Stochastic Operator Learning for Chemistry in Non-Equilibrium FlowsThis work presents a novel framework for physically consistent model error characterization and operator learning for reduced-order models of non-equilibrium chemical kinetics. By leveraging the…Mridula Kuppa, Roger Ghanem, Marco Panesi·Oct 16, 2024SaveLearn
Generative Neural Reparameterization for Differentiable PDE-constrained OptimizationPartial-differential-equation (PDE)-constrained optimization is a well-worn technique for acquiring optimal parameters of systems governed by PDEs. However, this approach is limited to providing a…Archis S. Joglekar·Oct 16, 2024SaveLearn
Machine learning of the Ising model on a spherical Fibonacci latticeWe investigate the Ising model on a spherical surface, utilizing a Fibonacci lattice to approximate uniform coverage. This setup poses challenges in achieving consistent lattice distribution across…Zheng Zhou, Chen-Hui Song, Xu-Yang Hou et al.·Oct 15, 2024SaveLearn
Multiple scales homogenisation of a porous viscoelastic material with rigid inclusions: application to lithium-ion battery electrodesThis paper explores the mechanical behaviour of the composite materials used in modern lithium-ion battery electrodes. These contain relatively high modulus active particle inclusions within a…J. M. Foster, A. F. Galvis, B. Protas et al.·Oct 15, 2024SaveLearn
Nonintrusive projection-based reduced order modeling using stable learned differential operatorsNonintrusive projection-based reduced order models (ROMs) are essential for dynamics prediction in multi-query applications where access to the source of the underlying full order model (FOM) is…Aviral Prakash, Yongjie Jessica Zhang·Oct 15, 2024SaveLearn
A thermodynamically consistent discretization of 1D thermal-fluid models using their metriplectic 4-bracket structureThermodynamically consistent models in continuum physics, i.e. models which satisfy the first and second laws of thermodynamics, may be expressed using the metriplectic formalism. In this work, we…William Barham, Philip J. Morrison, Azeddine Zaidni·Oct 14, 2024SaveLearn
Fast Plasma Frequency Sweep in Drude-like EM Scatterers via the Reduced-Basis MethodIn this work, we propose to use the Reduced-Basis Method (RBM) as a model order reduction approach to solve Maxwell's equations in electromagnetic (EM) scatterers based on plasma to build a…Clara Iglesias-Tesouro, Valentin de la Rubia, Alessio Monti et al.·Oct 14, 2024SaveLearn
Physics-informed AI and ML-based sparse system identification algorithm for discovery of PDE's representing nonlinear dynamic systemsSparse system identification of nonlinear dynamic systems is still challenging, especially for stiff and high-order differential equations for noisy measurement data. The use of highly correlated…Ashish Pal, Sutanu Bhowmick, Satish Nagarajaiah·Oct 13, 2024SaveLearn
Combined WENO schemes for increasing the accuracy of the numerical solution of conservation lawsIn this article, we introduce a new method which allows utilizing all the available sub-stencils of a WENO scheme to increase the accuracy of the numerical solution of conservation laws while…Hossein Mahmoodi Darian·Oct 12, 2024SaveLearn
Simulation of 24,000 Electrons Dynamics: Real-Time Time-Dependent Density Functional Theory (TDDFT) with the Real-Space Multigrids (RMG)We present the theory, implementation, and benchmarking of a real-time time-dependent density functional theory (RT-TDDFT) module within the RMG code, designed to simulate the electronic response of…Jacek Jakowski, Wenchang Lu, Emil Briggs et al.·Oct 11, 2024SaveLearn
From Ferminet to PINN. Connections between neural network-based algorithms for high-dimensional Schr\"odinger HamiltonianIn this note, we establish some connections between standard (data-driven) neural network-based solvers for PDE and eigenvalue problems developed on one side in the applied mathematics and…Mashhood Khan, Emmanuel Lorin·Oct 11, 2024SaveLearn
Accelerated ray-tracing simulations using McXtraceMcXtrace is an established Monte Carlo based ray-tracing tool to simulate synchrotron beamlines and X-ray laboratory instruments. This work explains and demonstrates the new capability of…Steffen Sloth, Peter Kjær Willendrup, Hans Henrik Brandenborg Sørensen et al.·Oct 11, 2024SaveLearn
