Episode description
Episode description
During this time of lockdown, the centre for quantum software and information (QSI) at the University of Technology Sydney has launched an online seminar series. With talks once or twice a week from leading researchers in the field, meQuanics is supporting this series by mirroring the audio from each talk. I would encourage if you listen to this episode, to visit and subscribe to the UTS:QSI YouTube page to see each of these talks with the associated slides to help it make more sense.
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/1908.01082Experimental Demonstration of Self-Guided Quantum Tomography: https://arxiv.org/abs/1602.04194Self-guided quantum tomography: https://arxiv.org/abs/1406.4101
OTHER LINKS: Chris Ferrie: csferrie.com/