AiiDA plugin of the high-performance density functional theory code JuKKR (www.judft.de) for high-throughput electronic structure calculations.
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Updated
Apr 29, 2026 - Python
AiiDA plugin of the high-performance density functional theory code JuKKR (www.judft.de) for high-throughput electronic structure calculations.
SEISGEN is a python package to acquire and generate the Greens function and synthetic waveform from the stored receiver-side 3D database including the Strain Greens Tensor (SGT) database and the (displacement) Greens function (DGF) database.
Numerically exact Green's functions for lattice polaron models, easily and efficiently
Quick and dirty TRIQS wrapper around the Pomerol exact diagonalization library
Python module initialization and post processing of data for Green-Phys software suite.
Collection of tools for condensed matter computational physics.
Modular Python Code for Multiconfigurational Non-Equilibrium Green's Function Methodologies
Green's function methods using auxiliary space
Matrix classes for matrices that are block-tridiagonal. Contains specialized class that uses a specialized algorithm for inverting these types of matrices. Much faster than the numpy and scipy equivalents when a particular matrix is block tridiagonal and large enough.
Exact diagonalization of fermionic (many-body) systems
Generation of all possible electron-phonon interaction Green's function corrections, and reduction into irreducible Feynman diagrams
A repo containing code for TSC (topological superconductivity) simulations.
Provides analytical steady-state solutions to a system of masses and springs driven by white noise.
Generation of all possible electron-electron interaction Green's function corrections, and reduction into irreducible Feynman diagrams
Non Equillibrium Green's Functions (NEGF) solver of the atomic linear chain for educational purposes.
A physics-informed machine learning approach for analytic continuation of Green’s functions. Uses a Variational Autoencoder (VAE) to reconstruct spectral functions by explicitly learning poles and residues from imaginary-time Quantum Monte Carlo data. Robust, interpretable, and designed for noisy inputs.
The Irikura recipe is a strong ground motion simulation methodology, based on greens functions and source characterization. This code generates acceleration for a large fault from acceleration records of a smaller source.
Calculation of exchange interaction integrals for Weyl semimetal tight-binding models
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