Accurate Ab-initio Neural-network Solutions to Large-Scale Electronic Structure ProblemsWe present finite-range embeddings (FiRE), a novel wave function ansatz for accurate large-scale ab-initio electronic structure calculations. Compared to contemporary neural-network wave functions,…Michael Scherbela, Nicholas Gao, Philipp Grohs et al.·Apr 8, 2025SaveLearn
Infinite Boundary Terms and Pairwise Interactions: A Unified Framework for Periodic Coulomb SystemsThe introduction of the infinite boundary terms and the pairwise interactions [J. Chem. Theory Comput., 10, 5254, (2014)] enables a physically intuitive approach for deriving electrostatic energy and…Yihao Zhao, Zhonghan Hu·Apr 8, 2025SaveLearn
Sparse Reconstruction of Multi-Dimensional Kinetic DistributionsIn the present work, we propose a novel method for reconstruction of multi-dimensional kinetic distributions, based on their representation as a mixture of Dirac delta functions. The representation…Georgii Oblapenko, Manuel Torrilhon, Michael Herty·Apr 8, 2025SaveLearn
Spectral Similarity Masks Structural Diversity at Hydrophobic Water InterfacesThe air-water and graphene-water interfaces represent quintessential examples of the liquid-gas and liquid-solid boundaries, respectively. While the sum-frequency generation (SFG) spectra of these…Yong Wang, Yifan Li, Linhan Du et al.·Apr 8, 2025SaveLearn
Phase transitions in swarm optimization algorithmsNatural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and…Tomáš Vantuch, Ivan Zelinka, Andrew Adamatzky et al.·Apr 7, 2025SaveLearn
Regression Model for Measurement of Wound Dimensions by Webcam Scanners and Time-of-Flight SensorsOne use of image processing is for medical equipment such as wound identification. This technology is carried out non-invasively by taking images so as to avoid direct touch with the wound thereby…S. B. Wibowo, A. A. Nugroho, L. Awaludin et al.·Apr 7, 2025SaveLearn
asKAN: Active Subspace embedded Kolmogorov-Arnold NetworkThe Kolmogorov-Arnold Network (KAN) has emerged as a promising neural network architecture for small-scale AI+Science applications. However, it suffers from inflexibility in modeling ridge functions,…Zhiteng Zhou, Zhaoyue Xu, Yi Liu et al.·Apr 7, 2025SaveLearn
GPU-based compressible lattice Boltzmann simulations on non-uniform grids using standard C++ parallelism: From best practices to aerodynamics, aeroacoustics and supersonic flow simulationsDespite decades of research, creating accurate, robust, and efficient lattice Boltzmann methods (LBM) on non-uniform grids with seamless GPU acceleration remains challenging. This work introduces a…Christophe Coreixas, Jonas Latt·Apr 6, 2025SaveLearn
Improving the robustness of the immersed interface method through regularized velocity reconstructionRobust, broadly applicable fluid-structure interaction (FSI) algorithms remain a challenge for computational mechanics. In previous work, we introduced an immersed interface method (IIM) for discrete…Qi Sun, Ebrahim M. Kolahdouz, Boyce E. Griffith·Apr 4, 2025SaveLearn
Behavior of the scaling correlation functions under severe subsamplingScale-invariance is a ubiquitous observation in the dynamics of large distributed complex systems. The computation of its scaling exponents, which provide clues on its origin, is often hampered by…Sabrina Camargo, Nahuel Zamponi, Daniel A. Martin et al.·Apr 4, 2025SaveLearn
Applying Space-Group Symmetry to Speed up Hybrid-Functional Calculations within the Framework of Numerical Atomic OrbitalsBuilding upon the efficient implementation of hybrid density functionals (HDFs) for large-scale periodic systems within the framework of numerical atomic orbital bases using the localized resolution…Yu Cao, Min-Ye Zhang, Peize Lin et al.·Apr 3, 2025SaveLearn
Perturbations and Phase Transitions in Swarm Optimization AlgorithmsNatural systems often exhibit chaotic behavior in their space-time evolution. Systems transiting between chaos and order manifest a potential to compute, as shown with cellular automata and…Tomáš Vantuch, Ivan Zelinka, Andrew Adamatzky et al.·Apr 2, 2025SaveLearn
Random Phase Approximation Correlation Energy using Real-Space Density Functional Perturbation TheoryWe present a real-space method for computing the random phase approximation (RPA) correlation energy within Kohn-Sham density functional theory, leveraging the low-rank nature of the…Boqin Zhang, Shikhar Shah, John E. Pask et al.·Apr 2, 2025SaveLearn
