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Small quantum computers and large classical data sets

May 20, 2020 - 11:00am
Speaker: 
Aram Harrow
Institution: 
MIT

Can a quantum computer help us analyze a large classical data set? Data stored classically cannot be queried in superposition, which rules out direct Grover searches, and it can often be classically accessed with some level of parallelism, which would negate the advantage of Grover even if it were possible. In this talk I will explore how to use quantum computers for data analysis tasks, such as maximum likelihood estimation, in the setting where the data set is too large to fit on the quantum computer, and at the same time, large classical computers are available.  Based on https://arxiv.org/abs/2004.00026

https://www.youtube.com/watch?v=Cl7pw1PuaNo

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