scattered electrons can be obtained from the code either for a Gaussian-distributed beam or for a general beam whose distribution function is given. In addition, scattered electrons can be tracked through the beam line and the local beam-loss rate and beam halo information recorded.
Applications of Maxent to quantum Monte Carlo
Silver, R.N.; Sivia, D.S.; Gubernatis, J.E. ); Jarrell, M. . Dept. of Physics)
1990-01-01
We consider the application of maximum entropy methods to the analysis of data produced by computer simulations. The focus is the calculation of the dynamical properties of quantum many-body systems by Monte Carlo methods, which is termed the Analytical Continuation Problem.'' For the Anderson model of dilute magnetic impurities in metals, we obtain spectral functions and transport coefficients which obey Kondo Universality.'' 24 refs., 7 figs.
NASA Astrophysics Data System (ADS)
Quan, Guotao; Gong, Hui; Deng, Yong; Fu, Jianwei; Luo, Qingming
2011-02-01
High-speed fluorescence molecular tomography (FMT) reconstruction for 3-D heterogeneous media is still one of the most challenging problems in diffusive optical fluorescence imaging. In this paper, we propose a fast FMT reconstruction method that is based on Monte Carlo (MC) simulation and accelerated by a cluster of graphics processing units (GPUs). Based on the Message Passing Interface standard, we modified the MC code for fast FMT reconstruction, and different Green's functions representing the flux distribution in media are calculated simultaneously by different GPUs in the cluster. A load-balancing method was also developed to increase the computational efficiency. By applying the Fréchet derivative, a Jacobian matrix is formed to reconstruct the distribution of the fluorochromes using the calculated Green's functions. Phantom experiments have shown that only 10 min are required to get reconstruction results with a cluster of 6 GPUs, rather than 6 h with a cluster of multiple dual opteron CPU nodes. Because of the advantages of high accuracy and suitability for 3-D heterogeneity media with refractive-index-unmatched boundaries from the MC simulation, the GPU cluster-accelerated method provides a reliable approach to high-speed reconstruction for FMT imaging.
Shypailo, R J; Ellis, K J
2011-05-21
During construction of the whole body counter (WBC) at the Children's Nutrition Research Center (CNRC), efficiency calibration was needed to translate acquired counts of (40)K to actual grams of potassium for measurement of total body potassium (TBK) in a diverse subject population. The MCNP Monte Carlo n-particle simulation program was used to describe the WBC (54 detectors plus shielding), test individual detector counting response, and create a series of virtual anthropomorphic phantoms based on national reference anthropometric data. Each phantom included an outer layer of adipose tissue and an inner core of lean tissue. Phantoms were designed for both genders representing ages 3.5 to 18.5 years with body sizes from the 5th to the 95th percentile based on body weight. In addition, a spherical surface source surrounding the WBC was modeled in order to measure the effects of subject mass on room background interference. Individual detector measurements showed good agreement with the MCNP model. The background source model came close to agreement with empirical measurements, but showed a trend deviating from unity with increasing subject size. Results from the MCNP simulation of the CNRC WBC agreed well with empirical measurements using BOMAB phantoms. Individual detector efficiency corrections were used to improve the accuracy of the model. Nonlinear multiple regression efficiency calibration equations were derived for each gender. Room background correction is critical in improving the accuracy of the WBC calibration.
NASA Astrophysics Data System (ADS)
Chuang, Ching-Cheng; Chen, Chung-Ming; Lee, Chia-Yen; Tsai, Jui-che; Lu, Chih-Wei; Sun, Chia-Wei
2010-02-01
The scattering and absorption properties of human breast are very important for cancer diagnosis based on diffuse optical tomography (DOT). In this study, the dynamics of photon migration in three-dimensional human breast model with various source-detector separations is simulated based on a Monte Carlo algorithm. The three-dimensional human breast structure is obtained from in vivo MRI image. The breast model consists of skin, fatty tissue, glandular tissue, sternum and ribcage. The backscattered diffuse photons from each layer in breast are recorded by marking the deepest layer which every photon can reach. The experimental results indicate that the re-emitted photons contain more information from deep tissue regions with the source-detector separations because of the strong dependence to the resolution and sensitivity in DOT imaging. The geometric position of the source-detector separations were optimized in this study. The different sizes of breast tumor were modeled to analysis of optical image characterizations. Finally, the tumor images from different deep information were obtained with temporal profiles.
Quan, Guotao; Gong, Hui; Deng, Yong; Fu, Jianwei; Luo, Qingming
2011-02-01
High-speed fluorescence molecular tomography (FMT) reconstruction for 3-D heterogeneous media is still one of the most challenging problems in diffusive optical fluorescence imaging. In this paper, we propose a fast FMT reconstruction method that is based on Monte Carlo (MC) simulation and accelerated by a cluster of graphics processing units (GPUs). Based on the Message Passing Interface standard, we modified the MC code for fast FMT reconstruction, and different Green's functions representing the flux distribution in media are calculated simultaneously by different GPUs in the cluster. A load-balancing method was also developed to increase the computational efficiency. By applying the Fréchet derivative, a Jacobian matrix is formed to reconstruct the distribution of the fluorochromes using the calculated Green's functions. Phantom experiments have shown that only 10 min are required to get reconstruction results with a cluster of 6 GPUs, rather than 6 h with a cluster of multiple dual opteron CPU nodes. Because of the advantages of high accuracy and suitability for 3-D heterogeneity media with refractive-index-unmatched boundaries from the MC simulation, the GPU cluster-accelerated method provides a reliable approach to high-speed reconstruction for FMT imaging.
Stott-Miller, Marni; Heike, Carrie L.; Kratz, Mario; Starr, Jacqueline R.
2010-01-01
Summary Our objective was to evaluate whether infants born to obese or diabetic women are at higher risk of non-syndromic orofacial clefting. We conducted a population-based case–control study using Washington State birth certificate and hospitalisation data for the years 1987–2005. Cases were infants born with orofacial clefts (n = 2153) and controls infants without orofacial clefts (n = 18 070). The primary exposures were maternal obesity (body mass index ≥30) and diabetes (either pre-existing or gestational). We estimated adjusted odds ratios (ORs) to compare, for mothers of cases and controls, the proportions of obese vs. normal-weight women and diabetic vs. non-diabetic women. We additionally performed Monte Carlo-based simulation analysis to explore possible influences of biases. Obese women had a small increased risk of isolated orofacial clefts in their offspring compared with normal-body mass index women [adjusted OR 1.26; 95% confidence interval 1.03, 1.55]. Results were similar regardless of type of cleft. Bias analyses suggest that estimates may represent underlying ORs of stronger magnitude. Results for diabetic women were highly imprecise and inconsistent. We and others have observed weak associations of similar magnitude between maternal obesity and risk of nonsyndromic orofacial clefts. These results could be due to bias or residual confounding. However, it is also possible that these results represent a stronger underlying association. More precise exposure measurement could help distinguish between these two possibilities. PMID:20670231
NASA Astrophysics Data System (ADS)
Stamenkovic, Dragan D.; Popovic, Vladimir M.
2015-02-01
Warranty is a powerful marketing tool, but it always involves additional costs to the manufacturer. In order to reduce these costs and make use of warranty's marketing potential, the manufacturer needs to master the techniques for warranty cost prediction according to the reliability characteristics of the product. In this paper a combination free replacement and pro rata warranty policy is analysed as warranty model for one type of light bulbs. Since operating conditions have a great impact on product reliability, they need to be considered in such analysis. A neural network model is used to predict light bulb reliability characteristics based on the data from the tests of light bulbs in various operating conditions. Compared with a linear regression model used in the literature for similar tasks, the neural network model proved to be a more accurate method for such prediction. Reliability parameters obtained in this way are later used in Monte Carlo simulation for the prediction of times to failure needed for warranty cost calculation. The results of the analysis make possible for the manufacturer to choose the optimal warranty policy based on expected product operating conditions. In such a way, the manufacturer can lower the costs and increase the profit.
NASA Astrophysics Data System (ADS)
Shypailo, R. J.; Ellis, K. J.
2011-05-01
During construction of the whole body counter (WBC) at the Children's Nutrition Research Center (CNRC), efficiency calibration was needed to translate acquired counts of 40K to actual grams of potassium for measurement of total body potassium (TBK) in a diverse subject population. The MCNP Monte Carlo n-particle simulation program was used to describe the WBC (54 detectors plus shielding), test individual detector counting response, and create a series of virtual anthropomorphic phantoms based on national reference anthropometric data. Each phantom included an outer layer of adipose tissue and an inner core of lean tissue. Phantoms were designed for both genders representing ages 3.5 to 18.5 years with body sizes from the 5th to the 95th percentile based on body weight. In addition, a spherical surface source surrounding the WBC was modeled in order to measure the effects of subject mass on room background interference. Individual detector measurements showed good agreement with the MCNP model. The background source model came close to agreement with empirical measurements, but showed a trend deviating from unity with increasing subject size. Results from the MCNP simulation of the CNRC WBC agreed well with empirical measurements using BOMAB phantoms. Individual detector efficiency corrections were used to improve the accuracy of the model. Nonlinear multiple regression efficiency calibration equations were derived for each gender. Room background correction is critical in improving the accuracy of the WBC calibration.
Ye, Hong-Zhou; Sun, Chong; Jiang, Hong
2015-03-14
Materials with spin-crossover (SCO) properties hold great potential in information storage and therefore have received a lot of concerns in recent decades. The hysteresis phenomena accompanying SCO are attributed to the intermolecular cooperativity whose underlying mechanism may have a vibronic origin. In this work, a new vibronic Ising-like model in which the elastic coupling between SCO centers is included by considering harmonic stretching and bending (SAB) interactions is proposed and solved by Monte Carlo (MC) simulations. The key parameters in the new model, k1 and k2, corresponding to the elastic constant of the stretching and bending mode, respectively, can be directly related to the macroscopic bulk and shear modulus of the material of study, which can be readily estimated either based on experimental measurements or first-principles calculations. Using realistic parameters estimated based on density-functional theory calculations of a specific polymeric coordination SCO compound, [Fe(pz)Pt(CN)4]·2H2O (pz = pyrazine), temperature-induced hysteresis and pressure effects on SCO phenomena are simulated successfully. Our MC simulations shed light on the role of the vibronic couplings in the thermal hysteresis of SCO systems, and also point out the limitations of highly simplified Ising-like models for quantitative description of real SCO systems, which will be of great value for the development of more realistic SCO models.
NASA Astrophysics Data System (ADS)
Gomez-Cadenas, J. J.; Benlloch-Rodríguez, J. M.; Ferrario, P.; Monrabal, F.; Rodríguez, J.; Toledo, J. F.
2016-09-01
The measurement of the time of flight of the two 511 keV gammas recorded in coincidence in a PET scanner provides an effective way of reducing the random background and therefore increases the scanner sensitivity, provided that the coincidence resolving time (CRT) of the gammas is sufficiently good. The best commercial PET-TOF system today (based in LYSO crystals and digital SiPMs), is the VEREOS of Philips, boasting a CRT of 316 ps (FWHM). In this paper we present a Monte Carlo investigation of the CRT performance of a PET scanner exploiting the scintillating properties of liquid xenon. We find that an excellent CRT of 70 ps (depending on the PDE of the sensor) can be obtained if the scanner is instrumented with silicon photomultipliers (SiPMs) sensitive to the ultraviolet light emitted by xenon. Alternatively, a CRT of 160 ps can be obtained instrumenting the scanner with (much cheaper) blue-sensitive SiPMs coated with a suitable wavelength shifter. These results show the excellent time of flight capabilities of a PET device based in liquid xenon.
Paudel, Moti R; Kim, Anthony; Sarfehnia, Arman; Ahmad, Sayed B; Beachey, David J; Sahgal, Arjun; Keller, Brian M
2016-11-08
A new GPU-based Monte Carlo dose calculation algorithm (GPUMCD), devel-oped by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios - tumor-in-lung, lung, and bone-in-tissue - was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correc-tion. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for 2 × 2 cm2, 5 × 5 cm2, and 10 × 10 cm2 field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within 2%/2 mm of film measurements and within 1% of ion chamber measurements. For the tumor-in-lung phantom, the calculated doses were within 2.5%/2.5 mm of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within 3%/3 mm of film measurements, except for the 2 × 2 cm2 field size where the CCC algorithm underestimated the depth dose by ~ 5% in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within 2%/2 mm of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly.
