Quantum thermometry aims at determining temperature with ultimate precision in the quantum regime. Standard equilibrium approaches, limited by the quantum Fisher information given by static energy fluctuations, lose sensitivity outside a fixed temperature window. Nonequilibrium strategies have therefore been recently proposed to overcome these limits, but their advantages are typically model dependent or tailored for a specific purpose. This Letter establishes a general, model-independent result showing that any temperature-dependent unitary driving applied to a thermalized probe enhances its quantum Fisher information with respect to its equilibrium value. Such information gain is expressed analytically through a positive semidefinite kernel of information currents that quantify the flow of statistical distinguishability. Our results, together with an analysis of the relation between information gain and control cost, are benchmarked on a driven spin-1=2 thermometer, furthermore showing that resonant modulations remarkably restore the quadratic-in-time scaling of the Fisher information and allow the sensitivity peak to be shifted across arbitrary temperature ranges.
Shake before Use: Universal Enhancement of Quantum Thermometry by Unitary Driving
Tumbiolo E.
;Maccone L.;Macchiavello C.;Guarnieri G.
2026-01-01
Abstract
Quantum thermometry aims at determining temperature with ultimate precision in the quantum regime. Standard equilibrium approaches, limited by the quantum Fisher information given by static energy fluctuations, lose sensitivity outside a fixed temperature window. Nonequilibrium strategies have therefore been recently proposed to overcome these limits, but their advantages are typically model dependent or tailored for a specific purpose. This Letter establishes a general, model-independent result showing that any temperature-dependent unitary driving applied to a thermalized probe enhances its quantum Fisher information with respect to its equilibrium value. Such information gain is expressed analytically through a positive semidefinite kernel of information currents that quantify the flow of statistical distinguishability. Our results, together with an analysis of the relation between information gain and control cost, are benchmarked on a driven spin-1=2 thermometer, furthermore showing that resonant modulations remarkably restore the quadratic-in-time scaling of the Fisher information and allow the sensitivity peak to be shifted across arbitrary temperature ranges.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


