Demonstrating the flexibility and precision of quantum singular value transform (QSVT) to implement tools in quantum linear algebra, quantum noise recovery and optimal quantum measurements.
TITLE: Introduction to Quantum Singular Value Transform with Applications to Petz map, Polar Decomposition and Pretty-Good Measurements
SPEAKER: Yihui Quek
AFFILIATION: Stanford University, California, USA
ABSTRACT:
The recently-introduced quantum algorithmic technique of quantum singular value transform (QSVT) has been hailed as a ‘grand unification of quantum algorithms’. In this talk, we give a pedagogical introduction to this toolbox, and illustrate its flexibility and precision by using it to implement tools in quantum linear algebra, quantum noise recovery and optimal quantum measurements: i) the quantum polar decomposition ii) the Petz recovery channel iii) pretty-good measurements. Previously, a significant hurdle to the experimental realization of these vaunted theoretical tools was the lack of a systematic and efficient method to implement them; we rectify this lack by proposing quantum algorithms for all three tools based on QSVT.
This talk is based on arXiv:2006.16924 (https://arxiv.org/abs/2006.16924) and arXiv:2106.07634 (https://arxiv.org/abs/2106.07634).
HOSTED BY: Dr Mária Kieferová, Centre for Quantum Software and Information, University of Technology Sydney, Australia
https://www.uts.edu.au/research-and-teaching/our-research/centre-quantum-software-and-information