Paudel, Moti R; Kim, Anthony; Sarfehnia, Arman; Ahmad, Sayed B; Beachey, David J; Sahgal, Arjun; Keller, Brian M
2016-11-01
A new GPU-based Monte Carlo dose calculation algorithm (GPUMCD), developed by the vendor Elekta for the Monaco treatment planning system (TPS), is capable of modeling dose for both a standard linear accelerator and an Elekta MRI linear accelerator. We have experimentally evaluated this algorithm for a standard Elekta Agility linear accelerator. A beam model was developed in the Monaco TPS (research version 5.09.06) using the commissioned beam data for a 6 MV Agility linac. A heterogeneous phantom representing several scenarios - tumor-in-lung, lung, and bone-in-tissue - was designed and built. Dose calculations in Monaco were done using both the current clinical Monte Carlo algorithm, XVMC, and the new GPUMCD algorithm. Dose calculations in a Pinnacle TPS were also produced using the collapsed cone convolution (CCC) algorithm with heterogeneity correction. Calculations were compared with the measured doses using an ionization chamber (A1SL) and Gafchromic EBT3 films for 2×2 cm2,5×5 cm2, and 10×2 cm2 field sizes. The percentage depth doses (PDDs) calculated by XVMC and GPUMCD in a homogeneous solid water phantom were within 2%/2 mm of film measurements and within 1% of ion chamber measurements. For the tumor-in-lung phantom, the calculated doses were within 2.5%/2.5 mm of film measurements for GPUMCD. For the lung phantom, doses calculated by all of the algorithms were within 3%/3 mm of film measurements, except for the 2×2 cm2 field size where the CCC algorithm underestimated the depth dose by ∼5% in a larger extent of the lung region. For the bone phantom, all of the algorithms were equivalent and calculated dose to within 2%/2 mm of film measurements, except at the interfaces. Both GPUMCD and XVMC showed interface effects, which were more pronounced for GPUMCD and were comparable to film measurements, whereas the CCC algorithm showed these effects poorly. PACS number(s): 87.53.Bn, 87.55.dh, 87.55.km. © 2016 The Authors.
Path Integral Monte Carlo Methods for Fermions
NASA Astrophysics Data System (ADS)
Ethan, Ethan; Dubois, Jonathan; Ceperley, David
2014-03-01
In general, Quantum Monte Carlo methods suffer from a sign problem when simulating fermionic systems. This causes the efficiency of a simulation to decrease exponentially with the number of particles and inverse temperature. To circumvent this issue, a nodal constraint is often implemented, restricting the Monte Carlo procedure from sampling paths that cause the many-body density matrix to change sign. Unfortunately, this high-dimensional nodal surface is not a priori known unless the system is exactly solvable, resulting in uncontrolled errors. We will discuss two possible routes to extend the applicability of finite-temperatue path integral Monte Carlo. First we extend the regime where signful simulations are possible through a novel permutation sampling scheme. Afterwards, we discuss a method to variationally improve the nodal surface by minimizing a free energy during simulation. Applications of these methods will include both free and interacting electron gases, concluding with discussion concerning extension to inhomogeneous systems. Support from DOE DE-FG52-09NA29456, DE-AC52-07NA27344, LLNL LDRD 10- ERD-058, and the Lawrence Scholar program.
Numerical reproducibility for implicit Monte Carlo simulations
Cleveland, M.; Brunner, T.; Gentile, N.
2013-07-01
We describe and compare different approaches for achieving numerical reproducibility in photon Monte Carlo simulations. Reproducibility is desirable for code verification, testing, and debugging. Parallelism creates a unique problem for achieving reproducibility in Monte Carlo simulations because it changes the order in which values are summed. This is a numerical problem because double precision arithmetic is not associative. In [1], a way of eliminating this roundoff error using integer tallies was described. This approach successfully achieves reproducibility at the cost of lost accuracy by rounding double precision numbers to fewer significant digits. This integer approach, and other extended reproducibility techniques, are described and compared in this work. Increased precision alone is not enough to ensure reproducibility of photon Monte Carlo simulations. A non-arbitrary precision approaches required a varying degree of rounding to achieve reproducibility. For the problems investigated in this work double precision global accuracy was achievable by using 100 bits of precision or greater on all unordered sums which where subsequently rounded to double precision at the end of every time-step. (authors)
A Monte Carlo Approach for Adaptive Testing with Content Constraints
ERIC Educational Resources Information Center
Belov, Dmitry I.; Armstrong, Ronald D.; Weissman, Alexander
2008-01-01
This article presents a new algorithm for computerized adaptive testing (CAT) when content constraints are present. The algorithm is based on shadow CAT methodology to meet content constraints but applies Monte Carlo methods and provides the following advantages over shadow CAT: (a) lower maximum item exposure rates, (b) higher utilization of the…
An Overview of the Monte Carlo Methods, Codes, & Applications Group
Trahan, Travis John
2016-08-30
This report sketches the work of the Group to deliver first-principle Monte Carlo methods, production quality codes, and radiation transport-based computational and experimental assessments using the codes MCNP and MCATK for such applications as criticality safety, non-proliferation, nuclear energy, nuclear threat reduction and response, radiation detection and measurement, radiation health protection, and stockpile stewardship.
Bayesian Monte Carlo Method for Nuclear Data Evaluation
Koning, A.J.
2015-01-15
A Bayesian Monte Carlo method is outlined which allows a systematic evaluation of nuclear reactions using TALYS. The result will be either an EXFOR-weighted covariance matrix or a collection of random files, each accompanied by an experiment based weight.
Monte Carlo study of the atmospheric spread function
NASA Technical Reports Server (NTRS)
Pearce, W. A.
1986-01-01
Monte Carlo radiative transfer simulations are used to study the atmospheric spread function appropriate to satellite-based sensing of the earth's surface. The parameters which are explored include the nadir angle of view, the size distribution of the atmospheric aerosol, and the aerosol vertical profile.
Determining MTF of digital detector system with Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Jeong, Eun Seon; Lee, Hyung Won; Nam, Sang Hee
2005-04-01
We have designed a detector based on a-Se(amorphous Selenium) and done simulation the detector with Monte Carlo method. We will apply the cascaded linear system theory to determine the MTF for whole detector system. For direct comparison with experiment, we have simulated 139um pixel pitch and used simulated X-ray tube spectrum.
Monte Carlo Production Management at CMS
NASA Astrophysics Data System (ADS)
Boudoul, G.; Franzoni, G.; Norkus, A.; Pol, A.; Srimanobhas, P.; Vlimant, J.-R.
2015-12-01
The analysis of the LHC data at the Compact Muon Solenoid (CMS) experiment requires the production of a large number of simulated events. During the RunI of LHC (20102012), CMS has produced over 12 Billion simulated events, organized in approximately sixty different campaigns each emulating specific detector conditions and LHC running conditions (pile up). In order to aggregate the information needed for the configuration and prioritization of the events production, assure the book-keeping of all the processing requests placed by the physics analysis groups, and to interface with the CMS production infrastructure, the web- based service Monte Carlo Management (McM) has been developed and put in production in 2013. McM is based on recent server infrastructure technology (CherryPy + AngularJS) and relies on a CouchDB database back-end. This contribution covers the one and half year of operational experience managing samples of simulated events for CMS, the evolution of its functionalities and the extension of its capability to monitor the status and advancement of the events production.
NASA Astrophysics Data System (ADS)
Saghamanesh, S.; Aghamiri, S. M.; Kamali-Asl, A.; Yashiro, W.
2017-09-01
An important challenge in real-world biomedical applications of x-ray phase contrast imaging (XPCI) techniques is the efficient use of the photon flux generated by an incoherent and polychromatic x-ray source. This efficiency can directly influence dose and exposure time and ideally should not affect the superior contrast and sensitivity of XPCI. In this paper, we present a quantitative evaluation of the photon detection efficiency of two laboratory-based XPCI methods, grating interferometry (GI) and coded-aperture (CA). We adopt a Monte Carlo approach to simulate existing prototypes of those systems, tailored for mammography applications. Our simulations were validated by means of a simple experiment performed on a CA XPCI system. Our results show that the fraction of detected photons in the standard energy range of mammography are about 1.4% and 10% for the GI and CA techniques, respectively. The simulations indicate that the design of the optical components plays an important role in the higher efficiency of CA compared to the GI method. It is shown that the use of lower absorbing materials as the substrates for GI gratings can improve its flux efficiency by up to four times. Along similar lines, we also show that an optimized and compact configuration of GI could lead to a 3.5 times higher fraction of detected counts compared to a standard and non-optimised GI implementation.
Veselinović, Aleksandar M; Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M
2014-01-01
Monte Carlo method has been used as a computational tool for building QSAR models for the reactivation of sarin inhibited acetylcholinesterase (AChE) by quaternary pyridinium oximes. Simplified molecular input line entry system (SMILES) together with hydrogen-suppressed graph (HSG) was used to represent molecular structure. Total number of considered oximes was 46 and activity was defined as logarithm of the AChE reactivation percentage by oximes with concentration of 0.001 M. One-variable models have been calculated with CORAL software for one data split into training, calibration and test set. Computational experiments indicated that this approach can satisfactorily predict the desired endpoint. Best QSAR model had the following statistical parameters: for training set r2=0.7096, s=0.177, MAE=0.148; calibration set: r2=0.6759, s=0.330, MAE=0.271 and test set: r2=0.8620, s=0.182, MAE=0.150. Structural indicators (SMILES based molecular fragments) for the increase and the decrease of the stated activity are defined. Using defined structural alerts computer aided design of new oxime derivatives with desired activity is presented.
Veselinović, Aleksandar M; Veselinović, Jovana B; Toropov, Andrey A; Toropova, Alla P; Nikolić, Goran M
2014-11-26
For three random splits, one-variable models of oximes reactivation of sarin inhibited acetylcholinesterase (logarithm of the AChE reactivation percentage by oximes with concentration of 0.001 M) have been calculated with CORAL software. The total number of considered oximes was 42. Simplified molecular input line entry system (SMILES) and hydrogen-suppressed graph (HSG) are used to represent the molecular structure. Using CORAL software by means of the calculation with Monte Carlo optimization of the so called correlation weights for the molecular fragments, optimal SMILES-based descriptors were defined, which are correlated with an endpoint for the training set. The predictability of these descriptors for an external test are estimated. In this study hybrid representation HSG together with SMILES was used. The "classic" scheme (i.e. split data into the training set and test set) of building up quantitative structure-activity relationships was employed. Computational experiments indicated that this approach can satisfactorily predict the desired endpoint. Best model had following statistical characteristics n=32, r2= 0.6012, s= 0.279, F= 45 for training and n=10, r2= 0.9301, s= 0.076, Rm2=0.9206 for test set.
NASA Astrophysics Data System (ADS)
He, Xin; Caffo, Brian S.; Frey, Eric C.
2007-03-01
The ideal observer (IO) employs complete knowledge of the available data statistics and sets an upper limit on the observer performance on a binary classification task. Kupinski proposed an IO estimation method using Markov chain Monte Carlo (MCMC) techniques. In principle, this method can be generalized to any parameterized phantoms and simulated imaging systems. In practice, however, it can be computationally burdensome, because it requires sampling the object distribution and simulating the imaging process a large number of times during the MCMC estimation process. In this work we propose methods that allow application of MCMC techniques to cardiac SPECT imaging IO estimation using a parameterized torso phantom and an accurate analytical projection algorithm that models the SPECT image formation process. To accelerate the imaging simulation process and thus enable the MCMC IO estimation, we used a phantom model with discretized anatomical parameters and continuous uptake parameters. The imaging process simulation was modeled by pre-computing projections for each organ in the finite number of discretely-parameterized anatomic models and taking linear combinations of the organ projections based on sampling of the continuous organ uptake parameters. The proposed method greatly reduces the computational burden and makes MCMC IO estimation for cardiac SPECT imaging possible.