Event-chain Monte Carlo and the true self-avoiding walkWe study the large-scale dynamics of event chain Monte Carlo algorithms in one dimension, and their relation to the true self-avoiding walk. In particular, we study the influence of stress, and…A. C. Maggs·Oct 11, 2024SaveLearn
Tensor Train MultiplicationWe present the Tensor Train Multiplication (TTM) algorithm for the elementwise multiplication of two tensor trains with bond dimension . The computational complexity and memory requirements of…Alexios A Michailidis, Christian Fenton, Martin Kiffner·Oct 10, 2024SaveLearn
Metamizer: a versatile neural optimizer for fast and accurate physics simulationsEfficient physics simulations are essential for numerous applications, ranging from realistic cloth animations or smoke effects in video games, to analyzing pollutant dispersion in environmental…Nils Wandel, Stefan Schulz, Reinhard Klein·Oct 10, 2024SaveLearn
Simultaneous estimation of electrical conductivity and permittivity in quantitative thermoacoustic tomographyIn this work, the inverse problem of quantitative thermoacoustic tomography is studied. In quantitative thermoacoustic tomography, dielectric parameters of an imaged target are estimated from an…Teemu Sahlström, Timo Lähivaara, Tanja Tarvainen·Oct 9, 2024SaveLearn
dCG -- differentiable connected geometries for AI-compatible multi-domain optimization and inverse designIn the domain of geometry and topology optimization, discovering geometries that optimally satisfy specific problem criteria is a complex challenge in both engineering and scientific research. In…Alexander Luce, Daniel Grünbaum, Florian Marquardt·Oct 8, 2024SaveLearn
PINN-MG: A Multigrid-Inspired Hybrid Framework Combining Iterative Method and Physics-Informed Neural NetworksIterative methods are widely used for solving partial differential equations (PDEs). However, the difficulty in eliminating global low-frequency errors significantly limits their convergence speed.…Daiwei Dong, Wei Suo, Jiaqing Kou et al.·Oct 8, 2024SaveLearn
A Metric on the Polycrystalline Microstructure State SpaceMaterial microstructures are traditionally compared using sets of statistical measures that are incomplete, e.g., two visually distinct microstructures can have identical grain size distributions and…Dylan Miley, Ethan Suwandi, Benjamin Schweinhart et al.·Oct 7, 2024SaveLearn
Universal Approximation of Mean-Field Models via TransformersThis paper investigates the use of transformers to approximate the mean-field dynamics of interacting particle systems exhibiting collective behavior. Such systems are fundamental in modeling…Shiba Biswal, Karthik Elamvazhuthi, Rishi Sonthalia·Oct 6, 2024SaveLearn
Quantum algorithm for the advection-diffusion equation and the Koopman-von Neumann approach to nonlinear dynamical systemsWe propose an explicit algorithm based on the Linear Combination of Hamiltonian Simulations technique to simulate both the advection-diffusion equation and a nonunitary discretized version of the…Ivan Novikau, Ilon Joseph·Oct 4, 2024SaveLearn
Fast Algorithm for Full-wave EM Scattering Analysis of Large-scale Chaff Cloud with Arbitrary Orientation, Spatial Distribution, and LengthWe propose a new fast algorithm optimized for full-wave electromagnetic (EM) scattering analysis of a large-scale cloud of chaffs with arbitrary orientation, spatial distribution, and length. By…Chung Hyun Lee, Dong-Kook Kang, Kyoung Il Kwon et al.·Oct 4, 2024SaveLearn
Vehicle Suspension Recommendation System: Multi-Fidelity Neural Network-based Mechanism Design OptimizationMechanisms are designed to perform functions in various fields. Often, there is no unique mechanism that performs a well-defined function. For example, vehicle suspensions are designed to improve…Sumin Lee, Namwoo Kang·Oct 3, 2024SaveLearn
A discrete cohesive zone model for beam element: Application to adhesively bonded laminates and sandwich panelsA new discrete cohesive zone model (DCZM) is presented for modeling the interface behavior of adhesive-bonded thin laminates and sandwich panels. The proposed model treats the interface as a spring…Himanshu, Ananth Ramaswamy·Oct 3, 2024SaveLearn
Domain decomposition of the modified Born series approach for large-scale wave propagation simulationsThe modified Born series (MBS) is a fast and accurate method for simulating wave propagation in complex structures. In the current implementation of the MBS, the simulation size is limited by the…Swapnil Mache, Ivo M. Vellekoop·Oct 3, 2024SaveLearn