Trending Research

A flexible framework for large-scale FDTD simulations: open-source inverse design for 3D nanostructures

ymahlau/fdtdx 16 Dec 2024

We introduce an efficient open-source python package for the inverse design of three-dimensional photonic nanostructures using the Finite-Difference Time-Domain (FDTD) method.

Optics Computational Physics

128
0.05 stars / hour

AFLOW: An automatic framework for high-throughput materials discovery

learningmatter-mit/matex 26 Aug 2013

Recent advances in computational materials science present novel opportunities for structure discovery and optimization, including uncovering of unsuspected compounds and metastable structures, electronic structure, surface, and nano-particle properties.

Materials Science

16
0.04 stars / hour

PyGRO: a Python Integrator for General Relativistic Orbits

rdellamonica/pygro 28 Apr 2025

Advancement in recent years in the field of experimental gravitation has allowed to test the equivalence principle in regimes that were previously unexplored, allowing for unprecedented verifications of general relativity and also enabling tests of alternative theories of gravity.

General Relativity and Quantum Cosmology

11
0.04 stars / hour

PtyRAD: A High-performance and Flexible Ptychographic Reconstruction Framework with Automatic Differentiation

chiahao3/ptyrad 12 May 2025

Electron ptychography has recently achieved unprecedented resolution, offering valuable insights across diverse material systems, including in three dimensions.

Materials Science Optics

29
0.03 stars / hour

Climate in a Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere

NVlabs/cBottle 10 May 2025

AI emulators offer a path to compressing, boosting limited ensembles, and improving the latency of interacting with petabyte-scale climate prediction data.

Atmospheric and Oceanic Physics

53
0.03 stars / hour

Seismic Full-Waveform Inversion Using Deep Learning Tools and Techniques

ar4/deepwave 31 Jan 2018

I demonstrate that the conventional seismic full-waveform inversion algorithm can be constructed as a recurrent neural network and so implemented using deep learning software such as TensorFlow.

Geophysics Computational Physics

266
0.03 stars / hour

NEP89: Universal neuroevolution potential for inorganic and organic materials across 89 elements

brucefan1983/GPUMD 30 Apr 2025

While machine-learned interatomic potentials offer near-quantum-mechanical accuracy for atomistic simulations, many are material-specific or computationally intensive, limiting their broader use.

Materials Science

588
0.03 stars / hour

A foundation model for atomistic materials chemistry

acesuit/mace-mp 29 Dec 2023

Machine-learned force fields have transformed the atomistic modelling of materials by enabling simulations of ab initio quality on unprecedented time and length scales.

Chemical Physics Materials Science

122
0.03 stars / hour

Geodesic intersections

geographiclib/geographiclib 1 Aug 2023

A complete treatment of the intersections of two geodesics on the surface of an ellipsoid of revolution is given.

Geophysics

377
0.03 stars / hour

DeePMD-kit v3: A Multiple-Backend Framework for Machine Learning Potentials

deepmodeling/deepmd-kit 26 Feb 2025

In recent years, machine learning potentials (MLPs) have become indispensable tools in physics, chemistry, and materials science, driving the development of software packages for molecular dynamics (MD) simulations and related applications.

Chemical Physics

1,685
0.04 stars / hour