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Calibration and high fidelity measurement of a quantum photonic chip.

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Title: Calibration and high fidelity measurement of a quantum photonic chip.
Authors: Li, H. W.1, Wabnig, J.1, Bitauld, D.1, Shadbolt, P.2, Politi, A.2,3, Laing2, A., O'Brien, J. L.2, Niskanen, A. O.1 antti.niskanen@nokia.com
Source: New Journal of Physics. 2013, Vol. 15 Issue 6, p1-15. 15p.
Subjects: Quantum states, Photonics, Calibration, Bayesian analysis, Markov chain Monte Carlo, Tomography
Abstract: Integrated quantum photonic circuits are becoming increasingly complex. Accurate calibration of device parameters and detailed characterization of the prepared quantum states are critically important for future progress. Here we report on an effective experimental calibration method based on Bayesian updating and Markov chain Monte Carlo integration. We use this calibration technique to characterize a two qubit chip and extract the reflectivities of its directional couplers. An average quantum state tomography fidelity of 93.79± 1.05% against the four Bell states is achieved. Furthermore, comparing the measured density matrices against a model using the non-ideal device parameters derived from the calibration we achieve an average fidelity of 97.57±0.96%. This pinpoints non-ideality of chip parameters as a major factor in the decrease of Bell state fidelity. We also perform quantum state tomography for Bell states while continuously varying photon distinguishability and find excellent agreement with theory. [ABSTRACT FROM AUTHOR]
Copyright of New Journal of Physics is the property of IOP Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
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DbLabel: Engineering Source
An: 90130920
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
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  Data: Calibration and high fidelity measurement of a quantum photonic chip.
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  Data: Integrated quantum photonic circuits are becoming increasingly complex. Accurate calibration of device parameters and detailed characterization of the prepared quantum states are critically important for future progress. Here we report on an effective experimental calibration method based on Bayesian updating and Markov chain Monte Carlo integration. We use this calibration technique to characterize a two qubit chip and extract the reflectivities of its directional couplers. An average quantum state tomography fidelity of 93.79± 1.05% against the four Bell states is achieved. Furthermore, comparing the measured density matrices against a model using the non-ideal device parameters derived from the calibration we achieve an average fidelity of 97.57±0.96%. This pinpoints non-ideality of chip parameters as a major factor in the decrease of Bell state fidelity. We also perform quantum state tomography for Bell states while continuously varying photon distinguishability and find excellent agreement with theory. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of New Journal of Physics is the property of IOP Publishing and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1088/1367-2630/15/6/063017
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      – SubjectFull: Calibration
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      – SubjectFull: Bayesian analysis
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      – SubjectFull: Markov chain Monte Carlo
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      – SubjectFull: Tomography
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              Text: 2013
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