Babilas, Rafał; Łukowiec, Dariusz; Temleitner, Laszlo
2017-01-01
The structure of a multicomponent metallic glass, Mg65Cu20Y10Ni5, was investigated by the combined methods of neutron diffraction (ND), reverse Monte Carlo modeling (RMC) and high-resolution transmission electron microscopy (HRTEM). The RMC method, based on the results of ND measurements, was used to develop a realistic structure model of a quaternary alloy in a glassy state. The calculated model consists of a random packing structure of atoms in which some ordered regions can be indicated. The amorphous structure was also described by peak values of partial pair correlation functions and coordination numbers, which illustrated some types of cluster packing. The N = 9 clusters correspond to the tri-capped trigonal prisms, which are one of Bernal's canonical clusters, and atomic clusters with N = 6 and N = 12 are suitable for octahedral and icosahedral atomic configurations. The nanocrystalline character of the alloy after annealing was also studied by HRTEM. The selected HRTEM images of the nanocrystalline regions were also processed by inverse Fourier transform analysis. The high-angle annular dark-ﬁeld (HAADF) technique was used to determine phase separation in the studied glass after heat treatment. The HAADF mode allows for the observation of randomly distributed, dark contrast regions of about 4-6 nm. The interplanar spacing identified for the orthorhombic Mg2Cu crystalline phase is similar to the value of the first coordination shell radius from the short-range order.
Czarnecki, D; Voigts-Rhetz, P von; Shishechian, D Uchimura; Zink, K
2015-06-15
Purpose: Developing a fast and accurate calculation model to reconstruct the applied photon fluence from an external photon radiation therapy treatment based on an image recorded by an electronic portal image device (EPID). Methods: To reconstruct the initial photon fluence the 2D EPID image was corrected for scatter from the patient/phantom and EPID to generate the transmitted primary photon fluence. This was done by an iterative deconvolution using precalculated point spread functions (PSF). The transmitted primary photon fluence was then backprojected through the patient/phantom geometry considering linear attenuation to receive the initial photon fluence applied for the treatment.The calculation model was verified using Monte Carlo simulations performed with the EGSnrc code system. EPID images were produced by calculating the dose deposition in the EPID from a 6 MV photon beam irradiating a water phantom with air and bone inhomogeneities and the ICRP anthropomorphic voxel phantom. Results: The initial photon fluence was reconstructed using a single PSF and position dependent PSFs which depend on the radiological thickness of the irradiated object. Appling position dependent point spread functions the mean uncertainty of the reconstructed initial photon fluence could be reduced from 1.13 % to 0.13 %. Conclusion: This study presents a calculation model for fluence reconstruction from EPID images. The{sup Result} show a clear advantage when position dependent PSF are used for the iterative reconstruction. The basic work of a reconstruction method was established and further evaluations must be made in an experimental study.
Łukowiec, Dariusz; Temleitner, Laszlo
2017-01-01
The structure of a multicomponent metallic glass, Mg65Cu20Y10Ni5, was investigated by the combined methods of neutron diffraction (ND), reverse Monte Carlo modeling (RMC) and high-resolution transmission electron microscopy (HRTEM). The RMC method, based on the results of ND measurements, was used to develop a realistic structure model of a quaternary alloy in a glassy state. The calculated model consists of a random packing structure of atoms in which some ordered regions can be indicated. The amorphous structure was also described by peak values of partial pair correlation functions and coordination numbers, which illustrated some types of cluster packing. The N = 9 clusters correspond to the tri-capped trigonal prisms, which are one of Bernal’s canonical clusters, and atomic clusters with N = 6 and N = 12 are suitable for octahedral and icosahedral atomic configurations. The nanocrystalline character of the alloy after annealing was also studied by HRTEM. The selected HRTEM images of the nanocrystalline regions were also processed by inverse Fourier transform analysis. The high-angle annular dark-ﬁeld (HAADF) technique was used to determine phase separation in the studied glass after heat treatment. The HAADF mode allows for the observation of randomly distributed, dark contrast regions of about 4–6 nm. The interplanar spacing identified for the orthorhombic Mg2Cu crystalline phase is similar to the value of the first coordination shell radius from the short-range order. PMID:28685118
NASA Astrophysics Data System (ADS)
Gallis, M. A.; Torczynski, J. R.
2012-01-01
The direct simulation Monte Carlo (DSMC) method of Bird is used to develop simple closed-form expressions for the mass flow rate and the pressure profile for the steady isothermal flow of an ideal gas through a microscale tube connecting two infinite reservoirs at different pressures but at the temperature of the tube wall. Gas molecules reflect from the tube wall according to the Maxwell model (a linear combination of specular and diffuse reflections at the wall temperature) with a unity or sub-unity value of the accommodation coefficient (the probability that molecules reflect diffusely from the wall). The DSMC-based expressions have four parameters. Two parameters are specified so that the mass flow rate reduces to the known expression in the free-molecular regime. One parameter was previously determined by comparison to DSMC simulations in the slip regime. The remaining parameter is determined by comparison to DSMC simulations for pressures spanning the transition regime with several values of the accommodation coefficient. The expressions for the mass flow rate and the pressure profile agree well with the DSMC simulations (rms and maximum differences of 2% and 5% for all cases examined), with other more complicated expressions and with recent experiments involving microscale tubes and channels for all flow regimes.
3D polymer gel dosimetry and Geant4 Monte Carlo characterization of novel needle based X-ray source
NASA Astrophysics Data System (ADS)
Liu, Y.; Sozontov, E.; Safronov, V.; Gutman, G.; Strumban, E.; Jiang, Q.; Li, S.
2010-11-01
In the recent years, there have been a few attempts to develop a low energy x-ray radiation sources alternative to conventional radioisotopes used in brachytherapy. So far, all efforts have been centered around the intent to design an interstitial miniaturized x-ray tube. Though direct irradiation of tumors looks very promising, the known insertable miniature x-ray tubes have many limitations: (a) difficulties with focusing and steering the electron beam to the target; (b)necessity to cool the target to increase x-ray production efficiency; (c)impracticability to reduce the diameter of the miniaturized x-ray tube below 4mm (the requirement to decrease the diameter of the x-ray tube and the need to have a cooling system for the target have are mutually exclusive); (c) significant limitations in changing shape and energy of the emitted radiation. The specific aim of this study is to demonstrate the feasibility of a new concept for an insertable low-energy needle x-ray device based on simulation with Geant4 Monte Carlo code and to measure the dose rate distribution for low energy (17.5 keV) x-ray radiation with the 3D polymer gel dosimetry.
Saghamanesh, S; Aghamiri, S M; Kamali-Asl, A; Yashiro, W
2017-09-01
An important challenge in real-world biomedical applications of x-ray phase contrast imaging (XPCI) techniques is the efficient use of the photon flux generated by an incoherent and polychromatic x-ray source. This efficiency can directly influence dose and exposure time and ideally should not affect the superior contrast and sensitivity of XPCI. In this paper, we present a quantitative evaluation of the photon detection efficiency of two laboratory-based XPCI methods, grating interferometry (GI) and coded-aperture (CA). We adopt a Monte Carlo approach to simulate existing prototypes of those systems, tailored for mammography applications. Our simulations were validated by means of a simple experiment performed on a CA XPCI system. Our results show that the fraction of detected photons in the standard energy range of mammography are about 1.4% and 10% for the GI and CA techniques, respectively. The simulations indicate that the design of the optical components plays an important role in the higher efficiency of CA compared to the GI method. It is shown that the use of lower absorbing materials as the substrates for GI gratings can improve its flux efficiency by up to four times. Along similar lines, we also show that an optimized and compact configuration of GI could lead to a 3.5 times higher fraction of detected counts compared to a standard and non-optimised GI implementation.
NASA Astrophysics Data System (ADS)
Demidov, A.; Eschlböck-Fuchs, S.; Kazakov, A. Ya.; Gornushkin, I. B.; Kolmhofer, P. J.; Pedarnig, J. D.; Huber, N.; Heitz, J.; Schmid, T.; Rössler, R.; Panne, U.
2016-11-01
The improved Monte-Carlo (MC) method for standard-less analysis in laser induced breakdown spectroscopy (LIBS) is presented. Concentrations in MC LIBS are found by fitting model-generated synthetic spectra to experimental spectra. The current version of MC LIBS is based on the graphic processing unit (GPU) computation and reduces the analysis time down to several seconds per spectrum/sample. The previous version of MC LIBS which was based on the central processing unit (CPU) computation requested unacceptably long analysis times of 10's minutes per spectrum/sample. The reduction of the computational time is achieved through the massively parallel computing on the GPU which embeds thousands of co-processors. It is shown that the number of iterations on the GPU exceeds that on the CPU by a factor > 1000 for the 5-dimentional parameter space and yet requires > 10-fold shorter computational time. The improved GPU-MC LIBS outperforms the CPU-MS LIBS in terms of accuracy, precision, and analysis time. The performance is tested on LIBS-spectra obtained from pelletized powders of metal oxides consisting of CaO, Fe2O3, MgO, and TiO2 that simulated by-products of steel industry, steel slags. It is demonstrated that GPU-based MC LIBS is capable of rapid multi-element analysis with relative error between 1 and 10's percent that is sufficient for industrial applications (e.g. steel slag analysis). The results of the improved GPU-based MC LIBS are positively compared to that of the CPU-based MC LIBS as well as to the results of the standard calibration-free (CF) LIBS based on the Boltzmann plot method.
Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun
2017-01-07
Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6 ± 15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.
NASA Astrophysics Data System (ADS)
Li, Yongbao; Tian, Zhen; Song, Ting; Wu, Zhaoxia; Liu, Yaqiang; Jiang, Steve; Jia, Xun
2017-01-01
Monte Carlo (MC)-based spot dose calculation is highly desired for inverse treatment planning in proton therapy because of its accuracy. Recent studies on biological optimization have also indicated the use of MC methods to compute relevant quantities of interest, e.g. linear energy transfer. Although GPU-based MC engines have been developed to address inverse optimization problems, their efficiency still needs to be improved. Also, the use of a large number of GPUs in MC calculation is not favorable for clinical applications. The previously proposed adaptive particle sampling (APS) method can improve the efficiency of MC-based inverse optimization by using the computationally expensive MC simulation more effectively. This method is more efficient than the conventional approach that performs spot dose calculation and optimization in two sequential steps. In this paper, we propose a computational library to perform MC-based spot dose calculation on GPU with the APS scheme. The implemented APS method performs a non-uniform sampling of the particles from pencil beam spots during the optimization process, favoring those from the high intensity spots. The library also conducts two computationally intensive matrix-vector operations frequently used when solving an optimization problem. This library design allows a streamlined integration of the MC-based spot dose calculation into an existing proton therapy inverse planning process. We tested the developed library in a typical inverse optimization system with four patient cases. The library achieved the targeted functions by supporting inverse planning in various proton therapy schemes, e.g. single field uniform dose, 3D intensity modulated proton therapy, and distal edge tracking. The efficiency was 41.6 ± 15.3% higher than the use of a GPU-based MC package in a conventional calculation scheme. The total computation time ranged between 2 and 50 min on a single GPU card depending on the problem size.
Commensurabilities between ETNOs: a Monte Carlo survey
NASA Astrophysics Data System (ADS)
de la Fuente Marcos, C.; de la Fuente Marcos, R.
2016-07-01
Many asteroids in the main and trans-Neptunian belts are trapped in mean motion resonances with Jupiter and Neptune, respectively. As a side effect, they experience accidental commensurabilities among themselves. These commensurabilities define characteristic patterns that can be used to trace the source of the observed resonant behaviour. Here, we explore systematically the existence of commensurabilities between the known ETNOs using their heliocentric and barycentric semimajor axes, their uncertainties, and Monte Carlo techniques. We find that the commensurability patterns present in the known ETNO population resemble those found in the main and trans-Neptunian belts. Although based on small number statistics, such patterns can only be properly explained if most, if not all, of the known ETNOs are subjected to the resonant gravitational perturbations of yet undetected trans-Plutonian planets. We show explicitly that some of the statistically significant commensurabilities are compatible with the Planet Nine hypothesis; in particular, a number of objects may be trapped in the 5:3 and 3:1 mean motion resonances with a putative Planet Nine with semimajor axis ˜700 au.
