arXiv subjects

Matteo G. A. Paris

Publications and source records attributed to Matteo G. A. Paris.

At least 37 records · Page 2Linked to original sources

arXiv2026

Multi-Parameter Multi-Critical Metrology of the Dicke Model

Critical quantum metrology exploits the hypersensitivity of quantum systems near phase transitions to achieve enhanced precision in parameter estimation. While single-parameter estimation near critical points is well established, the simultaneous estimation of multiple parameters, which is essential for practical sensing applications, remains challenging. This difficulty arises from sloppiness, a phenomenon that typically renders the quantum Fisher information matrix (QFIM) singular or nearly singular. In this work, we demonstrate that multiparameter critical metrology is not only feasible but can also retain divergent precision scaling, provided one accepts a trade-off in the scaling exponent. Using the ground state of the single-cavity Dicke model (DM), we show that two Hamiltonian parameters can be simultaneously estimated with a scalar variance bound scaling as the square root of the critical parameter. This overcomes the inherent sloppiness by leveraging higher-order contributions to the QFIM. To recover the optimal quadratic scaling, we introduce the Dicke dimer (DD) with photon hopping. In this extended model, a triple point in the phase diagram enables the simultaneous closure of two excitation gaps, which effectively increases the rank of the QFIM and restores the ideal single-parameter scaling for specific parameter pairs. Furthermore, we extend our analysis to dissipative settings subject to photon loss. Finally, we establish a connection between the derived critical scalings and the fundamental state preparation time, providing a unified framework to operationally compare different sensing strategies. Our results demonstrate that critical quantum metrology can be made robust against dissipation and scalable to multiparameter scenarios, paving the way for practical quantum sensors operating near phase transitions.

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arXiv2026

Optimizing quantum sensing networks via genetic algorithms and deep learning

We investigate the optimization of graph topologies for quantum sensing networks designed to estimate weak magnetic fields. The sensors are modeled as spin systems governed by a transverse-field Ising Hamiltonian in thermal equilibrium at low temperatures. Using a genetic algorithm (GA), we evolve network topologies to maximize a perturbative spectral sensitivity measure, which serves as the fitness function for the GA. For the best-performing graphs, we compute the corresponding quantum Fisher information (QFI) to assess the ultimate bounds on estimation precision. To enable efficient scaling, we use the GA-generated data to train a deep neural network, allowing extrapolation to larger graph sizes where direct computation becomes prohibitive. Our results show that while both the fitness function and QFI initially increase with system size, the QFI exhibits a clear non-monotonic behavior - saturating and eventually declining beyond a critical graph size. This reflects the loss of superlinear scaling of the QFI, as the narrowing of the energy gap signals a crossover to classical scaling of the QFI with system size. The effect is reminiscent of the microeconomic law of diminishing returns: beyond an optimal graph size, further increases yield reduced sensing performance. This saturation and decline in precision are particularly pronounced under Kac scaling, where both the QFI and spin squeezing plateau or degrade with increasing system size. We also attribute observed even-odd oscillations in the spectral sensitivity measure and QFI to quantum interference effects in spin phase space, as confirmed by our phase-space analysis. These findings highlight the critical role of optimizing interaction topology - rather than simply increasing network size - and demonstrate the potential of hybrid evolutionary and learning-based approaches for designing high-performance quantum sensors.

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arXiv2026

Phase-space complexity of discrete-variable quantum states and operations

We introduce a quantifier of phase-space complexity for discrete-variable (DV) quantum systems. Motivated by a recent framework developed for continuous-variable systems, we construct a complexity measure of quantum states based on the Husimi Q-function defined over spin coherent states. The quantifier combines into a single scalar quantity two complementary information-theoretic quantities, the Wehrl entropy, which captures phase-space spread, and the Fisher information, which captures localization. We derive fundamental properties of this measure, including its invariance under SU(2) displacements. The complexity is normalized such that coherent states have unit complexity, while the completely mixed state has zero complexity, a feature distinct from the continuous-variable case. We provide analytic expressions for several relevant families of states, including Gibbs and Dicke states, and perform a numerical analysis of spin-squeezed states, NOON states, and randomly generated states. Numerical results reveal a monotonic, but not deterministic, relationship between complexity and purity, leading us to conjecture that maximal complexity is attained by pure states, thereby connecting the problem to the optimization of Wehrl entropy via Majorana constellations. Finally, we extend the framework to quantum channels, defining measures for both the generation and breaking of complexity. We analyze the performance of common unitary gates and the amplitude damping channel, showing that while low-dimensional systems can achieve maximal complexity via spin squeezing or NOON states, this becomes impossible in higher dimensions. These results highlight dimension-dependent limitations in the generation of phase-space complexity and establish a unified phase-space approach to complexity across both continuous and discrete variable regimes.

