Experimental Realization of Randomized Compiling for <i>in-situ</i> Error Reduction
ORAL
Abstract
We present work on reducing the average error during the operation of an algorithm through randomized compiling (RC) [1], which tailors arbitrary Markovian noise into stochastic Pauli errors. By compiling random single-qubit twirling gates into the bare sequence of an algorithm and averaging over many initializations of an RC circuit, the total error of an algorithm is reduced because the error per single qubit gate has been averaged into a stochastic noise channel that is independent of the gate itself. Here, we demonstrate experimental work towards implementing RC in both random circuits and quantum protocols for optimization problems. We show that RC suppresses coherent errors in a circuit and that it increases the probability of measuring the correct solution of an algorithm.
[1] J.J. Wallman and J. Emerson, Noise tailoring for scalable quantum computation via randomized compiling, Phys Rev A 94, 052325 (2016).
[1] J.J. Wallman and J. Emerson, Noise tailoring for scalable quantum computation via randomized compiling, Phys Rev A 94, 052325 (2016).
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Presenters
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Akel Hashim
University of California, Berkeley, Univ of California - Berkeley
Authors
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Akel Hashim
University of California, Berkeley, Univ of California - Berkeley
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Kasra Nowrouzi
Lawrence Berkeley National Laboratory
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Alexis Morvan
Lawrence Berkeley National Laboratory
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Ravi Kaushik Naik
University of California, Berkeley, Physics, University of California, Berkeley
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John Mark Kreikebaum
University of California, Berkeley
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Irfan Siddiqi
University of California, Berkeley, Univ of California - Berkeley, Univ of California – Berkeley, Physics, University of California, Berkeley