Towards Signed Distance Function based Metamaterial Design: Neural Operator Transformer for Forward Prediction and Diffusion Model for Inverse DesignThe inverse design of metamaterial architectures presents a significant challenge, particularly for nonlinear mechanical properties involving large deformations, buckling, contact, and plasticity.…Qibang Liu, Seid Koric, Diab Abueidda et al.·Apr 1, 2025SaveLearn
An improved update rule for probabilistic computersMany hard combinatorial problems can be mapped onto Ising models, which replicate the behavior of classical spins. Recent advances in probabilistic computers are characterized by parallelization and…Andrew Rockovich, Gregory Lafyatis, Daniel J. Gauthier·Apr 1, 2025SaveLearn
Principal Component Stochastic Subspace Identification for Output-Only Modal AnalysisStochastic Subspace Identification (SSI) is widely used in modal analysis of engineering structures, known for its numerical stability and high accuracy in modal parameter identification. SSI methods…Biqi Chen, Jun Zhang, Ying Wang·Apr 1, 2025SaveLearn
Plane-Wave Decomposition and Randomised Training; a Novel Path to Generalised PINNs for SHMIn this paper, we introduce a formulation of Physics-Informed Neural Networks (PINNs), based on learning the form of the Fourier decomposition, and a training methodology based on a spread of…Rory Clements, James Ellis, Geoff Hassall et al.·Mar 31, 2025SaveLearn
Pyrometheus: Symbolic abstractions for XPU and automatically differentiated computation of combustion kinetics and thermodynamicsThe cost of combustion simulations is often dominated by the evaluation of net production rates of chemical species and mixture thermodynamics (thermochemistry). Execution on computing accelerators…Esteban Cisneros-Garibay, Henry Le Berre, Dimitrios Adam et al.·Mar 31, 2025SaveLearn
Data-driven construction of a generalized kinetic collision operator from molecular dynamicsWe introduce a data-driven approach to learn a generalized kinetic collision operator directly from molecular dynamics. Unlike the conventional (e.g., Landau) models, the present operator takes an…Yue Zhao, Joshua W. Burby, Andrew Christlieb et al.·Mar 31, 2025SaveLearn
Force-Free Molecular Dynamics Through Autoregressive Equivariant NetworksMolecular dynamics (MD) simulations play a crucial role in scientific research. Yet their computational cost often limits the timescales and system sizes that can be explored. Most data-driven…Fabian L. Thiemann, Thiago Reschützegger, Massimiliano Esposito et al.·Mar 31, 2025SaveLearn
JAX-BTE: A GPU-Accelerated Differentiable Solver for Phonon Boltzmann Transport EquationsThis paper introduces JAX-BTE, a GPU-accelerated, differentiable solver for the phonon Boltzmann Transport Equation (BTE) based on differentiable programming. JAX-BTE enables accurate, efficient and…Wenjie Shang, Jiahang Zhou, J. P. Panda et al.·Mar 31, 2025SaveLearn
Interpretable Machine Learning in Physics: A ReviewMachine learning is increasingly transforming various scientific fields, enabled by advancements in computational power and access to large data sets from experiments and simulations. As artificial…Sebastian Johann Wetzel, Seungwoong Ha, Raban Iten et al.·Mar 30, 2025SaveLearn
OpenOrbitalOptimizer -- a reusable open source library for self-consistent field calculationsAccording to the modern paradigms of software engineering, standard tasks are best accomplished by reusable open source libraries. We describe OpenOrbitalOptimizer: a reusable open source C++ library…Susi Lehtola, Lori A. Burns·Mar 29, 2025SaveLearn
Numerical Analysis of Temperature and Stress Fields in Mass Concrete Based on Average Forming Temperature MethodMass concrete plays a crucial role in large-scale projects such as water conservancy hubs and transportation infrastructure. Due to its substantial volume and poor thermal conductivity, the…Sana Ullah, Peng Wu, Ting Peng et al.·Mar 29, 2025SaveLearn
Permutation of Tensor-Train Cores for Computing Moments on Stochastic Differential EquationsTensor networks, particularly the tensor train (TT) format, have emerged as powerful tools for high-dimensional computations in physics and computer science. In solving coupled differential…Kayo Kinjo, Rihito Sakurai, Tatsuya Kishimoto et al.·Mar 29, 2025SaveLearn