Mapping confinement potentials and charge densities of interacting quantum systems using conditional generative adversarial networks

Accurate and efficient tools for calculating the ground state properties of interacting quantum systems are essential in the design of nanoelectronic devices. The exact diagonalization method fully accounts for the Coulomb interaction beyond mean field approximations and it is regarded as the gold-s...

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Bibliographic Details
Published in:Machine learning: science and technology 2023-06, Vol.4 (2), p.25023
Main Authors: Pantis-Simut, Calin-Andrei, Preda, Amanda Teodora, Ion, Lucian, Manolescu, Andrei, Alexandru Nemnes, George
Format: Article
Language:English
Subjects:
Computing costs
Computing time
conditional generative adversarial networks
Confinement
Generative adversarial networks
Ground state
Inverse problems
Machine learning
Mapping
Nanoelectronics
Nanotechnology devices
pix2pix
potential-density mapping
quantum many-body systems
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Summary:Accurate and efficient tools for calculating the ground state properties of interacting quantum systems are essential in the design of nanoelectronic devices. The exact diagonalization method fully accounts for the Coulomb interaction beyond mean field approximations and it is regarded as the gold-standard for few electron systems. However, by increasing the number of instances to be solved, the computational costs become prohibitive and new approaches based on machine learning techniques can provide a significant reduction in computational time and resources, maintaining a reasonable accuracy. Here, we employ pix2pix , a general-purpose image-to-image translation method based on conditional generative adversarial network (cGAN), for predicting ground state densities from randomly generated confinement potentials. Other mappings were also investigated, like potentials to non-interacting densities and the translation from non-interacting to interacting densities. The architecture of the cGAN was optimized with respect to the internal parameters of the generator and discriminator. Moreover, the inverse problem of finding the confinement potential given the interacting density can also be approached by the pix2pix mapping, which is an important step in finding near-optimal solutions for confinement potentials.
ISSN:2632-2153
2632-2153
DOI:10.1088/2632-2153/acd6d8