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Ilaria Gianani

Publications and source records attributed to Ilaria Gianani.

At least 19 recordsLinked to original sources

Quantum noise in ranging with optical pulses

Optical frequency combs combine ultrashort pulse duration and phase stability, making them powerful resources for high-precision ranging even when affected by atmospheric dispersion. It has been established that by classical modal engineering and mdoe-sensitive detection sensitivity to distance at the standard limit can be achieved, however attaining improved uncertainties by the use of squeezing has not been explored. Here, we apply an effective Hamiltonian framework to the problem of ranging with quantum frequency combs in order to derive the associated precision bounds for distance estimation. We analyse the role of intensity anti-squeezing and temporal beam shaping, and find that quantum solutions may be appealing mostly for short-distance applications.

quant-ph↗

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.

quant-ph↗

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.

quant-ph↗

Thresholded quantum LIDAR in turbolent media

Light detection and ranging is a key technology for a number of applications, from relatively simple distance ranging to environmental monitoring. When dealing with low photon numbers an important issue is the improvement of the signal- to-noise-ratio, which is severely affected by external sources whose emission is captured by the detection apparatus. In this paper, we present an extension of the technique developed in [Phys. Rev. Lett. 123, 203601] to the effects caused by the propagation of light through a turbulent media, as well as the detection through photon counting devices bearing imperfections in terms of efficiency and number resolution. Our results indicate that even less performing technology can result in a useful detection scheme.

quant-ph↗

Quasiprobability distributions with weak measurements

We discuss and experimentally demonstrate the role of quantum coherence in a sequence of two measurements collected at different times using weak measurements. For this purpose, we have realized a weak-sequential measurement protocol with photonic qubits, where the first measurement is carried out as a positive operator-valued measure, whereas the second one is a projective operation. We determine the quasiprobability distributions associated to this procedure using both the commensurate and the Margenau-Hill quasiprobabilities approaches. By tuning the weak measurements, we obtain a quasidistribution that may or may not exhibit negative parts, depending on the suitability of a contextual model for describing the experiment. Our results show how quasidistributions may find application in inspecting quantum monitoring, when part of the initial quantum coherence needs to be preserved.

quant-ph↗

Quantum multiphase estimation

Quantum phase estimation is fundamental to advancing quantum science and technology. While much of the research has concentrated on estimating a single phase, the simultaneous estimation of multiple phases can yield significantly enhanced sensitivities when using specially tailored input quantum states. This work reviews recent theoretical and experimental advancements in the parallel estimation of multiple arbitrary phases. We highlight strategies for constructing optimal measurement protocols and discuss the experimental platforms best suited for implementing these techniques.

quant-ph↗

Experimental protocol for qubit-environment entanglement detection

Decoherence is a manifestation of the coupling of a system with its environment. The resulting loss of information can hamper the functioning of quantum devices, hence the need of understanding its origin and dynamics. Decoherence can stem from entanglement, but it can also be classical in nature. Indeed, methods have been developed to understand whether qubit-environment entanglement (QEE) is actually present in some important classes of quantum channels - pure dephasing. Their practicality resides in the fact they only require accessing the system qubit. In this article we show an implementation of this technique in a photonic quantum channel simulator via a scheme that has been tailored to the system under study. By controlling the input state of the environment in our simulation, we can check the occurrence of qubit environment entanglement in simple, yet insightful test cases. Our results showcase the usefulness and experimental relevance of the QEE witnessing technique.

quant-ph↗

Near Infrared Quantum Ghost Spectroscopy for Threats Detection

Quantum Sensing is a rapidly growing branch of research within the area of quantum science and technology offering key resources, beyond classical ones, with potential for commercialisation of novel (quantum) sensors. The exploitation of quantum resources offered by photons can boost the performance of quantum sensors for innovative and challenging applications. In this paper we build on the idea of the Quantum Ghost Spectroscopy (QGS), i.e. the counterpart in the frequency domain of Quantum Ghost Imaging (QGI), targeting specific applications in the detection of possible threats. This is implemented by exploiting the opportunities offered by Quantum Optics, i.e. the generation of photon pairs characterized by spectral correlations. We will discuss our main results obtained with pure QGS experiments showing that it is possible to assess the presence of a target dealing with a low resources measurement. The time-frequency domain reveals a huge potential for several applications and frequency correlations represent a versatile tool that can be exploited to enable the spectral analysis of objects where a direct measurement would not be feasible (e.g. security). The use of nondegenerate sources of correlated photons allowed to reveal spectral features in the near infrared wavelengths employing the usual detectors for the visible region.

