Towards room-temperature integrated quantum photonics through reduction of the quantum decoherence using machine learning

Pablo A. Postigo

doi:10.1117/12.2683220

19 July 2023 Towards room-temperature integrated quantum photonics through reduction of the quantum decoherence using machine learning

Pablo A. Postigo

Author Affiliations +

Proceedings Volume PC12633, Photonics for Quantum 2023; PC126330G (2023) https://doi.org/10.1117/12.2683220
Event: Photonics for Quantum, 2023, Rochester, New York, United States

Abstract

The development of on-chip, CMOS-compatible quantum photonics is critical for future scalable quantum communications, quantum computing, and quantum sensing. Integrated photonic waveguides, photonic resonators, and single-photon emitters are essential building blocks for such a purpose. In this talk, I will present how machine learning (ML) can enhance the quantum properties of these building blocks, specifically the indistinguishability (I) of the generated single photons, with a further decrease in quantum decoherence.

Conference Presentation

Citation Download Citation

Pablo A. Postigo "Towards room-temperature integrated quantum photonics through reduction of the quantum decoherence using machine learning", Proc. SPIE PC12633, Photonics for Quantum 2023, PC126330G (19 July 2023); https://doi.org/10.1117/12.2683220

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available