The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Quantum Algorithms for Quantum Field Theories
Open accessAbstract
Quantum Leap?: Quantum computers are expected to be able to solve some of the most difficult problems in mathematics and physics. It is not known, however, whether quantum field theories (QFTs) can be simulated efficiently with a quantum computer. QFTs are used in particle and condensed matter physics and have an infinite number of degrees of freedom; discretization is necessary to simulate them digitally. Jordan et al. (p. 1130 ; see the Perspective by Hauke et al. ) present an algorithm for the efficient simulation of a particular kind of QFT (with quartic interactions) and estimate the error caused by discretization. Even for the most difficult case of strong interactions, the run time of the algorithm was polynomial (rather than exponential) in parameters such as the number of particles, their energy, and the prescribed precision, making it much more efficient than the best classical algorithms.
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Cites
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Cited by
Georgescu, I. M., Ashhab, S., & Nori, F. (2014) · Reviews of Modern Physics · doi:10.1103/revmodphys.86.153 · Cited by 2,932
“Another proposal for the DQS of field theories was given in (Jordan et al., 2012).”
BackgroundMajorana zero modes and topological quantum computation
Sarma, S. D., Freedman, M., & Nayak, C. (2015) · npj Quantum Information · doi:10.1038/npjqi.2015.1 · Cited by 1,180
Quantum algorithms: an overview
Montanaro, A. (2016) · npj Quantum Information · doi:10.1038/npjqi.2015.23 · Cited by 1,071
“Examples include work on increasing the accuracy of quantum simulation while retaining a fast runtime [14]; optimising the algorithm for particular applications such as quantum chemistry [48]; and exploring applications to new areas such as quantum (cid:12)eld theory [53].”
Self-verifying variational quantum simulation of lattice models
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Toward the first quantum simulation with quantum speedup
Childs, A. M., Maslov, D., Nam, Y., Ross, N. J., & Su, Y. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1801723115 · Cited by 551
Metadata
- Authors
- Jordan, S. P., Lee, K. S. M., & Preskill, J.
- Venue
- Science
- Published
- 2012-06
- Volume
- 336
- Issue
- 6085
- Pages
- 1130-1133
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W1982899292
- Cited by
- 517
- References
- 43
- FWCI
- 19.31
- Type
- journal article
- Language
- en
- Open access
- green
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
