Berkeley, California, United States
A graduate student enthusiastic about quantum computing, worked on deep learning and quantum machine learning researches but more interested in experimental realization of quantum computers. Currently focusing on trapped electron quantum information processing. A physicist by heart and a strong believer of the Bousso-Susskind Multiverse Interpretation of Quantum Mechanics. Amateur in music, with an interest in playing some traditional Chinese music instruments.
Conducted numerical simulations to study the temperature requirements for forming electron Coulomb crystals in a linear Paul Trap; Designed and improved the experiemental control system for trapping electrons as qubits using ARTIQ and LabRAD.
Organized panels on quantum computing by reaching out to experts in the industry and academia, outlining the procedure for the panel, and devising inquiries for the panelists; administered the Study Group by giving short lectures on quantum computing, answering questions regarding theories or algorithms, and explaining tutorials on using the Qiskit package; developed the Project Group by giving presentations on quantum Sudoku solver, sharing papers on quantum Parrondo's paradox, and initiating algorithm implementation projects on quantum games.
Applied Graph Neural Networks for reconstructing the mass of tau leptons in particle collision events in collaboration with the ATLAS group; Constructed an attention model with relational inductive bias to improve the accuracy of reconstruction; Completed a model that predicts the invariant mass of two tau leptons in a collision event with mean pull value of 0.002.
Simulated a star with star-spot features and created an artificial surface brightness map with hypothetical line spectra; reconstructed the surface brightness map from the hypothetical spectra using the maximum entropy method; studied and compared the results obtained from the maximum entropy method with other methods including pseudo inverse and least square.