A continuation multilevel Monte Carlo algorithm
Collier, Nathan; Haji-Ali, Abdul-Lateef; Nobile, Fabio; von Schwerin, Erik; Tempone, Raúl
2014-09-05
Here, we propose a novel Continuation Multi Level Monte Carlo (CMLMC) algorithm for weak approximation of stochastic models. The CMLMC algorithm solves the given approximation problem for a sequence of decreasing tolerances, ending when the required error tolerance is satisfied. CMLMC assumes discretization hierarchies that are defined a priori for each level and are geometrically refined across levels. Moreover, the actual choice of computational work across levels is based on parametric models for the average cost per sample and the corresponding variance and weak error. These parameters are calibrated using Bayesian estimation, taking particular notice of the deepest levels of the discretization hierarchy, where only few realizations are available to produce the estimates. The resulting CMLMC estimator exhibits a non-trivial splitting between bias and statistical contributions. We also show the asymptotic normality of the statistical error in the MLMC estimator and justify in this way our error estimate that allows prescribing both required accuracy and confidence in the final result. Our numerical results substantiate the above results and illustrate the corresponding computational savings in examples that are described in terms of differential equations either driven by random measures or with random coefficients.
Quantum Monte Carlo Study of Surface Energy
NASA Astrophysics Data System (ADS)
Hsing, Cheng-Rong; Wei, Ching-Ming
2012-02-01
The accuracy of Density Functional Theory (DFT) is based on the exchange-correlation approximation used and needs to be checked by highly accurate quantum many-body approaches. We have performed calculations of the surface energies using the state-of-the-art diffusion quantum Monte Carlo (QMC) method to examine the accuracy of LDA and GGA (PBE) functionals in the study of surface energy. The systems studied include NaCl(100), MgO(100), CaO(100), TiO2(110), Si(100)-(2x2), C(100)-(2x2), and Ge(100)-(2x2) surfaces. Our results indicate that (i) the surface energy by DMC is always larger than the surface energy by LDA; and (ii) the surface energy by LDA is always larger than the surface energy by GGA. For the surface energies of NaCl(100) and MgO(100), the DMC results reproduce the experimental measured values accurately. To conclude, when compared the surface energies obtained by DFT and DMC, the results predicted by DFT using either LDA or GGA functional are underestimated.
Quantum Monte Carlo studies of surface adsorptions
NASA Astrophysics Data System (ADS)
Wei, Ching-Ming; Hsing, Cheng-Rong
2012-02-01
Surface adsorption is the first step to the study of surface catalytic reaction. The most common used tool is the Density Functional Theory (DFT) based on exchange-correlation approximations and the accuracy usually has not been checked carefully by highly accurate quantum many-body approaches. We have performed calculations of the surface adsorptions using the state-of-the-art diffusion quantum Monte Carlo (QMC) method to examine the accuracy of LDA and GGA (PBE) functionals in the study of surface adsorptions. The systems examined include the H2O and OH adsorptions on various types of surfaces such as NaCl(100), MgO(100), TiO2(110), graphene, Si(100)-(2x2) and Al(100). By comparing GGA (PBE) results with DMC, our results indicate that (i) for the H2O adsorption, PBE predicts the correct adsorption energies; (ii) for the OH adsorption, PBE has predicted a large over-binding effect except on graphene and Si(100) surfaces. This fact indicates that one needs to be cautious when using DFT to study the surface adsorptions of OH free radical.
Automated Monte Carlo biasing for photon-generated electrons near surfaces.
Franke, Brian Claude; Crawford, Martin James; Kensek, Ronald Patrick
2009-09-01
This report describes efforts to automate the biasing of coupled electron-photon Monte Carlo particle transport calculations. The approach was based on weight-windows biasing. Weight-window settings were determined using adjoint-flux Monte Carlo calculations. A variety of algorithms were investigated for adaptivity of the Monte Carlo tallies. Tree data structures were used to investigate spatial partitioning. Functional-expansion tallies were used to investigate higher-order spatial representations.
Li, Y; Tian, Z; Jiang, S; Jia, X; Song, T; Wu, Z; Liu, Y
2015-06-15
Purpose: Intensity-modulated proton therapy (IMPT) is increasingly used in proton therapy. For IMPT optimization, Monte Carlo (MC) is desired for spots dose calculations because of its high accuracy, especially in cases with a high level of heterogeneity. It is also preferred in biological optimization problems due to the capability of computing quantities related to biological effects. However, MC simulation is typically too slow to be used for this purpose. Although GPU-based MC engines have become available, the achieved efficiency is still not ideal. The purpose of this work is to develop a new optimization scheme to include GPU-based MC into IMPT. Methods: A conventional approach using MC in IMPT simply calls the MC dose engine repeatedly for each spot dose calculations. However, this is not the optimal approach, because of the unnecessary computations on some spots that turned out to have very small weights after solving the optimization problem. GPU-memory writing conflict occurring at a small beam size also reduces computational efficiency. To solve these problems, we developed a new framework that iteratively performs MC dose calculations and plan optimizations. At each dose calculation step, the particles were sampled from different spots altogether with Metropolis algorithm, such that the particle number is proportional to the latest optimized spot intensity. Simultaneously transporting particles from multiple spots also mitigated the memory writing conflict problem. Results: We have validated the proposed MC-based optimization schemes in one prostate case. The total computation time of our method was ∼5–6 min on one NVIDIA GPU card, including both spot dose calculation and plan optimization, whereas a conventional method naively using the same GPU-based MC engine were ∼3 times slower. Conclusion: A fast GPU-based MC dose calculation method along with a novel optimization workflow is developed. The high efficiency makes it attractive for clinical
Ahmad, I.; Back, B.B.; Betts, R.R.
1995-08-01
An essential component in the assessment of the significance of the results from APEX is a demonstrated understanding of the acceptance and response of the apparatus. This requires detailed simulations which can be compared to the results of various source and in-beam measurements. These simulations were carried out using the computer codes EGS and GEANT, both specifically designed for this purpose. As far as is possible, all details of the geometry of APEX were included. We compared the results of these simulations with measurements using electron conversion sources, positron sources and pair sources. The overall agreement is quite acceptable and some of the details are still being worked on. The simulation codes were also used to compare the results of measurements of in-beam positron and conversion electrons with expectations based on known physics or other methods. Again, satisfactory agreement is achieved. We are currently working on the simulation of various pair-producing scenarios such as the decay of a neutral object in the mass range 1.5-2.0 MeV and also the emission of internal pairs from nuclear transitions in the colliding ions. These results are essential input to the final results from APEX on cross section limits for various, previously proposed, sharp-line producing scenarios.
Díez, A; Largo, J; Solana, J R
2006-08-21
Computer simulations have been performed for fluids with van der Waals potential, that is, hard spheres with attractive inverse power tails, to determine the equation of state and the excess energy. On the other hand, the first- and second-order perturbative contributions to the energy and the zero- and first-order perturbative contributions to the compressibility factor have been determined too from Monte Carlo simulations performed on the reference hard-sphere system. The aim was to test the reliability of this "exact" perturbation theory. It has been found that the results obtained from the Monte Carlo perturbation theory for these two thermodynamic properties agree well with the direct Monte Carlo simulations. Moreover, it has been found that results from the Barker-Henderson [J. Chem. Phys. 47, 2856 (1967)] perturbation theory are in good agreement with those from the exact perturbation theory.
Wan Chan Tseung, H; Ma, J; Ma, D; Beltran, C
2015-06-15
Purpose: To demonstrate the feasibility of fast Monte Carlo (MC) based biological planning for the treatment of thyroid tumors in spot-scanning proton therapy. Methods: Recently, we developed a fast and accurate GPU-based MC simulation of proton transport that was benchmarked against Geant4.9.6 and used as the dose calculation engine in a clinically-applicable GPU-accelerated IMPT optimizer. Besides dose, it can simultaneously score the dose-averaged LET (LETd), which makes fast biological dose (BD) estimates possible. To convert from LETd to BD, we used a linear relation based on cellular irradiation data. Given a thyroid patient with a 93cc tumor volume, we created a 2-field IMPT plan in Eclipse (Varian Medical Systems). This plan was re-calculated with our MC to obtain the BD distribution. A second 5-field plan was made with our in-house optimizer, using pre-generated MC dose and LETd maps. Constraints were placed to maintain the target dose to within 25% of the prescription, while maximizing the BD. The plan optimization and calculation of dose and LETd maps were performed on a GPU cluster. The conventional IMPT and biologically-optimized plans were compared. Results: The mean target physical and biological doses from our biologically-optimized plan were, respectively, 5% and 14% higher than those from the MC re-calculation of the IMPT plan. Dose sparing to critical structures in our plan was also improved. The biological optimization, including the initial dose and LETd map calculations, can be completed in a clinically viable time (∼30 minutes) on a cluster of 25 GPUs. Conclusion: Taking advantage of GPU acceleration, we created a MC-based, biologically optimized treatment plan for a thyroid patient. Compared to a standard IMPT plan, a 5% increase in the target’s physical dose resulted in ∼3 times as much increase in the BD. Biological planning was thus effective in escalating the target BD.
D'Amours, Michel; Pouliot, Jean; Dagnault, Anne; Verhaegen, Frank; Beaulieu, Luc
2011-12-01
Purpose: Brachytherapy planning software relies on the Task Group report 43 dosimetry formalism. This formalism, based on a water approximation, neglects various heterogeneous materials present during treatment. Various studies have suggested that these heterogeneities should be taken into account to improve the treatment quality. The present study sought to demonstrate the feasibility of incorporating Monte Carlo (MC) dosimetry within an inverse planning algorithm to improve the dose conformity and increase the treatment quality. Methods and Materials: The method was based on precalculated dose kernels in full patient geometries, representing the dose distribution of a brachytherapy source at a single dwell position using MC simulations and the Geant4 toolkit. These dose kernels are used by the inverse planning by simulated annealing tool to produce a fast MC-based plan. A test was performed for an interstitial brachytherapy breast treatment using two different high-dose-rate brachytherapy sources: the microSelectron iridium-192 source and the electronic brachytherapy source Axxent operating at 50 kVp. Results: A research version of the inverse planning by simulated annealing algorithm was combined with MC to provide a method to fully account for the heterogeneities in dose optimization, using the MC method. The effect of the water approximation was found to depend on photon energy, with greater dose attenuation for the lower energies of the Axxent source compared with iridium-192. For the latter, an underdosage of 5.1% for the dose received by 90% of the clinical target volume was found. Conclusion: A new method to optimize afterloading brachytherapy plans that uses MC dosimetric information was developed. Including computed tomography-based information in MC dosimetry in the inverse planning process was shown to take into account the full range of scatter and heterogeneity conditions. This led to significant dose differences compared with the Task Group report
D'Amours, Michel; Pouliot, Jean; Dagnault, Anne; Verhaegen, Frank; Beaulieu, Luc
2011-12-01
Brachytherapy planning software relies on the Task Group report 43 dosimetry formalism. This formalism, based on a water approximation, neglects various heterogeneous materials present during treatment. Various studies have suggested that these heterogeneities should be taken into account to improve the treatment quality. The present study sought to demonstrate the feasibility of incorporating Monte Carlo (MC) dosimetry within an inverse planning algorithm to improve the dose conformity and increase the treatment quality. The method was based on precalculated dose kernels in full patient geometries, representing the dose distribution of a brachytherapy source at a single dwell position using MC simulations and the Geant4 toolkit. These dose kernels are used by the inverse planning by simulated annealing tool to produce a fast MC-based plan. A test was performed for an interstitial brachytherapy breast treatment using two different high-dose-rate brachytherapy sources: the microSelectron iridium-192 source and the electronic brachytherapy source Axxent operating at 50 kVp. A research version of the inverse planning by simulated annealing algorithm was combined with MC to provide a method to fully account for the heterogeneities in dose optimization, using the MC method. The effect of the water approximation was found to depend on photon energy, with greater dose attenuation for the lower energies of the Axxent source compared with iridium-192. For the latter, an underdosage of 5.1% for the dose received by 90% of the clinical target volume was found. A new method to optimize afterloading brachytherapy plans that uses MC dosimetric information was developed. Including computed tomography-based information in MC dosimetry in the inverse planning process was shown to take into account the full range of scatter and heterogeneity conditions. This led to significant dose differences compared with the Task Group report 43 approach for the Axxent source. Copyright © 2011
Chi, Y; Li, Y; Tian, Z; Gu, X; Jiang, S; Jia, X
2015-06-15
Purpose: Pencil-beam or superposition-convolution type dose calculation algorithms are routinely used in inverse plan optimization for intensity modulated radiation therapy (IMRT). However, due to their limited accuracy in some challenging cases, e.g. lung, the resulting dose may lose its optimality after being recomputed using an accurate algorithm, e.g. Monte Carlo (MC). It is the objective of this study to evaluate the feasibility and advantages of a new method to include MC in the treatment planning process. Methods: We developed a scheme to iteratively perform MC-based beamlet dose calculations and plan optimization. In the MC stage, a GPU-based dose engine was used and the particle number sampled from a beamlet was proportional to its optimized fluence from the previous step. We tested this scheme in four lung cancer IMRT cases. For each case, the original plan dose, plan dose re-computed by MC, and dose optimized by our scheme were obtained. Clinically relevant dosimetric quantities in these three plans were compared. Results: Although the original plan achieved a satisfactory PDV dose coverage, after re-computing doses using MC method, it was found that the PTV D95% were reduced by 4.60%–6.67%. After re-optimizing these cases with our scheme, the PTV coverage was improved to the same level as in the original plan, while the critical OAR coverages were maintained to clinically acceptable levels. Regarding the computation time, it took on average 144 sec per case using only one GPU card, including both MC-based beamlet dose calculation and treatment plan optimization. Conclusion: The achieved dosimetric gains and high computational efficiency indicate the feasibility and advantages of the proposed MC-based IMRT optimization method. Comprehensive validations in more patient cases are in progress.
