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Quantum Optics with Machine-Learning: Introduction to Machine Learning Enhanced Quantum State Tomography
In this webinar hosted by the Optics in Digital Systems Technical Group, Dr. Ray-Kuang Lee will be covering fundamental details about machine-learning (ML) enhanced quantum state tomography (QST) for squeezed states.

Implementation of machine learning architecture with a convolutional neural network will be illustrated and demonstrated through the experimentally measured data generated from squeezed vacuum states. Dr. Lee will discuss the measurement results in detail. Dr. Lee will also cover progress in applying such an MLQST as an essential diagnostic toolbox for applications with squeezed states, from quantum information process, quantum metrology, and advanced gravitational wave detectors to macroscopic quantum state generation.

Subject Matter Level:
• Introductory - Assumes little previous knowledge of the topic

What You Will Learn:
• Quantum noise squeezing in quantum optics
• Quantum state tomography
• Machine-learning enhanced quantum state tomography

Who Should Attend:
• Students
• Ph.D. research scholars
• Early-stage researchers/post-doctoral fellows

Aug 10, 2022 10:00 AM in Eastern Time (US and Canada)

Webinar is over, you cannot register now. If you have any questions, please contact Webinar host: Optica Technical Groups.