Scalable Compilation of Quantum Circuits via Approximate Ensembles

ORAL

Abstract

As quantum processors scale in the number of qubits, the compilation workflow becomes paramount to the ability to run useful quantum algorithms. In our talk, we present a scalable workflow that is able to generate large ensembles of approximate compilations. Basing off prior work by Campbell and Hastings, we present theoretical results that demonstrate quadratic suppression of worst-case unitary error through ensemble sampling. By integrating these theoretical results with state-of-the-art compilation tools, we are able to create a scalable workflow leveraging numerical circuit synthesis for code generation. These approximate solutions are often shorter and less complex, which further limits the errors that arise on chip during an algorithm’s execution. We demonstrate our workflow on several benchmark algorithmic circuits acting on up to 380 qubits, and show that it can simultaneously achieve substantial reductions in resource-intensive gates and control output errors, offering a practical and scalable strategy for both near-term and fault-tolerant quantum computing.

*This work was supported by the U.S. Department of Energy, Office of Science, Office of Advanced Scientific Computing Research through the Accelerated Research in QuantumComputing Program MACH-Q Project. This research used resources of the National Energy Research Scientific Computing Center (NERSC), a Department of Energy Office of ScienceUser Facility using NERSC award DDR-ERCAPm4141. M.S.also acknowledges support from the Laboratory Directed Research and Development program (Project 233972) at Sandia National Laboratories. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc. for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Publication: https://arxiv.org/pdf/2510.18000

Presenters

  • Justin Isac Kalloor

    • University of California, Berkeley

Authors

  • Justin Isac Kalloor

    • University of California, Berkeley
  • Lucas Kovalsky

    • Sandia National Laboratories
  • Mohan Sarovar

    • Sandia National Laboratories
  • Mathias Weiden

    • University of California, Berkeley
    • UC Berkeley
  • John D Kubiatowicz

    • University of California, Berkeley
    • UC Berkeley
  • Ed Younis

    • Lawrence Berkeley National Laboratory
  • Costin C Iancu

    • Lawrence Berkeley National Laboratory