Contrastive learning of dynamical representations for enhanced molecular samplingIdentifying collective variables that capture slow dynamical modes is essential for sampling rare events in complex systems. Existing machine-learning approaches often require predefined metastable…Kai Zhu, Jintu Zhang, Pietro Novelli et al.·Jun 22, 2026SaveLearn
An Oscillation-Free Real Fluid Quasi-Conservative Finite Volume Method for Transcritical and Phase-Change FlowsA new Real Fluid Quasi-Conservative (RFQC) finite volume method is developed to address the numerical simulation of real fluids involving shock waves in transcritical and phase-change flows. To…Haotong Bai, Wenjia Xie, Yixin Yang et al.·Jun 22, 2026SaveLearn
Inverse Identification of Surface Elastic Parameters in Soft Solids Using GA-ANN Surrogate ModelSurface elasticity plays a crucial role in the mechanics of soft solids at the scale of micrometers and may become significant even at the scale of millimeters in exceptional cases. However, despite…Md. Ayaz, Abhishek Ghosh, Andrew McBride et al.·Jun 20, 2026SaveLearn
Observations Regarding the Construction of Multipoint Kinetics Models from Observational DataThe multipoint kinetics (MPK) equations extend point kinetics models by tracking neutron populations in lumped reactor regions, offering improved spatial resolution at modest computational cost.…K. G. Howey, Giorgio Valocchi, Dean Price·Jun 19, 2026SaveLearn
AI-accelerated metallized σ-bonding screening for superconductor discoveryThe computational discovery of phonon-mediated superconductors is hindered by the prohibitive cost of density functional perturbation theory (DFPT). Here, guided by the metallized σ-bonding…Zechen Tang, Wen-Han Dong, Baochun Wu et al.·Jun 19, 2026SaveLearn
Physics-Informed Neural Networks for coupled stiff transport systemsPurpose: Physics-Informed Neural Networks (PINNs) struggle with stiff, regime-changing transport equations due to instability, loss imbalance, and violations of physical consistency. This paper…Laetitia Laguzet, Gabriel Turinici·Jun 19, 2026SaveLearn
Data-driven time-dependent bases for turbulent airfoil wake-extreme gust interactionsWe analyze interactions between turbulent airfoil wakes and extreme gusts using a data-driven framework with time-dependent bases. The current approach represents each snapshot with time-varying…Shaghayegh Zamani Ashtiani, Kai Fukami·Jun 19, 2026SaveLearn
A Social Force Model of the Evacuation from a Big Box StoreWe include elliptical cross-sections to physically represent people, and irregular polygons to represent wheelchair users, in an anisotropic social force model whose velocity and angular dependence…Gavin A. Buxton·Jun 18, 2026SaveLearn
Advancing Threshold-Inception Modeling for Predictive Simulation of Ionic Wind Fan PerformanceThis study investigates the predictive capability of a threshold inception-based multiphysics modeling approach for ionic wind fans by direct comparison with experimental measurements. A…Siim Heering, Juri Volodin, Vootele Mets et al.·Jun 18, 2026SaveLearn
The Heat Kernel Expansion: Curvature for Shock Detection in Higher-Order Financial NetworksThis work follows the evolution of financial networks in Norway over a period of nine years at a monthly rate. The data consist of board directors and their affiliations to companies, which we model…Mohammad Elsayed, Sara Najem·Jun 18, 2026SaveLearn
An adaptive framework for the axisymmetric pulsar magnetosphere using physics-informed Kolmogorov-Arnold networksThe pulsar magnetosphere has only recently been addressed using Physics-Informed Neural Networks (PINNs), by deploying a domain-decomposition approach and treating the separatrix and equatorial…Spyros Rigas, Ioannis Contopoulos, Georgios Alexandridis et al.·Jun 18, 2026SaveLearn
On the Fast Fourier Transform on SU(2)The special unitary group SU(2) plays a fundamental role in the description of symmetries in quantum mechanics, theoretical physics, and spherical signal processing. In this paper, we address the…Julio Delgado, Alejandro Umaña·Jun 18, 2026SaveLearn
A deep learning framework for jointly solving transient Fokker-Planck equations with arbitrary parameters and initial distributionsEfficiently solving the Fokker-Planck equation (FPE) is central to analyzing complex parameterized stochastic systems. However, current numerical methods lack parallel computation capabilities across…Xiaolong Wang, Jing Feng, Qi Liu et al.·Jun 18, 2026SaveLearn
