This event is part of Statistical Methods and Mathematical Analysis for Quantum Information Science View Details

The Power of Near-Term Quantum Experiments

Algorithms, Noise, and Quantum Advantage beyond NISQ

Description

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We are currently in a critical period for the field of quantum computation known as the Noisy Intermediate Scale Quantum (NISQ) era, which has been marked by the first claims of experimentally implemented quantum advantage.  Despite this we do not fully understand the computational power of near-term quantum systems which are limited by uncorrected noise and relatively modest quantum resources such as number of qubits and circuit depth.  

Many important questions remain: can we prove that current quantum experiments can outperform efficient classical algorithms at solving certain specific tasks?  Can classical algorithms take advantage of uncorrected noise to quickly simulate near-term quantum experiments?  And perhaps most pressingly, how can we mitigate the noise in quantum experiments to achieve a robust quantum computational advantage without incurring the formidable overhead of quantum error-correction?  This workshop will bring together researchers from a variety of perspectives — including computer scientists, physicists, and mathematicians, with the goal of answering these questions to rigorously characterize the power of near-term quantum computation.

Organizer

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B F
Bill Fefferman University of Chicago

Speakers

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S D
Shaun Datta Stanford University
A D
Abhinav Deshpande IBM
A G
Alexey Gorshkov University of Maryland and NIST
D G
David Gosset University of Waterloo
D G
Daniel Grier University of California, San Diego
Y L
Yunchao Liu University of California, Berkeley
C O
Changhun Oh Korea Advanced Institute of Science & Technology
Y Q
Yihui Quek Harvard University
N Q
Nicholas Quesada Polytechnique Montreal
A S
Adam Shaw Caltech
B V
Benjamin Villalonga Google
J W
James Watson University of Maryland

Registration

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