quant-ph↗

SPIDERweb: a Neural Network approach to spectral phase interferometry

Reliably characterised pulses are the starting point of any application of ultrafast techniques. Unfortunately, experimental constraints do not always allow optimising the characterisation conditions. This dictates the need for refined analysis methods. Here we show that neutral networks can provide a viable characterisation when applied to data from SPIDER. We have adopted a cascade of convolutional networks, addressing the multiparameter structure of the interferogram with a reasonable computing power. In particular, the necessity of precalibration is reduced, thus pointing towards the introduction of neural networks in more generic arrangements.

physics.optics↗

Fisher information susceptibility for multiparameter quantum estimation

Noise affects the performance of quantum technologies, hence the importance of elaborating operative figures of merit that can capture its impact in exact terms. In quantum metrology, the introduction of the Fisher information measurement noise susceptibility now allows to quantify the robustness of measurement for single-parameter estimation. Here we extend this notion to the multiparameter quantum estimation scenario. We provide its mathematical definition in the form of a semidefinite program. Although a closed formula could not be found, we further derive an upper and a lower bound to the susceptibility. We then apply these techniques to two paradigmatic examples of multiparameter estimation: the joint estimation of phase and phase-diffusion and the estimation of the different parameters describing the incoherent mixture of optical point sources. Our figure of merit provides clear indications on conditions allowing or hampering robustness of multiparameter measurements.

quant-ph↗

Quantum steering from phase measurements with limited resources

Quantum steering captures the ability of one party, Alice, to control through quantum correlations the state at a distant location, Bob, with superior ability than allowed by a local hidden state model. Verifying the presence of quantum steering has implications for the certification of quantum channels, and its connection to the metrological power of the quantum state has been recently proved. This link is established by means of the violation of a Cramér-Rao bound holding for non-steerable states: its direct assessment would then require operation in the asymptotic regime of a large number of repetitions. Here, we extend previous work to account explicitly for the use of a limited number of resources, and put this modified approach to test in a quantum optics experiment. The imperfections in the apparatus demand an adaptation of the original test in the multiparameter setting. Our results provide guidelines to apply such a metrological approach to the validation of quantum channels.

quant-ph↗

A Quantum Ghost Imaging Spectrometer

We present a device that exploits spatial and spectral correlations in parametric downconversion at once. By using a ghost imaging arrangement, we have been able to reconstruct remotely the frequency profile of a composite system. The presence of distinct spectral regions is corroborated by a model-independent statistical analysis that constitutes an intriguing possibility also in the low count regime.

quant-ph↗

Observing thermal lensing with quantum light

The introduction of quantum methods in spectroscopy can provide enhanced performance and technical advantages in the management of noise. We investigate the application of quantum illumination in a pump and probe experiment. Thermal lensing in a suspension of gold nanorods is explored using a classical beam as the pump and the emission from parametric downconversion as the probe. We obtain an insightful description of the behaviour of the suspension under pumping with a method known to provide good noise rejection. Our findings are a further step towards investigating effects of quantum light in complex plasmonic media.

quant-ph↗

Fundamental precision limits of fluorescence microscopy: a new perspective on MINFLUX

