Quantum Supremacy through the Quantum Approximate Optimization Algorithm
Edward Farhi, Aram W Harrow

TL;DR
This paper argues that the Quantum Approximate Optimization Algorithm (QAOA) can demonstrate quantum supremacy by producing output distributions that are hard to simulate classically, even at low depths, making it promising for near-term quantum computers.
Contribution
It establishes that QAOA's output distribution cannot be efficiently simulated classically under reasonable assumptions, highlighting its potential for quantum supremacy beyond optimization.
Findings
QAOA's output distribution is hard to simulate classically.
Classical simulation of QAOA would collapse the Polynomial Hierarchy.
QAOA is a promising candidate for demonstrating quantum supremacy.
Abstract
The Quantum Approximate Optimization Algorithm (QAOA) is designed to run on a gate model quantum computer and has shallow depth. It takes as input a combinatorial optimization problem and outputs a string that satisfies a high fraction of the maximum number of clauses that can be satisfied. For certain problems the lowest depth version of the QAOA has provable performance guarantees although there exist classical algorithms that have better guarantees. Here we argue that beyond its possible computational value the QAOA can exhibit a form of Quantum Supremacy in that, based on reasonable complexity theoretic assumptions, the output distribution of even the lowest depth version cannot be efficiently simulated on any classical device. We contrast this with the case of sampling from the output of a quantum computer running the Quantum Adiabatic Algorithm (QADI) with the restriction that the…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Low-power high-performance VLSI design
