Framework for efficient ab initio electronic structure with Gaussian Process States
We present a general framework for the efficient simulation of realistic fermionic systems
with modern machine-learning-inspired representations of quantum many-body states …
with modern machine-learning-inspired representations of quantum many-body states …
A Nonstochastic Optimization Algorithm for Neural-Network Quantum States
Neural-network quantum states (NQS) employ artificial neural networks to encode many-
body wave functions in a second quantization through variational Monte Carlo (VMC). They …
body wave functions in a second quantization through variational Monte Carlo (VMC). They …
Neural-network quantum states: a systematic review
DR Vivas, J Madroñero, V Bucheli, LO Gómez… - arxiv preprint arxiv …, 2022 - arxiv.org
The so-called contemporary AI revolution has reached every corner of the social, human
and natural sciences--physics included. In the context of quantum many-body physics, its …
and natural sciences--physics included. In the context of quantum many-body physics, its …
Bayesian Modelling Approaches for Quantum States--The Ultimate Gaussian Process States Handbook
Y Rath - arxiv preprint arxiv:2308.07669, 2023 - arxiv.org
Capturing the correlation emerging between constituents of many-body systems accurately
is one of the key challenges for the appropriate description of various systems whose …
is one of the key challenges for the appropriate description of various systems whose …
[PDF][PDF] Bayesian Modelling Approaches for Quantum States
Y Rath - 2023 - kclpure.kcl.ac.uk
Capturing the correlation emerging between constituents of many-body systems is one of
the key challenges to describe various quantum systems accurately. This thesis discusses …
the key challenges to describe various quantum systems accurately. This thesis discusses …