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arXiv · 1804.06521

Method to solve quantum few-body problems with artificial neural networks

Hiroki Saito
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Abstract

A machine learning technique to obtain the ground states of quantum few-body systems using artificial neural networks is developed. Bosons in continuous space are considered and a neural network is optimized in such a way that when particle positions are input into the network, the ground-state wave function is output from the network. The method is applied to the Calogero-Sutherland model in one-dimensional space and Efimov bound states in three-dimensional space.

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Hiroki Saito. 2018-04-18. Method to solve quantum few-body problems with artificial neural networks. https://doi.org/10.7566/jpsj.87.074002

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