Quantum sensing is one of the key areas that exemplify the superiority of quantum technologies. Nonetheless, most quantum sensing protocols operate efficiently only when the unknown parameters vary within a very narrow region, i.e., local sensing. Here, we provide a systematic formulation for quantifying the precision of a probe for multiparameter global sensing when there is no prior information about the parameters. In many-body probes, in which extra tunable parameters exist, our protocol can tune the performance for harnessing the quantum criticality over arbitrarily large sensing intervals. For the single-parameter sensing, our protocol optimizes a control field such that an Ising probe is tuned to always operate around its criticality. This significantly enhances the performance of the probe even when the interval of interest is so large that the precision is bounded by the standard limit. For the multiparameter case, our protocol optimizes the control fields such that the probe operates at the most efficient point along its critical line. Finally, it is shown that even a simple magnetization measurement significantly benefits from our global sensing protocol.
Quantum sensing is one of the key areas that exemplify the superiority of quantum technologies. Nonetheless, most quantum sensing protocols operate efficiently only when the unknown parameters vary within a very narrow region, i.e., local sensing. Here, we provide a systematic formulation for quantifying the precision of a probe for multiparameter global sensing when there is no prior information about the parameters. In many-body probes, in which extra tunable parameters exist, our protocol can tune the performance for harnessing the quantum criticality over arbitrarily large sensing intervals. For the single-parameter sensing, our protocol optimizes a control field such that an Ising probe is tuned to always operate around its criticality. This significantly enhances the performance of the probe even when the interval of interest is so large that the precision is bounded by the standard limit. For the multiparameter case, our protocol optimizes the control fields such that the probe operates at the most efficient point along its critical line. Finally, it is shown that even a simple magnetization measurement significantly benefits from our global sensing protocol.
Conventional formulation of quantum sensing has been mostly developed in the context of local estimation, where the unknown parameter is roughly known. In contrast, global sensing, where the prior information is incomplete and the unknown parameter is only known to lie within a broad interval, is practically more engaging but has received far less theoretical attention. Available formulations of global sensing rely on adaptive Bayesian strategies requiring on-the-fly change in measurement settings, or minimizing average uncertainty yielding unsaturable bounds. Here, we provide an operationally motivated approach to global sensing for fixed but optimized settings. Our scheme yields a saturable precision bound optimizing the measurement as well as the probe preparation simultaneously. The formalism is general and computationally scalable for generic bosonic multimode Gaussian or many-particle free-fermionic quantum sensors. We illustrate the implications for Gaussian thermometry and Gaussian phase estimation by showing that the optimal measurement changes, either gradually or abruptly, from homodyne for local sensing, towards heterodyne for global sensing. In contrast, for fermionic transverse XY probes, the optimal measurement basis stays fixed independent of width.
Abstract Quantum sensors are now universally acknowledged as one of the most promising near-term quantum technologies. The traditional formulation of quantum sensing introduces a concrete bound on ultimate precision through the so-called local sensing framework, in which a significant knowledge of prior information about the unknown parameter value is implicitly assumed. Moreover, the framework provides a systematic approach for optimizing the sensing protocol. In contrast, the paradigm of global sensing aims to find a precision bound for parameter estimation in the absence of such prior information. In recent years, vigorous research has been pursued to describe the contours of global quantum estimation. Here, we review some of these emerging developments. These developments are both in the realm of finding ultimate precision bounds with respect to appropriate figures of merit in the global sensing paradigm, as well as in the search for algorithms that achieve these bounds. We categorize these developments into two largely mutually exclusive camps; one employing Bayesian updating and the other seeking to generalize the frequentist picture of local sensing towards the global paradigm. In the first approach, in order to achieve the best performance, one has to optimize the measurement settings adaptively. In the second approach, the measurement setting is fixed, however the challenge is to identify this fixed measurement optimally.
For single-parameter sensing, Greenberger-Horne-Zeilinger (GHZ) probes achieve optimal quantum-enhanced precision across the unknown parameter range, solely relying on parameter-independent separable measurement strategies for all values of the unknown parameter. However, in the multiparameter setting, a single GHZ probe not only fails to achieve quantum advantage but also the corresponding optimal measurement becomes complex and dependent on the unknown parameters. Here, we provide a recipe for multiparameter sensing with GHZ probes using quantum error correction techniques by treating all but one unknown parameters as noise, whose effects can be corrected. This strategy restores the core advantage of single parameter GHZ-based quantum sensing, namely reaching optimally quantum-enhanced precision for all unknown parameter values while keeping the measurements separable and fixed. Specifically, given one shielded ancilla qubit per GHZ probe, our protocol extracts optimal possible precision for any probe size. While this optimal precision is shot-noise limited for a single GHZ probe, we recover the Heisenberg scaling through use of multiple complementary GHZ probes. We demonstrate the effectiveness of the protocol with Bayesian estimation.