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arXiv2026

Quantum Estimation Theory Limits in Neutrino Oscillation Experiments

Measurements of the Pontecorvo-Maki-Nakagawa-Sakata (PMNS) neutrino mixing parameters have entered a precision era, enabling increasingly stringent tests of neutrino oscillations. Within the framework of quantum estimation theory, we investigate whether flavor measurements, the only observables currently accessible experimentally, are optimal for extracting the oscillation parameters. We compute the Quantum Fisher Information (QFI) and the classical Fisher Information (FI) associated with ideal flavor projections for all oscillation parameters, considering accelerator muon (anti)neutrino and reactor electron antineutrino beams propagating in vacuum. Two main results emerge. First, flavor measurements saturate the QFI at the first oscillation maximum for $θ_{13}$, $θ_{23}$, and $θ_{12}$, demonstrating their information-theoretic optimality for these parameters. In contrast, they are far from optimal for $δ_{CP}$. In particular, only a small fraction of the available information on $δ_{CP}$ is extracted at the first maximum; the sensitivity improves at the second maximum, in line with the strategy of ESS$ν$SB, a planned facility. Second, the QFI associated with $δ_{CP}$ is approximately one order of magnitude smaller than that of the mixing angles, indicating that the neutrino state intrinsically encodes less information about CP violation. Nevertheless, this quantum bound lies well below current experimental uncertainties, implying that the present precision on $δ_{CP}$ is not fundamentally limited. Our results provide a quantitative framework to disentangle fundamental from practical limitations and establish a benchmark for optimizing future neutrino facilities.

hep-ph↗

arXiv2026

Routing Qubits on Noisy Networks

Robust quantum routing is essential for scalable quantum technologies. This paper investigates the resilience of routing protocols in network architectures designed for perfect, high-fidelity transfer of both classical and quantum information under ideal conditions. We encode information in the position of a quantum walker on a graph, modelling the routing of a generic qubit state from a single input to multiple (orthogonal) outputs. We analyse and assess routing performance in various regimes, evaluating their robustness against static and dynamical noise.

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arXiv2026

Configuration-dependent precision in magnetometry and thermometry using multi-qubit quantum sensors

We study the performance of quantum sensors composed of four qubits arranged in different geometries for magnetometry and thermometry. The qubits interact via the transverse-field Ising model with both ferromagnetic and antiferromagnetic couplings, maintained in thermal equilibrium with a heat bath under an external magnetic field. Using quantum Fisher information, we evaluate the metrological precision of these sensors. For ferromagnetic couplings, weakly connected graphs (e.g., the chain graph, P_4) perform optimally in estimating weak magnetic fields, whereas highly connected graphs (e.g., the complete graph, K_4) excel at strong fields. Conversely, K_4 achieves the highest sensitivity for temperature estimation in the weak-field regime. In the antiferromagnetic case, we uncover a fundamental trade-off dictated by spectral degeneracy: configurations with non-degenerate energy spectra - such as the pan-like graph (three qubits in a triangle with the fourth attached) - exhibit strong magnetic field sensitivity due to their pronounced response to perturbations. In contrast, symmetric structures like the square graph, featuring degenerate energy levels (particularly ground-state degeneracy), are better suited for precise thermometry. Notably, our four-qubit sensors achieve peak precision in the low-temperature, weak-field regime. Finally, we introduce a spectral sensitivity measure that quantifies energy spectrum deformations under small perturbations, providing a simple heuristic indicator of metrological sensitivity.

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arXiv2025

Quadratic and cubic scrambling in the estimation of two successive phase-shifts

Multiparameter quantum estimation becomes challenging when the parameters are incompatible, i.e., when their respective symmetric logarithmic derivatives do not commute, or when the model is sloppy, meaning that the quantum probe depends only on combinations of parameters leading to a degenerate or ill-conditioned Fisher information matrix. In this work, we explore the use of scrambling operations between parameter encoding to overcome sloppiness. We consider a bosonic model with two phase-shift parameters and analyze the performance of second- and third-order nonlinear scrambling using two classes of probe states: squeezed vacuum states and coherent states. Our results demonstrate that nonlinear scrambling mitigates sloppiness, increases compatibility, and improves overall estimation precision. We find third-order nonlinearity to be more effective than second-order under both fixed-probe and fixed-energy constraints. Furthermore, by comparing joint estimation to a stepwise estimation strategy, we show that a threshold for nonlinear coupling exists. For coherent probes, joint estimation outperforms the stepwise strategy if the nonlinearity is sufficiently large, while for squeezed probes, this advantage is observed specifically with third-order nonlinearity.

