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Quantum Physics

arXiv:2011.01490 (quant-ph)
[Submitted on 3 Nov 2020]

Title:Surpassing the Classical Limit in Magic Square Game with Distant Quantum Dots Coupled to Optical Cavities

Authors:Sinan Bugu, Fatih Ozaydin, Tetsuo Kodera
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Abstract:The emergence of quantum technologies is heating up the debate on quantum supremacy, usually focusing on the feasibility of looking good on paper algorithms in realistic settings, due to the vulnerability of quantum systems to myriad sources of noise. In this vein, an interesting example of quantum pseudo-telepathy games that quantum mechanical resources can theoretically outperform classical resources is the Magic Square game (MSG), in which two players play against a referee. Due to noise, however, the unit winning probability of the players can drop well below the classical limit. Here, we propose a timely and unprecedented experimental setup for quantum computation with quantum dots inside optical cavities, along with ancillary photons for realizing interactions between distant dots to implement the MSG. Considering various physical imperfections of our setup, we first show that the MSG can be implemented with the current technology, outperforming the classical resources under realistic conditions. Next, we show that our work gives rise to a new version of the game. That is, if the referee has information on the physical realization and strategy of the players, he can bias the game through filtered randomness and increase his winning probability. We believe our work contributes to not only quantum game theory, but also quantum computing with quantum dots.
Comments: 11 pages, 5 figures
Subjects: Quantum Physics (quant-ph); Mesoscale and Nanoscale Physics (cond-mat.mes-hall)
Cite as: arXiv:2011.01490 [quant-ph]
  (or arXiv:2011.01490v1 [quant-ph] for this version)
  https://doi.org/10.48550/arXiv.2011.01490
arXiv-issued DOI via DataCite
Journal reference: Sci Rep 10, 22202 (2020)
Related DOI: https://doi.org/10.1038/s41598-020-79295-x
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From: Sinan Bugu Mr. [view email]
[v1] Tue, 3 Nov 2020 05:45:06 UTC (1,307 KB)
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