Four decades of implicit Monte Carlo
Wollaber, Allan B.
2016-02-23
In 1971, Fleck and Cummings derived a system of equations to enable robust Monte Carlo simulations of time-dependent, thermal radiative transfer problems. Denoted the “Implicit Monte Carlo” (IMC) equations, their solution remains the de facto standard of high-fidelity radiative transfer simulations. Over the course of 44 years, their numerical properties have become better understood, and accuracy enhancements, novel acceleration methods, and variance reduction techniques have been suggested. In this review, we rederive the IMC equations—explicitly highlighting assumptions as they are made—and outfit the equations with a Monte Carlo interpretation. We put the IMC equations in context with other approximate forms of the radiative transfer equations and present a new demonstration of their equivalence to another well-used linearization solved with deterministic transport methods for frequency-independent problems. We discuss physical and numerical limitations of the IMC equations for asymptotically small time steps, stability characteristics and the potential of maximum principle violations for large time steps, and solution behaviors in an asymptotically thick diffusive limit. We provide a new stability analysis for opacities with general monomial dependence on temperature. Here, we consider spatial accuracy limitations of the IMC equations and discussion acceleration and variance reduction techniques.
Four decades of implicit Monte Carlo
Wollaber, Allan B.
2016-02-23
In 1971, Fleck and Cummings derived a system of equations to enable robust Monte Carlo simulations of time-dependent, thermal radiative transfer problems. Denoted the “Implicit Monte Carlo” (IMC) equations, their solution remains the de facto standard of high-fidelity radiative transfer simulations. Over the course of 44 years, their numerical properties have become better understood, and accuracy enhancements, novel acceleration methods, and variance reduction techniques have been suggested. In this review, we rederive the IMC equations—explicitly highlighting assumptions as they are made—and outfit the equations with a Monte Carlo interpretation. We put the IMC equations in context with other approximate formsmore » of the radiative transfer equations and present a new demonstration of their equivalence to another well-used linearization solved with deterministic transport methods for frequency-independent problems. We discuss physical and numerical limitations of the IMC equations for asymptotically small time steps, stability characteristics and the potential of maximum principle violations for large time steps, and solution behaviors in an asymptotically thick diffusive limit. We provide a new stability analysis for opacities with general monomial dependence on temperature. Here, we consider spatial accuracy limitations of the IMC equations and discussion acceleration and variance reduction techniques.« less
Global Monte Carlo Simulation with High Order Polynomial Expansions
William R. Martin; James Paul Holloway; Kaushik Banerjee; Jesse Cheatham; Jeremy Conlin
2007-12-13
The functional expansion technique (FET) was recently developed for Monte Carlo simulation. The basic idea of the FET is to expand a Monte Carlo tally in terms of a high order expansion, the coefficients of which can be estimated via the usual random walk process in a conventional Monte Carlo code. If the expansion basis is chosen carefully, the lowest order coefficient is simply the conventional histogram tally, corresponding to a flat mode. This research project studied the applicability of using the FET to estimate the fission source, from which fission sites can be sampled for the next generation. The idea is that individual fission sites contribute to expansion modes that may span the geometry being considered, possibly increasing the communication across a loosely coupled system and thereby improving convergence over the conventional fission bank approach used in most production Monte Carlo codes. The project examined a number of basis functions, including global Legendre polynomials as well as “local” piecewise polynomials such as finite element hat functions and higher order versions. The global FET showed an improvement in convergence over the conventional fission bank approach. The local FET methods showed some advantages versus global polynomials in handling geometries with discontinuous material properties. The conventional finite element hat functions had the disadvantage that the expansion coefficients could not be estimated directly but had to be obtained by solving a linear system whose matrix elements were estimated. An alternative fission matrix-based response matrix algorithm was formulated. Studies were made of two alternative applications of the FET, one based on the kernel density estimator and one based on Arnoldi’s method of minimized iterations. Preliminary results for both methods indicate improvements in fission source convergence. These developments indicate that the FET has promise for speeding up Monte Carlo fission source
On a full Monte Carlo approach to quantum mechanics
NASA Astrophysics Data System (ADS)
Sellier, J. M.; Dimov, I.
2016-12-01
The Monte Carlo approach to numerical problems has shown to be remarkably efficient in performing very large computational tasks since it is an embarrassingly parallel technique. Additionally, Monte Carlo methods are well known to keep performance and accuracy with the increase of dimensionality of a given problem, a rather counterintuitive peculiarity not shared by any known deterministic method. Motivated by these very peculiar and desirable computational features, in this work we depict a full Monte Carlo approach to the problem of simulating single- and many-body quantum systems by means of signed particles. In particular we introduce a stochastic technique, based on the strategy known as importance sampling, for the computation of the Wigner kernel which, so far, has represented the main bottleneck of this method (it is equivalent to the calculation of a multi-dimensional integral, a problem in which complexity is known to grow exponentially with the dimensions of the problem). The introduction of this stochastic technique for the kernel is twofold: firstly it reduces the complexity of a quantum many-body simulation from non-linear to linear, secondly it introduces an embarassingly parallel approach to this very demanding problem. To conclude, we perform concise but indicative numerical experiments which clearly illustrate how a full Monte Carlo approach to many-body quantum systems is not only possible but also advantageous. This paves the way towards practical time-dependent, first-principle simulations of relatively large quantum systems by means of affordable computational resources.
A separable shadow Hamiltonian hybrid Monte Carlo method
NASA Astrophysics Data System (ADS)
Sweet, Christopher R.; Hampton, Scott S.; Skeel, Robert D.; Izaguirre, Jesús A.
2009-11-01
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
A separable shadow Hamiltonian hybrid Monte Carlo method.
Sweet, Christopher R; Hampton, Scott S; Skeel, Robert D; Izaguirre, Jesús A
2009-11-07
Hybrid Monte Carlo (HMC) is a rigorous sampling method that uses molecular dynamics (MD) as a global Monte Carlo move. The acceptance rate of HMC decays exponentially with system size. The shadow hybrid Monte Carlo (SHMC) was previously introduced to reduce this performance degradation by sampling instead from the shadow Hamiltonian defined for MD when using a symplectic integrator. SHMC's performance is limited by the need to generate momenta for the MD step from a nonseparable shadow Hamiltonian. We introduce the separable shadow Hamiltonian hybrid Monte Carlo (S2HMC) method based on a formulation of the leapfrog/Verlet integrator that corresponds to a separable shadow Hamiltonian, which allows efficient generation of momenta. S2HMC gives the acceptance rate of a fourth order integrator at the cost of a second-order integrator. Through numerical experiments we show that S2HMC consistently gives a speedup greater than two over HMC for systems with more than 4000 atoms for the same variance. By comparison, SHMC gave a maximum speedup of only 1.6 over HMC. S2HMC has the additional advantage of not requiring any user parameters beyond those of HMC. S2HMC is available in the program PROTOMOL 2.1. A Python version, adequate for didactic purposes, is also in MDL (http://mdlab.sourceforge.net/s2hmc).
Monte Carlo capabilities of the SCALE code system
Rearden, Bradley T.; Petrie, Jr., Lester M.; Peplow, Douglas E.; Bekar, Kursat B.; Wiarda, Dorothea; Celik, Cihangir; Perfetti, Christopher M.; Ibrahim, Ahmad M.; Hart, S. W. D.; Dunn, Michael E.; Marshall, William J.
2014-09-12
SCALE is a broadly used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. Finally, an overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.
Monte Carlo capabilities of the SCALE code system
Rearden, Bradley T.; Petrie, Jr., Lester M.; Peplow, Douglas E.; ...
2014-09-12
SCALE is a broadly used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a “plug-and-play” framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport asmore » well as activation, depletion, and decay calculations. SCALE’s graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2 will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. Finally, an overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.« less
Parallel Monte Carlo simulation of multilattice thin film growth
NASA Astrophysics Data System (ADS)
Shu, J. W.; Lu, Qin; Wong, Wai-on; Huang, Han-chen
2001-07-01
This paper describe a new parallel algorithm for the multi-lattice Monte Carlo atomistic simulator for thin film deposition (ADEPT), implemented on parallel computer using the PVM (Parallel Virtual Machine) message passing library. This parallel algorithm is based on domain decomposition with overlapping and asynchronous communication. Multiple lattices are represented by a single reference lattice through one-to-one mappings, with resulting computational demands being comparable to those in the single-lattice Monte Carlo model. Asynchronous communication and domain overlapping techniques are used to reduce the waiting time and communication time among parallel processors. Results show that the algorithm is highly efficient with large number of processors. The algorithm was implemented on a parallel machine with 50 processors, and it is suitable for parallel Monte Carlo simulation of thin film growth with either a distributed memory parallel computer or a shared memory machine with message passing libraries. In this paper, the significant communication time in parallel MC simulation of thin film growth is effectively reduced by adopting domain decomposition with overlapping between sub-domains and asynchronous communication among processors. The overhead of communication does not increase evidently and speedup shows an ascending tendency when the number of processor increases. A near linear increase in computing speed was achieved with number of processors increases and there is no theoretical limit on the number of processors to be used. The techniques developed in this work are also suitable for the implementation of the Monte Carlo code on other parallel systems.
Diffuse photon density wave measurements and Monte Carlo simulations
NASA Astrophysics Data System (ADS)
Kuzmin, Vladimir L.; Neidrauer, Michael T.; Diaz, David; Zubkov, Leonid A.
2015-10-01
Diffuse photon density wave (DPDW) methodology is widely used in a number of biomedical applications. Here, we present results of Monte Carlo simulations that employ an effective numerical procedure based upon a description of radiative transfer in terms of the Bethe-Salpeter equation. A multifrequency noncontact DPDW system was used to measure aqueous solutions of intralipid at a wide range of source-detector separation distances, at which the diffusion approximation of the radiative transfer equation is generally considered to be invalid. We find that the signal-noise ratio is larger for the considered algorithm in comparison with the conventional Monte Carlo approach. Experimental data are compared to the Monte Carlo simulations using several values of scattering anisotropy and to the diffusion approximation. Both the Monte Carlo simulations and diffusion approximation were in very good agreement with the experimental data for a wide range of source-detector separations. In addition, measurements with different wavelengths were performed to estimate the size and scattering anisotropy of scatterers.
