Real-Time Prediction of Solid-State Quantum Multi-Emitter Systems with Deep Learning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Spectral jumps in quantum emitters are detrimental to scalable quantum architecture. We analyze spectral jumps in multiple single-photon emitters based on the SiN platform and predict them using a deep-learning algorithm.

Original languageEnglish
Title of host publication2025 Conference on Lasers and Electro-Optics, CLEO 2025
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781957171500
StatePublished - 2025
Event2025 Conference on Lasers and Electro-Optics, CLEO 2025 - Long Beach, United States
Duration: May 4 2025May 9 2025

Publication series

Name2025 Conference on Lasers and Electro-Optics, CLEO 2025

Conference

Conference2025 Conference on Lasers and Electro-Optics, CLEO 2025
Country/TerritoryUnited States
CityLong Beach
Period05/4/2505/9/25

Funding

This material is based upon work supported by the U.S. Department of Energy, Office of Science, Office of Basic Energy Sciences Energy Frontier Research Centers program under Award Number DE-SC0025620. Cryo-photoluminescence measurements were supported by the Center for Nanophase Materials Sciences (CNMS), which is a US Department of Energy, Office of Science User Facility at Oak Ridge National Laboratory

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