All Projects → dftlibs → xcfun

dftlibs / xcfun

Licence: MPL-2.0 license
XCFun: A library of exchange-correlation functionals with arbitrary-order derivatives

Programming Languages

C++
36643 projects - #6 most used programming language
python
139335 projects - #7 most used programming language
CMake
9771 projects
c
50402 projects - #5 most used programming language
fortran
972 projects
shell
77523 projects

Projects that are alternatives of or similar to xcfun

TB2J
a python package for computing magnetic interaction parameters
Stars: ✭ 35 (-30%)
Mutual labels:  dft
omd
JAX code for the paper "Control-Oriented Model-Based Reinforcement Learning with Implicit Differentiation"
Stars: ✭ 43 (-14%)
Mutual labels:  automatic-differentiation
inelastica
Python package for eigenchannels, vibrations and inelastic electron transport based on SIESTA/TranSIESTA DFT
Stars: ✭ 22 (-56%)
Mutual labels:  dft
Pruned-DFT-s-FBMC Python
Simulates pruned DFT spread FBMC and compares the performance to OFDM, SC-FDMA and conventional FBMC. The included classes (QAM, DoublySelectiveChannel, OFDM, FBMC) can be reused in other projects.
Stars: ✭ 22 (-56%)
Mutual labels:  dft
ooura
Javascript port of Ooura FFT implementation
Stars: ✭ 23 (-54%)
Mutual labels:  dft
AdFem.jl
Innovative, efficient, and computational-graph-based finite element simulator for inverse modeling
Stars: ✭ 62 (+24%)
Mutual labels:  automatic-differentiation
old-audiosync
First implementation of the audio synchronization feature for Vidify, now obsolete
Stars: ✭ 16 (-68%)
Mutual labels:  dft
Fortran-Tools
Fortran compilers, preprocessors, static analyzers, transpilers, IDEs, build systems, etc.
Stars: ✭ 31 (-38%)
Mutual labels:  automatic-differentiation
admc
Infinite order automatic differentiation for Monte Carlo with unnormalized probability distribution
Stars: ✭ 17 (-66%)
Mutual labels:  automatic-differentiation
Causing
Causing: CAUsal INterpretation using Graphs
Stars: ✭ 47 (-6%)
Mutual labels:  automatic-differentiation
spectrogram
Taking an audio signal (wav) and converting it into a spectrogram. Written in Go programming language.
Stars: ✭ 34 (-32%)
Mutual labels:  dft
atomate2
atomate2 is a library of computational materials science workflows
Stars: ✭ 67 (+34%)
Mutual labels:  dft
ADAM
ADAM implements a collection of algorithms for calculating rigid-body dynamics in Jax, CasADi, PyTorch, and Numpy.
Stars: ✭ 51 (+2%)
Mutual labels:  automatic-differentiation
pseudo dojo
Python framework for generating and validating pseudo potentials
Stars: ✭ 32 (-36%)
Mutual labels:  dft
Tensors.jl
Efficient computations with symmetric and non-symmetric tensors with support for automatic differentiation.
Stars: ✭ 142 (+184%)
Mutual labels:  automatic-differentiation
EzReson
An efficient toolkit for chemical resonance analysis based on quantum chemistry calculations. It implements the quantitative theory of resonance by expansion of the wave function from a DFT/HF calculation in terms of those of the Lewis structures.
Stars: ✭ 14 (-72%)
Mutual labels:  dft
DMFTwDFT
DMFTwDFT: An open-source code combining Dynamical Mean Field Theory with various Density Functional Theory packages
Stars: ✭ 39 (-22%)
Mutual labels:  dft
MissionImpossible
A concise C++17 implementation of automatic differentiation (operator overloading)
Stars: ✭ 18 (-64%)
Mutual labels:  automatic-differentiation
cgdms
Differentiable molecular simulation of proteins with a coarse-grained potential
Stars: ✭ 44 (-12%)
Mutual labels:  automatic-differentiation
MultiScaleArrays.jl
A framework for developing multi-scale arrays for use in scientific machine learning (SciML) simulations
Stars: ✭ 63 (+26%)
Mutual labels:  automatic-differentiation

Build and test XCFun Build Status GitHub license DOI

XCFun: A library of exchange-correlation functionals with arbitrary-order derivatives

Copyright Ulf Ekström and contributors 2009-2020.

License

XCFun is licensed under version 2.0 of the Mozilla Public License (MPLv2.0), see LICENSE.md.

Documentation

The documentation is available at https://xcfun.readthedocs.io.

XCFun can be installed with popular package managers:

Note that the project description data, including the texts, logos, images, and/or trademarks, for each open source project belongs to its rightful owner. If you wish to add or remove any projects, please contact us at [email protected].