An efficient circuit compilation flow for quantum approximate optimization algorithm

Mahabubul Alam, Abdullah Ash Saki, Swaroop Ghosh

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Quantum approximate optimization algorithm (QAOA) is a promising quantum-classical hybrid algorithm to solve hard combinatorial optimization problems. The two-qubits gates used in quantum circuit for QAOA are commutative i.e., the order of gates can be altered without changing the logical output. This re-ordering leads to execution of more gates in parallel and a smaller number of additional gates to compile the QAOA circuit resulting in lower circuit depth and gate-count which is beneficial for circuit run-time and noise. A lower number of gates means a lower accumulation of gate errors, and a lower circuit depth means the quantum bits will have a lower time to decohere (lose state). However, finding the best re-ordered circuit is a difficult problem and does not scale well with circuit size. This paper presents a compilation flow with 3 approaches to find an optimal re-ordered circuit with reduced depth and gate count. Our approaches can reduce gate count up to 23.21% and circuit depth up to 53.65%. Our approaches are compiler agnostic, can be integrated with existing compilers, and scalable.

Original languageEnglish (US)
Title of host publication2020 57th ACM/IEEE Design Automation Conference, DAC 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781450367257
DOIs
StatePublished - Jul 2020
Event57th ACM/IEEE Design Automation Conference, DAC 2020 - Virtual, San Francisco, United States
Duration: Jul 20 2020Jul 24 2020

Publication series

NameProceedings - Design Automation Conference
Volume2020-July
ISSN (Print)0738-100X

Conference

Conference57th ACM/IEEE Design Automation Conference, DAC 2020
CountryUnited States
CityVirtual, San Francisco
Period7/20/207/24/20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Modeling and Simulation

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