On the rank-reduced relativistic coupled cluster methodAn efficiency of the Tucker decomposition of amplitude tensors within the single-reference relativistic coupled cluster method with single and double excitations (RCCSD) was studied in a series of…Alexander V. Oleynichenko, Artem S. Rumiantsev, Andrei Zaitsevskii et al.·Jun 26, 2025SaveLearn
Resolvent4py: a parallel Python package for analysis, model reduction and control of large-scale linear systemsIn this paper, we present resolvent4py, a parallel Python package for the analysis, model reduction and control of large-scale linear systems with millions or billions of degrees of freedom. This…Alberto Padovan, Vishal Anantharaman, Clarence W. Rowley et al.·Jun 25, 2025SaveLearn
Efficient calculation of thermodynamic properties of baryon-rich QCD matter from heavy-ion transport modelsThis study presents the MATRICS framework (Modeling Aggregated Tensors for Relativistic Ion Collision Simulations) that implements modular workflows to enable parallel execution of particle…Lipei Du·Jun 24, 2025SaveLearn
From Brownian dynamics to Poisson-Nernst-Planck equations: multi-resolution simulations of ionsStarting with a microscopic (individual-based) Brownian dynamics model of charged particles (ions), its macroscopic description is derived as a system of partial differential equations that govern…Jinyuan Zhang, Radek Erban·Jun 24, 2025SaveLearn
A Machine Learning Framework for Scattering Kernel Derivation Using Molecular Dynamics Data in Very Low Earth OrbitThe free molecular flow regime in VLEO makes gas-surface interactions (GSIs) crucial for satellite aerodynamic modeling. The Direct Simulation Monte Carlo (DSMC) method is required to estimate…Miklas Schütte, Stephen Hocker, Hansjörg Lipp et al.·Jun 24, 2025SaveLearn
Optimized auxiliary functions for robust mitigation of finite-size errors in periodic hybrid density functional theoryWhen calculating properties of periodic systems at the thermodynamic limit (TDL), the dominant source of finite size error (FSE) arises from the long-range Coulomb interaction, and can manifest as a…Stephen Jon Quiton, Juan D. F. Pottecher, Xin Xing et al.·Jun 23, 2025SaveLearn
ECLEIRS: Exact conservation law embedded identification of reduced states for parameterized partial differential equations from sparse and noisy dataMulti-query applications such as parameter estimation, uncertainty quantification and design optimization for parameterized PDE systems are expensive due to the high computational cost of…Aviral Prakash, Ben S. Southworth, Marc L. Klasky·Jun 23, 2025SaveLearn
Quantifying Gibbs measures of disordered crystals up to the solid-liquid phase transitionQuantifying the configuration space and the Gibbs measure of thermally disordered condensed matter systems has been a long standing problem. The challenge is to avoid the Gibbs paradox, which forbids…Vladislav Efremkin, Julian Heske, Thomas D. Kühne et al.·Jun 22, 2025SaveLearn
Stochastic dynamics simulation of the focused electron beam induced deposition processThis work reports on the development of a new approach to the multiscale computational modelling of the focused electron beam-induced deposition (FEBID), realised using the advanced software…Ilia A. Solov'yov, Alexey Prosvetov, Gennady Sushko et al.·Jun 22, 2025SaveLearn
JAX-LaB: A High-Performance, Differentiable, Lattice Boltzmann Library for Modeling Multiphase Fluid Dynamics in Geosciences and EngineeringWe introduce JAX-LaB, a differentiable, Python-based Lattice Boltzmann simulation library designed for modeling multiphase and multiphysics fluid dynamics problems in hydrologic, geologic, and…Piyush Pradhan, Pierre Gentine, Shaina Kelly·Jun 21, 2025SaveLearn
Refining Tc Prediction in Hydrides via Symbolic-Regression-Enhanced Electron-Localization-Function-Based DescriptorsHydrogen-based materials are able to possess extremely high superconducting critical temperatures, s, due to hydrogen's low atomic mass and strong electron-phonon interaction. Recently, a…Francesco Belli, Sean Torres, Julia Contreras-Garcìa et al.·Jun 20, 2025SaveLearn
PCG-Informed Neural Solvers for High-Resolution Homogenization of Periodic MicrostructuresThe mechanical properties of periodic microstructures are pivotal in various engineering applications. Homogenization theory is a powerful tool for predicting these properties by averaging the…Yu Xing, Yang Liu, Lipeng Chen et al.·Jun 20, 2025SaveLearn
