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Found 3 papers, 2 papers with code
Transferable Neural Wavefunctions for Solids
To mitigate this problem, recent research has proposed optimizing a single neural network across multiple systems, reducing the cost per system.
Accurate Computation of Quantum Excited States with Neural Networks
We present a variational Monte Carlo algorithm for estimating the lowest excited states of a quantum system which is a natural generalization of the estimation of ground states.
Neural Wave Functions for Superfluids
We demonstrate key limitations of the FermiNet Ansatz in studying the unitary Fermi gas and propose a simple modification based on the idea of an antisymmetric geminal power singlet (AGPs) wave function.
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