Numerical and geometrical aspects of flow-based variational quantum Monte Carlo
In: Machine Learning: Science and Technology, Jg. 4 (2023), Heft 2, S. 021001-21001
Online
academicJournal
Zugriff:
This article aims to summarize recent and ongoing efforts to simulate continuous-variable quantum systems using flow-based variational quantum Monte Carlo techniques, focusing for pedagogical purposes on the example of bosons in the field amplitude (quadrature) basis. Particular emphasis is placed on the variational real- and imaginary-time evolution problems, carefully reviewing the stochastic estimation of the time-dependent variational principles and their relationship with information geometry. Some practical instructions are provided to guide the implementation of a PyTorch code. The review is intended to be accessible to researchers interested in machine learning and quantum information science.
Titel: |
Numerical and geometrical aspects of flow-based variational quantum Monte Carlo
|
---|---|
Autor/in / Beteiligte Person: | Stokes, James ; Chen, Brian ; Veerapaneni, Shravan |
Link: | |
Zeitschrift: | Machine Learning: Science and Technology, Jg. 4 (2023), Heft 2, S. 021001-21001 |
Veröffentlichung: | IOP Publishing, 2023 |
Medientyp: | academicJournal |
ISSN: | 2632-2153 (print) |
DOI: | 10.1088/2632-2153/acc8b9 |
Schlagwort: |
|
Sonstiges: |
|