Experimental quantum hamiltonian learning using a silicon photonic chip and a nitrogen-vacancy electron spin in diamond

Stefano Paesani, Jianwei Wang, Raffaele Santagati, Sebastian Knauer, Antonio Andreas Gentile, Nathan Wiebe, Maurangelo Petruzzella, Anthony Laing, John Rarity, Jeremy O'Brien, Mark Thompson

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

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Abstract

The efficient characterization and validation of the underlying model of a quantum physical system is a central challenge in the development of quantum devices and for our understanding of foundational quantum physics. However, the impossibility to efficiently predict the behaviour of complex quantum models on classical machines makes this challenge to be intractable to classical approaches. Quantum Hamiltonian Learning (QHL) [1, 2] combines the capabilities of quantum information processing and classical machine learning to allow the efficient characterisation of the model of quantum systems. In QHL the behaviour of a quantum Hamiltonian model is efficiently predicted by a quantum simulator, and the predictions are contrasted with the data obtained from the quantum system to infer the system Hamiltonian via Bayesian methods.
Original languageEnglish
Title of host publication2017 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC)
Subtitle of host publicationProceedings of a meeting held 25-29 June 2017, Munich, Germany
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISBN (Electronic)9781509067367
ISBN (Print)9781509067374
DOIs
Publication statusPublished - 30 Oct 2017
EventConference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC 2017 - Munich, Germany
Duration: 25 Jun 201729 Jun 2017
http://www.cleoeurope.org/

Conference

ConferenceConference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC 2017
Abbreviated titleCLEO/Europe-EQEC
CountryGermany
CityMunich
Period25/06/1729/06/17
Internet address

Structured keywords

  • Bristol Quantum Information Institute

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  • Projects

    Fabricating a photonic quantum computer.

    O'Brien, J. L.

    1/04/1331/03/18

    Project: Research

    Cite this

    Paesani, S., Wang, J., Santagati, R., Knauer, S., Gentile, A. A., Wiebe, N., Petruzzella, M., Laing, A., Rarity, J., O'Brien, J., & Thompson, M. (2017). Experimental quantum hamiltonian learning using a silicon photonic chip and a nitrogen-vacancy electron spin in diamond. In 2017 Conference on Lasers and Electro-Optics Europe & European Quantum Electronics Conference (CLEO/Europe-EQEC): Proceedings of a meeting held 25-29 June 2017, Munich, Germany Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/CLEOE-EQEC.2017.8087392