Cluster state preparation using gates operating at arbitrary success probabilities
Open accessAbstract
Several physical architectures allow for measurement-based quantum computing using sequential preparation of cluster states by means of probabilistic quantum gates. In such an approach, the order in which partial resources are combined to form the final cluster state turns out to be crucially important. We determine the influence of this classical decision process on the expected size of the final cluster. Extending earlier work, we consider different quantum gates operating at various probabilites of success. For finite resources, we employ a computer algebra system to obtain the provably optimal classical control strategy and derive symbolic results for the expected final size of the cluster. We identify two regimes: when the success probability of the elementary gates is high, the influence of the classical control strategy is found to be negligible. In that case, other figures of merit become more relevant. In contrast, for small probabilities of success, the choice of an appropriate strategy is crucial.
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Due to the non-deterministic nature of entangling gates, the one-way model is the most natural approach to scalable quantum computation in hybrid optical-matter schemes.
“Due to the non-deterministic nature of the entangling gates, the one-way model is, again, the most natural approach to scalable quantum computation either via non-deterministic strategies 39,53 , repeat-until-success strategies 52 or so-called 'broker-client' approaches 54 .”
From Measurement-based quantum computation (2009) · cites this paper as [53]
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References 25 · Cited by 21
Research works printed but not linked: 7
- Raussendorf R and Briegel H J 2001 Phys. Rev. Lett. 86 910 · DOI · Paper page
- Briegel H J and Raussendorf R 2001 Phys. Rev. Lett. 86 5188 · DOI · Paper page
- Gross D and Eisert J 2006 Preprint quant-ph/0609149 · arXiv
- Bao X-H, Chen T-Y, Zhang Q, Yang J, Zhang H, Yang T and Pan J-W 2006 Preprint quant-ph/0610182 · arXiv
- Louis S G R, Nemoto K, Munro W J and Spiller T P 2006 Preprint quant-ph/0607060 · arXiv
- Duan L-M, Madsen M J, Moehring D L, Maunz P, Kohn Jr R N and Monroe C 2006 Preprint quant-ph/0603285 · arXiv
- Kieling K, Rudolph T and Eisert J 2006 Preprint quant-ph/0611140 · arXiv
- Authors
- Kieling, K., Gross, D., & Eisert, J.
- Affiliations
- London Institute for Mathematical Sciences (GB)
- ORCID
- Eisert, J
- Venue
- New Journal of Physics
- Publisher
- IOP Publishing
- Published
- 2007-06-29
- Volume
- 9
- Issue
- 6
- Pages
- 200-200
- ISSN
- 1367-2630 (ISSN-L)
- OpenAlex
- W2098496471
- Cited by
- 21
- References
- 25
- Citations by year
- 2021: 1 · 2015: 1 · 2014: 2 · 2013: 1 · 2012: 3
- FWCI
- 3.55
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- New Journal of Physics (publishedVersion, cc-by)
- arXiv (Cornell University) (publishedVersion)
- CERN Document Server (European Organization for Nuclear Research) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Microsoft Research
- Deutsche Forschungsgemeinschaft
- Engineering and Physical Sciences Research Council
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Computing Algorithms and Architecture
- Physical Sciences › Computer Science › Artificial Intelligence › Quantum Information and Cryptography
- Physical Sciences › Physics and Astronomy › Atomic and Molecular Physics, and Optics › Quantum many-body systems
- Keywords
- measurement-based quantum computation, optimal control policy, finite resources
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