Related papers: A Monte Carlo simulation and collimator optimizati…
The results of Monte Carlo Simulation (MCS) studies of Most likely position (MLP) and position vector (PV) methods in TOFPET system are presented. MCS based on GEANT3.21 is carried out where the geometry of a real TOFPET system is…
Purpose: Handheld gamma cameras with coded aperture collimators are under investigation for intraoperative imaging in nuclear medicine. Coded apertures are a promising collimation technique for applications such as lymph node localization…
A new approach to simulating rotational cooling using a direct simulation Monte Carlo (DSMC) method is described and applied to the rotational cooling of ammonia seeded into a helium supersonic jet. The method makes use of ab initio…
New manufacturing techniques such as 3D printing have recently enabled the creation of previously infeasible chemical reactor designs. Optimizing the geometry of the next generation of chemical reactors is important to understand the…
Due to the complex characteristics of bottle-brush polymers, it became a challenge to develop an efficient algorithm for studying such macromolecules under various solvent conditions or some constraints in the space by using computer…
A general purpose, self-adapting, Monte Carlo (MC) event generator (simulator) is described. The high efficiency of the MC, that is small maximum weight or variance of the MC weight is achieved by means of dividing the integration domain…
Numerical simulations of models and theories that describe complex systems such as spin glasses are becoming increasingly important. Beyond fundamental research, these computational methods also find practical applications in fields like…
Disordered lattice spin systems are crucial in both theoretical and applied physics. However, understanding their properties poses significant challenges for Monte Carlo simulations. In this work, we investigate the two-dimensional…
We analyze and compare the computational complexity of different simulation strategies for Monte Carlo in the setting of classically scaled population processes. This allows a range of widely used competing strategies to be judged…
Parallel hole collimators which are currently routinely used in SPECT imaging were designed a few decades ago, when filtered backprojection (FBP) was used for tomographic reconstruction. Statistical reconstruction methods with precise…
We present a new quantum Monte Carlo algorithm suitable for generically complex problems, such as systems coupled to external magnetic fields or anyons in two spatial dimensions. We find that the choice of gauge plays a nontrivial role, and…
We present a new implementation of the Monte Carlo method to simulate the evolution of star clusters. The major improvement with respect to the previously developed codes is the treatment of the external tidal field taking into account for…
The Self-Learning Monte Carlo (SLMC) method is a Monte Carlo approach that has emerged in recent years by integrating concepts from machine learning with conventional Monte Carlo techniques. Designed to accelerate the numerical study of…
We present a new, for plasma physics, highly efficient multilevel Monte Carlo numerical method for simulating Coulomb collisions. The method separates and optimally minimizes the finite-timestep and finite-sampling errors inherent in the…
One bottleneck of quantum Monte Carlo (QMC) simulation of strongly correlated electron systems lies at the scaling relation of computational complexity with respect to the system sizes. For generic lattice models of interacting fermions,…
During the last decades, neutron beam transportation has been a well-known and established subject for designing proper neutron guides. However, sometimes unusual adaptation or adjustments are required out of original projects and after…
In this paper we investigate, with a detailed Monte-Carlo simulation based on Geant4, the novel approach [Nucl. Instrum. Methods A588 (2008) 457] to 3D imaging with photon scattering. A monochromatic and well collimated gamma beam is used…
Training deep learning models for corneal optical coherence tomography (OCT) imaging is limited by the availability of large, well-annotated datasets. We present a configurable Monte Carlo simulation framework that generates synthetic…
Understanding the properties of the hot corona is important for studying the accretion disks in black hole X-ray binary systems. Using the Monte-Carlo technique to simulate the inverse Compton scattering between photons emitted from the…
We design and implement HPMC, a scalable hard particle Monte Carlo simulation toolkit, and release it open source as part of HOOMD-blue. HPMC runs in parallel on many CPUs and many GPUs using domain decomposition. We employ BVH trees…