Quantum Advantage in Phase Unitary Learning with a Continuous-Variable Quantum Compiler
We demonstrate a continuous-variable quantum compiler with 3.6-fold faster convergence and 5.4-fold enhanced precision for optical phase unitary learning, highlighting the advantages of squeezing in learning the dynamics of quantum systems.
Authors
- Raphael C. Pooser (ORCID: https://orcid.org/0000-0002-2922-453X)
- Tyler Volkoff (ORCID: https://orcid.org/0000-0002-5511-3913)
- Alberto M. Marino (ORCID: https://orcid.org/0000-0001-5377-1122)
- Seongjin Hong (ORCID: https://orcid.org/0000-0002-9000-5512)
- Andrew T. Sornborger (ORCID: https://orcid.org/0000-0001-8036-6624)
- Zoë Holmes (ORCID: https://orcid.org/0000-0001-6841-4507)
- Matthew Feldman (ORCID: https://orcid.org/0000-0002-2494-6533)
- Claire Marvinney
Institutions
- Oak Ridge National Laboratory (US)
- Los Alamos National Laboratory (US)
- Quantis (Switzerland) (CH)
- Quantum Science Center (US)
- École Polytechnique Fédérale de Lausanne (CH)
Publication Details
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1364/quantum.2025.qw2a.5
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 0.00