Publication

Hidden-nucleons neural-network quantum states for the nuclear many-body problem

Giuseppe Carleo
2022
Journal Articles

Abstract

We generalize the hidden-fermion family of neural network quantum states to encompass both continuous and discrete degrees of freedom and solve the nuclear many-body Schrodinger equation in a systematically improvable fashion. We demonstrate that adding hidden nucleons to the original Hilbert space considerably augments the expressivity of the neural-network architecture compared to the Slater-Jastrow ansatz. The benefits of explicitly encoding in the wave function point symmetries such as parity and timereversal are also discussed. Leveraging on improved optimization methods and sampling techniques, the hidden-nucleon ansatz achieves an accuracy comparable to the numericallyexact hyperspherical harmonic method in light nuclei and to the auxiliary field diffusion Monte Carlo in 16O. Thanks to its polynomial scaling with the number of nucleons, this method opens the way to highly-accurate quantum Monte Carlo studies of medium-mass nuclei.

Official source

https://infoscience.epfl.ch/entities/publication/92b7ac50-06db-4b8f-906b-1c780eb5393f

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Giuseppe Carleo
2022
Journal Articles

Abstract

Official source

https://infoscience.epfl.ch/entities/publication/92b7ac50-06db-4b8f-906b-1c780eb5393f

About this result

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