Quantum many-body systems undergoing phase transitions have been proposed as probes enabling beyond-classical enhancement of sensing precision. However, this enhancement is usually limited to a very narrow region around the critical point. Here, we systematically develop a modular approach for introducing multiple phase transitions in a many-body system. This naturally allows us to enlarge the region of quantum-enhanced precision by encompassing the newly created phase boundaries. Our approach is general and can be applied to both symmetry-breaking and topological quantum sensors. In symmetry-breaking sensors, we show that the newly created critical points inherit the original universality class and a simple total magnetization measurement already suffices to locate them. In topological sensors, our modular construction creates multiple bands which leads to a rich phase diagram. In both cases, Heisenberg scaling for Hamiltonian parameter estimation is achieved at all the phase boundaries. This can be exploited to create a global sensor which significantly outperforms a uniform probe.
Estimating multiple unknown parameters simultaneously is essential for practical quantum sensing. However, it faces a fundamental challenge: the optimal strategy for estimating one parameter is often incompatible with that for another, making it impossible to simultaneously achieve the ultimate precision limits for all parameters. Here we develop a general and efficient computational framework that jointly optimizes probe states, control operations, and measurements across different strategy families, including parallel, sequential, and those with indefinite causal order. Our approach provides exact semidefinite-program formulations for several precision bounds, including the Holevo, Nagaoka-Hayashi, and quantum Cramér-Rao bounds. We demonstrate the capabilities of the framework in multiparameter magnetometry and frequency estimation, identifying optimal protocols within each class and revealing a strict hierarchy among the achievable performances of different classes in the multiparameter regime. The framework also directly incorporates resource constraints, such as energy budgets, enabling systematic investigation of experimentally realistic sensing scenarios. Furthermore, we develop a finite-memory optimization method for sequential strategies with restricted ancillary-memory dimension. By decomposing the protocol into initial probe preparation and intermediate control operations, this method provides a practical route to designing resource-constrained sequential sensing schemes. Our work establishes a versatile computational tool for determining fundamental precision limits and designing optimal quantum-sensing protocols in complex multiparameter settings.
Fundamental scientific advances are often facilitated by breakthroughs in calibration and readout techniques that increase the measurement precision of sensors. The betterment of sensing technologies enables the validation of existing scientific theories and congruently, may also pave the way for identifying breakdowns in these frameworks, signalling the necessity for new theoretical developments. A significant facet of the growing interest in quantum metrology is that it represents a prime example in which quantum features such as entanglement, squeezing, and criticality, can be harnessed to enhance the precision of parameter estimation well beyond the capacity of their classical counterparts. We begin by exploring the paradigmatic problem of temperature estimation using impurity probes embedded in a host environment. The physical setup considered provides a natural mechanism for the probe-environment unit to equilibrate and thermalize. Furthermore the nature of probe-environment interactions allows us to investigate the role that entanglement plays in equilibrium temperature estimation problems. Our analysis reveal that spectral features of the environment are imprinted on the probe system due to established entanglement and uncover a low temperature regime with a universal thermometric response that is independent of the microscopic details of the environment. Physical incarnations of nanoelectronic devices are operated in the linear-response regime with transport properties representing the measurement of choice. Motivated by this, we next propose nanoelectronic devices operated in this way as a novel paradigm for quantum sensing. We derive general expressions for the quantum Fisher information --- allowing us to provide a precision benchmark for quantum transport coefficients in the linear-response regime. The latter half of this thesis is concerned with aspects of quantum critical metrology and multiparameter estimation. Our first contribution is to propose an alternative platform for critical quantum metrology, the two-impurity Kondo model --- which does not rely on the preparation of exotic critical states, but instead can be passively tuned to criticality. Employing local measurements of the in situ probe at finite temperature, we find enhanced precision at criticality in estimating inter-impurity coupling, but low precision when utilized as a thermometer. Considering uncertainty in both of these parameters, we find the quantum Fisher information matrix to be singular, despite these parameters being physically independent. We demonstrate that application of a known control field can lift the singularity. In practical settings, an external parameter is tuned to bring a system to its quantum critical point. Therefore, we expect that experimental uncertainties in this control parameter to play a significant role in fully exploiting criticality as a resource for sensing. Motivated by this, we next propose a general framework interpolating between the single and multi-parameter settings. Applied to the Ising and Lipkin-Meshkov-Glick models, we establish a fundamental trade-off between the amount of uncertainty a critical system can withstand while still maintaining a quantum advantage for sensing. In the final chapter of the thesis, we investigate the physical origin of quantum fisher information matrix singularities. A singularity signals a fundamental breakdown in our ability to estimate parameters and bound their precision. We attribute these situations to emergent metrological symmetries whereby the same set of measurement outcomes are obtained for different combinations of the system parameters. We demonstrate that by using Bayesian estimation, deep insights can be revealed and estimation of effective parameters is possible by employing a parameter transformation of the Bayesian posterior distribution.