Scalable and Efficient Characterization of Noise for Fault-tolerant Quantum Computing

Abstract

In this proposal, we will develop methods for characterizing quantum devices of 10-100 qubits by utilizing our proven track record of creating robust and scalable protocols for characterizing relevant noise for fault-tolerant quantum computation (FTQC). It is currently unknown exactly what aspects of noise must be minimized to enable FTQC. We will determine these critical metrics and determine how to measure and certify them. Current proposals that model noise as incoherent will be examined in the context of FTQC, and we will develop tools to measure and quantify any residual coherent noise. We will seek to determine models of the noise that can be learned in a scalable and efficient manner, but where such models retain the information about the noise that is necessary to determine the ability to perform FTQC. We will show how such models can be used to improve, at a software level, the demonstrations and implementations (being pursued elsewhere) of FTQC on quantum devices. The PIs believe that we can build on our current implementation of scalable protocols and expertise in certification metrics to rise to this challenge.

Document Details

Document Type
DoD Grant Award
Publication Date
Oct 22, 2020
Source ID
W911NF2110001

Entities

People

  • Steven T. Flammia

Organizations

  • Army Contracting Command
  • National Security Agency
  • University of Sydney

Tags

Readers

  • Distributed Systems and Data Platform Development
  • Quantum spin resonance or Electron Paramagnetic Resonance spectroscopy.

Technology Areas

  • Quantum Computing