MadVfold: accelerating NLO event generation and reducing negative weights with SIMD vectorization and GPUsNLO simulations are essential for LHC physics analyses but are expensive, as they are not only slow but also lead to negative weights, which imply the need to simulate much larger samples of events.…Andrea Valassi·Sep 20, 2026SaveLearn
Diff-NekRS: A Scalable Differentiable Framework for Multi-Timestep Solver-in-the-Loop TrainingHybrid physics-machine-learning solvers improve under-resolved simulations by embedding trainable corrections into the time integration. During autoregressive inference, repeated solver-model…Junoh Jung, Riccardo Balin, Bethany Lusch et al.·Sep 19, 2026SaveLearn
Exact ballistic energy transport and emergent XXZ dynamics in an integrable three-state chainWe investigate the coupling dependence of ballistic energy transport and the emergent spin dynamics in an integrable Hermitian three-state chain that connects a clock interaction to a highly…Hanbing Liang, Fujun Liu·Sep 19, 2026SaveLearn
TubeLab: Interactive inverse design of wind instrument bores with hard spectral constraintsWe present TubeLab, a browser-based acoustic simulator and inverse design tool for wind instrument bores without tone holes. The direct problem is solved by a Transfer Matrix Method. Inverse design -…Carlo Andrea Rozzi, Andrea Ferroni·Sep 18, 2026SaveLearn
Stochastic consensus dynamics for decentralized decision systemsA fundamental mechanism underlying collective phenomena in social, technological, and economic systems is decentralized decision-making, in which the behavior of individual agents follows from local…André L. M. Vilela, Caio B. L. Silva, Kenric P. Nelson et al.·Sep 18, 2026SaveLearn
Dirac Cones in d-wave Altermagnets Enable High-Conductivity and High-Efficiency Spin SourcesLow critical charge-current density and low energy dissipation are highly desired in magnetic random-access memories, requiring spin sources to exhibit both high charge-to-spin conversion efficiency…Tianye Yu, Junwen Lai, Peitao Liu et al.·Sep 18, 2026SaveLearn
Perspective on Magnetic Nanoparticle Modeling: Interactions, Timescales and RegimesThe response of magnetic nanoparticles (MNPs) to applied magnetic fields underpins a broad range of biomedical and technological applications. In this Perspective, we review the principal modeling…Deniz Mostarac, Andrey A. Kuznetsov, Manuel Wolfschwenger et al.·Sep 18, 2026SaveLearn
Fundamental Bounds on the Polarizability of Macroscopic ScatterersPolarizability predicts how an object responds to an incident electromagnetic field, the interactions between small particles, or the optical forces exerted upon them. Polarizability is responsible…Lukas Jelinek, Miloslav Capek·Sep 18, 2026SaveLearn
Warp-Geo: Differentiable Geometry Representation for Dynamic-Boundary Simulation and Shape OptimizationModern inverse problems and adaptive simulations require efficient and differentiable representations of complex geometries that can be updated frequently for gradient-based optimization. Existing…Weijie Zhang, Xiantao Fan, Jian-Xun Wang·Sep 17, 2026SaveLearn
How Does Distribution Shift Shape Pretraining Gains in Neural PDE Surrogates?Pretraining a neural PDE surrogate can reduce the amount of new CFD data needed when geometry or modeled physics changes. However, it remains unclear how different components of distribution shift…Pochinapeddi Sai Bhargav, Nithin Somasekharan, Rohit Sunil Kanchi et al.·Sep 17, 2026SaveLearn
Mechanical resilience of ultra-low-density racing-shoe foamsHigh-performance racing shoes rely on ultra-low-density elastomeric foams that undergo large, repeated deformations during running. Yet little is known about how their mechanical properties vary…Jeremy A. McCulloch, Ellen Kuhl·Sep 17, 2026SaveLearn
Correlation-Free Transition Path Sampling through Shooting Point Generation Guided by Committor LearningStudying the dynamical behavior of a system often depends on characterizing how it transitions between long-lived states. Because such transitions are rare, observing them usually requires…Maximilian Negedly, Sebastian Falkner, Alessandro Coretti et al.·Sep 17, 2026SaveLearn
Exergy-Anergy Representation of Turbomachine Performance CharacteristicsThe performance synthesis calculation of aircraft engines relies on tabulated datasets for the simulation of the complex turbomachinery components at acceptable runtimes. Typically, these so-called…Tihomir Varchev, Yiwen Yuan, Tobias Schateikis et al.·Sep 17, 2026SaveLearn
