Schmidt quantum compressor
Abstract This work introduces the Schmidt quantum compressor, an innovative approach to quantum data compression that leverages the principles of Schmidt decomposition to encode quantum information efficiently. In contrast to traditional variational quantum autoencoders, which depend on stochastic optimization and face challenges such as shot noise, barren plateaus, and non-convex optimization landscapes, our deterministic method substantially reduces the complexity and computational overhead of quantum data compression. We evaluate the performance of the compressor through numerical experiments, demonstrating its ability to achieve high fidelity in quantum state reconstruction compared to variational quantum algorithms. Furthermore, we demonstrate the practical utility of the Schmidt quantum compressor in one-class classification tasks.
Authors
- Israel F. Araujo (ORCID: https://orcid.org/0000-0002-0308-8701)
- Nayeli A. Rodríguez-Briones (ORCID: https://orcid.org/0000-0002-3945-518X)
- Daniel K. Park (ORCID: https://orcid.org/0000-0002-3177-4143)
- Hyeondo Oh (ORCID: https://orcid.org/0009-0000-6331-3387)
Institutions
- TU Wien (AT)
- Yonsei University (KR)
- Universidade Federal de Pernambuco (BR)
- Miller College (US)
Publication Details
- Journal
- Quantum Science and Technology
- Published
- 2025-04-16
- DOI
- https://doi.org/10.1088/2058-9565/adcd99
- Primary Topic
- Advanced Thermodynamics and Statistical Mechanics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Adolph C. and Mary Sprague Miller Institute for Basic Research in Science, University of California Berkeley
- Yonsei University
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Korea Institute of Science and Technology
- National Research Foundation of Korea
- Österreichische Forschungsförderungsgesellschaft
- European Research Council
- Institute for Information and Communications Technology Promotion