Reconstructing local environments from concise atomistic representationsSymmetry-based representations of local atomic structure, such as the power spectrum or bispectrum, are routinely used to characterize the structural diversity of datasets and as input features for…Jigyasa Nigam, Tuong Phung, Ameya Daigavane et al.·Jul 22, 2026SaveLearn
Bayesian Inference: Kernel-Based Model for Surface Temperature Reconstruction in Ice Borehole ThermometryReconstructing past surface temperature from shallow ice borehole temperature profiles requires solving an ill-posed inverse problem while quantifying uncertainties arising from measurements and…Kshema Shaju, Thomas Laepple, Peter Zaspel·Jul 22, 2026SaveLearn
Dynamical and Optimization Trade-offs of Levi--Civita Coordinates for Learned Close-Encounter DynamicsClassical regularization removes the binary-collision singularity from the Kepler problem, but its value as a representation for learned Hamiltonian dynamics has not been systematically isolated. We…Abhishek Shankar·Jul 22, 2026SaveLearn
Mind the Gap: Where Analog Ising Machines Cease to Minimize the Ising HamiltonianThe design of nonlinear dynamical systems whose gradient flows minimize the Ising Hamiltonian has emerged as a compelling paradigm for realizing Ising machines, forming the foundation of…E. M. Hasantha Ekanayake, Arvind R. Venkatakrishnan, Francesco Bullo et al.·Jul 22, 2026SaveLearn
Variational Learning of Physical Intuition from a Few Observations: Charting Manifolds of Variational PhysicsHumans often generalize physical outcomes from few observations, a desirable capacity known as physical intuition. We show that it can be computationally approached through charting the manifolds of…Jingruo Peng, Shuze Zhu·Jul 22, 2026SaveLearn
An interaction potential method for passive and active dynamics of hyperelastic materialsSimulating active biological tissues, such as the myocardium, requires constitutive models that are both physically faithful and computationally efficient. The most common approach relies on finite…Francesco De Vita, Filippo Caruso Lombardi, Roberto Verzicco et al.·Jul 21, 2026SaveLearn
Random site percolation with complex neighborhoods in five dimensionIn this paper, the random site percolation problem in a five-dimensional space for complex neighborhoods is studied. The efficient C++ code (with ordinary work division) of the classical Newman--Ziff…Krzysztof Malarz, Maciej Wołoszyn·Jul 21, 2026SaveLearn
Uncertainty quantification in mechanics: A unified Bayesian perspectiveUncertainty quantification (UQ) is essential to experimental mechanics, but has become particularly relevant in computational mechanics, manifesting in two fundamental problem types: forward and…Sascha Ranftl, Malte Rolf, Gerhard A. Holzapfel et al.·Jul 21, 2026SaveLearn
Isochoric thermodynamic preconditioning for resolving mechanically induced phase change in fractured porous mediaRapid pore-volume changes can trigger phase change on timescales shorter than characteristic transport times and may therefore be skipped by conventional nonlinear solves and adaptive time stepping.…Veljko Lipovac, Eirik Keilegavlen, Inga Berre·Jul 21, 2026SaveLearn
anyakrakusuma: A Python Library for Entropic Schrödinger Bridges on Idealized GeometriesWe present anyakrakusuma, an open-source Python library that solves the discrete static Schrödinger bridge problem, the entropically regularized counterpart of optimal transport, through a log-domain…Dasapta Erwin Irawan, Sandy Hardian Susanto Herho, Agus Wahyu Jatmiko et al.·Jul 20, 2026SaveLearn
One-shot acceleration of transient PDE solvers via online-learned preconditionersData-driven acceleration of scientific computing workflows has been a high-profile aim of machine learning (ML) for science, with numerical simulation of transient partial differential equations…Mikhail Khodak, Min Ki Jung, Brian Wynne et al.·Jul 20, 2026SaveLearn
CADAQUES: A Cost-Aware Dual Architecture for Query-Efficient Autonomous DiscoveryAutonomous discovery systems couple a resource that answers queries (a simulator, instrument, or analytic model) to an algorithm that selects what to query next. Most software frameworks for this…Jorge Bravo-Abad·Jul 17, 2026SaveLearn
