Scalable mitigation of measurement errors on quantum computers

2021/08/27 by Paul D. Nation, Hwajung Kang, Neereja Sundaresan +1 · 6 citations
Physics and Astronomy · #quant-ph

paper · pdf · doi:10.1103/prxquantum.2.040326

published as PRX Quantum 2, 040326 (2021) · 9 pages, 8 figures, 1 table

arxiv created 2021/08/27 · arxiv updated 2021/11/11

Abstract

We present a method for mitigating measurement errors on quantum computing platforms that does not form the full assignment matrix, or its inverse, and works in a subspace defined by the noisy input bit-strings. This method accommodates both uncorrelated and correlated errors, and allows for computing accurate error bounds. Additionally, we detail a matrix-free preconditioned iterative solution method that converges in O(1) steps that is performant and uses orders of magnitude less memory than direct factorization. We demonstrate the validity of our method, and mitigate errors in a few seconds on numbers of qubits that would otherwise be intractable.

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