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.
https://youtu.be/OfY7lFIBTGY
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/