In the past years, optical fluorescence microscopy (OFM) made steady progress towards increasing the localisation precision of fluorescent emitters in biological samples. The high precision achieved by these techniques has prompted new claims, whose rigorous validation is an outstanding problem. For this purpose, local estimation theory (LET) has emerged as the most used mathematical tool. We establish a novel multi-parameter estimation framework that captures the full complexity of single-emitter localisation in an OFM experiment. Our framework relies on the fact that there are other unknown parameters alongside the emitter's coordinates, such as the average number of photons emitted (brightness), that are correlated to the emitter position, and affect the localisation precision. The increasing complexity of a multi-parameter approach allows for a more accountable assessment of the precision. We showcase our method with MINFLUX microscopy, the OFM approach that nowadays generates images with the best resolution. Introducing the brightness as an unknown parameter, we shed light on features that remain obscure in the conventional approach: the precision can be increased only by increasing the brightness, (i.e., illumination power or exposition time), whereas decreasing the beam separation offers limited advantages. We demonstrate that the proposed framework is a solid and general method for the quantification of single-emitter localisation precision for any OFM approach on equal footing, evaluating the localization precision of stimulated emission depletion (STED) microscopy and making a comparison with MINFLUX microscopy.

physics.optics↗

Improved Tomographic Estimates by Specialised Neural Networks

Characterization of quantum objects, being them states, processes, or measurements, complemented by previous knowledge about them is a valuable approach, especially as it leads to routine procedures for real-life components. To this end, Machine Learning algorithms have demonstrated to successfully operate in presence of noise, especially for estimating specific physical parameters. Here we show that a neural network (NN) can improve the tomographic estimate of parameters by including a convolutional stage. We applied our technique to quantum process tomography for the characterization of several quantum channels. We demonstrate that a stable and reliable operation is achievable by training the network only with simulated data. The obtained results show the viability of this approach as an effective tool based on a completely new paradigm for the employment of NNs operating on classical data produced by quantum systems.

quant-ph↗

Singular Spectrum Analysis of Two Photon Interference from Distinct Quantum Emitters

Two-photon interference underlies the functioning of many quantum photonics devices. It also serves as the prominent tool for testing the indistinguishability of distinct photons. However, as their time-spectral profile becomes more involved, extracting relevant parameters, foremost the central frequency difference, may start suffering difficulties. In a parametric approach, these arise from the need for an exhaustive model combined with limited count statistics. Here we discuss a solution to curtail these effects on the evaluation of frequency separation relying on a semiparametric method. The time trace of the quantum interference pattern of two photons from two independent solid-state emitters is preprocessed by means of singular spectral analysis before inspecting its spectral content. This approach allows to single out the relevant oscillations from both the envelope and the noise, without resorting to fitting. This opens the way for robust and efficient on-line monitoring of quantum emitters.

quant-ph↗

Experimental investigation of Bayesian bounds in multiparameter estimation

Quantum parameter estimation offers solid conceptual grounds for the design of sensors enjoying quantum advantage. This is realised not only by means of hardware supporting and exploiting quantum properties, but data analysis has its impact and relevance, too. In this respect, Bayesian methods have emerged as an effective and elegant solution, with the perk of incorporating naturally the availability of a priori information. In this article we present an evaluation of Bayesian methods for multiple phase estimation, assessed based on bounds that work beyond the usual limit of large samples assumed in parameter estimation. Importantly, such methods are applied to experimental data generated from the output statistics of a three-arm interferometer seeded by single photons. Our studies provide a blueprint for a more comprehensive data analysis in quantum metrology.

quant-ph↗

Fast remote spectral discrimination through ghost spectrometry

Assessing the presence of chemical, biological, radiological and nuclear threats is a crucial task which is usually dealt with by analyzing the presence of spectral features in a measured absorption profile. The use of quantum light allows to perform these measurements remotely without compromising the measurement accuracy through ghost spectrometry. However, in order to have sufficient signal-to-noise ratio, it is typically required to wait long acquisition times, hence subtracting to the benefits provided by remote sensing. In many instances, though, reconstructing the full spectral lineshape of an object is not needed and the interest lies in discriminating whether a spectrally absorbing object may be present or not. Here we show that this task can be performed fast and accurately through ghost spectrometry by comparing the low resources measurement with a reference. We discuss the experimental results obtained with different samples and complement them with simulations to explore the most common scenarios.

quant-ph↗