The DOI matches its Crossref record; 36 of the 36 references it cites were found in a registry or an index.
Scalable Mitigation of Measurement Errors on Quantum Computers
Open accessAbstract
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 the computation of 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 impractical.
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Cites
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“…radius of one, that is diagonal in the computational basis Near-term algorithms such as the ubiquitous Variational Quantum Eigensolver (VQE) [20, 30] and quantum machine learning [22, 27] rely on the computation of expectation values, making the correction of measurement errors in these…”
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Cited by
Quantum many-body simulations on digital quantum computers: State-of-the-art and future challenges
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Metadata
- Authors
- Nation, P. D., Kang, H., Sundaresan, N., & Gambetta, J. M.
- Venue
- PRX Quantum
- Publisher
- American Physical Society (APS)
- Published
- 2021-11-08
- Volume
- 2
- Issue
- 4
- ISSN
- 2691-3399 (ISSN-L)
- OpenAlex
- W3197075881
- Cited by
- 269
- References
- 36
- FWCI
- 13.76
- Type
- journal article
- Language
- en
- Open access
- gold
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