An intramembranous ossification model for the in-silico analysis of bone tissue formation in tooth extraction sitesThe accurate modeling of biological processes allows to predict the spatio-temporal behavior of living tissues by computer-aided (in-silico) testing, a useful tool for the development of medical…Jennifer Paola Corredor-Gómez, Andrés Mauricio Rueda-Ramírez, Miguel Alejandro Gamboa-Márquez et al.·Feb 9, 2026SaveLearn
dewi-kadita: A Python Library for Idealized Fish Schooling Simulation with Entropy-Based DiagnosticsCollective motion in fish schools exemplifies emergent self-organization in active matter systems, yet computational tools for simulating and analyzing these dynamics remain fragmented across…Sandy H. S. Herho, Iwan P. Anwar, Faruq Khadami et al.·Feb 8, 2026SaveLearn
Compressed Sensing Methods for Memory Reduction in Monte Carlo SimulationsMonte Carlo simulations of neutronic systems are computationally intensive and demand significant memory resources for high-fidelity modeling. Compressed sensing enables accurate reconstruction of…Ethan Lame, Camille Palmer, Todd Palmer et al.·Feb 8, 2026SaveLearn
Surrogate Modeling for Neutron Transport: A Neural Operator ApproachThis work introduces a neural operator based surrogate modeling framework for neutron transport computation. Two architectures, the Deep Operator Network (DeepONet) and the Fourier Neural Operator…Md Hossain Sahadath, Qiyun Cheng, Shaowu Pan et al.·Feb 7, 2026SaveLearn
Event-Chain Monte Carlo: The global-balance breakthroughThe seminal 2009 paper by Bernard, Krauth, and Wilson marked a paradigm shift in Monte Carlo sampling. By abandoning the restrictive condition of detailed balance in favor of the more fundamental…E. A. J. F. Peters·Feb 6, 2026SaveLearn
Development of a single-parameter spring-dashpot rolling friction model for coarse-grained DEMSimulating granular materials composed of non-spherical particles remains a major challenge in discrete element method (DEM) simulations due to the complexity of contact detection and rotational…Putri Mustika Widartiningsih, Yoshiharu Tsugeno, Toshiki Imatani et al.·Feb 6, 2026SaveLearn
The extended gas-kinetic theory from Pullin equation: the relaxation rates, transport coefficients and model equationThe Borgnakke-Larsen model, widely used in rarefied flow predictions, serves as the mainstream energy-exchange kernel for polyatomic gases. However, it lacks integrability and does not guarantee…Sha Liu, Ningchao Ding, Ming Fang et al.·Feb 5, 2026SaveLearn
Numerical Evaluation of Angle-Dependent IR-Transparent Radiative Cooling Performance for Asymmetric Periodic StructuresInfrared (IR)-transparent passive radiative cooling (PRC) enables non-contact thermal management by regulating radiative heat exchange without direct attachment to the cooling object. While…Junwoo Gim, Jun Heo, Weng Cho Chew et al.·Feb 5, 2026SaveLearn
Path Sampling for Rare Events Boosted by Machine LearningThe study by Jung et al. (Jung H, Covino R, Arjun A, et al., Nat Comput Sci. 3:334-345 (2023)) introduced Artificial Intelligence for Molecular Mechanism Discovery (AIMMD), a novel sampling algorithm…Porhouy Minh, Sapna Sarupria·Feb 5, 2026SaveLearn
VR-PIC: An entropic variance-reduction method for particle-in-cell solutions of the Vlasov-Poisson equationWe extend the recently developed entropic and conservative variance reduction framework [M. Sadr, N. G. Hadjiconstantinou, A variance-reduced direct Monte Carlo simulation method for solving the…Victor Windhab, Andreas Adelmann, Mohsen Sadr·Feb 4, 2026SaveLearn
At the Top of the Mountain, the World can Look Boltzmann-Like: Sampling Dynamics of Noisy Double-Well SystemsThe success of the transistor as the cornerstone of digital computation motivates analogous efforts to identify an equivalent hardware primitive, the probabilistic bit or p-bit, for the emerging…Abir Hasan, Nikhil Shukla·Feb 3, 2026SaveLearn
Topology- and Geometry-Exact Coupling for Incompressible Fluids and Thin DeformablesWe introduce a topology-preserving discretization for coupling incompressible fluids with thin deformable structures, achieving guaranteed leakproofness through preservation of fluid domain…Jonathan Panuelos, Eitan Grinspun, David Levin·Feb 3, 2026SaveLearn