Great Restraining Wall in Multidimensional Collective Variable SpaceEnhanced sampling methods are pivotal for exploring rare events in molecular dynamics (MD), yet face challenges in high-dimensional collective variable (CV) spaces where exhaustive sampling becomes…Zhijun Pan, Maodong Li, Dechin Chen et al.·Jun 20, 2025SaveLearn
A Neural Operator based Hybrid Microscale Model for Multiscale Simulation of Rate-Dependent MaterialsThe behavior of materials is influenced by a wide range of phenomena occurring across various time and length scales. To better understand the impact of microstructure on macroscopic response,…Dhananjeyan Jeyaraj, Hamidreza Eivazi, Jendrik-Alexander Tröger et al.·Jun 20, 2025SaveLearn
Acceleration of the CASINO quantum Monte Carlo software using graphics processing units and OpenACCWe describe how quantum Monte Carlo calculations using the CASINO software can be accelerated using graphics processing units (GPUs) and OpenACC. In particular we consider offloading Ewald summation,…B. Thorpe, M. J. Smith, P. J. Hasnip et al.·Jun 19, 2025SaveLearn
UGKWP and IUGKP methods for Multi-Scale Phonon Transport with Dispersion and PolarizationThis paper presents two novel methods for solving multi-scale phonon transport problems with dispersion and polarization effects: the unified gas-kinetic wave-particle (UGKWP) method and the implicit…Hongyu Liu, Xiaojian Yang, Chuang Zhang et al.·Jun 19, 2025SaveLearn
Optimal Navigation in Microfluidics via the Optimization of a Discrete LossOptimal path planning and control of microscopic devices navigating in fluid environments is essential for applications ranging from targeted drug delivery to environmental monitoring. These tasks…Petr Karnakov, Lucas Amoudruz, Petros Koumoutsakos·Jun 18, 2025SaveLearn
An Atomic Cluster Expansion Potential for Twisted Multilayer GrapheneTwisted multilayer graphene, characterized by its moir\'e patterns arising from inter-layer rotational misalignment, serves as a rich platform for exploring quantum phenomena. Machine learning…Yangshuai Wang, Drake Clark, Sambit Das et al.·Jun 18, 2025SaveLearn
Improved energies and wave function accuracy with Weighted Variational Monte CarloNeural network parametrizations have increasingly been used to represent the ground and excited states in variational Monte Carlo (VMC) with promising results. However, traditional VMC methods only…Huan Zhang, Robert J. Webber, Michael Lindsey et al.·Jun 17, 2025SaveLearn
Quantized local reduced-order modeling in time (ql-ROM)Spatiotemporally chaotic systems, such as the solutions of some nonlinear partial differential equations, are dynamical systems that evolve toward a lower dimensional manifold. This manifold has an…Antonio Colanera, Luca Magri·Jun 16, 2025SaveLearn
Latent Representation Learning of Multi-scale Thermophysics: Application to Dynamics in Shocked Porous Energetic MaterialCoupling of physics across length and time scales plays an important role in the response of microstructured materials to external loads. In a multi-scale framework, unresolved (subgrid) meso-scale…Shahab Azarfar, Joseph B. Choi, Phong CH. Nguyen et al.·Jun 15, 2025SaveLearn
Analytical coarse grained potential parameterization by Reinforcement Learning for anisotropic celluloseCellulose nanocrystals (CNCs) are a type of cellulose with excellent mechanical performance and other merit attributes. According to previous reports, hydrogen bonds play a pivotal role in the…Xu Dong·Jun 15, 2025SaveLearn
Adaptive criterion and modification of wave-particle decomposition in UGKWP method for high-speed flow simulationBenefitting from the direct modeling of physical laws in a discretized space and the automatic decomposition of hydrodynamic waves and particles, the unified gas-kinetic wave-particle (UGKWP) method…Junzhe Cao, Yufeng Wei, Wenpei Long et al.·Jun 15, 2025SaveLearn
Data-Driven Surrogate Modeling of DSMC Solutions Using Deep Neural NetworksThis study presents a deep neural network (DNN) framework that accelerates Direct Simulation Monte Carlo (DSMC) computations for rarefied-gas flows, while maintaining high physical fidelity. First, a…Ehsan Roohi, Ahmad Shoja-sani·Jun 14, 2025SaveLearn
The Software Landscape for the Density Matrix Renormalization GroupThe density matrix renormalization group (DMRG) algorithm is a cornerstone computational method for studying quantum many-body systems, renowned for its accuracy and adaptability. Despite DMRG's…Per Sehlstedt, Jan Brandejs, Paolo Bientinesi et al.·Jun 14, 2025SaveLearn