arXiv subjects

Alessandro Ferraro

Publications and source records attributed to Alessandro Ferraro.

At least 19 recordsLinked to original sources

arXiv2026

Quantum computational resources and validation protocols for a three-mode non-Gaussian trilinear Hamiltonian

Non-Gaussian interactions are a key ingredient for achieving universality in continuous-variable quantum computation, yet their experimental characterization and the validation of their correct implementation remain challenging tasks. In this work, we focus on a three-mode non-Gaussian trilinear Hamiltonian that has recently been realized in superconducting microwave platforms, and present a comprehensive theoretical analysis of the computational resources it generates, together with experimentally accessible protocols to validate their presence. We systematically investigate its ability to generate two key resources for quantum computation: multipartite entanglement and Wigner negativity. In particular, using displaced-parity Bell tests, we demonstrate the generation of nonlocal states and thereby provide an operational certification of multipartite entanglement in the non-Gaussian states produced by the dynamics. We further quantify the Wigner logarithmic negativity and benchmark it against that of established non-Gaussian resource states. Building on this resource-based characterization, we introduce a measurement-efficient protocol for the experimental validation of the Hamiltonian implementation without requiring full reconstruction of the Wigner function. The protocol combines the measurement of zero-variance observables (nullifiers and stabilizers) with a limited number of targeted phase-space measurements, leading to a drastic reduction of the experimental overhead.

quant-ph↗

arXiv2026

A general estimation framework for continuous-variable systems

We show that informational completeness, while sufficient to have a bijection between ideal measurement probabilities and quantum states, does not guarantee statistically stable reconstruction from finite measurement data. To address this problem, we develop a general estimation theory for continuous-variable systems in which stable reconstructibility is characterized by the POVM effects forming a measurement frame. Informational completeness is therefore necessary, but not sufficient, for stable reconstruction. Our framework is based on measurement frames in a $\sigma$-regularized operator geometry, where the reference state $\sigma$ encodes prior information about relevant features of the measured states. For any fixed measurement scheme, observables may be inaccessible, weakly reconstructible only through estimators with divergent variance, or stably reconstructible by finite-variance unbiased estimators. The relevant regime is determined by the range of the POVM synthesis operator. Our framework provides practical methods for constructing estimators and gives an operational interpretation of singular quasiprobability distributions, including the Glauber-Sudarshan $P$ representation: quasiprobabilities act as unbiased estimators for associated observables, and their singularities reflect a pathological feature of the corresponding measurement: its lack of loewr frame bound. We furthermore show how this formalism naturally provides operational regularization procedures tied to prior information. Overall, our framework provides a unified view of continuous-variable tomography, quasiprobability representations, and classical-shadow estimation.

quant-ph↗

arXiv2026

Bosonic quantum error-correcting codes with finite stellar rank

Bosonic quantum error correction (QEC) relies on non-Gaussian bosonic encodings whose preparation cost is a central practical constraint. In this work, we use stellar rank as a resource measure to design and benchmark bosonic codes under finite non-Gaussian resources. For fixed cat and Gottesman--Kitaev--Preskill (GKP) code families, we show that finite stellar rank creates a trade-off among state approximability, energy, and logical protection under photon loss and photon-number dephasing, evaluated with optimal recovery. This trade-off implies that codewords with better ideal error-correction properties need not be optimal once finite-rank preparation constraints are imposed. Going beyond fixed-target codewords, we directly optimize bosonic encodings at fixed stellar rank, revealing noise-adapted code structures and concrete resource thresholds. Grid-like encodings emerge under photon loss, whereas approximately rotation-symmetric encodings arise under dephasing. In the optimized search, stellar rank k=2 suffices to surpass break-even for all dephasing strengths considered, while under photon loss the required rank increases with the loss rate. These results establish stellar rank as an operationally meaningful resource measure for bosonic QEC under practical state-preparation constraints.

quant-ph↗

arXiv2026

Efficient classical training of model-free quantum photonic reservoir

Model-independent estimation of the properties of quantum states is a central challenge in quantum technologies, as experimental imperfections, drifts, and imprecise models of the actual quantum dynamics inevitably hinder accurate reconstructions. Here, we introduce a training strategy for photonic quantum extreme learning machines in which both the learning stage and the optimization of the measurement settings are performed entirely with classical light, while inference is carried out on genuinely quantum states. The protocol is based on the identity between the normalized output intensities following the evolution of coherent states through a linear optical reservoir, and the output statistics obtained with separable input quantum states. Building on this correspondence, we implemented a model-free, gradient-based optimization of the reservoir measurement projection directly on experimental data, without relying on a prior model of the device transformation. We experimentally show that the resulting classical-to-quantum transfer enables accurate reconstruction of single-qubit Pauli observables for previously unseen single-photon states, and extends to the estimation of a two-qubit entanglement witness for arbitrary bipartite states. Beyond demonstrating a qualitatively distinct form of out-of-distribution generalization across the classical-to-quantum boundary, our results identify a practical route to fast, adaptive, and resource-efficient training of photonic quantum learning devices.

