Quasiprobability decompositions with reduced sampling overhead
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Date
2022
Publication Type
Journal Article
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yes
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Abstract
Quantum error-mitigation techniques can reduce noise on current quantum hardware without the need for fault-tolerant quantum error correction. For instance, the quasiprobability method simulates a noise-free quantum computer using a noisy one, with the caveat of only producing the correct expected values of observables. The cost of this error mitigation technique manifests as a sampling overhead which scales exponentially in the number of corrected gates. In this work, we present an algorithm based on mathematical optimization that aims to choose the quasiprobability decomposition in a noise-aware manner. This directly leads to a significantly lower basis of the sampling overhead compared to existing approaches. A key element of the novel algorithm is a robust quasiprobability method that allows for a tradeoff between an approximation error and the sampling overhead via semidefinite programming.
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published
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8 (1)
Pages / Article No.
12
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Nature
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Subject
Computational science; Information theory and computation
Organisational unit
03781 - Renner, Renato / Renner, Renato
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