For general sequential quantum measurements, the paper derives asymptotic covariance matrices of empirical distributions of outcome substrings and a relative-entropy measure of the influence of correlations.
Effect of Correlated Errors on Quantum Memory
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abstract
Recent results on constant overhead LDPC code-based fault-tolerance against i.i.d. errors naturally lead to the question of fault-tolerance against errors with long-range correlations. Ideally, any correlation can be captured by a joint (system and bath) Hamiltonian. However, an arbitrary joint Hamiltonian is often intractable, and hence, the joint Hamiltonian model with pairwise terms was introduced and developed in a series of foundational works. However, the analysis of the new constant overhead codes in that error model appears to be quite challenging. In this paper, to model correlated errors in quantum memory, we introduce a correlation model which is a generalization of the well-known hidden random fields. This proposed model, which includes stationary and ergodic (non-Markov) error distributions, is shown to capture correlations not captured by the joint Hamiltonian model with pairwise terms. On the other hand, building on non-i.i.d. measure concentration, we show that for a broad class of non-Markov and (possibly) non-stationary error distributions, quantum Tanner codes ensure an exponential retention time (in the number of physical qubits), when the error rate is below a threshold. An implication of these results is that the rate of decay of the correlation with distance does not necessarily differentiate between good and bad correlation.
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2024 1verdicts
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The role of correlations in a sequence of quantum observations on empirical measures
For general sequential quantum measurements, the paper derives asymptotic covariance matrices of empirical distributions of outcome substrings and a relative-entropy measure of the influence of correlations.