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Edward Farhi

Researcher at Google

Publications -  165
Citations -  26750

Edward Farhi is an academic researcher from Google. The author has contributed to research in topics: Quantum computer & Quantum algorithm. The author has an hindex of 57, co-authored 149 publications receiving 20226 citations. Previous affiliations of Edward Farhi include Sandia National Laboratories & University of California, Santa Barbara.

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Supplementary information for "Quantum supremacy using a programmable superconducting processor"

TL;DR: In this paper, an updated version of supplementary information to accompany "Quantum supremacy using a programmable superconducting processor", an article published in the October 24, 2019 issue of Nature, is presented.
Journal ArticleDOI

Quantum supremacy using a programmable superconducting processor

Frank Arute, +85 more
- 24 Oct 2019 - 
TL;DR: Quantum supremacy is demonstrated using a programmable superconducting processor known as Sycamore, taking approximately 200 seconds to sample one instance of a quantum circuit a million times, which would take a state-of-the-art supercomputer around ten thousand years to compute.
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A Quantum Adiabatic Evolution Algorithm Applied to Random Instances of an NP-Complete Problem

TL;DR: For the small examples that the authors could simulate, the quantum adiabatic algorithm worked well, providing evidence that quantum computers (if large ones can be built) may be able to outperform ordinary computers on hard sets of instances of NP-complete problems.
Posted Content

A Quantum Approximate Optimization Algorithm

TL;DR: A quantum algorithm that produces approximate solutions for combinatorial optimization problems that depends on a positive integer p and the quality of the approximation improves as p is increased, and is studied as applied to MaxCut on regular graphs.
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Quantum computation and decision trees

TL;DR: This work devise a quantum-mechanical algorithm that evolves a state, initially localized at the root, through the tree, and proves that if the classical strategy succeeds in reaching level $n$ in time polynomial in $n,$ then so does the quantum algorithm.