Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866910686214356992 |
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| author | Nys, Jannes Pescia, Gabriel Sinibaldi, Alessandro Carleo, Giuseppe |
| author_facet | Nys, Jannes Pescia, Gabriel Sinibaldi, Alessandro Carleo, Giuseppe |
| contents | Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical and computational challenge. Our work introduces a variational approach for fermionic time-dependent wave functions, surpassing mean-field approximations by accurately capturing many-body correlations. Therefore, we employ time-dependent Jastrow factors and backflow transformations, which are enhanced through neural networks parameterizations. To compute the optimal time-dependent parameters, we utilize the time-dependent variational Monte Carlo technique and a new method based on Taylor-root expansions of the propagator, enhancing the accuracy of our simulations. The approach is demonstrated in three distinct systems. In all cases, we show clear signatures of many-body correlations in the dynamics. The results showcase the ability of our variational approach to accurately capture the time evolution, providing insight into the quantum dynamics of interacting electronic systems, beyond the capabilities of mean-field. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_07447 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation Nys, Jannes Pescia, Gabriel Sinibaldi, Alessandro Carleo, Giuseppe Strongly Correlated Electrons Machine Learning Chemical Physics Computational Physics Quantum Physics Understanding the real-time evolution of many-electron quantum systems is essential for studying dynamical properties in condensed matter, quantum chemistry, and complex materials, yet it poses a significant theoretical and computational challenge. Our work introduces a variational approach for fermionic time-dependent wave functions, surpassing mean-field approximations by accurately capturing many-body correlations. Therefore, we employ time-dependent Jastrow factors and backflow transformations, which are enhanced through neural networks parameterizations. To compute the optimal time-dependent parameters, we utilize the time-dependent variational Monte Carlo technique and a new method based on Taylor-root expansions of the propagator, enhancing the accuracy of our simulations. The approach is demonstrated in three distinct systems. In all cases, we show clear signatures of many-body correlations in the dynamics. The results showcase the ability of our variational approach to accurately capture the time evolution, providing insight into the quantum dynamics of interacting electronic systems, beyond the capabilities of mean-field. |
| title | Ab-initio variational wave functions for the time-dependent many-electron Schrödinger equation |
| topic | Strongly Correlated Electrons Machine Learning Chemical Physics Computational Physics Quantum Physics |
| url | https://arxiv.org/abs/2403.07447 |