Nature Communications (Mar 2024)

Optimizing quantum gates towards the scale of logical qubits

  • Paul V. Klimov,
  • Andreas Bengtsson,
  • Chris Quintana,
  • Alexandre Bourassa,
  • Sabrina Hong,
  • Andrew Dunsworth,
  • Kevin J. Satzinger,
  • William P. Livingston,
  • Volodymyr Sivak,
  • Murphy Yuezhen Niu,
  • Trond I. Andersen,
  • Yaxing Zhang,
  • Desmond Chik,
  • Zijun Chen,
  • Charles Neill,
  • Catherine Erickson,
  • Alejandro Grajales Dau,
  • Anthony Megrant,
  • Pedram Roushan,
  • Alexander N. Korotkov,
  • Julian Kelly,
  • Vadim Smelyanskiy,
  • Yu Chen,
  • Hartmut Neven

DOI
https://doi.org/10.1038/s41467-024-46623-y
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 8

Abstract

Read online

Abstract A foundational assumption of quantum error correction theory is that quantum gates can be scaled to large processors without exceeding the error-threshold for fault tolerance. Two major challenges that could become fundamental roadblocks are manufacturing high-performance quantum hardware and engineering a control system that can reach its performance limits. The control challenge of scaling quantum gates from small to large processors without degrading performance often maps to non-convex, high-constraint, and time-dynamic control optimization over an exponentially expanding configuration space. Here we report on a control optimization strategy that can scalably overcome the complexity of such problems. We demonstrate it by choreographing the frequency trajectories of 68 frequency-tunable superconducting qubits to execute single- and two-qubit gates while mitigating computational errors. When combined with a comprehensive model of physical errors across our processor, the strategy suppresses physical error rates by ~3.7× compared with the case of no optimization. Furthermore, it is projected to achieve a similar performance advantage on a distance-23 surface code logical qubit with 1057 physical qubits. Our control optimization strategy solves a generic scaling challenge in a way that can be adapted to a variety of quantum operations, algorithms, and computing architectures.