Neural Hodge Corrective Solvers: A Hybrid Iterative-Neural FrameworkWe introduce the Neural Hodge Corrective Solver (NHCS), a hybrid iterative-neural framework for partial differential equations that embeds learned corrective operators within the Discrete Exterior…Arjun Puthli, Somdatta Goswami, Souvik Chakraborty·Feb 3, 2026SaveLearn
Semi-implicit Lax-Wendroff kinetic scheme for electron-phonon couplingA semi-implicit Lax-Wendroff scheme is developed for electron-phonon coupling process in metals based on the two-temperature kinetic equations. The core of this method is to integrate the evolution…Jiaming Li, Hong Liang, Meng Lian et al.·Feb 1, 2026SaveLearn
Accelerated Markov Chain Monte Carlo Simulation via Neural Network-Driven Importance SamplingAtomistic simulations provide valuable insights into the physical processes governing material behavior. However, their applicability is fundamentally constrained by the limited time scales…Michael Kim, Wei Cai·Jan 31, 2026SaveLearn
A new model for two-layer liquid-gas stratified flows in pipes with general cross sectionsIn this work, we derive a new model for immiscible two-layer gas-liquid stratified flows in pipes with general cross sections. The bottom layer is occupied by an incompressible fluid in liquid phase…Sarswati Shah, Gerardo Hernández-Dueñas·Jan 31, 2026SaveLearn
Addressing the ground state of the deuteron by physics-informed neural networksMachine learning techniques have proven to be effective in addressing the structure of atomic nuclei. Physics-Informed Neural Networks (PINNs) are a promising machine learning technique suitable…Lorenzo Brevi, Antonio Mandarino, Carlo Barbieri et al.·Jan 30, 2026SaveLearn
Stochastic Point Kinetics Model of Circulating-Fuel Reactors under Perfect Mixing ApproximationWe present a stochastic framework for low-population dynamics in circulating-fuel reactors (CFRs) that captures delayed-neutron precursor (DNP) transport without delay terms. Starting from a modified…Lubomír Bureš, Valeria Raffuzzi·Jan 30, 2026SaveLearn
UniPhy: Unifying Riemannian-Clifford Geometry and Biorthogonal Dynamics for Planetary-Scale Continuous Weather ModelingWhile data-driven weather models have achieved remarkable deterministic accuracy, they fundamentally rely on discrete-time mappings and closed-system assumptions, failing to capture the multi-scale…Ruiqing Yan, Haoyu Deng, Yuhang Shao et al.·Jan 29, 2026SaveLearn
Semi-implicit Lax-Wendroff kinetic scheme for hydrodynamic phonon transportA semi-implicit Lax-Wendroff kinetic scheme is developed for hydrodynamic phonon transport in solid materials based on the Boltzmann transport equation under the double relaxation time approximation,…Shijie Li, Hong Liang, Songze Chen et al.·Jan 29, 2026SaveLearn
Two-Step Diffusion: Fast Sampling and Reliable Prediction for 3D Keller--Segel and KPP Equations in Fluid FlowsWe study fast and reliable generative transport for the 3D KS (Keller-Segel) and KPP (Kolmogorov-Petrovsky-Piskunov) equations in the presence of fluid flows with the goal to approximate the map…Zhenda Shen, Zhongjian Wang, Jack Xin et al.·Jan 27, 2026SaveLearn
diffpy.morph: Python tools for model independent comparisons between sets of 1D functionsdiffpy.morph addresses a need to gain scientific insights from 1D scientific spectra in model independent ways. A powerful approach for this is to take differences between pairs of spectra and look…Andrew Yang, Christopher L. Farrow, Pavol Juhás et al.·Jan 27, 2026SaveLearn
DISCOVER: A Physics-Informed, GPU-Accelerated Symbolic Regression FrameworkSymbolic Regression (SR) enables the discovery of interpretable mathematical relationships from experimental and simulation data. These relationships are often coined descriptors which are defined as…Udaykumar Gajera, Mohsen Sotoudeh, Kanchan Sarkar et al.·Jan 27, 2026SaveLearn
Rimu.jl: Random integrators for many-body quantum systemsRimu.jl is a Julia package for solving many-body quantum problems. The core of the package is a matrix-free implementation of Hamiltonians and other operators and compact representation of Fock…Matija Čufar, C. J. Bradly, Ray Yang et al.·Jan 27, 2026SaveLearn
Transformer Learning of Chaotic Collective Dynamics in Many-Body SystemsLearning reduced descriptions of chaotic many-body dynamics is fundamentally challenging: although microscopic equations are Markovian, collective observables exhibit strong memory and exponential…Ho Jang, Gia-Wei Chern·Jan 27, 2026SaveLearn