arXiv subjects

Francesco Martini

Publications and source records attributed to Francesco Martini.

16 recordsLinked to original sources

arXiv2026

Graph automorphisms to obtain Clifford symmetries in open and closed qudit models

In the recent article [arXiv:2605.18966], we demonstrated that finding Clifford symmetries can be mapped to a Graph Automorphism (GA) problem. Here, we provide an algorithm to obtain such symmetries on general qudit systems, that works on the principle of encoding Clifford invariants of a Hamiltonian onto properties of a graph. Labelling Hamiltonian terms as vertices, a permutation of such vertices that respects the Clifford invariants (a GA) is both a valid Clifford, and a symmetry up to phase correction checks. We test this on multiple physical models and discuss the scaling with respect to the number of qudits and Pauli strings, as well as various strategies for optimisation in different regimes. We further show that the graph automorphism representation of Clifford symmetries can be expanded to open quantum systems.

quant-ph↗

arXiv2026

Attention-based optimizer for symmetry finding

Finding symmetries is crucial for understanding physical models. In this work, we present an optimization framework that searches Pauli symmetries of Hamiltonians, merging the fields of machine learning with automated symmetry finding. Built on a Set-Transformer architecture, our framework uses self-attention to encode the pairwise and higher-order correlations among the Pauli-Strings. The relations are then decoded as a candidate, which is further optimized with a custom commutation-based objective, and mapped to a symmetry of the input Hamiltonian. We apply our method to random Pauli Hamiltonians, periodic one and two dimensional transverse-field Ising model and the Toric code. We show that for physical Hamiltonians (Ising and Toric), our framework succeeds with near-deterministic probability while providing substantial advantage compared to state-of-the-art strategies. For random Pauli Hamiltonians, we estimate the required computational resources, specifically the number of parallel starts and the number of GPUs, to find a symmetry with high success probability under fixed design specifications.

quant-ph↗

arXiv2026

Clifford symmetries in quantum many-body systems

Obtaining the symmetries of a model is a critical step towards developing an understanding and ultimately analytically or numerically solving the model. However, finding symmetries is generally extremely complicated, often being the result of insightful thinking. In this work, we complement human ingenuity with an algorithm. We leverage the classically efficient Clifford group to find symmetries for arbitrary many-body Hamiltonians via a graph representation. We demonstrate our method on random and physical Hamiltonians, with instances of up to one thousand qubits and demonstrate how our approach can provide deeper understanding of the model.

quant-ph↗

arXiv2026

An Error-aware and Adaptive Method for the Estimation of Quantum Observables on Qudit-Based Quantum Computers

The accurate estimation of observables is a crucial task in quantum computing. Recent advances have highlighted the need for (a) specialized protocols for qudit-based devices, that include (b) error-aware strategies. Here, we present AQUIRE, the first protocol that can (a) accurately estimate both the mean and the error of an observable on qudit-based quantum computers. AQUIRE achieves this by constructing a Bayesian model to accommodate generalized Pauli operators. It is designed to continuously monitor the estimated average and the associated error of the observable, adjusting the subsequent measurements in real-time. Additionally, AQUIRE is (b) device- and experiment-specific error-aware, and accounts for hardware imperfections and experimental noise during the estimation process. We demonstrate AQUIRE's advantage via numerical simulations and showcase its ability to quantify the noise affecting the estimation by implementing it on a trapped-ion qudit quantum processor. By exploiting general commutation relations and overlap grouping measurements, our protocol is state-of-the-art when restricted to qubit-based quantum computers and extends this advantage to the qudit case.

quant-ph↗

arXiv2025

Securities Transaction Settlement Optimization on superconducting quantum devices

We describe a quantum variational algorithm for securities transactions settlement optimization, based on a novel mathematical formalization of the problem that includes the most relevant constraints considered in the pan-European securities settlement platform TARGET2-Securities. The proposed algorithm is designed for Noisy Intermediate-Scale Quantum devices, specifically targeting IBM's superconducting qubit machines. We adopt non-linear activation functions to encode inequality constraints in the objective function of the problem, and design customized noise mitigation techniques to alleviate the effect of readout errors. We consider batches of up to 40 trades obtained from real transactional data to benchmark our algorithm on quantum hardware against classical and quantum-inspired solvers.

quant-ph↗

arXiv2024

Linearly Multiplexed Photon Number Resolving Single-photon Detectors Array

Photon Number Resolving Detectors (PNRDs) are devices capable of measuring the number of photons present in an incident optical beam, enabling light sources to be measured and characterized at the quantum level. In this paper, we explore the performance and design considerations of a linearly multiplexed photon number-resolving single-photon detector array, integrated on a single mode waveguide. Our investigation focus on defining and analyzing the fidelity of such an array under various conditions and proposing practical designs for its implementation. Through theoretical analysis and numerical simulations, we show how propagation losses and dark counts may have a strong impact on the performance of the system and highlight the importance of mitigating these effects in practical implementations.

quant-ph↗

arXiv2023

Higher-order topological kernels via quantum computation

Topological data analysis (TDA) has emerged as a powerful tool for extracting meaningful insights from complex data. TDA enhances the analysis of objects by embedding them into a simplicial complex and extracting useful global properties such as the Betti numbers, i.e. the number of multidimensional holes, which can be used to define kernel methods that are easily integrated with existing machine-learning algorithms. These kernel methods have found broad applications, as they rely on powerful mathematical frameworks which provide theoretical guarantees on their performance. However, the computation of higher-dimensional Betti numbers can be prohibitively expensive on classical hardware, while quantum algorithms can approximate them in polynomial time in the instance size. In this work, we propose a quantum approach to defining topological kernels, which is based on constructing Betti curves, i.e. topological fingerprint of filtrations with increasing order. We exhibit a working prototype of our approach implemented on a noiseless simulator and show its robustness by means of some empirical results suggesting that topological approaches may offer an advantage in quantum machine learning.

