We address the metrological problem of estimating collective stochastic properties imprinted on a network of quantum sensors. Canonical examples include center-of-mass quadrature fluctuations in a system of bosonic modes and correlated dephasing in an ensemble of qubits (e.g., spins), bosons, or fermions. We develop a theoretical framework to determine the limits of correlated (weak) noise estimation with quantum sensor networks and reveal the requirements for entanglement advantage. Notably, an advantage emerges from the synergistic interplay between quantum correlations of the sensors and "classical" correlations of the noises. We determine optimal entangled probe states and identify a sensing protocol-reminiscent of a many-body echo-that achieves the fundamental limits of measurement sensitivity for a broad class of problems, unveiling a route toward entanglement-enhanced metrology of correlated many-body phenomena.
We address the metrological problem of estimating collective stochastic properties imprinted on a network of quantum sensors. Canonical examples include center-of-mass quadrature fluctuations in a system of bosonic modes and correlated dephasing in an ensemble of qubits (e.g., spins), bosons, or fermions. We develop a theoretical framework to determine the limits of correlated (weak) noise estimation with quantum sensor networks and reveal the requirements for entanglement advantage. Notably, an advantage emerges from the synergistic interplay between quantum correlations of the sensors and "classical" correlations of the noises. We determine optimal entangled probe states and identify a sensing protocol-reminiscent of a many-body echo-that achieves the fundamental limits of measurement sensitivity for a broad class of problems, unveiling a route toward entanglement-enhanced metrology of correlated many-body phenomena.
Correlated noise naturally arises in quantum systems due to, e.g., phase and amplitude fluctuations in global control or long-range correlations generated by a many-body sensing target near criticality. In this Letter, we propose a new form of exponential quantum advantage in the context of sensing correlated noise. Specifically, we focus on the problem of estimating parameters associated with Lindblad dephasing dynamics, and show that entanglement enhancement in the sensitivity (as quantified via quantum Fisher information of the sensor state) arises for estimating the strength of fluctuations in the noise fields' center-of-mass mode. In the presence of strong background fluctuations, such enhancement grows exponentially with the number of probes in the shot-limited regime, where the measurement and reset operations are slow. This result stands in stark contrast with previously studied scenarios of sensing uncorrelated dephasing noise, where one can prove that entanglement does not lead to an advantage in the signal-to-noise ratio. Our Letter thus opens a novel pathway toward achieving entanglement-based sensing advantage, which may find applications in characterizing decoherence dynamics of near-term quantum devices. Further, our approach provides a potential quantum-enhanced probe of many-body correlated phases by measuring noise generated by a sensing target. We also discuss realization of our protocol using near-term quantum hardware.
Dephasing noise is a ubiquitous source of decoherence in current atomic sensors. We address the problem of entanglement-assisted frequency estimation subject to classical dephasing noise with full spatial correlations (collective) and arbitrary temporal correlations. Our contributions are threefold. (i) We derive rigorous, state-independent bounds on the achievable estimation precision, showing how they are entirely determined by the short-time behavior of the decoherence function. For temporally uncorrelated (Markovian) dephasing, precision is limited by a probe-independent constant. For temporally correlated stationary noise, the bound approaches the noiseless limit for classical states, precluding any asymptotic quantum advantage. (ii) We show that these scaling bounds are tight, by constructing generalized Ramsey protocols that saturate them. These optimal protocols use squeezing at the input and before readout, both of which are available in state-of-the-art atomic interferometers. Implementing a perfect-echo protocol, which reaches Heisenberg scaling in the absence of noise, remains optimal in this noisy setting, irrespective of the noise temporal correlations. (iii) We prove that arbitrary collective open-loop control cannot lift the no-go for super-classical precision scaling under either Markovian or colored stationary noise, highlighting the detrimental nature of full spatial correlations. In the latter case, temporal correlations may nonetheless enable constant-factor improvements over the standard quantum limit, which may still be important in practical metrological scenarios.
Noise sensing underlies many physical applications including tests of non-classicality, thermometry, verification of correlated phases of quantum matter, and characterization of criticality. While previous works have shown that quantum resources such as entanglement and squeezing can enhance the sensitivity in estimating deterministic signals, less is known about the entanglement advantage in sensing correlated stochastic signals (noise). In this work, we compute the fundamental sensitivity limits of quantum sensors in probing spatiotemporally correlated noise. We first prove the fundamental quantum limits in sensing spatially correlated Markovian noise using entangled and unentangled sensors, respectively. Focusing on power-law spatial noise correlations, which naturally arise in condensed matter systems with long-range interactions and/or near criticality, we further derive a scalable entanglement advantage when the power-law decays slowly. Then, considering a target signal with a 1/fp-type spectrum, we demonstrate that non-Markovianity may entirely modify the nature of entanglement advantage in estimating spatial noise correlations. Our protocols can be implemented using state-of-the-art quantum sensing platforms including solid-state defects, superconducting circuits, and neutral atoms.
Interactions among sensors can provide, in addition to entanglement, an important resource for boosting the precision in quantum estimation protocols. Dephasing noise, however, remains a leading source of decoherence in state-of-the-art quantum sensing platforms. We analyze the impact of classical collective dephasing with arbitrary temporal correlations on the performance of generalized Ramsey interferometry protocols with quadratic encoding of a target frequency parameter. The optimal asymptotic precision bounds are derived for both product coherent spin states and a class of experimentally relevant entangled spin-squeezed states of N qubit sensors. While, as in linear metrology, entanglement offers no advantage if the noise is Markovian, a precision scaling of N−1 is reachable with classical input states in the quadratic setting, which is improved to N−5/4 when temporal correlations are present and the Zeno regime is accessible. The use of nonclassical spin-squeezed states and a nonlinear readout further allows for an N−3/2 precision scaling, which we prove is asymptotically optimal. We also show how to counter noise-induced bias by introducing a simple ratio estimator, which relies on detecting two suitable system observables, and we show that it remains asymptotically unbiased in the presence of dephasing, without detriment to the achievable precision.
This paper explores the potential of coordinated optimization within a network of quantum sensors for enhanced sensing capabilities in quantum information physics. The core challenge lies in leveraging the inherent sensitivity of individual quantum sensors while mitigating noise and maximizing overall system performance. We propose a framework utilizing advanced optimization algorithms to achieve this coordination. The framework considers the interconnectedness of sensors, accounting for correlated noise and exploiting synergistic effects. Mathematical models are presented to formalize the optimization problem, including expressions for sensor measurement uncertainties, noise correlation matrices, and the objective functions. We detail a multi-objective optimization approach, balancing precision, sensitivity, and robustness. The theoretical framework lays the groundwork for future experimental implementations, aiming to significantly improve the accuracy and reliability of quantum sensing applications. Key aspects covered include sensor network design, noise characterization, optimization algorithm selection, and performance evaluation metrics.
We investigate optimal metrological protocols for phase estimation in the presence of correlated dephasing noise, including spin-squeezed state sensing strategies as well as parallel and adaptive protocols optimized using tensor-network-based numerical methods. The results are benchmarked against fundamental bounds obtained either via the latest quantum comb extension method or an optimized classical simulation method. We find that the spin-squeezed states offer practically optimal performance in the regime where phase fluctuations are positively correlated but can be outperformed by tensor-network-optimized strategies for negatively correlated fluctuations.