Emulators and Artificial Neural Networks in Computational Quantum Continuum Physics
ORAL · Invited
Abstract
Emulator technology, particularly those using the reduced basis method (also known as eigenvector continuation in nuclear theory), is being actively used to develop new continuum methods or enhance existing calculations. I will highlight some promising advancements in this area. Meanwhile, artificial neural networks, considered as universal approximators, open up an exciting avenue for solving complex equation systems in quantum continuum physics. While recent research has predominantly focused on computing many-body ground states, I will discuss our efforts to extend this approach to excited states and continuum states.
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Publication: Xilin Zhang, A non-Hermitian quantum mechanics approach for extracting and emulating continuum physics based on bound-state-like calculations: technical details, [arXiv: 2411.06712].<br>Xilin Zhang, A non-Hermitian quantum mechanics approach for extracting and emulating continuum physics based on bound-state-like calculations, [arXiv: 2408.03309].<br>X. Zhang and R. J. Furnstahl, Fast emulation of quantum three-body scattering, Phys. Rev. C 105., no.6, 064004 (2022) [arXiv:2110.04269 ].<br>R. J. Furnstahl, A. J. Garcia, P. J. Millican and X. Zhang, Efficient emulators for scattering using eigenvector continuation, Phys. Lett. B 809, 135719 (2020) [arXiv:2007.03635 ].<br>J. A. Melendez, C. Drischler, R. J. Furnstahl, A. J. Garcia and X. Zhang, Model reduction methods for nuclear emulators, J. Phys. G 49, no.10, 102001 (2022) [arXiv:2203.05528].<br> C. Drischler, J. A. Melendez, R. J. Furnstahl, A. J. Garcia and X. Zhang, BUQEYE guide to projection-based emulators in nuclear physics, Front. in Phys. 10, 1092931 (2022) [arXiv:2212.04912].
Presenters
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Xilin Zhang
FRIB, Michigan State University
Authors
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Xilin Zhang
FRIB, Michigan State University