npj Quantum Information (Apr 2021)

Quantum circuit cutting with maximum-likelihood tomography

  • Michael A. Perlin,
  • Zain H. Saleem,
  • Martin Suchara,
  • James C. Osborn

DOI
https://doi.org/10.1038/s41534-021-00390-6
Journal volume & issue
Vol. 7, no. 1
pp. 1 – 8

Abstract

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Abstract We introduce maximum-likelihood fragment tomography (MLFT) as an improved circuit cutting technique for running clustered quantum circuits on quantum devices with a limited number of qubits. In addition to minimizing the classical computing overhead of circuit cutting methods, MLFT finds the most likely probability distribution for the output of a quantum circuit, given the measurement data obtained from the circuit’s fragments. We demonstrate the benefits of MLFT for accurately estimating the output of a fragmented quantum circuit with numerical experiments on random unitary circuits. Finally, we show that circuit cutting can estimate the output of a clustered circuit with higher fidelity than full circuit execution, thereby motivating the use of circuit cutting as a standard tool for running clustered circuits on quantum hardware.