ABSTRACT
As we have come into the second wave of the quantum revolution, the available quantum hardware is often noisy and with no explicit error correction scheme. Quantum computing tasks using such devices are known as NISQ algorithms [1]. Here, in this talk, I will tell you our recent effort in resource-efficient bosonic quantum simulation [2] given a limited number of qubits and gates, in particular, in the area of quantum simulations of quantum processors [3, 4], and adaptive ansatz construction [5]. Lastly, I will end the talk by briefly outlining our recent work on unsupervised classical machine learning quantum trajectories [6], and how one can make use of our proposal to help build better NISQ devices.
References:
[1] KB, ACL, THK, et. al., Noisy intermediate-scale quantum (NISQ) algorithms, arXiv:2101.08448 (2021)
[2] NPDS, TM, THK, et. al., Resource-efficient digital quantum simulation of d-level systems for photonic, vibrational, and spin-s Hamiltonians, npjQI (2020)
[3] THK, et. al., Quantum computer-aided design: digital quantum simulation of quantum processors, arXiv:2006.03070 (2020)
[4] JK, MK, THK, et. al., Quantum Computer-Aided design of Quantum Optics Hardware, arXiv:2006.03075 (2020)
[5] ZJZ, THK, et. al., Mutual information-assisted adaptive variational quantum eigensolver, QST (2021)
[6] MC, DFS, THK, AAG, Unsupervised machine learning quantum dynamics, (in preparation)
BIOGRAPHY
Dr. Thi Ha Kyaw is a recipient of the International Centre for Theoretical Physics Trieste TRIL fellowship and Niels Bohr Institute fellowship. He is currently a post-doctoral researcher at the University of Toronto. His Ph.D. thesis titled "Towards large-scale quantum computing platform in ultra-strong coupling regime" was named best of the best by Springer in 2019 and “Best New Quantum Computing Books To Read In 2021” by Bookauthority.org. His research interest includes quantum computing, quantum simulation, open quantum systems, ultra-strong light-matter interaction, and quantum controlled dynamics.
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