quant-ph↗

arXiv2026

Experimental investigation of the effect of dispersion on squeezing generation in a synchronously pumped optical parametric oscillator

An experimental investigation of intracavity dispersion effects in a synchronously pumped optical parametric oscillator (SPOPO) is presented. A flexible setup combining spectral and phase shaping of both pump and local oscillator fields with frequency-resolved balanced homodyne detection is employed to examine how intracavity dispersion influences squeezing. Different cavity configurations with varying finesse and dispersion conditions are studied, and the squeezing is measured as a function of pump power and local oscillator bandwidth. Contrary to expectations based on existing theoretical models, the measured squeezing levels remain essentially unchanged as dispersion varies. To account for these observations, a modeling approach is introduced in which intracavity dispersion is described as an effective spectral filtering occurring at the stage of SPOPO supermode generation. Within this framework, the filtering is incorporated directly into the interaction Hamiltonian of the nonlinear process. This perspective establishes a consistent experimental benchmark for the study of dispersion in SPOPOs and underscores the importance of spectral filtering in the interpretation of multimode squeezing experiments.

physics.optics↗

arXiv2025

Generation and detection of squeezed states via a synchronously pumped optical parametric oscillator

A synchronously pumped optical parametric oscillator (SPOPO) operating at 93 MHz is used to generate squeezed states at 1035 nm. The system features a counter-propagating beam at the same wavelength as the quantum state, which simultaneously actively stabilizes the cavity and, after transmission, acts as the local oscillator for homodyne detection. By deriving the local oscillator directly from the SPOPO cavity, the setup establishes an intrinsically excellent spatial mode overlap and high interference visibility, forming a distinctive self-referenced architecture. Two spatial light modulators enable precise spectral shaping of both the pump and the local oscillator in amplitude and phase, allowing investigation of the spectral properties of the generated states. The versatility of the setup further allows exploration of different SPOPO configurations, including regimes with varied finesse and escape efficiency. Representative measurements, including homodyne traces and squeezing levels as functions of pump power and local oscillator bandwidth, demonstrate the performance of the system. Theoretical simulations based on a multimode singular-value-decomposition model reproduce well the measured dependence of squeezing on pump power and LO bandwidth, confirming the accuracy of the description and the robustness of the setup. Measured squeezing levels up to -3.3 dB are achieved, corresponding to -5.7 dB at SPOPO output, evidencing the robustness and versatility of this platform for stable pulsed squeezed-light generation and advanced quantum optical applications.

quant-ph↗

arXiv2025

The non-stabilizerness cost of quantum state estimation

We study the non-stabilizer resources required to achieve informational completeness in single-setting quantum state estimation scenarios. We consider fixed-basis projective measurements preceded by quantum circuits acting on $n$-qubit input states, allowing ancillary qubits to increase retrievable information. We prove that when only stabilizer resources are allowed, these strategies are always informationally equivalent to projective measurements in a stabilizer basis, and therefore never informationally complete, regardless of the number of ancillas. We then show that incorporating $T$ gates enlarges the accessible information. Specifically, we prove that at least ${2n}/{\log_2 3}$ such gates are necessary for informational completeness, and that $2n$ suffice. We conjecture that $2n$ gates are indeed both necessary and sufficient. Finally, we unveil a tight connection between entanglement structure and informational power of measurements implemented with $t$-doped Clifford circuits. Our results recast notions of ``magic'' and stabilizerness - typically framed in computational terms - into the setting of quantum metrology.

quant-ph↗

arXiv2025

A minimalist self-differencing gating scheme for dead-time-free single-photon avalanche diodes at high repetition rate

