Lange, Hannah and van de Walle, Anka and Abedinnia, Atiye and Bohrdt, Annabelle (2024) From architectures to applications: a review of neural quantum states. QUANTUM SCIENCE AND TECHNOLOGY, 9 (4): 040501. ISSN 2058-9565
Full text not available from this repository. (Request a copy)Abstract
Due to the exponential growth of the Hilbert space dimension with system size, the simulation of quantum many-body systems has remained a persistent challenge until today. Here, we review a relatively new class of variational states for the simulation of such systems, namely neural quantum states (NQS), which overcome the exponential scaling by compressing the state in terms of the network parameters rather than storing all exponentially many coefficients needed for an exact parameterization of the state. We introduce the commonly used NQS architectures and their various applications for the simulation of ground and excited states, finite temperature and open system states as well as NQS approaches to simulate the dynamics of quantum states. Furthermore, we discuss NQS in the context of quantum state tomography.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | RESTRICTED BOLTZMANN MACHINES; MONTE-CARLO; TOMOGRAPHY; RECONSTRUCTION; REPRESENTATION; APPROXIMATION; NETWORKS; neural quantum states; quantum many-body systems; variational monte carlo; neural networks |
| Subjects: | 500 Science > 530 Physics |
| Divisions: | Physics > Institute of Theroretical Physics > Chair Professor Grifoni > Group Milena Grifoni |
| Depositing User: | Dr. Gernot Deinzer |
| Date Deposited: | 29 Oct 2025 11:28 |
| Last Modified: | 29 Oct 2025 11:28 |
| URI: | https://pred.uni-regensburg.de/id/eprint/64360 |
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