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A light weight regularization for wave function parameter gradients in quantum Monte Carlo
Shivesh Pathak,
Lucas K. Wagner
Physics
National Center for Supercomputing Applications (NCSA)
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Keyphrases
Quantum Monte Carlo
100%
Variational Monte Carlo
100%
Wave Function
100%
Function Parameters
100%
Weight Regularization
100%
Jastrow
66%
Nave
66%
Trial Wave Function
66%
Optimization Methods
66%
Finite Variance
66%
Copper(II) Oxide
33%
Optimization Techniques
33%
Zero Bias
33%
Monte Carlo Code
33%
Expectation Values
33%
Efficient Estimator
33%
Variance Estimation
33%
Function Optimization
33%
Monte Carlo Optimization
33%
Infinite Variance
33%
Regularized Estimator
33%
Stable Estimates
33%
Monte Carlo Wave Function
33%
Parameter Derivatives
33%
Mathematics
Monte Carlo
100%
Regularization
100%
wavefunction ψ
100%
Variance
50%
Expectation Value
25%
Variance Estimation
25%
Function Optimization
25%