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Quantum Metrology in Non-Markovian Environments

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abstract

We analyze precision bounds for a local phase estimation in the presence of general, non-Markovian phase noise. We demonstrate that the metrological equivalence of product and maximally entangled states that holds under strictly Markovian dephasing fails in the non-Markovian case. Using an exactly solvable model of a physically realistic finite bandwidth dephasing environment, we demonstrate that the ensuing non-Markovian dynamics enables quantum correlated states to outperform metrological strategies based on uncorrelated states using otherwise identical resources. We show that this conclusion is a direct result of the coherent dynamics of the global state of the system and environment and therefore the obtained scaling with the number of particles, which surpasses the standard quantum limit but does not achieve Heisenberg resolution, possesses general validity that goes beyond specific models. This is in marked contrast with the situation encountered under general Markovian noise, where an arbitrarily small amount of noise is enough to restore the scaling dictated by the standard quantum limit.

fields

quant-ph 1

years

2026 1

verdicts

UNVERDICTED 1

representative citing papers

Non-equilibrium quantum thermometry with bosonic samples

quant-ph · 2026-06-26 · unverdicted · novelty 7.0

Non-Markovian strong coupling in a bosonic probe produces non-monotonic quantum Fisher information with a finite optimal interrogation time for thermometry, while squeezed states give transient gains and strong coupling softens low-T error scaling from exponential to polynomial.

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Showing 1 of 1 citing paper.

  • Non-equilibrium quantum thermometry with bosonic samples quant-ph · 2026-06-26 · unverdicted · none · ref 36 · internal anchor

    Non-Markovian strong coupling in a bosonic probe produces non-monotonic quantum Fisher information with a finite optimal interrogation time for thermometry, while squeezed states give transient gains and strong coupling softens low-T error scaling from exponential to polynomial.