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Related Articles from SNS
A Diffusion Monte Carlo algorithm employing depth first traversal and a stack instead of a swarm
arXiv:2606.08946v1 Announce Type: cross Abstract: Diffusion Monte Carlo (DMC) and Monte Carlo for particle transport with importance sampling both involve simulations of weighted walkers that undergo birth and death processes (splitting and Russian Roulette). The established implementations of these methods are quite different: Particle simulation Monte Carlo employs a stack to handle the splitting history whereas in traditional DMC one follows a swarm of walkers. The particle simulation...
GPU optical photon Monte Carlo for noble liquid detectors: validation against Geant4 in a large liquid argon TPC benchmark
Announce Type: replace Abstract: Optical photon Monte Carlo simulation is a computational bottleneck for noble liquid Time Projection Chambers. Design studies require repeated, geometry dependent simulations of timing, wavelength shifting, and optical response, while reconstruction and particle identification workflows need labeled optical datasets. We present Simphony, a GPU optical simulation tool, formerly EIC-Opticks, built on Opticks with CUDA and NVIDIA OptiX. Simphony implements a GPU...
GPU optical photon Monte Carlo for noble liquid detectors: validation against Geant4 in a large liquid argon TPC benchmark
Announce Type: new Abstract: Optical photon Monte Carlo simulation is a computational bottleneck for noble liquid Time Projection Chambers. Design studies require repeated, geometry dependent simulations of timing, wavelength shifting, and optical response, while reconstruction and particle identification workflows need labeled optical datasets. We present Simphony, a GPU optical simulation tool, formerly EIC-Opticks, built on Opticks with CUDA and NVIDIA OptiX. Simphony implements a GPU...
Optimality of quasi-Monte Carlo methods and suboptimality of the sparse-grid Gauss--Hermite rule in Gaussian Sobolev spaces
Announce Type: replace Abstract: Optimality of several quasi-Monte Carlo methods and suboptimality of the sparse-grid quadrature based on the univariate Gauss--Hermite rule is proved in the Sobolev spaces of mixed dominating smoothness of order $\alpha$, where the optimality is in the sense of worst-case convergence rate. For sparse-grid Gauss--Hermite quadrature, lower and upper bounds are established, with rates coinciding up to a logarithmic factor. The dominant rate is found to be only...
Reinforced sequential Monte Carlo for amortised sampling
arXiv:2510.11711v2 Announce Type: replace Abstract: This paper proposes a synergy of amortised and particle-based methods for sampling from distributions defined by unnormalised density functions. We state a connection between sequential Monte Carlo (SMC) and neural sequential samplers trained by maximum-entropy reinforcement learning (MaxEnt RL), wherein learnt sampling policies and value functions define proposal kernels and twist functions. Exploiting this connection, we introduce an...
Towards stable and accurate electron dynamics via neural network based time-dependent variational Monte Carlo
arXiv:2606.05850v1 Announce Type: new Abstract: Real-time dynamics of interacting electrons lies at the interface between quantum mechanics and non-equilibrium physics, governing the microscopic origin of ultrafast phenomena of molecules and nano-materials. Though neural network variational Monte Carlo has achieved unprecedented accuracy for stationary state calculations, its extension to real-time evolution remains challenging. In this work, we introduce the neural basis time-dependent...
Multi-GPU Hybrid Particle-in-Cell Monte Carlo Simulations for Exascale Computing Systems
arXiv:2603.24508v3 Announce Type: replace Abstract: Particle-in-Cell (PIC) Monte Carlo (MC) simulations are central to plasma physics but face increasing challenges on heterogeneous HPC systems due to excessive data movement, synchronization overheads, and inefficient utilization of multiple accelerators. In this work, we present a portable, multi-GPU hybrid MPI+OpenMP implementation of BIT1 that enables scalable execution on both Nvidia and AMD accelerators through OpenMP target tasks with...
Deep Learning-Accelerated Dynamic Kinetic Monte Carlo Simulation for Hydrogen Transport in Tungsten
arXiv:2606.02084v2 Announce Type: replace-cross Abstract: In magnetic confinement fusion reactors, hydrogen plasma irradiation causes material saturation and recycling, where hydrogen released from the tungsten wall significantly impacts the peripheral plasma. Kinetic Monte Carlo (kMC) simulations are essential for investigating the dynamic balance between incident and emitted fluxes at the atomic scale. However, standard kMC frameworks are inadequate for handling realistic material...
A geometric $q$-analogue of Hamiltonian Monte Carlo
arXiv:2512.13246v3 Announce Type: replace Abstract: Hamiltonian Monte Carlo (HMC) generates efficient Markov transitions by combining Hamiltonian dynamics with a Metropolis correction. This paper develops a geometric \(q\)-analogue of HMC by replacing classical Hamiltonian dynamics with a \(q\)-deformed Hamiltonian system arising from \(q\)-calculus. Starting from a Lagrangian formulation, we derive the corresponding \(q\)-Hamiltonian equations and prove the formal invariance of the...
Mobility Heterogeneity in a 2D Gaussian Lattice Polymer: A Dynamic Monte Carlo Study
Announce Type: cross Abstract: We study mobility heterogeneity in a two-dimensional Gaussian lattice polymer using dynamic Monte Carlo simulations. The polymer dynamics is generated from a local three-monomer move dictionary, which explicitly enumerates allowed bond-preserving updates on a square lattice. As a homogeneous benchmark, this dictionary reproduces the expected Rouse-like behavior of an ideal chain, including the crossover in monomer mean-squared displacement (MSD) and the...