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arXiv2025

Bayesian stepwise estimation of qubit rotations

This work investigates Bayesian stepwise estimation (Se) for measuring the two parameters of a unitary qubit rotation. While asymptotic analysis predicts a precision advantage for SE over joint estimation (JE) in regimes where the quantum Fisher information matrix is near-singular ("sloppy" models), we demonstrate that this advantage is mitigated within a practical Bayesian framework with limited resources. We experimentally implement a SE protocol using polarisation qubits, achieving uncertainties close to the classical Van Trees bounds. However, comparing the total error to the ultimate quantum Van Trees bound for JE reveals that averaging over prior distributions erases the asymptotic SE advantage. Nevertheless, the stepwise strategy retains a significant practical benefit as it operates effectively with simple, fixed measurements, whereas saturating the JE bound typically requires complex, parameter-dependent operations.

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arXiv2025

Optimal quantum transport on a ring via locally monitored chiral quantum walks

In purely coherent transport on finite networks, destructive interference can significantly suppress transfer probabilities, which can only reach high values through careful fine-tuning of the evolution time or tailored initial-state preparations. We address this issue by investigating excitation transfer on a ring, modeling it as a locally monitored continuous-time chiral quantum walk. Chirality, introduced through time-reversal symmetry breaking, imparts a directional bias to the coherent dynamics and can lift dark states. Local monitoring, implemented via stroboscopic projective measurements at the target site, provides a practical detection protocol without requiring fine-tuning of the evolution time. By analyzing the interplay between chirality and measurement frequency, we identify optimal conditions for maximizing the asymptotic detection probability. The optimization of this transfer protocol relies on the spectral properties of the Perron-Frobenius operator, which capture the asymptotic non-unitary dynamics, and on the analysis of dark states. Our approach offers a general framework for enhancing quantum transport in monitored systems.

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arXiv2025

Is the large uncertainty of $δ_{CP}$ fundamentally encoded in the neutrino quantum state?

The precise measurement of the leptonic CP-violating phase $δ_{CP}$ remains one of the major open challenges in neutrino physics, as current experiments achieve only very limited accuracy. We address this issue through the lens of quantum estimation theory. A distinctive feature of neutrino oscillation experiments is that they cannot freely optimize the probe or measurement, since both are constrained by the production and detection of flavor eigenstates. We therefore examine whether the large uncertainty in $δ_{CP}$ originates from intrinsic reasons, either of the neutrino quantum state or of flavor measurements, or if it instead stems from experimental limitations. By comparing quantum and classical Fisher information, we demonstrate that the limited sensitivity to $δ_{CP}$ originates primarily from the information content of flavor measurements. Furthermore, we show that targeting the second oscillation maximum, as in the ESS$ν$SB proposal, substantially enhances $δ_{CP}$ information compared to experiments centered on the first maximum.

hep-ph↗

arXiv2025

Orders matter: tight bounds on the precision of sequential quantum estimation for multiparameter models

In multiparameter quantum metrology, the ultimate precision of joint estimation is dictated by the Holevo Cramér-Rao bound. In this paper, we discuss and analyze in detail an alternative approach: the stepwise estimation strategy. In this approach, parameters are estimated sequentially, using an optimized fraction of the total available resources allocated to each step. We derive a tight and achievable precision bound for this protocol, the stepwise separable bound, and provide its closed-form analytical expression, revealing a crucial dependence on the chosen measurement ordering. We provide a rigorous comparison with the joint measurement strategy, deriving analytical conditions that determine when the stepwise approach offers superior precision. Through the analysis of several paradigmatic SU(2) unitary encoding models, we demonstrate that the stepwise strategy can indeed outperform joint measurements, particularly in scenarios characterized by non-optimal probes or models with a high degree of sloppiness. Our findings establish stepwise estimation as a powerful alternative to joint and collective measurements, proving that sequential protocols can provide a genuine metrological advantage, especially in resource-constrained or imperfect experimental settings.

