MACE: A Machine learning Approach to Chemistry EmulationThe chemistry of an astrophysical environment is closely coupled to its dynamics, the latter often found to be complex. Hence, to properly model these environments a 3D context is necessary. However,…S. Maes, F. De Ceuster, M. Van de Sande et al.·May 6, 2024SaveLearn
Quantitative analysis of the prediction performance of a Convolutional Neural Network evaluating the surface elastic energy of a strained filmA Deep Learning approach is devised to estimate the elastic energy density at the free surface of an undulated stressed film. About 190000 arbitrary surface profiles h(x) are randomly…Luis Martín Encinar, Daniele Lanzoni, Andrea Fantasia et al.·May 5, 2024SaveLearn
Projected gradient descent algorithm for ab initio crystal structure relaxation under a fixed unit cell volumeThis paper is concerned with ab initio crystal structure relaxation under a fixed unit cell volume, which is a step in calculating the static equations of state and forms the basis of…Yukuan Hu, Junlei Yin, Xingyu Gao et al.·May 5, 2024SaveLearn
A Massively Parallel Performance Portable Free-space Spectral Poisson SolverVico et al. (2016) suggest a fast algorithm for computing volume potentials, beneficial to fields with problems requiring the solution of the free-space Poisson's equation, such as beam and plasma…Sonali Mayani, Veronica Montanaro, Antoine Cerfon et al.·May 4, 2024SaveLearn
Analytical approximations for multiple scattering in one-dimensional waveguides with small inclusionsWe propose a new model to approximate the wave response of waveguides containing an arbitrary number of small inclusions. The theory is developed to consider any one-dimensional waveguide…Mario Lázaro, Richard Wiltshaw, Richard Vaughan Craster et al.·May 4, 2024SaveLearn
cuPSS: a package for pseudo-spectral integration of stochastic PDEsA large part of modern research, especially in the broad field of complex systems, relies on the numerical integration of PDEs, with and without stochastic noise. This is usually done with eiher…Fernando Caballero·May 3, 2024SaveLearn
XtalOpt Version 13: Multi-Objective Evolutionary Search for Novel Functional MaterialsVersion 13 of XtalOpt, an evolutionary algorithm for crystal structure prediction, is now available for download from the CPC program library or the XtalOpt website, https://xtalopt.github.io. In the…Samad Hajinazar, Eva Zurek·May 3, 2024SaveLearn
3-center and 4-center 2-particle Gaussian AO integrals on modern accelerated processorsWe report an implementation of the McMurchie-Davidson (MD) algorithm for 3-center and 4-center 2-particle integrals over Gaussian atomic orbitals (AOs) with low and high angular momenta l and…Andrey Asadchev, Edward F. Valeev·May 3, 2024SaveLearn
Multimodal reconstruction of TbCo thin film structure with Basyeian analysis of polarised neutron reflectivityWe implemented the Bayesian analysis to the polarised neutron reflectivity data. Reflectivity data from a magnetic TbCo thin film structure was studied using the bundle of a Monte-Carlo Markov-chain…P. S. Savchenkov, K. V. Nikolaev, V. I. Bodnarchuk et al.·May 2, 2024SaveLearn
General synthetic iterative scheme for rarefied gas mixture flowsThe numerical simulation of rarefied gas mixtures with disparate mass and concentration is a huge research challenge. Based on our recent kinetic modelling for monatomic gas mixture flows, this…Jianan Zeng, Qi Li, Lei Wu·May 2, 2024SaveLearn
Deep-learning design of graphene metasurfaces for quantum control and Dirac electron holographyMetasurfaces are sub-wavelength patterned layers for controlling waves in physical systems. In optics, meta-surfaces are created by materials with different dielectric constants and are capable of…Chen-Di Han, Li-Li Ye, Zin Lin et al.·May 1, 2024SaveLearn
Uncertainty quantification for charge transport in GNRs through particle Galerkin methods for the semiclassical Boltzmann equationIn this article, we investigate some issues related to the quantification of uncertainties associated with the electrical properties of graphene nanoribbons. The approach is suited to understand the…Andrea Medaglia, Giovanni Nastasi, Vittorio Romano et al.·Apr 30, 2024SaveLearn
