Globally Optimizing QAOA Circuit Depth for Constrained Optimization Problems

Abstract

We develop a global variable substitution method that reduces n-variable monomials in combinatorial optimization problems to equivalent instances with monomials in fewer variables. We apply this technique to 3-SAT and analyze the optimal quantum unitary circuit depth needed to solve the reduced problem using the quantum approximate optimization algorithm. For benchmark 3-SAT problems, we find that the upper bound of the unitary circuit depth is smaller when the problem is formulated as a product and uses the substitution method to decompose gates than when the problem is written in the linear formulation, which requires no decomposition.

Document Details

Document Type
Pub Defense Publication
Publication Date
Oct 11, 2021
Source ID
10.3390/a14100294

Entities

People

  • George Siopsis
  • James Ostrowski
  • Lorna Treffert
  • Phillip C. Lotshaw
  • Rebekah Herrman
  • Travis Humble

Organizations

  • Air Force Office of Scientific Research
  • Army Research Office
  • Defense Advanced Research Projects Agency
  • National Science Foundation

Tags

Fields of Study

  • Mathematics

Readers

  • Graph Algorithms and Convex Optimization.
  • Operations Research

Technology Areas

  • Quantum Computing