Optimal shaping of quantum noise in multimode nonlinear photonics

We theoretically show that coherently shaping the input signal to a nonlinear multimode system strongly enhances the ability to generate light with quantum statistics, relative to simple unshaped inputs. This is illustrated for several nonlinear systems.

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Publication Details

Published
2025-01-01
DOI
https://doi.org/10.1364/cleo_fs.2025.ff139_1
Primary Topic
Neural Networks and Reservoir Computing
Type
article
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article

Optimal shaping of quantum noise in multimode nonlinear photonics

Shiekh Zia Uddin, Nicholas Rivera, Michael Horodynski, Marin Soljačić et al.
Neural Networks and Reservoir Computing
article

Optimal shaping of quantum noise in multimode nonlinear photonics

Shiekh Zia Uddin, Nicholas Rivera, Michael Horodynski, Marin Soljačić, Jamison Sloan
article en

Abstract

We theoretically show that coherently shaping the input signal to a nonlinear multimode system strongly enhances the ability to generate light with quantum statistics, relative to simple unshaped inputs. This is illustrated for several nonlinear systems.

Openalex Percentile: Top 87%
Neural Networks and Reservoir Computing
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Optimal shaping of quantum noise in multimode nonlinear photonics — Shiekh Zia Uddin, Nicholas Rivera, et al. · (2025) | TGRS Research Map | TGRS