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Title: Reduced phase noise in an erbium frequency comb via intensity noise suppression
Award ID(s):
1654425
NSF-PAR ID:
10054026
Author(s) / Creator(s):
; ; ;
Date Published:
Journal Name:
Optics Express
Volume:
25
Issue:
15
ISSN:
1094-4087
Page Range / eLocation ID:
18175
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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  2. Abstract

    We study the distribution over measurement outcomes of noisy random quantum circuits in the regime of low fidelity, which corresponds to the setting where the computation experiences at least one gate-level error with probability close to one. We model noise by adding a pair of weak, unital, single-qubit noise channels after each two-qubit gate, and we show that for typical random circuit instances, correlations between the noisy output distribution$$p_{\text {noisy}}$$pnoisyand the corresponding noiseless output distribution$$p_{\text {ideal}}$$pidealshrink exponentially with the expected number of gate-level errors. Specifically, the linear cross-entropy benchmarkFthat measures this correlation behaves as$$F=\text {exp}(-2s\epsilon \pm O(s\epsilon ^2))$$F=exp(-2sϵ±O(sϵ2)), where$$\epsilon $$ϵis the probability of error per circuit location andsis the number of two-qubit gates. Furthermore, if the noise is incoherent—for example, depolarizing or dephasing noise—the total variation distance between the noisy output distribution$$p_{\text {noisy}}$$pnoisyand the uniform distribution$$p_{\text {unif}}$$punifdecays at precisely the same rate. Consequently, the noisy output distribution can be approximated as$$p_{\text {noisy}}\approx Fp_{\text {ideal}}+ (1-F)p_{\text {unif}}$$pnoisyFpideal+(1-F)punif. In other words, although at least one local error occurs with probability$$1-F$$1-F, the errors are scrambled by the random quantum circuit and can be treated as global white noise, contributing completely uniform output. Importantly, we upper bound the average total variation error in this approximation by$$O(F\epsilon \sqrt{s})$$O(Fϵs). Thus, the “white-noise approximation” is meaningful when$$\epsilon \sqrt{s} \ll 1$$ϵs1, a quadratically weaker condition than the$$\epsilon s\ll 1$$ϵs1requirement to maintain high fidelity. The bound applies if the circuit size satisfies$$s \ge \Omega (n\log (n))$$sΩ(nlog(n)), which corresponds to onlylogarithmic depthcircuits, and if, additionally, the inverse error rate satisfies$$\epsilon ^{-1} \ge {\tilde{\Omega }}(n)$$ϵ-1Ω~(n), which is needed to ensure errors are scrambled faster thanFdecays. The white-noise approximation is useful for salvaging the signal from a noisy quantum computation; for example, it was an underlying assumption in complexity-theoretic arguments that noisy random quantum circuits cannot be efficiently sampled classically, even when the fidelity is low. Our method is based on a map from second-moment quantities in random quantum circuits to expectation values of certain stochastic processes for which we compute upper and lower bounds.

     
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