Low frequency signal detection via correlated Ramsey measurements

TL;DR

This paper demonstrates that correlated Ramsey measurements, with carefully timed sequences, are highly effective for detecting low frequency signals, outperforming traditional methods and enabling spectral reconstruction regardless of signal frequency.

Contribution

It introduces an optimized correlated Ramsey measurement protocol that rivals or surpasses existing techniques for low frequency signal detection using quantum probes.

Findings

Correlated Ramsey sequences outperform dynamical decoupling in low frequency detection.

The protocol enables simultaneous amplitude and phase tracking of signals.

Post-processing correlation improves spectral reconstruction efficiency.

Abstract

The low frequency region of the spectrum is a challenging regime for quantum probes. We support the idea that, in this regime, performing Ramsey measurements carefully controlling the time at which each measurement is initiated is an excellent signal detection strategy. We use the Fisher information to demonstrate a high quality performance in the low frequency regime, compared to more elaborated measurement sequences, and to optimise the correlated Ramsey sequence according to any given experimental parameters, showing that correlated Ramsey rivals with state-of-the-art protocols, and can even outperform commonly employed sequences such as dynamical decoupling in the detection of low frequency signals. Contrary to typical quantum detection protocols for oscillating signals, which require adjusting the time separation between pulses to match the half period of the target signal, and consequently see their scope limited to signals whose period is shorter than the characteristic decoherence time of the probe, or to those protocols whose target is primarily static signals, the time-tagged correlated Ramsey sequence simultaneously tracks the amplitude and the phase information of the target signal, regardless of its frequency, which crucially permits correlating measurements in post-processing, leading to efficient spectral reconstruction.