Machine Learning-Enhanced Integrated Optical Couplers for Trapped Ion Qubits

We propose machine learning-driven grating coupler in silicon nitride for trapped Ca + ion qubit manipulation, achieving −28.3 dB crosstalk, 0.56 μm beam radius, and 34% efficiency, paving the way to high-fidelity trapped-ion quantum information systems..

Authors

Publication Details

Published
2025-01-01
DOI
https://doi.org/10.1364/cleo_at.2025.jps200_106
Primary Topic
Quantum Information and Cryptography
Type
article
Field-Weighted Citation Impact
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article

Machine Learning-Enhanced Integrated Optical Couplers for Trapped Ion Qubits

Maxim R. Shcherbakov, Melika Momenzadeh
Quantum Information and Cryptography
article

Machine Learning-Enhanced Integrated Optical Couplers for Trapped Ion Qubits

Maxim R. Shcherbakov, Melika Momenzadeh
article en

Abstract

We propose machine learning-driven grating coupler in silicon nitride for trapped Ca + ion qubit manipulation, achieving −28.3 dB crosstalk, 0.56 μm beam radius, and 34% efficiency, paving the way to high-fidelity trapped-ion quantum information systems..

Openalex Percentile: Top 87%
Quantum Information and Cryptography
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Machine Learning-Enhanced Integrated Optical Couplers for Trapped Ion Qubits — Maxim R. Shcherbakov, Melika Momenzadeh · (2025) | TGRS Research Map | TGRS