skip to main content
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: QAOA for Max-Cut requires hundreds of qubits for quantum speed-up

Abstract

Computational quantum technologies are entering a new phase in which noisy intermediate-scale quantum computers are available, but are still too small to benefit from active error correction. Even with a finite coherence budget to invest in quantum information processing, noisy devices with about 50 qubits are expected to experimentally demonstrate quantum supremacy in the next few years. Defined in terms of artificial tasks, current proposals for quantum supremacy, even if successful, will not help to facilitate solutions to practical problems. In contrast, we believe that future users of quantum computers are interested in actual applications and that noisy quantum devices may still provide value by approximately solving hard combinatorial problems via hybrid classical-quantum algorithms. To lower bound the size of quantum computers with practical utility, we perform realistic simulations of the Quantum Approximate Optimization Algorithm and conclude that quantum speedup will not be attainable, at least for a representative combinatorial problem, until several hundreds of qubits are available.

Authors:
ORCiD logo [1];  [1]
  1. Intel Corp., Santa Clara, CA (United States)
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22). Scientific User Facilities Division
OSTI Identifier:
1527339
Grant/Contract Number:  
AC02-05CH11231
Resource Type:
Accepted Manuscript
Journal Name:
Scientific Reports
Additional Journal Information:
Journal Volume: 9; Journal Issue: 1; Journal ID: ISSN 2045-2322
Publisher:
Nature Publishing Group
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING

Citation Formats

Guerreschi, Gian Giacomo, and Matsuura, A. Y. QAOA for Max-Cut requires hundreds of qubits for quantum speed-up. United States: N. p., 2019. Web. doi:10.1038/s41598-019-43176-9.
Guerreschi, Gian Giacomo, & Matsuura, A. Y. QAOA for Max-Cut requires hundreds of qubits for quantum speed-up. United States. doi:10.1038/s41598-019-43176-9.
Guerreschi, Gian Giacomo, and Matsuura, A. Y. Mon . "QAOA for Max-Cut requires hundreds of qubits for quantum speed-up". United States. doi:10.1038/s41598-019-43176-9. https://www.osti.gov/servlets/purl/1527339.
@article{osti_1527339,
title = {QAOA for Max-Cut requires hundreds of qubits for quantum speed-up},
author = {Guerreschi, Gian Giacomo and Matsuura, A. Y.},
abstractNote = {Computational quantum technologies are entering a new phase in which noisy intermediate-scale quantum computers are available, but are still too small to benefit from active error correction. Even with a finite coherence budget to invest in quantum information processing, noisy devices with about 50 qubits are expected to experimentally demonstrate quantum supremacy in the next few years. Defined in terms of artificial tasks, current proposals for quantum supremacy, even if successful, will not help to facilitate solutions to practical problems. In contrast, we believe that future users of quantum computers are interested in actual applications and that noisy quantum devices may still provide value by approximately solving hard combinatorial problems via hybrid classical-quantum algorithms. To lower bound the size of quantum computers with practical utility, we perform realistic simulations of the Quantum Approximate Optimization Algorithm and conclude that quantum speedup will not be attainable, at least for a representative combinatorial problem, until several hundreds of qubits are available.},
doi = {10.1038/s41598-019-43176-9},
journal = {Scientific Reports},
number = 1,
volume = 9,
place = {United States},
year = {2019},
month = {5}
}

Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record

Citation Metrics:
Cited by: 5 works
Citation information provided by
Web of Science

Figures / Tables:

Figure 1 Figure 1: Schematic diagram of the QAOA algorithm and auxiliary tasks to solve a single Max-Cut instance. The two branches, labelled “simulation” and “experiment” respectively, distinguish between the operations to simulate the variational algorithm with classical computers and those to perform it experimentally with quantum devices. In our study, 10000more » samples are used to estimate the value of the cost function $\langle$γ, β|C|γ,β$\rangle$ at each variational iteration.« less

Save / Share:

Works referenced in this record:

Compiling quantum circuits to realistic hardware architectures using temporal planners
journal, February 2018

  • Venturelli, Davide; Do, Minh; Rieffel, Eleanor
  • Quantum Science and Technology, Vol. 3, Issue 2
  • DOI: 10.1088/2058-9565/aaa331

Max 2-SAT with up to 108 qubits
journal, April 2014


Characterizing quantum supremacy in near-term devices
journal, April 2018


Restless Tuneup of High-Fidelity Qubit Gates
journal, April 2017


0-1 Quadratic programming approach for optimum solutions of two scheduling problems
journal, February 1994

  • Alidaee, Bahram; Kochenberger, Gary A.; Ahmadian, Ahmad
  • International Journal of Systems Science, Vol. 25, Issue 2
  • DOI: 10.1080/00207729408928968

Evidence for quantum annealing with more than one hundred qubits
journal, February 2014

  • Boixo, Sergio; Rønnow, Troels F.; Isakov, Sergei V.
  • Nature Physics, Vol. 10, Issue 3
  • DOI: 10.1038/nphys2900

From the Quantum Approximate Optimization Algorithm to a Quantum Alternating Operator Ansatz
journal, February 2019

  • Hadfield, Stuart; Wang, Zhihui; O'Gorman, Bryan
  • Algorithms, Vol. 12, Issue 2
  • DOI: 10.3390/a12020034

Error Sensitivity to Environmental Noise in Quantum Circuits for Chemical State Preparation
journal, June 2016

  • Sawaya, Nicolas P. D.; Smelyanskiy, Mikhail; McClean, Jarrod R.
  • Journal of Chemical Theory and Computation, Vol. 12, Issue 7
  • DOI: 10.1021/acs.jctc.6b00220

Superconducting quantum circuits at the surface code threshold for fault tolerance
journal, April 2014


Two-step approach to scheduling quantum circuits
journal, July 2018


Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming
journal, November 1995

  • Goemans, Michel X.; Williamson, David P.
  • Journal of the ACM, Vol. 42, Issue 6
  • DOI: 10.1145/227683.227684

Combinatorial 5/6-approximation of Max Cut in graphs of maximum degree 3
journal, September 2008


MAX CUT in cubic graphs
journal, November 2004


Applications of cut polyhedra — I
journal, November 1994


Quantum Computing in the NISQ era and beyond
journal, August 2018


Quantum Mechanics Helps in Searching for a Needle in a Haystack
journal, July 1997


Noise gates for decoherent quantum circuits
journal, March 2008


Strategies for quantum computing molecular energies using the unitary coupled cluster ansatz
journal, October 2018

  • Romero, Jonathan; Babbush, Ryan; McClean, Jarrod R.
  • Quantum Science and Technology, Vol. 4, Issue 1
  • DOI: 10.1088/2058-9565/aad3e4

Hardware-efficient variational quantum eigensolver for small molecules and quantum magnets
journal, September 2017

  • Kandala, Abhinav; Mezzacapo, Antonio; Temme, Kristan
  • Nature, Vol. 549, Issue 7671
  • DOI: 10.1038/nature23879

Superconducting Circuits for Quantum Information: An Outlook
journal, March 2013


Quantum approximate optimization algorithm for MaxCut: A fermionic view
journal, February 2018


A blueprint for demonstrating quantum supremacy with superconducting qubits
journal, April 2018


Scalable Quantum Simulation of Molecular Energies
journal, July 2016

  • O’Malley, P. J. J.; Babbush, R.; Kivlichan, I. D.
  • Physical Review X, Vol. 6, Issue 3
  • DOI: 10.1103/PhysRevX.6.031007

    Figures / Tables found in this record:

      Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.