Gated quenched SPAD detectors are widely used in quantum communication and quantum computing setups employing high-repetition-rate lasers. Here, we present a novel scheme for high-repetition-rate (100 MHz) sine-wave gated SPADs, based on the self-differencing technique, which significantly simplifies previous designs while offering additional advantages. These include straightforward implementation, more precise control of the SPAD biasing, and an improved SNR. We implemented this approach using an InGaAs photodiode and characterized it experimentally with 100 MHz attenuated laser pulses, measuring quantum efficiency, dark count rate, and afterpulsing behavior. Importantly, we demonstrate that the detector recovers full quantum efficiency in less than one pulse-repetition period after a detection event, enabling continuous operation at 100 MHz, which, in principle, could reach the GHz regime.

quant-ph↗

arXiv2025

A machine learning based approach to the identification of spectral densities in quantum open systems

We present a machine learning-based approach for characterising the environment that affects the dynamics of an open quantum system. We focus on the case of an exactly solvable spin-boson model, where the system-environment interaction, whose strength is encoded in the spectral density, induces pure dephasing. By using artificial neural networks trained on the Fourier-transformed time evolution of some observables of the system, we perform both classification -- distinguishing sub-Ohmic, Ohmic, and super-Ohmic spectral densities -- and regression -- thus estimating key parameters of the spectral density function, when the latter is expressed through a power law. Our results demonstrate high classification accuracy and robust parameter estimation, highlighting the potential of machine learning as a powerful tool for probing environmental features in quantum systems and advancing quantum noise spectroscopy.

quant-ph↗

arXiv2025

Towards fault-tolerant quantum computation with universal continuous-variable gates

Continuous-variable (CV) systems have shown remarkable potential for quantum computation, particularly excelling in scalability and error correction through bosonic encoding. Within this framework, the foundational notion of computational universality was introduced in [Phys. Rev. Lett. 82, 1784 (1999)], and has proven especially successful since it allows for the identification of finite sets of universal CV gates independent of the encoding scheme. However, achieving the critical objective of fault-tolerant computation requires some form of encoding, and to date there has been no proof that these universal CV gates can lead to encoded fault tolerance. We present compelling evidence in this direction by utilizing the Gottesman-Kitaev-Preskill (GKP) encoding. Specifically, we numerically optimize the generation of GKP states from vacua using circuits comprised solely of universal CV gates. We demonstrate that these states can be attained with sufficient quality to exhibit error probabilities lower than the threshold needed to achieve a fault-tolerant memory via concatenated GKP-stabilizer codes.

quant-ph↗

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.

quant-ph↗

arXiv2025

Quantum reservoir computing for photonic entanglement witnessing

Accurately estimating properties of quantum states, such as entanglement, while essential for the development of quantum technologies, remains a challenging task. Standard approaches to property estimation rely on detailed modeling of the measurement apparatus and a priori assumptions on their working principles. Even small deviations can greatly affect reconstruction accuracy and prediction reliability. Here, we demonstrate that quantum reservoir computing embodies a powerful alternative for witnessing quantum entanglement and, more generally, estimating quantum features from experimental data. We leverage the orbital angular momentum of photon pairs as an ancillary degree of freedom to enable informationally complete single-setting measurements of their polarization. Our approach does not require fine-tuning or refined knowledge of the setup, at the same time outperforming conventional approaches. It automatically adapts to noise and imperfections while avoiding overfitting, ensuring robust reconstruction of entanglement witnesses and paving the way to the assessment of quantum features of experimental multiparty states.

quant-ph↗

arXiv2025

Machine Learning-Enhanced Characterisation of Structured Spectral Densities: Leveraging the Reaction Coordinate Mapping

Spectral densities encode essential information about system-environment interactions in open-quantum systems, playing a pivotal role in shaping the system's dynamics. In this work, we leverage machine learning techniques to reconstruct key environmental features, going beyond the weak-coupling regime by simulating the system's dynamics using the reaction coordinate mapping. For a dissipative spin-boson model with a structured spectral density expressed as a sum of Lorentzian peaks, we demonstrate that the time evolution of a system observable can be used by a neural network to classify the spectral density as comprising one, two, or three Lorentzian peaks and accurately predict their central frequency.

quant-ph↗

arXiv2024

Classical simulation of circuits with realistic odd-dimensional Gottesman-Kitaev-Preskill states