Automated variance reduction for Monte Carlo shielding analyses with MCNP
NASA Astrophysics Data System (ADS)
Radulescu, Georgeta
Variance reduction techniques are employed in Monte Carlo analyses to increase the number of particles in the space phase of interest and thereby lower the variance of statistical estimation. Variance reduction parameters are required to perform Monte Carlo calculations. It is well known that adjoint solutions, even approximate ones, are excellent biasing functions that can significantly increase the efficiency of a Monte Carlo calculation. In this study, an automated method of generating Monte Carlo variance reduction parameters, and of implementing the source energy biasing and the weight window technique in MCNP shielding calculations has been developed. The method is based on the approach used in the SAS4 module of the SCALE code system, which derives the biasing parameters from an adjoint one-dimensional Discrete Ordinates calculation. Unlike SAS4 that determines the radial and axial dose rates of a spent fuel cask in separate calculations, the present method provides energy and spatial biasing parameters for the entire system that optimize the simulation of particle transport towards all external surfaces of a spent fuel cask. The energy and spatial biasing parameters are synthesized from the adjoint fluxes of three one-dimensional Discrete Ordinates adjoint calculations. Additionally, the present method accommodates multiple source regions, such as the photon sources in light-water reactor spent nuclear fuel assemblies, in one calculation. With this automated method, detailed and accurate dose rate maps for photons, neutrons, and secondary photons outside spent fuel casks or other containers can be efficiently determined with minimal efforts.
Diffuse photon density wave measurements and Monte Carlo simulations.
Kuzmin, Vladimir L; Neidrauer, Michael T; Diaz, David; Zubkov, Leonid A
2015-10-01
Diffuse photon density wave (DPDW) methodology is widely used in a number of biomedical applications. Here, we present results of Monte Carlo simulations that employ an effective numerical procedure based upon a description of radiative transfer in terms of the Bethe–Salpeter equation. A multifrequency noncontact DPDW system was used to measure aqueous solutions of intralipid at a wide range of source–detector separation distances, at which the diffusion approximation of the radiative transfer equation is generally considered to be invalid. We find that the signal–noise ratio is larger for the considered algorithm in comparison with the conventional Monte Carlo approach. Experimental data are compared to the Monte Carlo simulations using several values of scattering anisotropy and to the diffusion approximation. Both the Monte Carlo simulations and diffusion approximation were in very good agreement with the experimental data for a wide range of source–detector separations. In addition, measurements with different wavelengths were performed to estimate the size and scattering anisotropy of scatterers.
Error estimations and their biases in Monte Carlo eigenvalue calculations
Ueki, Taro; Mori, Takamasa; Nakagawa, Masayuki
1997-01-01
In the Monte Carlo eigenvalue calculation of neutron transport, the eigenvalue is calculated as the average of multiplication factors from cycles, which are called the cycle k{sub eff}`s. Biases in the estimators of the variance and intercycle covariances in Monte Carlo eigenvalue calculations are analyzed. The relations among the real and apparent values of variances and intercycle covariances are derived, where real refers to a true value that is calculated from independently repeated Monte Carlo runs and apparent refers to the expected value of estimates from a single Monte Carlo run. Next, iterative methods based on the foregoing relations are proposed to estimate the standard deviation of the eigenvalue. The methods work well for the cases in which the ratios of the real to apparent values of variances are between 1.4 and 3.1. Even in the case where the foregoing ratio is >5, >70% of the standard deviation estimates fall within 40% from the true value.
Monte Carlo Capabilities of the SCALE Code System
NASA Astrophysics Data System (ADS)
Rearden, B. T.; Petrie, L. M.; Peplow, D. E.; Bekar, K. B.; Wiarda, D.; Celik, C.; Perfetti, C. M.; Ibrahim, A. M.; Hart, S. W. D.; Dunn, M. E.
2014-06-01
SCALE is a widely used suite of tools for nuclear systems modeling and simulation that provides comprehensive, verified and validated, user-friendly capabilities for criticality safety, reactor physics, radiation shielding, and sensitivity and uncertainty analysis. For more than 30 years, regulators, licensees, and research institutions around the world have used SCALE for nuclear safety analysis and design. SCALE provides a "plug-and-play" framework that includes three deterministic and three Monte Carlo radiation transport solvers that can be selected based on the desired solution, including hybrid deterministic/Monte Carlo simulations. SCALE includes the latest nuclear data libraries for continuous-energy and multigroup radiation transport as well as activation, depletion, and decay calculations. SCALE's graphical user interfaces assist with accurate system modeling, visualization, and convenient access to desired results. SCALE 6.2, to be released in 2014, will provide several new capabilities and significant improvements in many existing features, especially with expanded continuous-energy Monte Carlo capabilities for criticality safety, shielding, depletion, and sensitivity and uncertainty analysis. An overview of the Monte Carlo capabilities of SCALE is provided here, with emphasis on new features for SCALE 6.2.
A Monte Carlo Dispersion Analysis of the X-33 Simulation Software
NASA Technical Reports Server (NTRS)
Williams, Peggy S.
2001-01-01
A Monte Carlo dispersion analysis has been completed on the X-33 software simulation. The simulation is based on a preliminary version of the software and is primarily used in an effort to define and refine how a Monte Carlo dispersion analysis would have been done on the final flight-ready version of the software. This report gives an overview of the processes used in the implementation of the dispersions and describes the methods used to accomplish the Monte Carlo analysis. Selected results from 1000 Monte Carlo runs are presented with suggestions for improvements in future work.
Combined Monte Carlo and quantum mechanics study of the hydration of the guanine-cytosine base pair.
Coutinho, Kaline; Ludwig, Valdemir; Canuto, Sylvio
2004-06-01
We present a computer simulation study of the hydration of the guanine-cytosine (GC) hydrogen-bonded complex. Using first principles density-functional theory, with gradient-corrected exchange-correlation and Monte Carlo simulation, we include thermal contribution, structural effects, solvent polarization, and the water-water and water-GC hydrogen bond interaction to show that the GC interaction in an aqueous environment is weakened to about 70% of the value obtained for an isolated complex. We also analyze in detail the preferred hydration sites of the GC pair and show that on the average it makes around five hydrogen bonds with water.
Araki, Fujio
2012-11-21
The purpose of this study was to investigate the perturbation correction factors and inhomogeneity correction factors (ICFs) for a thin-walled cylindrical ion chamber in a heterogeneous phantom including solid water, lung and bone plastic materials. The perturbation factors due to the replacement of the air cavity, non-water equivalence of the wall and the stem, non-air equivalence of the central electrode and the overall perturbation factor, P(Q), for a cylindrical chamber, in the heterogeneous phantom were calculated with the EGSnrc/Cavity Monte Carlo code for 6 and 15 MV photon beams. The PTW31010 (0.125 cm(3)) chamber was modeled with Monte Carlo simulations, and was used for measurements and calculations of percentage depth ionization (PDI) or percentage depth dose (PDD). ICFs were calculated from the ratio of the product of the stopping power ratios (SPRs) and P(Q) of lung or bone to solid water. Finally, the measured PDIs were converted to PDDs by using ICFs and were compared with those calculated by the Monte Carlo method. The perturbation effect for the ion chamber in lung material is insignificant at 5 × 5 and 10 × 10 cm(2) fields, but the effect needs to be considered under conditions of lateral electron disequilibrium with a 3 × 3 cm(2) field. ICFs in lung varied up to 2% and 4% depending on the field size for 6 and 15 MV, respectively. For bone material, the perturbation effects due to the chamber wall and the stem were more significant at up to 3.5% and 1.6% for 6 MV, respectively. ICFs for bone material were approximately 0.945 and 0.940 for 6 and 15 MV, respectively. The converted PDDs by using ICFs were in good agreement with Monte Carlo calculated PDDs. The chamber perturbation correction and SPRs should strictly be considered for ion chamber dosimetry in heterogeneous media. This is more important for small field dosimetry in lung and bone materials.
Reply to "Comment on 'A study on tetrahedron-based inhomogeneous Monte-Carlo optical simulation'".
Shen, Haiou; Wang, Ge
2011-04-19
We compare the accuracy of TIM-OS and MMCM in response to the recent analysis made by Fang [Biomed. Opt. Express 2, 1258 (2011)]. Our results show that the tetrahedron-based energy deposition algorithm used in TIM-OS is more accurate than the node-based energy deposition algorithm used in MMCM.
NASA Astrophysics Data System (ADS)
Li, Dong; Chen, Bin; Ran, Wei Yu; Wang, Guo Xiang; Wu, Wen Juan
2015-09-01
The voxel-based Monte Carlo method (VMC) is now a gold standard in the simulation of light propagation in turbid media. For complex tissue structures, however, the computational cost will be higher when small voxels are used to improve smoothness of tissue interface and a large number of photons are used to obtain accurate results. To reduce computational cost, criteria were proposed to determine the voxel size and photon number in 3-dimensional VMC simulations with acceptable accuracy and computation time. The selection of the voxel size can be expressed as a function of tissue geometry and optical properties. The photon number should be at least 5 times the total voxel number. These criteria are further applied in developing a photon ray splitting scheme of local grid refinement technique to reduce computational cost of a nonuniform tissue structure with significantly varying optical properties. In the proposed technique, a nonuniform refined grid system is used, where fine grids are used for the tissue with high absorption and complex geometry, and coarse grids are used for the other part. In this technique, the total photon number is selected based on the voxel size of the coarse grid. Furthermore, the photon-splitting scheme is developed to satisfy the statistical accuracy requirement for the dense grid area. Result shows that local grid refinement technique photon ray splitting scheme can accelerate the computation by 7.6 times (reduce time consumption from 17.5 to 2.3 h) in the simulation of laser light energy deposition in skin tissue that contains port wine stain lesions.
Wang, Zhihui; Bordas, Veronika; Deisboeck, Thomas S
2011-01-01
To date, parameters defining biological properties in multiscale disease models are commonly obtained from a variety of sources. It is thus important to examine the influence of parameter perturbations on system behavior, rather than to limit the model to a specific set of parameters. Such sensitivity analysis can be used to investigate how changes in input parameters affect model outputs. However, multiscale cancer models require special attention because they generally take longer to run than does a series of signaling pathway analysis tasks. In this article, we propose a global sensitivity analysis method based on the integration of Monte Carlo, resampling, and analysis of variance. This method provides solutions to (1) how to render the large number of parameter variation combinations computationally manageable, and (2) how to effectively quantify the sampling distribution of the sensitivity index to address the inherent computational intensity issue. We exemplify the feasibility of this method using a two-dimensional molecular-microscopic agent-based model previously developed for simulating non-small cell lung cancer; in this model, an epidermal growth factor (EGF)-induced, EGF receptor-mediated signaling pathway was implemented at the molecular level. Here, the cross-scale effects of molecular parameters on two tumor growth evaluation measures, i.e., tumor volume and expansion rate, at the microscopic level are assessed. Analysis finds that ERK, a downstream molecule of the EGF receptor signaling pathway, has the most important impact on regulating both measures. The potential to apply this method to therapeutic target discovery is discussed.
NASA Astrophysics Data System (ADS)
Bozkurt, Ahmet
The distribution of absorbed doses in the body can be computationally determined using mathematical or tomographic representations of human anatomy. A whole- body model was developed from the color images of the National Library of Medicine's Visible Human Project® for simulating the transport of radiation in the human body. The model, called Visible Photographic Man (VIP-Man), has sixty-one organs and tissues represented in the Monte Carlo code MCNPX at 4-mm voxel resolution. Organ dose calculations from external neutron sources were carried out using VIP-man and MCNPX to determine a new set of dose conversion coefficients to be used in radiation protection. Monoenergetic neutron beams between 10-9 MeV and 10 GeV were studied under six different irradiation geometries: anterior-posterior, posterior-anterior, right lateral, left lateral, rotational and isotropic. The results for absorbed doses in twenty-four organs and the effective doses based on twelve critical organs are presented in tabular form. A comprehensive comparison of the results with those from the mathematical models show discrepancies that can be attributed to the variations in body modeling (size, location and shape of the individual organs) and the use of different nuclear datasets or models to derive the reaction cross sections, as well as the use of different transport packages for simulation radiation effects. The organ dose results based on the realistic VIP-Man body model allow the existing radiation protection dosimetry on neutrons to be re-evaluated and improved.