Efficient Mixed-Precision Matrix Factorization of the Inverse Overlap Matrix in Electronic Structure Calculations with AI-Hardware and GPUsIn recent years, a new kind of accelerated hardware has gained popularity in the Artificial Intelligence (AI) and Machine Learning (ML) communities which enables extremely high-performance tensor…Adela Habib, Joshua Finkelstein, Anders M. N. Niklasson·Apr 29, 2024SaveLearn
Machine Learning Interatomic Potentials with Keras APIA neural network is used to train, predict, and evaluate a model to calculate the energies of 3-dimensional systems composed of Ti and O atoms. Python classes are implemented to quantify atomic…James Paolo Rili·Apr 29, 2024SaveLearn
Computing Classical Orbital Elements with Improved Efficiency and AccuracyThis paper reviews the standard algorithm for converting spacecraft state vectors to Keplerian orbital elements with a focus on its computer implementation. It analyzes the shortcomings of the scheme…Roberto Flores, Elena Fantino·Apr 28, 2024SaveLearn
FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural NetworksDeep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. Development of novel model reduction methods, coupled with…Zhe Bai, Xishuo Wei, William Tang et al.·Apr 26, 2024SaveLearn
Portable, Massively Parallel Implementation of a Material Point Method for Compressible FlowsThe recent evolution of software and hardware technologies is leading to a renewed computational interest in Particle-In-Cell (PIC) methods such as the Material Point Method (MPM). Indeed, provided…Paolo Joseph Baioni, Tommaso Benacchio, Luigi Capone et al.·Apr 25, 2024SaveLearn
Atomistic Modelling of High-Entropy Layered Anodes and Their Electrolyte InterfaceVan der Waals (vdW) heterostructures have attracted intense interest worldwide as they offer several routes to design materials with novel features and wide-ranging applications. Unfortunately, at…Amreen Bano, Dan T Major·Apr 25, 2024SaveLearn
Boltzmann Generators and the New Frontier of Computational Sampling in Many-Body SystemsThe paper by No\'e et al. [F. No\'e, S. Olsson, J. K\"ohler and H. Wu, Science, 365:6457 (2019)] introduced the concept of Boltzmann Generators (BGs), a deep generative model that can produce…Alessandro Coretti, Sebastian Falkner, Jan Weinreich et al.·Apr 25, 2024SaveLearn
Improvement of Geant4 Neutron-HP package: Unresolved Resonance Region description with Probability TablesWhether for shielding applications or for criticality safety studies, solving the neutron transport equation with good accuracy requires to take into account the resonant structure of cross sections…M. Zmeškal, L. Thulliez, P. Tamagno et al.·Apr 25, 2024SaveLearn
Neural Operators Learn the Local Physics of MagnetohydrodynamicsMagnetohydrodynamics (MHD) plays a pivotal role in describing the dynamics of plasma and conductive fluids, essential for understanding phenomena such as the structure and evolution of stars and…Taeyoung Kim, Youngsoo Ha, Myungjoo Kang·Apr 24, 2024SaveLearn
Reconstructing the Magnetic Field in an Arbitrary Domain via Data-driven Bayesian Methods and Numerical SimulationsInverse problems are prevalent in numerous scientific and engineering disciplines, where the objective is to determine unknown parameters within a physical system using indirect measurements or…Georgios E. Pavlou, Vasiliki Pavlidou, Vagelis Harmandaris·Apr 24, 2024SaveLearn
Distinguishing noisy crystal symmetries in coarse-grained computer simulations: New procedures for noise reduction and lattice reconstructionWe suggest new modification (we call it a noise reduction procedure) for Steinhardt parameters which are often used for detecting crystalline structures in computer simulation of solids and soft…Evgeniia Filimonova, Viktor Ivanov, Timur Shakirov·Apr 23, 2024SaveLearn
A Python GPU-accelerated solver for the Gross-Pitaevskii equation and applications to many-body cavity QEDTorchGPE is a general-purpose Python package developed for solving the Gross-Pitaevskii equation (GPE). This solver is designed to integrate wave functions across a spectrum of linear and non-linear…Lorenzo Fioroni, Luca Gravina, Justyna Stefaniak et al.·Apr 22, 2024SaveLearn
Comparing Meta-GGAs, +U Corrections, and Hybrid Functionals for Polaronic Point Defects in Layered MnO2, NiO2, and KCoO2Defects in a material can significantly tune properties and enhance utility. Hybrid functionals like HSE06 are often used to describe solids with such defects. However, geometry optimization…Raj K. Sah, Michael J. Zdilla, Eric Borguet et al.·Apr 22, 2024SaveLearn