mdsunivie/deeperwin
DeepErwin is a python 3.8+ package that implements and optimizes JAX 2.x wave function models for numerical solutions to the multi-electron Schrödinger equation. DeepErwin supports weight-sharing when optimizing wave functions for multiple nuclear geometries and the usage of pre-trained neural network weights to accelerate optimization.
This project helps quantum chemists and materials scientists determine the ground state electronic wave function and energy for atoms and molecules. You input atomic positions and charges, and it outputs an optimized neural network wave function and the corresponding energy. This is for researchers and computational scientists studying molecular properties and reactions.
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Use this if you need highly accurate solutions to the multi-electron Schrödinger equation, especially for multiple molecular geometries or when you want to leverage pre-trained models to speed up your calculations.
Not ideal if you are looking for a quick, approximate solution or if you lack computational resources like GPUs for faster processing.
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Language
Python
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Last pushed
Apr 18, 2025
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