NASA Astrophysics Data System (ADS)
Wen, Xiulan; Xu, Youxiong; Li, Hongsheng; Wang, Fenglin; Sheng, Danghong
2012-09-01
Straightness error is an important parameter in measuring high-precision shafts. New generation geometrical product specification(GPS) requires the measurement uncertainty characterizing the reliability of the results should be given together when the measurement result is given. Nowadays most researches on straightness focus on error calculation and only several research projects evaluate the measurement uncertainty based on "The Guide to the Expression of Uncertainty in Measurement(GUM)". In order to compute spatial straightness error(SSE) accurately and rapidly and overcome the limitations of GUM, a quasi particle swarm optimization(QPSO) is proposed to solve the minimum zone SSE and Monte Carlo Method(MCM) is developed to estimate the measurement uncertainty. The mathematical model of minimum zone SSE is formulated. In QPSO quasi-random sequences are applied to the generation of the initial position and velocity of particles and their velocities are modified by the constriction factor approach. The flow of measurement uncertainty evaluation based on MCM is proposed, where the heart is repeatedly sampling from the probability density function(PDF) for every input quantity and evaluating the model in each case. The minimum zone SSE of a shaft measured on a Coordinate Measuring Machine(CMM) is calculated by QPSO and the measurement uncertainty is evaluated by MCM on the basis of analyzing the uncertainty contributors. The results show that the uncertainty directly influences the product judgment result. Therefore it is scientific and reasonable to consider the influence of the uncertainty in judging whether the parts are accepted or rejected, especially for those located in the uncertainty zone. The proposed method is especially suitable when the PDF of the measurand cannot adequately be approximated by a Gaussian distribution or a scaled and shifted t-distribution and the measurement model is non-linear.
Palma, Bianey Atriana; Sánchez, Ana Ureba; Salguero, Francisco Javier; Arráns, Rafael; Sánchez, Carlos Míguez; Zurita, Amadeo Walls; Hermida, María Isabel Romero; Leal, Antonio
2012-03-07
The purpose of this study was to present a Monte-Carlo (MC)-based optimization procedure to improve conventional treatment plans for accelerated partial breast irradiation (APBI) using modulated electron beams alone or combined with modulated photon beams, to be delivered by a single collimation device, i.e. a photon multi-leaf collimator (xMLC) already installed in a standard hospital. Five left-sided breast cases were retrospectively planned using modulated photon and/or electron beams with an in-house treatment planning system (TPS), called CARMEN, and based on MC simulations. For comparison, the same cases were also planned by a PINNACLE TPS using conventional inverse intensity modulated radiation therapy (IMRT). Normal tissue complication probability for pericarditis, pneumonitis and breast fibrosis was calculated. CARMEN plans showed similar acceptable planning target volume (PTV) coverage as conventional IMRT plans with 90% of PTV volume covered by the prescribed dose (D(p)). Heart and ipsilateral lung receiving 5% D(p) and 15% D(p), respectively, was 3.2-3.6 times lower for CARMEN plans. Ipsilateral breast receiving 50% D(p) and 100% D(p) was an average of 1.4-1.7 times lower for CARMEN plans. Skin and whole body low-dose volume was also reduced. Modulated photon and/or electron beams planned by the CARMEN TPS improve APBI treatments by increasing normal tissue sparing maintaining the same PTV coverage achieved by other techniques. The use of the xMLC, already installed in the linac, to collimate photon and electron beams favors the clinical implementation of APBI with the highest efficiency.
Monte Carlo simulation of moderator and reflector in coal analyzer based on a D-T neutron generator.
Shan, Qing; Chu, Shengnan; Jia, Wenbao
2015-11-01
Coal is one of the most popular fuels in the world. The use of coal not only produces carbon dioxide, but also contributes to the environmental pollution by heavy metals. In prompt gamma-ray neutron activation analysis (PGNAA)-based coal analyzer, the characteristic gamma rays of C and O are mainly induced by fast neutrons, whereas thermal neutrons can be used to induce the characteristic gamma rays of H, Si, and heavy metals. Therefore, appropriate thermal and fast neutrons are beneficial in improving the measurement accuracy of heavy metals, and ensure that the measurement accuracy of main elements meets the requirements of the industry. Once the required yield of the deuterium-tritium (d-T) neutron generator is determined, appropriate thermal and fast neutrons can be obtained by optimizing the neutron source term. In this article, the Monte Carlo N-Particle (MCNP) Transport Code and Evaluated Nuclear Data File (ENDF) database are used to optimize the neutron source term in PGNAA-based coal analyzer, including the material and shape of the moderator and neutron reflector. The optimized targets include two points: (1) the ratio of the thermal to fast neutron is 1:1 and (2) the total neutron flux from the optimized neutron source in the sample increases at least 100% when compared with the initial one. The simulation results show that, the total neutron flux in the sample increases 102%, 102%, 85%, 72%, and 62% with Pb, Bi, Nb, W, and Be reflectors, respectively. Maximum optimization of the targets is achieved when the moderator is a 3-cm-thick lead layer coupled with a 3-cm-thick high-density polyethylene (HDPE) layer, and the neutron reflector is a 27-cm-thick hemispherical lead layer.
Aguirre-Urreta, Miguel I; Ellis, Michael E; Sun, Wenying
2012-03-01
This research investigates the performance of a proportion-based approach to meta-analytic moderator estimation through a series of Monte Carlo simulations. This approach is most useful when the moderating potential of a categorical variable has not been recognized in primary research and thus heterogeneous groups have been pooled together as a single sample. Alternative scenarios representing different distributions of group proportions are examined along with varying numbers of studies, subjects per study, and correlation combinations. Our results suggest that the approach is largely unbiased in its estimation of the magnitude of between-group differences and performs well with regard to statistical power and type I error. In particular, the average percentage bias of the estimated correlation for the reference group is positive and largely negligible, in the 0.5-1.8% range; the average percentage bias of the difference between correlations is also minimal, in the -0.1-1.2% range. Further analysis also suggests both biases decrease as the magnitude of the underlying difference increases, as the number of subjects in each simulated primary study increases, and as the number of simulated studies in each meta-analysis increases. The bias was most evident when the number of subjects and the number of studies were the smallest (80 and 36, respectively). A sensitivity analysis that examines its performance in scenarios down to 12 studies and 40 primary subjects is also included. This research is the first that thoroughly examines the adequacy of the proportion-based approach. Copyright © 2012 John Wiley & Sons, Ltd. Copyright © 2012 John Wiley & Sons, Ltd.
Li, Dong; Chen, Bin; Ran, Wei Yu; Wang, Guo Xiang; Wu, Wen Juan
2015-01-01
The voxel-based Monte Carlo method (VMC) is now a gold standard in the simulation of light propagation in turbid media. For complex tissue structures, however, the computational cost will be higher when small voxels are used to improve smoothness of tissue interface and a large number of photons are used to obtain accurate results. To reduce computational cost, criteria were proposed to determine the voxel size and photon number in 3-dimensional VMC simulations with acceptable accuracy and computation time. The selection of the voxel size can be expressed as a function of tissue geometry and optical properties. The photon number should be at least 5 times the total voxel number. These criteria are further applied in developing a photon ray splitting scheme of local grid refinement technique to reduce computational cost of a nonuniform tissue structure with significantly varying optical properties. In the proposed technique, a nonuniform refined grid system is used, where fine grids are used for the tissue with high absorption and complex geometry, and coarse grids are used for the other part. In this technique, the total photon number is selected based on the voxel size of the coarse grid. Furthermore, the photon-splitting scheme is developed to satisfy the statistical accuracy requirement for the dense grid area. Result shows that local grid refinement technique photon ray splitting scheme can accelerate the computation by 7.6 times (reduce time consumption from 17.5 to 2.3 h) in the simulation of laser light energy deposition in skin tissue that contains port wine stain lesions.
NASA Astrophysics Data System (ADS)
Zhang, Junlong; Li, Yongping; Huang, Guohe; Chen, Xi; Bao, Anming
2016-07-01
Without a realistic assessment of parameter uncertainty, decision makers may encounter difficulties in accurately describing hydrologic processes and assessing relationships between model parameters and watershed characteristics. In this study, a Markov-Chain-Monte-Carlo-based multilevel-factorial-analysis (MCMC-MFA) method is developed, which can not only generate samples of parameters from a well constructed Markov chain and assess parameter uncertainties with straightforward Bayesian inference, but also investigate the individual and interactive effects of multiple parameters on model output through measuring the specific variations of hydrological responses. A case study is conducted for addressing parameter uncertainties in the Kaidu watershed of northwest China. Effects of multiple parameters and their interactions are quantitatively investigated using the MCMC-MFA with a three-level factorial experiment (totally 81 runs). A variance-based sensitivity analysis method is used to validate the results of parameters' effects. Results disclose that (i) soil conservation service runoff curve number for moisture condition II (CN2) and fraction of snow volume corresponding to 50% snow cover (SNO50COV) are the most significant factors to hydrological responses, implying that infiltration-excess overland flow and snow water equivalent represent important water input to the hydrological system of the Kaidu watershed; (ii) saturate hydraulic conductivity (SOL_K) and soil evaporation compensation factor (ESCO) have obvious effects on hydrological responses; this implies that the processes of percolation and evaporation would impact hydrological process in this watershed; (iii) the interactions of ESCO and SNO50COV as well as CN2 and SNO50COV have an obvious effect, implying that snow cover can impact the generation of runoff on land surface and the extraction of soil evaporative demand in lower soil layers. These findings can help enhance the hydrological model
Monte-Carlo simulation of Callisto's exosphere
NASA Astrophysics Data System (ADS)
Vorburger, A.; Wurz, P.; Lammer, H.; Barabash, S.; Mousis, O.
2015-12-01
We model Callisto's exosphere based on its ice as well as non-ice surface via the use of a Monte-Carlo exosphere model. For the ice component we implement two putative compositions that have been computed from two possible extreme formation scenarios of the satellite. One composition represents the oxidizing state and is based on the assumption that the building blocks of Callisto were formed in the protosolar nebula and the other represents the reducing state of the gas, based on the assumption that the satellite accreted from solids condensed in the jovian sub-nebula. For the non-ice component we implemented the compositions of typical CI as well as L type chondrites. Both chondrite types have been suggested to represent Callisto's non-ice composition best. As release processes we consider surface sublimation, ion sputtering and photon-stimulated desorption. Particles are followed on their individual trajectories until they either escape Callisto's gravitational attraction, return to the surface, are ionized, or are fragmented. Our density profiles show that whereas the sublimated species dominate close to the surface on the sun-lit side, their density profiles (with the exception of H and H2) decrease much more rapidly than the sputtered particles. The Neutral gas and Ion Mass (NIM) spectrometer, which is part of the Particle Environment Package (PEP), will investigate Callisto's exosphere during the JUICE mission. Our simulations show that NIM will be able to detect sublimated and sputtered particles from both the ice and non-ice surface. NIM's measured chemical composition will allow us to distinguish between different formation scenarios.
A Monte Carlo approach to water management
NASA Astrophysics Data System (ADS)
Koutsoyiannis, D.