Atomic Design Transformer: Scaffold-Conditioned 3D Molecule Generation via xTB-Reward Reinforcement LearningWe present an SE(3)-invariant transformer for 3D-molecule generation, the Atomic Design Transformer (ADT). ADT places atoms one at a time, autoregressively. SE(3) invariance is achieved by…Takao Kotani·Jul 17, 2026SaveLearn
Transformation front kinetics in deformable ferromagnetsMaterials such as magnetic shape-memory alloys possess an intrinsic coupling between material's magnetisation and mechanical deformation. These materials also undergo structural phase…Michael Poluektov·Jul 17, 2026SaveLearn
Loss of positive definiteness is a symptom, not the cause, of high-Weissenberg-number breakdownNumerical breakdown at high Weissenberg number is often attributed to loss of symmetric positive definiteness (SPD) of the conformation tensor. That conclusion follows from Maxwell-type models…Yuan Yu, Lanjin Lian, Feiyang Chu·Jul 16, 2026SaveLearn
Translation of transient acoustic fieldsA method is presented for the translation of acoustic field data from a source to a target region. Field data are represented as spherical harmonic expansions on spheres surrounding the source and…Michael J. Carley·Jul 16, 2026SaveLearn
A fast summation method for the DFT-D3 dispersion correctionThe DFT-D3 dispersion correction is routinely added to machine learning force fields (MLFFs) trained on dispersion-deficient functionals such as PBE. Its environment-dependent pair coefficients,…Victoria Valeeva, Cheuk Hin Ho, Mario Geiger et al.·Jul 16, 2026SaveLearn
λPIC: A callback-centric particle-in-cell frameworkWe present λPIC, a Python-based electromagnetic particle-in-cell framework built around a callback-centric architecture. Existing PIC codes typically tie high performance to static, pre-compiled…Xuesong Geng, Yunwei Cui, Lingang Zhang et al.·Jul 16, 2026SaveLearn
Contact-resolved deployment of the Contour Neurovascular System in patient-specific intracranial aneurysmsWhile intrasaccular flow disruptors are widely used to treat wide-neck intracranial aneurysms, state-of-the-art patient-specific computational models routinely neglect the deployment mechanics by…Ratnadeep Pramanik, Fina Gießler, Martin Frank et al.·Jul 15, 2026SaveLearn
A Showcase of Using the Partial-Structure R1 to Assemble Small-Molecule Crystal StructuresUsing a few concrete examples this paper has demonstrated a few observations on using the partial-structure R1 (pR1) to assemble small-molecule crystal structures. (1) Assembling can start with…Xiaodong Zhang·Jul 15, 2026SaveLearn
jaxFMM: An Adaptive, GPU-Parallel Implementation of the Fast Multipole Method in JAXWe introduce jaxFMM, an open-source, adaptive, highly parallel point-charge Fast Multipole Method implementation for the Laplace kernel written in JAX. It is based on a non-uniform refinement…Robert Kraft, Florian Bruckner, Dieter Suess et al.·Jul 15, 2026SaveLearn
Towards end-to-end optimization in multimaterial 3D printingMultimaterial 3D printing enables the fabrication of functionally graded components, but optimizing their spatial material distribution alongside structural topology remains a formidable challenge…Xue-Ling Luo, Steven Yang, Jingye Tan et al.·Jul 14, 2026SaveLearn
Inverse Engineering of Optical Constants in Photochromic Micron-Scale Hybrid FilmsPhotochromic materials enable dynamic optical modulation through reversible transitions between distinct absorption states, with broad potential for smart windows, adaptive optics, and reconfigurable…Bahrem Serhat Danis, Amin Tabatabaei Mohseni, Smagul Karazhanov et al.·Jul 14, 2026SaveLearn
Toward AI-Agent-Driven Particle Transport Simulations: Implementation of AI-Assisted Workflows for PHITSMonte Carlo particle transport codes are powerful tools, but their use requires substantial knowledge of input preparation, execution, and result analysis. In this study, we present a code-side…Tatsuhiko Sato, Shintaro Hashimoto, Tatsuhiko Ogawa et al.·Jul 13, 2026SaveLearn
Uncertainty-Aware Structure-Property Mapping of Spinodoid Metamaterials via Heteroscedastic Gaussian Process RegressionSpinodoid metamaterials offer a broad, tunable design space for anisotropic mechanical properties, yet their structure-property relationships are commonly treated as representative mappings from…Minwoo Park, Junseo Park, Mingyu Lee et al.·Jul 13, 2026SaveLearn