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Investigates the impact of finite memory on decoherence rates in non-Markovian systems, suggesting revised models for accurate measurements.
We investigate the validity of exponential models in the analysis of Ramsey coherence measurements and show that finite environmental memory is consistent with a systematic bias in the extracted decoherence rate. Starting from a system–bath Hamiltonian, we derive a finite-memory decoherence function using a second-order cumulant expansion under the assumption of Gaussian noise with finite correlation time. The resulting dynamics exhibit a time-dependent effective decay rate, reducing to exponential behavior only in the long-time limit. We derive an explicit closed-form expression for the decoherence rate extracted by least-squares exponential fitting over a finite time window [0, T], as an explicit function of both T and the environmental correlation time τ_c. We show that the extracted rate γ_fit(T) strictly underestimates the intrinsic decoherence rate γ for all finite T > 0, with the deficit decaying as T⁻¹ in the long-window limit, while in the short-window limit the fitted rate scales linearly with T , a regime not directly accessible experimentally due to limited signal contrast at early times. The central implication is that decoherence rates extracted from exponential fits are not intrinsic observables in non-Markovian environments: they encode a protocol-dependent effective average that depends systematically on the chosen fitting window. The conventionally reported coherence time T₂* = 1/γ_fit is therefore protocol-dependent in non-Markovian environments. Finally, we connect this behavior to experimentally observed non-exponential decay profiles and noise spectra, providing a unified framework for interpreting deviations from exponential coherence decay. These results identify a structural limitation in standard Ramsey analysis and motivate the use of physically grounded models in extracting decoherence parameters.
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Mazen Zaino (2026) studied this question.
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