A complete phase-field fracture model for brittle materials subjected to thermal shocksBrittle materials subjected to thermal shocks experience strong temperature gradients that in turn give rise to mechanical stresses that can be large enough to induce fracture. This work presents a…Bo Zeng, John E. Dolbow·Jun 18, 2026SaveLearn
TorchNEP: Ultra-Efficient and Accurate Training of Neuroevolution PotentialsNeuroevolution Potential (NEP) is one of the most efficient machine-learned interatomic potential frameworks for large-scale atomistic simulations. However, its original training strategy remains…Yong-Chao Wu, Xiaoya Chang, Tero Mäkinen et al.·Jun 17, 2026SaveLearn
sft-wick: A formalism and package for Feynman-diagram expansion and evaluation in stochastic field theoriesWhen stochastic field dynamics are cast into a path-integral formulation, perturbation theory becomes systematic but the resulting expansion quickly grows combinatorially large. The setting targeted…Zheng Zhang·Jun 17, 2026SaveLearn
Acceleration of an algebraic multigrid pressure solver using graph neural networksSolving the pressure-Poisson equation remains the primary computational bottleneck in incompressible unstructured flow solvers primarily due to the inherent sensitivity of traditional linear solvers…Eric Chillón, Artur K. Lidtke, Nguyen Anh Khoa Doan et al.·Jun 17, 2026SaveLearn
Discovering a well-conditioned analytic continuation problem via dictionary learningMany fields of physics use quantum Monte Carlo (QMC) simulations to simulate quantum systems in imaginary-time τ and estimate imaginary-time correlation functions (ITCF). However, extracting…Thomas Chuna, Phil-Alexander Hofmann, Alexander Benedix-Robles et al.·Jun 17, 2026SaveLearn
Extension of a multi-region free-surface MHD solver beyond the inductionless approximationFree-surface liquid metal flows are a leading candidate for the plasma-facing components of future fusion reactors. Existing transient, three-dimensional, free-surface MHD solvers rely on the…Min Ki Jung, Brian Wynne, Francisco Saenz et al.·Jun 17, 2026SaveLearn
Characterization of Thermal Systems from Noisy and Low-resolution Measurements Using Dynamic Mode DecompositionThermal monitoring in practical applications is often constrained by sparse sensing, measurement noise, and limited spatial resolution, which hinder the identification of heat transfer dynamics. In…M. E. P. Silva, L. S. Araujo, F. T. Colombo et al.·Jun 16, 2026SaveLearn
Singular Vector Finite Element Basis Functions for Tetrahedra in Complex Electromagnetic GeometriesElectromagnetic finite element method (FEM) implementations using traditional basis functions struggle to accurately represent field behavior near singular features such as conducting wedges. To…Samuel T. Elkin, Ghazi Khan, Ebrahim Forati et al.·Jun 16, 2026SaveLearn
High-Order Simulation of Particle-Laden Flows in Moving Domains Using Coupled ALE and Sliding Mesh ApproachesIn practical applications, compressible particle-laden flows in moving geometries involve complex, non-linear, and multi-scale inter-actions with turbulent structures. Resolving these dynamics…Anna Schwarz, Patrick Kopper·Jun 16, 2026SaveLearn
Latent Residual-Closure Fourier Neural Operator for Robust Multi-Field Solving in Particle-in-Cell SimulationsParticle-in-cell (PIC) simulations are widely used for kinetic plasma modeling in energy applications, but their efficiency is often limited by repeated field solves on dense meshes. This work…Jianhua Lyu, Linlin Zhong·Jun 16, 2026SaveLearn
Constitutive modelling of magneto-active polymers at finite strains: A surveyMagneto-active polymers (MAPs) are field-responsive soft composites whose mechanical behaviour can be actively modified by external magnetic fields. Their ability to exhibit field-induced stiffening,…Abhishek Ghosh, Chennakesava Kadapa, Mokarram Hossain·Jun 16, 2026SaveLearn
Estimation of Dielectric Parameters from Ultrasound Waves in Quantitative Thermoacoustic TomographyThermoacoustic tomography (TAT) is an imaging technique based on the thermoacoustic effect, combining electromagnetic contrast and high resolution of ultrasound imaging. In TAT, a short micro- or…Teemu Sahlström, Tanja Tarvainen·Jun 16, 2026SaveLearn