Mollified-sharp decomposition: a probabilistic regularization of parametric POD for shock-bearing flowsThis paper introduces the mollified-sharp decomposition, a probabilistic regularization of moving shocks in parametric reduced-order models. Each detected shock location is treated as a random…Oliver T. Schmidt·Sep 17, 2026SaveLearn
Load balancing for adaptive-precision interatomic potentials in materials scienceFor atomistic molecular dynamics simulations, we consider a recently developed hybrid coupling between the highly accurate machine learning (ML)-based atomic cluster expansion (ACE) interaction model…David Immel, Godehard Sutmann·Sep 16, 2026SaveLearn
Braided endovascular implants for intracranial aneurysms: mechanics, hemodynamics, and clinical translationEndovascular implants prevent intracranial aneurysm rupture by altering the mechanical and hemodynamic environment at the aneurysm neck. Yet many in silico workflows prescribe or reconstruct the…Ratnadeep Pramanik, Duygu Dengiz, Mariya S. Pravdivtseva et al.·Sep 16, 2026SaveLearn
Moment-informed force rescaling for random-batch Langevin dynamicsRandom-batch methods accelerate molecular dynamics by replacing full interaction sums with stochastic force estimators. In Langevin simulations, however, random-batch force errors can cause…Xingguo Wu, Yangshuai Wang, Zhenli Xu·Sep 16, 2026SaveLearn
Van der Waals interactions in supercritical water under Earth's mantle conditionsThe properties of water under high pressure and high temperature (HP-HT) are critical in multiple geochemical processes in deep Earth. Ab initio molecular dynamics (AIMD) is a promising approach to…Jiajia Huang, Rui Hou, Ding Pan·Sep 16, 2026SaveLearn
Fully differentiable framework for inverse identification of geometry and material parameters with application to determining stress-free configuration of soft tissuesMedical images of soft tissues typically depict loaded configurations rather than true unloaded (stress-free) states, which can bias biomechanical simulations and inverse material identification. A…Hyunoh Bae, Tianyi Hu, Adrian Buganza Tepole et al.·Sep 16, 2026SaveLearn
Improved lattice Boltzmann method for conjugate magnetohydrodynamic simulationsIn the simulation of conjugate magnetohydrodynamic (MHD) flows, where a moving conducting fluid dynamically interacts with bounding conducting walls under the influence of an externally imposed…Jun Li, Wai Hong Ronald Chan, Kun Ting Eddie Chua·Sep 16, 2026SaveLearn
A consistent and conservative Phase-Field method for compressible multiphase flows with the six-equation modelIn the present study, the consistent and conservative Phase-Field method is extended to the six-equation model for compressible multiphase flows. Based solely on the conservation laws and the second…Ziyang Huang·Sep 16, 2026SaveLearn
MLegS: A modern mapped Legendre spectral method solver for unbounded domains with parallelizationMLegS is an open-source Modern Fortran code package for solving linear and nonlinear time-dependent partial differential equations on radially unbounded domains. It builds on an earlier in-house…Sangjoon Lee, Jinge Wang·Sep 16, 2026SaveLearn
Machine learning kinetics from molecular dynamics dataMost molecular transitions occur on timescales far beyond direct molecular dynamics simulations. The committor, the probability that a configuration reaches a product state before a reactant state,…Jonathan Weare, Aaron R. Dinner·Sep 15, 2026SaveLearn
Adding slow magnetoacoustic mode to the HLL-type multi-state approximate Riemann solutionMulti-state HLL-type approximate Riemann solutions of ideal magnetohydrodynamics (MHD) typically assume that the medium within the Riemann fan is incompressible, and thus the slow magnetoacoustic…Fan Zhang, Stefaan Poedts, Andrea Lani·Sep 15, 2026SaveLearn
An energy stable and accuracy-preserving finite volume scheme based on the SAV method with application to wall-distance computationA novel semi-implicit second-order finite volume scheme integrating the scalar auxiliary variable (SAV) approach is proposed for solving the pseudo-time Eikonal equation in wall-distance computation.…Xiaorui Xu, Qian Wang·Sep 15, 2026SaveLearn