2012-04-01
Common methods for making optimal decisions in water management problems are insufficient. Linear programming methods are inappropriate because hydrosystems are nonlinear with respect to their dynamics, operation constraints and objectives. Dynamic programming methods are inappropriate because water management problems cannot be divided into sequential stages. Also, these deterministic methods cannot properly deal with the uncertainty of future conditions (inflows, demands, etc.). Even stochastic extensions of these methods (e.g. linear-quadratic-Gaussian control) necessitate such drastic oversimplifications of hydrosystems that may make the obtained results irrelevant to the real world problems. However, a Monte Carlo approach is feasible and can form a general methodology applicable to any type of hydrosystem. This methodology uses stochastic simulation to generate system inputs, either unconditional or conditioned on a prediction, if available, and represents the operation of the entire system through a simulation model as faithful as possible, without demanding a specific mathematical form that would imply oversimplifications. Such representation fully respects the physical constraints, while at the same time it evaluates the system operation constraints and objectives in probabilistic terms, and derives their distribution functions and statistics through Monte Carlo simulation. As the performance criteria of a hydrosystem operation will generally be highly nonlinear and highly nonconvex functions of the control variables, a second Monte Carlo procedure, implementing stochastic optimization, is necessary to optimize system performance and evaluate the control variables of the system. The latter is facilitated if the entire representation is parsimonious, i.e. if the number of control variables is kept at a minimum by involving a suitable system parameterization. The approach is illustrated through three examples for (a) a hypothetical system of two reservoirs
Quantum Monte Carlo for vibrating molecules
Brown, W.R. |
1996-08-01
Quantum Monte Carlo (QMC) has successfully computed the total electronic energies of atoms and molecules. The main goal of this work is to use correlation function quantum Monte Carlo (CFQMC) to compute the vibrational state energies of molecules given a potential energy surface (PES). In CFQMC, an ensemble of random walkers simulate the diffusion and branching processes of the imaginary-time time dependent Schroedinger equation in order to evaluate the matrix elements. The program QMCVIB was written to perform multi-state VMC and CFQMC calculations and employed for several calculations of the H{sub 2}O and C{sub 3} vibrational states, using 7 PES`s, 3 trial wavefunction forms, two methods of non-linear basis function parameter optimization, and on both serial and parallel computers. In order to construct accurate trial wavefunctions different wavefunctions forms were required for H{sub 2}O and C{sub 3}. In order to construct accurate trial wavefunctions for C{sub 3}, the non-linear parameters were optimized with respect to the sum of the energies of several low-lying vibrational states. In order to stabilize the statistical error estimates for C{sub 3} the Monte Carlo data was collected into blocks. Accurate vibrational state energies were computed using both serial and parallel QMCVIB programs. Comparison of vibrational state energies computed from the three C{sub 3} PES`s suggested that a non-linear equilibrium geometry PES is the most accurate and that discrete potential representations may be used to conveniently determine vibrational state energies.
Status of Monte-Carlo Event Generators
Hoeche, Stefan; /SLAC
2011-08-11
Recent progress on general-purpose Monte-Carlo event generators is reviewed with emphasis on the simulation of hard QCD processes and subsequent parton cascades. Describing full final states of high-energy particle collisions in contemporary experiments is an intricate task. Hundreds of particles are typically produced, and the reactions involve both large and small momentum transfer. The high-dimensional phase space makes an exact solution of the problem impossible. Instead, one typically resorts to regarding events as factorized into different steps, ordered descending in the mass scales or invariant momentum transfers which are involved. In this picture, a hard interaction, described through fixed-order perturbation theory, is followed by multiple Bremsstrahlung emissions off initial- and final-state and, finally, by the hadronization process, which binds QCD partons into color-neutral hadrons. Each of these steps can be treated independently, which is the basic concept inherent to general-purpose event generators. Their development is nowadays often focused on an improved description of radiative corrections to hard processes through perturbative QCD. In this context, the concept of jets is introduced, which allows to relate sprays of hadronic particles in detectors to the partons in perturbation theory. In this talk, we briefly review recent progress on perturbative QCD in event generation. The main focus lies on the general-purpose Monte-Carlo programs HERWIG, PYTHIA and SHERPA, which will be the workhorses for LHC phenomenology. A detailed description of the physics models included in these generators can be found in [8]. We also discuss matrix-element generators, which provide the parton-level input for general-purpose Monte Carlo.
NASA Astrophysics Data System (ADS)
Obot, I. B.; Kaya, Savaş; Kaya, Cemal; Tüzün, Burak
2016-06-01
DFT and Monte Carlo simulation were performed on three Schiff bases namely, 4-(4-bromophenyl)-N‧-(4-methoxybenzylidene)thiazole-2-carbohydrazide (BMTC), 4-(4-bromophenyl)-N‧-(2,4-dimethoxybenzylidene)thiazole-2-carbohydrazide (BDTC), 4-(4-bromophenyl)-N‧-(4-hydroxybenzylidene)thiazole-2-carbohydrazide (BHTC) recently studied as corrosion inhibitor for steel in acid medium. Electronic parameters relevant to their inhibition activity such as EHOMO, ELUMO, Energy gap (ΔE), hardness (η), softness (σ), the absolute electronegativity (χ), proton affinity (PA) and nucleophilicity (ω) etc., were computed and discussed. Monte Carlo simulations were applied to search for the most stable configuration and adsorption energies for the interaction of the inhibitors with Fe (110) surface. The theoretical data obtained are in most cases in agreement with experimental results.
The Monte Carlo code MCPTV--Monte Carlo dose calculation in radiation therapy with carbon ions.
Karg, Juergen; Speer, Stefan; Schmidt, Manfred; Mueller, Reinhold
2010-07-07
The Monte Carlo code MCPTV is presented. MCPTV is designed for dose calculation in treatment planning in radiation therapy with particles and especially carbon ions. MCPTV has a voxel-based concept and can perform a fast calculation of the dose distribution on patient CT data. Material and density information from CT are taken into account. Electromagnetic and nuclear interactions are implemented. Furthermore the algorithm gives information about the particle spectra and the energy deposition in each voxel. This can be used to calculate the relative biological effectiveness (RBE) for each voxel. Depth dose distributions are compared to experimental data giving good agreement. A clinical example is shown to demonstrate the capabilities of the MCPTV dose calculation.
Monte Carlo study of disorder in HMTA
NASA Astrophysics Data System (ADS)
Goossens, D. J.; Welberry, T. R.
2001-12-01
We investigate disordered solids by automated fitting of a Monte Carlo simulation of a crystal to observed single-crystal diffuse X-ray scattering. This method has been extended to the study of crystals of relatively large organic molecules by using a z-matrix to describe the molecules. This allows exploration of motions within molecules. We refer to the correlated thermal motion observed in benzil, and to the occupational and thermal disorder in the 1:1 adduct of hexamethylenetetramine and azelaic acid, HMTA. The technique is capable of giving insight into modes of vibration within molecules and correlated motions between molecules.
Monte Carlo radiation transport¶llelism
Cox, L. J.; Post, S. E.
2002-01-01
This talk summarizes the main aspects of the LANL ASCI Eolus project and its major unclassified code project, MCNP. The MCNP code provide a state-of-the-art Monte Carlo radiation transport to approximately 3000 users world-wide. Almost all hardware platforms are supported because we strictly adhere to the FORTRAN-90/95 standard. For parallel processing, MCNP uses a mixture of OpenMp combined with either MPI or PVM (shared and distributed memory). This talk summarizes our experiences on various platforms using MPI with and without OpenMP. These platforms include PC-Windows, Intel-LINUX, BlueMountain, Frost, ASCI-Q and others.
Markov chain Monte Carlo without likelihoods.
Marjoram, Paul; Molitor, John; Plagnol, Vincent; Tavare, Simon
2003-12-23
Many stochastic simulation approaches for generating observations from a posterior distribution depend on knowing a likelihood function. However, for many complex probability models, such likelihoods are either impossible or computationally prohibitive to obtain. Here we present a Markov chain Monte Carlo method for generating observations from a posterior distribution without the use of likelihoods. It can also be used in frequentist applications, in particular for maximum-likelihood estimation. The approach is illustrated by an example of ancestral inference in population genetics. A number of open problems are highlighted in the discussion.
Monte Carlo methods to calculate impact probabilities
NASA Astrophysics Data System (ADS)
Rickman, H.; Wiśniowski, T.; Wajer, P.; Gabryszewski, R.; Valsecchi, G. B.
2014-09-01
Context. Unraveling the events that took place in the solar system during the period known as the late heavy bombardment requires the interpretation of the cratered surfaces of the Moon and terrestrial planets. This, in turn, requires good estimates of the statistical impact probabilities for different source populations of projectiles, a subject that has received relatively little attention, since the works of Öpik (1951, Proc. R. Irish Acad. Sect. A, 54, 165) and Wetherill (1967, J. Geophys. Res., 72, 2429). Aims: We aim to work around the limitations of the Öpik and Wetherill formulae, which are caused by singularities due to zero denominators under special circumstances. Using modern computers, it is possible to make good estimates of impact probabilities by means of Monte Carlo simulations, and in this work, we explore the available options. Methods: We describe three basic methods to derive the average impact probability for a projectile with a given semi-major axis, eccentricity, and inclination with respect to a target planet on an elliptic orbit. One is a numerical averaging of the Wetherill formula; the next is a Monte Carlo super-sizing method using the target's Hill sphere. The third uses extensive minimum orbit intersection distance (MOID) calculations for a Monte Carlo sampling of potentially impacting orbits, along with calculations of the relevant interval for the timing of the encounter allowing collision. Numerical experiments are carried out for an intercomparison of the methods and to scrutinize their behavior near the singularities (zero relative inclination and equal perihelion distances). Results: We find an excellent agreement between all methods in the general case, while there appear large differences in the immediate vicinity of the singularities. With respect to the MOID method, which is the only one that does not involve simplifying assumptions and approximations, the Wetherill averaging impact probability departs by diverging toward
Discovering correlated fermions using quantum Monte Carlo
NASA Astrophysics Data System (ADS)
Wagner, Lucas K.; Ceperley, David M.
2016-09-01
It has become increasingly feasible to use quantum Monte Carlo (QMC) methods to study correlated fermion systems for realistic Hamiltonians. We give a summary of these techniques targeted at researchers in the field of correlated electrons, focusing on the fundamentals, capabilities, and current status of this technique. The QMC methods often offer the highest accuracy solutions available for systems in the continuum, and, since they address the many-body problem directly, the simulations can be analyzed to obtain insight into the nature of correlated quantum behavior.
Quantum Monte Carlo calculations for light nuclei
Wiringa, R.B.
1997-10-01
Quantum Monte Carlo calculations of ground and low-lying excited states for nuclei with A {le} 8 have been made using a realistic Hamiltonian that fits NN scattering data. Results for more than two dozen different (J{sup {pi}}, T) p-shell states, not counting isobaric analogs, have been obtained. The known excitation spectra of all the nuclei are reproduced reasonably well. Density and momentum distributions and various electromagnetic moments and form factors have also been computed. These are the first microscopic calculations that directly produce nuclear shell structure from realistic NN interactions.
Quantum Monte Carlo calculations for light nuclei.
Wiringa, R. B.
1998-10-23
Quantum Monte Carlo calculations of ground and low-lying excited states for nuclei with A {le} 8 are made using a realistic Hamiltonian that fits NN scattering data. Results for more than 40 different (J{pi}, T) states, plus isobaric analogs, are obtained and the known excitation spectra are reproduced reasonably well. Various density and momentum distributions and electromagnetic form factors and moments have also been computed. These are the first microscopic calculations that directly produce nuclear shell structure from realistic NN interactions.
Introduction to Cluster Monte Carlo Algorithms
NASA Astrophysics Data System (ADS)
Luijten, E.
This chapter provides an introduction to cluster Monte Carlo algorithms for classical statistical-mechanical systems. A brief review of the conventional Metropolis algorithm is given, followed by a detailed discussion of the lattice cluster algorithm developed by Swendsen and Wang and the single-cluster variant introduced by Wolff. For continuum systems, the geometric cluster algorithm of Dress and Krauth is described. It is shown how their geometric approach can be generalized to incorporate particle interactions beyond hardcore repulsions, thus forging a connection between the lattice and continuum approaches. Several illustrative examples are discussed.
Cluster hybrid Monte Carlo simulation algorithms.
Plascak, J A; Ferrenberg, Alan M; Landau, D P
2002-06-01
We show that addition of Metropolis single spin flips to the Wolff cluster-flipping Monte Carlo procedure leads to a dramatic increase in performance for the spin-1/2 Ising model. We also show that adding Wolff cluster flipping to the Metropolis or heat bath algorithms in systems where just cluster flipping is not immediately obvious (such as the spin-3/2 Ising model) can substantially reduce the statistical errors of the simulations. A further advantage of these methods is that systematic errors introduced by th