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arXiv2025

Quantum walks as a tool to design robust quantum batteries: the role of topology and chirality

The maximum work that can be extracted from a quantum battery is bounded by the ergotropy of the system, which is determined by the spectral properties of the Hamiltonian. In this paper, we employ the formalism of quantum walks to investigate how the topology of the battery and the chirality of the Hamiltonian influence its performance as an energy storage unit. We analyze architectures of battery cells based on ring, complete, and wheel graph structures and analyze their behavior in the presence of noise. Our results show that these structures exhibit distinct ergotropy scaling, with the interplay between chirality and topology providing a tunable mechanism to optimize work extraction and enhance robustness against decoherence. In particular, chirality enhances ergotropy for complete quantum cells, without altering the linear scaling with size, whereas in ring cells, it bridges the performance gap between configurations with odd and even number of units. Additionaly, chirality may be exploited to force degeneracies in the Hamiltonian, a condition that can spare the ergotropy to vanish in the presence of pure dephasing. We conclude that topology and chirality are key resources for improving ergotropy, offering guidelines to optimize quantum energy devices and protocols.

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arXiv2025

Statistical phase-space complexity of continuous-variable quantum channels

The statistical complexity of continuous-variable quantum states can be characterized with a quantifier defined in terms of information-theoretic quantities derived from the Husimi Q-function. In this work, we utilize this complexity quantifier of quantum states to study the complexity of single-mode bosonic quantum channels. We define the complexity of quantum channels as the maximal amount of complexity they can generate from an initial state with the minimal complexity. We illustrate this concept by evaluating the complexity of Gaussian channels and some examples of non-Gaussian channels.

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arXiv2025

Controlling Sloppiness in Two-Phase Estimation with a Tunable Weak Measurement

The description of complex systems requires a progressively larger number of parameters. However, in practice, it often happens that a small subset of parameters suffices to describe the dynamics of the system itself: these combinations are usually referred to as \textit{stiff} combinations. In turn, the remaining combinations, called \textit{sloppy}, only play a minor role in the dynamics of the system, hence provide little information on it. While this effect can reduce model complexity, it can also limit the estimation precision when the stiff and sloppy combinations are unknown to the experimenter, and one is forced to estimate the potentially sloppy model parameters. We explored how such a sloppy behavior can be controlled and counteracted via quantum weak measurements in the estimation of two sequential phases. We showed that the introduction of a weak measurement of variable strength in-between the two phases allows to switch from a fully sloppy setup to a fully determined one where both phases can be estimated with quantum-limited precision. Our work provides an important insight of sloppiness detection in quantum systems, with promising applications in quantum metrology and imaging, as well as to quantum security and quantum monitoring.

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arXiv2025

Enhanced quantum frequency estimation by nonlinear scrambling

Frequency estimation, a cornerstone of basic and applied sciences, has been significantly enhanced by quantum sensing strategies. Despite breakthroughs in quantum-enhanced frequency estimation, key challenges remain: static probes limit flexibility, and the interplay between resource efficiency, sensing precision, and potential enhancements from nonlinear probes remains not fully understood. In this work, we show that dynamically encoding an unknown frequency in a nonlinear quantum electromagnetic field can significantly improve frequency estimation. To provide a fair comparison of resources, we define the energy cost as the figure of merit for our sensing strategy. We further show that specific higher-order nonlinear processes lead to nonlinear-enhanced frequency estimation. This enhancement results from quantum scrambling, where local quantum information spreads across a larger portion of the Hilbert space. We quantify this effect using the Wigner-Yanase skew information, which measures the degree of noncommutativity in the Hamiltonian structure. Our work sheds light on the connection between Wigner-Yanase skew information and quantum sensing, providing a direct method to optimize nonlinear quantum probes.

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arXiv2025

Measuring spatial coherence of quantum and classical light with an ultrastable monolithic interferometer

We describe a monolithic interferometer for spatial coherence measurements of both classical and quantum light sources. The design combines parametric down-conversion with a thermal source, using two identical calcite crystals to control beam alignment via birefringence. The monolithic structure ensures inherent stability. Spatial coherence is measured through temporal interferograms and spectral analysis, with both methods showing close agreement with theoretical predictions. The system is robust and performs reliably for both quantum and classical light. Its design enables automated, rapid coherence measurements across different source types.

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arXiv2025

Enhanced quantum sensing of gravitational acceleration constant

We investigate the use of quantum probes to accurately determine the strength of the local gravitational field on Earth. Our findings show that delocalized probes generally outperform localized ones, with the precision enhancement scaling quadratically with the separation between the two wavefunction components. This advantage persists under realistic position measurements, which can achieve precision not too far from the ultimate bound. We also discuss the influence of Earth's surface, demonstrating that its effect can be neglected until shortly before the particle hits the floor. Finally, we address the joint estimation of the gravitational acceleration $g$ and the probe mass $m$, proving that the excess estimation noise arising from their inherent incompatibility is negligible.

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arXiv2025

Saturable global quantum sensing

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.

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