Self-Guided Quantum Learning: Estimation via optimisation applied to quantum estimation
TITLE: Self-Guided Quantum Learning
SPEAKER: Associate Professor Chris Ferrie
AFFILIATION: Centre for Quantum Software and Information, University of Technology Sydney, Australia
HOSTED BY: Dr Clara Javaherian, UTS Centre for Quantum Software and Information, Australia
ABSTRACT:
Quantum state learning is often understood as a data analytics problem—large amounts of data collected from many prior repetitions of incompatible measurements need to be churned into a single estimate of a quantum state or channel. In this talk, I will present an adaptive optimisation algorithm which achieves the same goal, but at a drastic reduction in time and space complexity.
RELATED ARTICLES:
Experimental realization of self-guided quantum process tomography: https://arxiv.org/abs/1908.01082
Experimental Demonstration of Self-Guided Quantum Tomography: https://arxiv.org/abs/1602.04194
Self-guided quantum tomography: https://arxiv.org/abs/1406.4101
OTHER LINKS:
Chris Ferrie: csferrie.com/
UTS Centre for Quantum Software and Information: https://www.uts.edu.au/research-and-teaching/our-research/centre-quantum-software-and-information
Clara Javaherian: https://www.uts.edu.au/staff/clara.javaherian
