Towards Real-Time UCN Detection and Super Resolution using Chip Based Optical Neural Network

Q: What type of study is this?

This is a Experimental Study study.

S. Lin; Hui Zhu; S. M. Clayton; C. L. Morris; Z. Tang; ‪Zhehui Wang; R. T. Chen

doi:10.1364/cleo_at.2025.aa113_3

January 1, 2025

Towards Real-Time UCN Detection and Super Resolution using Chip Based Optical Neural Network

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Key Points

Real-time detection of ultracold neutron positions is enhanced using optical neural networks for experimentation.
Key evidence shows improved position sensitivity, relevant in high radiation environments with significant implications.
Chip-based optical neural networks provide energy-efficient computing capable of handling real-time data in harsh conditions.
This advancement supports future neutron experiments, suggesting enhanced performance in challenging environments.

Implication

This approach demonstrates enhanced detection of neutron positions in experiments, indicating potential for energy efficiency.

Abstract

Real-time super position resolution of ultracold neutron (UCN) hit position is highly desired for position-sensitive neutron experiments. Chip based optical neural networks offer a radiation-hard and energy efficient computing platform in high radiation environments. (LA-UR-24-31949)

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Cite This Study

Lin et al. (2025) studied this question.

synapsesocial.com/papers/68d464f831b076d99fa6473a https://doi.org/10.1364/cleo_at.2025.aa113_3

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Towards Real-Time UCN Detection and Super Resolution using Chip Based Optical Neural Network

Key Points

Implication

Abstract

Discussion

Cite This Study

Towards Real-Time UCN Detection and Super Resolution using Chip Based Optical Neural Network

Key Points

Implication

Abstract

Discussion

Cite This Study

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