Related papers: PyNMC: An Open-Source Framework for Neutron Multip…
Mathematical models in computational physics contain uncertain parameters that impact prediction accuracy. In turbulence modeling, this challenge is especially significant: Reynolds averaged Navier-Stokes (RANS) models, such as the…
We present a Nested Markov chain Monte Carlo (NMC) scheme for building equilibrium averages based on accurate potentials such as density functional theory. Metropolis sampling of a reference system, defined by an inexpensive but approximate…
Average-atom models are an important tool in studying matter under extreme conditions, such as those conditions experienced in planetary cores, brown and white dwarfs, and during inertial confinement fusion. In the right context,…
Nuclear fission reactors are abundant sources of antineutrinos. The flux and spectrum of antineutrinos emitted by a reactor can indicate its activity and composition, suggesting potential applications of neutrino measurements beyond…
Numba is a game-changing compiler for high-performance computing with Python. It produces machine code that runs outside of the single-threaded Python interpreter and that fully utilizes the resources of modern CPUs. This means support for…
Predictive simulations and experimental design involving extreme aero-chemo-thermo-mechanical regimes require high-fidelity material representation across diverse physical states. However, data for metals, polymers, and propellants,…
We present OpenMM-Python-Force, a plugin designed to extend OpenMM's functionality by enabling integration of energy and force calculations from external Python programs via a callback mechanism. During molecular dynamics simulations, data…
Plasma-neutral interactions, including reactive kinetics, are often either studied in 0D using ODE based descriptions, or in multi-dimensional fluid or particle based plasma codes. The latter case involves a complex assembly of procedures…
Analog in-memory computing (AIMC) cores offers significant performance and energy benefits for neural network inference with respect to digital logic (e.g., CPUs). AIMCs accelerate matrix-vector multiplications, which dominate these…
Multilevel Monte Carlo (MLMC) reduces the total computational cost of financial option pricing by combining SDE approximations with multiple resolutions. This paper explores a further avenue for reducing cost and improving power efficiency…
The high-performance computing (HPC) community has recently seen a substantial diversification of hardware platforms and their associated programming models. From traditional multicore processors to highly specialized accelerators, vendors…
Radiomics enables the extraction of quantitative biomarkers from medical images for precision modeling, but reproducibility and scalability remain limited due to heterogeneous software implementations and incomplete adherence to standards.…
Monte Carlo (MC) neutron transport provides detailed estimates of radiological quantities within fission reactors. This involves tracking individual neutrons through a computational geometry. CPU-based MC codes use multiple polymorphic…
Australia's New Payments Platform (NPP) processes 5.2 million real-time transactions per day under a 2,000 ms SLA. With cryptographically relevant quantum computers projected by 2030-2035 and the Harvest Now, Decrypt Later (HNDL) threat…
Electrochemical energy storage always involves the capacitive process. The prevailing electrode model used in the molecular simulation of polarizable electrode-electrolyte systems is the Siepmann-Sprik model developed for perfect metal…
Quantifying inherent neutron sources in matter, particularly $(\alpha, n)$ reactions and spontaneous fission, is important in nuclear engineering and other fields. The SOURCES code is a common tool for calculating the yield and spectrum of…
Finding a software engineering approach that allows for portability, rapid development, and open collaboration for high-performance computing on GPUs and CPUs is a challenge. We implement a portability scheme using the Numba compiler for…
We present and discuss the characteristics and performances, both in term of computational speed and precision, of a numerical code which numerically integrates the equation of motions of N 'particles' interacting via Newtonian gravitation…
Over the past decade, the Python-based Simulations of Chemistry Framework (PySCF) has developed into a widely used open-source platform for electronic structure theory and quantum chemical method development. This article reviews the major…
Precise measurements of parameters in the PMNS framework might lead to new physics beyond the Standard Model. However, they are incredibly challenging to determine in neutrino oscillation experiments. Quantum simulations can be a powerful…