Classically simulating circuits with bosonic codes is challenging due to the prohibitive cost of simulating quantum systems with many, possibly infinite, energy levels. We propose an algorithm to simulate circuits with encoded Gottesman-Kitaev-Preskill (GKP) states, specifically for odd-dimensional encoded qudits. Our approach is tailored to be especially effective in the most challenging but practically relevant regime, where the codeword states exhibit high (but finite) squeezing. Our algorithm leverages the Zak-Gross Wigner function introduced by J. Davis et al. [arXiv:2407.18394], which represents infinitely squeezed encoded stabilizer states positively. The runtime of the algorithm scales with the negativity of the Wigner function, allowing for efficient simulation of certain large-scale circuits - namely, input stabilizer GKP states undergoing generalized GKP-encoded Clifford operations followed by modular measurements - with a high degree of squeezing. For stabilizer GKP states exhibiting 12 dB of squeezing, our algorithm can simulate circuits with up to 1,000 modes with less than double the number of samples required for a single input mode, in stark contrast to existing simulators. Therefore, this approach holds significant potential for benchmarking early implementations of quantum computing architectures utilizing bosonic codes.

quant-ph↗

arXiv2024

Assessing non-Gaussian quantum state conversion with the stellar rank

State conversion is a fundamental task in quantum information processing. Quantum resource theories allow for analyzing and bounding conversions that use restricted sets of operations. In the context of continuous-variable systems, state conversions restricted to Gaussian operations are crucial for both fundamental and practical reasons, particularly in state preparation and quantum computing with bosonic codes. However, previous analysis did not consider the relevant case of approximate state conversion. In this work, we introduce a framework for assessing approximate Gaussian state conversion by extending the stellar rank to the approximate stellar rank, which serves as an operational measure of non-Gaussianity. We derive bounds for Gaussian state conversion and distillation under approximate and probabilistic conditions, yielding new no-go results for non-Gaussian state preparation and enabling a reliable assessment of the performance of Gaussian conversion protocols. We also provide an open-source Python library to compute stellar-rank-related quantities and to assess Gaussian conversion.

quant-ph↗

arXiv2024

Qubit magic-breaking channels

We develop a notion of quantum channels that can make states useless for universal quantum computation by destroying their magic (non-stabilizerness) - we refer to them as magic-breaking channels. We establish the properties of these channels in arbitrary dimensions. We prove the necessary and sufficient criteria for qubit channels to be magic-breaking and present an algorithm for determining the same. Moreover, we provide compact criteria in terms of the parameters for several classes of qubit channels to be magic-breaking under various post-processing operations. Further, we investigate the necessary and sufficient conditions for the tensor product of multiple qubit channels to be magic-breaking. We establish implications of the same for the dynamical resource theory of magic preservability.

quant-ph↗

arXiv2023

Classification of quantum states of light using random measurements through a multimode fiber

Extracting meaningful information about unknown quantum states without performing a full tomography is an important task. Low-dimensional projections and random measurements can provide such insight but typically require careful crafting. In this paper, we present an optical scheme based on sending unknown input states through a multimode fiber and performing two-point intensity and coincidence measurements. A short multimode fiber implements effectively a random projection in the spatial domain, while a long-dispersive multimode fiber performs a spatial and spectral projection. We experimentally show that useful properties -- i.e., the purity, dimensionality, and degree of indistinguishability -- of various states of light including spectrally entangled biphoton states, can be obtained by measuring statistical properties of photocurrents and their correlation between two outputs over many realizations of unknown random projections. Moreover, we show that this information can then be used for state classification.

quant-ph↗

arXiv2023

Sufficient condition for universal quantum computation using bosonic circuits

Continuous-variable bosonic systems stand as prominent candidates for implementing quantum computational tasks. While various necessary criteria have been established to assess their resourcefulness, sufficient conditions have remained elusive. We address this gap by focusing on promoting circuits that are otherwise simulatable to computational universality. The class of simulatable, albeit non-Gaussian, circuits that we consider is composed of Gottesman-Kitaev-Preskill (GKP) states, Gaussian operations, and homodyne measurements. Based on these circuits, we first introduce a general framework for mapping a continuous-variable state into a qubit state. Subsequently, we cast existing maps into this framework, including the modular and stabilizer subsystem decompositions. By combining these findings with established results for discrete-variable systems, we formulate a sufficient condition for achieving universal quantum computation. Leveraging this, we evaluate the computational resourcefulness of a variety of states, including Gaussian states, finite-squeezing GKP states, and cat states. Furthermore, our framework reveals that both the stabilizer subsystem decomposition and the modular subsystem decomposition (of position-symmetric states) can be constructed in terms of simulatable operations. This establishes a robust resource-theoretical foundation for employing these techniques to evaluate the logical content of a generic continuous-variable state, which can be of independent interest.

quant-ph↗