A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data

lululxvi/deepxde 10 Nov 2021

Neural operators can learn nonlinear mappings between function spaces and offer a new simulation paradigm for real-time prediction of complex dynamics for realistic diverse applications as well as for system identification in science and engineering.

Computational Physics

0.06 stars / hour

Social Force Model for Pedestrian Dynamics

srl-freiburg/pedsim_ros 20 May 1998

The corresponding force concept is discussed in more detail and can be also applied to the description of other behaviors.

Statistical Mechanics Pattern Formation and Solitons patt-sol

0.04 stars / hour

Pushing the limit of molecular dynamics with ab initio accuracy to 100 million atoms with machine learning

deepmodeling/deepmd-kit 1 May 2020

For 35 years, {\it ab initio} molecular dynamics (AIMD) has been the method of choice for modeling complex atomistic phenomena from first principles.

Computational Physics

0.04 stars / hour

Investigating Quantum Approximate Optimization Algorithms under Bang-bang Protocols

google-research/google-research 27 May 2020

The quantum approximate optimization algorithm (QAOA) is widely seen as a possible usage of noisy intermediate-scale quantum (NISQ) devices.

Quantum Physics

0.04 stars / hour

HotQCD on Multi-GPU Systems

latticeqcd/simulateqcd 19 Nov 2021

We present $\texttt{SIMULATeQCD}$, HotQCD's software for performing lattice QCD calculations on GPUs.

High Energy Physics - Lattice

0.04 stars / hour

PyMatching: A Python package for decoding quantum codes with minimum-weight perfect matching

oscarhiggott/PyMatching 27 May 2021

This paper introduces PyMatching, a fast open-source Python package for decoding quantum error-correcting codes with the minimum-weight perfect matching (MWPM) algorithm.

Quantum Physics

0.04 stars / hour

Crystal Graph Convolutional Neural Networks for an Accurate and Interpretable Prediction of Material Properties

txie-93/cgcnn Phys. Rev. Lett. 2017

The use of machine learning methods for accelerating the design of crystalline materials usually requires manually constructed feature vectors or complex transformation of atom coordinates to input the crystal structure, which either constrains the model to certain crystal types or makes it difficult to provide chemical insights.

Band Gap Formation Energy Materials Science

0.04 stars / hour

Intel Quantum Simulator: A cloud-ready high-performance simulator of quantum circuits

iqusoft/intel-qs 28 Jan 2020

Classical simulation of quantum computers will continue to play an essential role in the progress of quantum information science, both for numerical studies of quantum algorithms and for modelings noise and errors.

Quantum Physics Distributed, Parallel, and Cluster Computing Computational Physics

0.03 stars / hour

Trackintel: An open-source Python library for human mobility analysis

mie-lab/trackintel 7 Jun 2022

Trackintel can serve as an essential tool to standardize mobility data analysis and increase the transparency and comparability of novel research on human mobility.

Physics and Society

0.03 stars / hour

Simulating the Sycamore quantum supremacy circuits

jcmgray/cotengra 4 Mar 2021

We propose a general tensor network method for simulating quantum circuits.

Quantum Physics Computational Physics

0.03 stars / hour