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September 19, 2025

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

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Authors

PMPranshu MaanYCYuheng ChenSBSean Borneman

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Overview

Observational analysis predicts spectral jumps in quantum emitters, suggesting improvements for scalable quantum architecture.

Key Points

  • The deep learning model predicts spectral jumps in quantum emitters, enhancing performance in quantum systems.
  • Spectral jumps were analyzed in multiple single-photon emitters based on the SiN platform, revealing critical behavior.
  • The approach utilized deep learning algorithms to provide real-time predictions related to quantum emitters.
  • Potential improvements in scalable quantum architectures may be realized through better predictions of emitter behaviors.

Cite This Study

Maan et al. (2025) studied this question.

synapsesocial.com/papers/68d464f131b076d99fa644dbhttps://doi.org/10.1364/cleo_at.2025.jps200_111
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