Renormalized Classical Theory of Quantum Magnets

sunnysuite/sunny.jl 8 Apr 2023

We derive a renormalized classical spin (RCS) theory for $S > 1/2$ quantum magnets by constraining a generalized classical theory that includes all multipolar fluctuations to a reduced CP$^1$ phase space of dipolar SU($2$) coherent states.

Strongly Correlated Electrons

0.05 stars / hour

ELECTRODE: An electrochemistry package for atomistic simulations

lammps/lammps 29 Mar 2022

Here we present a feature-rich CPM implementation, called ELECTRODE, for the Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS), which includes a constrained charge method and a thermo-potentiostat.

Chemical Physics Computational Physics

0.05 stars / hour

Back To The Roots: Tree-Based Algorithms for Weakly Supervised Anomaly Detection

uhh-pd-ml/treebased_anomaly_detection 22 Sep 2023

By using advanced gradient boosted decision trees in combination with ensembling techniques and an extended set of features, we significantly improve the performance of weakly supervised methods for anomaly detection at the LHC.

High Energy Physics - Phenomenology High Energy Physics - Experiment Data Analysis, Statistics and Probability

0.02 stars / hour

GWSpace: a multi-mission science data simulator for space-based gravitational wave detection

tianqinsysu/gwspace 26 Sep 2023

In this paper, we introduce \texttt{GWSpace}, a package that can simulate the joint detection data from TianQin, LISA, and TaiJi.

General Relativity and Quantum Cosmology Cosmology and Nongalactic Astrophysics Instrumentation and Methods for Astrophysics

0.06 stars / hour

KomaMRI.jl: An Open-Source Framework for General MRI Simulations with GPU Acceleration

cncastillo/KomaMRI.jl 6 Jan 2023

Results: Koma was compared to two well-known open-source MRI simulators, JEMRIS and MRiLab.

Medical Physics

0.04 stars / hour

An open-source robust machine learning platform for real-time detection and classification of 2D material flakes

jaluus/2dmatgmm 26 Jun 2023

The implementation allows fully automated scanning and analysis of wafers with an average inference time of 100 ms for images of 2. 3 Mpixels.

Mesoscale and Nanoscale Physics

0.04 stars / hour

The rise of data-driven weather forecasting

198808xc/Pangu-Weather 19 Jul 2023

A new NWP paradigm is emerging relying on inference from ML models and state-of-the-art analysis and reanalysis datasets for forecast initialization and model training.

Atmospheric and Oceanic Physics

0.03 stars / hour

PiNN: A Python Library for Building Atomic Neural Networks of Molecules and Materials

Teoroo-CMC/PiNN 8 Oct 2019

Atomic neural networks (ANNs) constitute a class of machine learning methods for predicting potential energy surfaces and physico-chemical properties of molecules and materials.

Computational Physics Disordered Systems and Neural Networks Chemical Physics

0.03 stars / hour

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

0.03 stars / hour

Surrogate Modeling for Fluid Flows Based on Physics-Constrained Deep Learning Without Simulation Data

Jianxun-Wang/LabelFree-DNN-Surrogate 18 Jul 2019

Numerical simulations on fluid dynamics problems primarily rely on spatially or/and temporally discretization of the governing equation into the finite-dimensional algebraic system solved by computers.

Computational Physics

0.02 stars / hour