acbbullock/Neural-Network-Quantum-States
A machine learning demonstration of neural network quantum states in Modern Fortran
This project helps quantum physicists and computational chemists model complex quantum systems by using neural networks to approximate quantum states. It takes parameters of a quantum system, like the number of spins and magnetic field strength, and outputs approximations of key properties such as system energy and correlations. Researchers in quantum physics or computational materials science who need to simulate many-body quantum systems without full state space knowledge would find this useful.
No commits in the last 6 months.
Use this if you are a quantum physicist or computational chemist struggling with the computational complexity of modeling large quantum systems and need an approximation technique.
Not ideal if you require exact solutions for small quantum systems or are not working with spin-1/2 fermion systems.
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8
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1
Language
Fortran
License
MIT
Category
Last pushed
Mar 11, 2024
Commits (30d)
0
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