×

IQIM Caltech's video: IQIM Virtual Seminar April 17 2020 Hsin-Yuan Robert Huang

@IQIM Virtual Seminar, April 17, 2020 – Hsin-Yuan (Robert) Huang
Speaker: Hsin-Yuan (Robert) Huang, Graduate student, Vidick/Preskill groups Title: Predicting Many Properties of a Quantum System from Very Few Measurements Abstract: Predicting properties of complex, large-scale quantum systems is essential for developing quantum technologies. We present an efficient method for constructing an approximate classical description of a quantum state using very few measurements of the state. This description, called a classical shadow, can be used to predict many different properties: order log(M) measurements suffice to accurately predict M different functions of the state with high success probability. The number of measurements is independent of the system size and saturates information-theoretic lower bounds. Moreover, target properties to predict can be selected after the measurements are completed. We support our theoretical findings with extensive numerical experiments. We apply classical shadows to predict quantum fidelities, entanglement entropies, two-point correlation functions, expectation values of local observables, and the energy variance of many-body local Hamiltonians. The numerical results highlight the advantages of classical shadows relative to previously known methods. (This work will appear on Nature Physics and the arXiv link is at https://arxiv.org/abs/2002.08953)

21

0
IQIM Caltech
Subscribers
20.7K
Total Post
54
Total Views
8.5M
Avg. Views
156.6K
View Profile
This video was published on 2020-04-21 04:51:14 GMT by @IQIM-Caltech on Youtube. IQIM Caltech has total 20.7K subscribers on Youtube and has a total of 54 video.This video has received 21 Likes which are lower than the average likes that IQIM Caltech gets . @IQIM-Caltech receives an average views of 156.6K per video on Youtube.This video has received 0 comments which are lower than the average comments that IQIM Caltech gets . Overall the views for this video was lower than the average for the profile.

Other post by @IQIM Caltech