Efficient strategies for reducing sampling error in quantum Krylov subspace diagonalization
Sampling error in quantum Krylov subspace diagonalization is significantly reduced using novel shifting and coefficient splitting techniques.
Authors
- Gwonhak Lee (ORCID: https://orcid.org/0000-0002-9302-5834)
- Seonghoon Choi (ORCID: https://orcid.org/0000-0002-1904-0059)
- Artur F. Izmaylov (ORCID: https://orcid.org/0000-0001-8035-6020)
- Joonsuk Huh (ORCID: https://orcid.org/0000-0002-8792-5641)
Institutions
- University of Toronto (CA)
- Yonsei University (KR)
- Scarborough Health Network (CA)
- Sungkyunkwan University (KR)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d4dd00321g
- Citations
- 4
- Primary Topic
- Quantum Computing Algorithms and Architecture
- Type
- article
- Field-Weighted Citation Impact
- 9.92
Funders
- National Research Foundation
- Ministry of Trade, Industry and Energy
- Ministry of Science, ICT and Future Planning
- National Research Foundation of Korea
- Ministry of Education, Science and Technology
- Ministry of Science and ICT, South Korea
- Natural Sciences and Engineering Research Council of Canada
- Institute for Information and Communications Technology Promotion