ABSTRACT
In this talk, I will first illustrate the implementation of our machine-learning (ML) enhanced quantum state tomography (QST) for continuous variables, through the experimentally measured data generated from squeezed vacuum states, as an example of quantum machine learning. Our recent progress in applying such a ML-QST as a crucial diagnostic toolbox for applications with squeezed states, from Wigner currents, optical cat state generation, and Bayesian estimation for GWD will be reported.
BIOGRAPHY
Prof. Ray-Kuang Lee received his BS degree from National Taiwan University in 1997, and his MS and PhD degrees from National Chiao Tung University, in 1999 and 2004, respectively. In 2005, he joined the Institute of Photonics Technologies at National Tsing Hua University (NTHU) and was promoted to full Professor in 2013. He is a Fellow from Optical Society of America. He received Outstanding Research Award (ORA) twice from the National Science and Technology Council (NSTC), Taiwan, Young Investigator Award from the Academic Sinica, Wu Ta You Memorial Award from the National Science Council.
Prof. Lee’s research interests cover a wide range of topics on the quantum properties of light. Currently, he is working on the implementation of quantum noise reduction for the advanced gravitational wave detectors (KAGRA and Einstein Telescope), photonic quantum chips with error-correction codes, the development on the quantum machine learning for quantum state tomography and quantum metrology.
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