quant-ph↗

arXiv2023

Are We All in a Truman Show? Spotting Instagram Crowdturfing through Self-Training

Influencer Marketing generated $16 billion in 2022. Usually, the more popular influencers are paid more for their collaborations. Thus, many services were created to boost profiles' popularity metrics through bots or fake accounts. However, real people recently started participating in such boosting activities using their real accounts for monetary rewards, generating ungenuine content that is extremely difficult to detect. To date, no works have attempted to detect this new phenomenon, known as crowdturfing (CT), on Instagram. In this work, we propose the first Instagram CT engagement detector. Our algorithm leverages profiles' characteristics through semi-supervised learning to spot accounts involved in CT activities. Compared to the supervised approaches used so far to identify fake accounts, semi-supervised models can exploit huge quantities of unlabeled data to increase performance. We purchased and studied 1293 CT profiles from 11 providers to build our self-training classifier, which reached 95\% F1-score. We tested our model in the wild by detecting and analyzing CT engagement from 20 mega-influencers (i.e., with more than one million followers), and discovered that more than 20% was artificial. We analyzed the CT profiles and comments, showing that it is difficult to detect these activities based solely on their generated content.

cs.SI↗

arXiv2023

Optimal Amplitude Multiplexing of a Series of Superconducting Nanowire Single Photon Detectors

Integrated arrays of Superconducting Nanowire Single Photon Detectors (SNSPDs) have shown capabilities such as Photon Number Resolution, single photon imaging and coincidences detection, and can be effectively used also in other different applications related to quantum optics. The growing complexity of such applications requires the use of multiplexing schemes for the simultaneous readout of different detectors. A simple multiplexing scheme can be realized by arranging a series of SNSPDs elements, shunted by appropriate resistances. The goal of this work is to investigate and optimize this scheme, developing a general method able to identify the optimal sets of shunting resistences for any different application. The methodology obtained is very general, and can be extended to other detection systems.

quant-ph↗

arXiv2022

Automatic and effective discovery of quantum kernels

Quantum computing can empower machine learning models by enabling kernel machines to leverage quantum kernels for representing similarity measures between data. Quantum kernels are able to capture relationships in the data that are not efficiently computable on classical devices. However, there is no straightforward method to engineer the optimal quantum kernel for each specific use case. We present an approach to this problem, which employs optimization techniques, similar to those used in neural architecture search and AutoML, to automatically find an optimal kernel in a heuristic manner. To this purpose we define an algorithm for constructing a quantum circuit implementing the similarity measure as a combinatorial object, which is evaluated based on a cost function and then iteratively modified using a meta-heuristic optimization technique. The cost function can encode many criteria ensuring favorable statistical properties of the candidate solution, such as the rank of the Dynamical Lie Algebra. Importantly, our approach is independent of the optimization technique employed. The results obtained by testing our approach on a high-energy physics problem demonstrate that, in the best-case scenario, we can either match or improve testing accuracy with respect to the manual design approach, showing the potential of our technique to deliver superior results with reduced effort.

quant-ph↗

arXiv2018

High-Q/V two-dimensional photonic crystals cavities in 3C-SiC

Solid state quantum emitters are between the most promising candidates for single photon generation in quantum technologies. However, they suffer from decoherence effects which limit their efficiency and indistinguishability. For instance, the radiation emitted in the zero phonon line (ZPL) of most color centers is on the order of a few percent (e.g. $NV^-$ centers in Diamond, $V_{Si}V_{C}$ in SiC) limiting the emission rate of single photons as well as the efficiency. At the same time, reliable interfacing with photons in an integrated manner still remains a challenge on both diamond and SiC technology. Here we develop photonic crystal cavities with Q factors in the order of 7,100 in 3C SiC. We discuss how this high confinement cavity can significantly enhance the fraction of photons emitted in the ZPL and improve their characteristics. In particular, the increased efficiency and improved indistinguishability can open the way to quantum technologies in the solid state.

quant-ph↗

arXiv2018

Amplitude-Multiplexed readout of single photon detectors based on superconducting nanowires

The realization of large-scale photonic circuit for quantum optics experiments at telecom wavelengths requires an increasing number of integrated detectors. Superconductive nanowire single photon detectors (SNSPDs) can be easily integrated on chip and they can efficiently detect the light propagating inside waveguides. The thermal budget of cryostats poses a limit on the maximum number of elements that can be integrated on the same chip due to the thermal impact of the readout electronics. In this paper, we propose and implement a novel scheme able for an efficient reading of several SNSPDs with only one readout port, enabling the realization of photonic circuits with a large number of modes.

quant-ph↗

arXiv2018

Second harmonic generation from strongly coupled localized and propagating phonon-polariton modes

We experimentally investigate second harmonic generation from strongly coupled localized and propagative phonon polariton modes in arrays of silicon carbide nanopillars. Our results clearly demonstrate the hybrid nature of the system's eigenmodes and distinct manifestation of strong coupling in the linear and nonlinear response. While in linear reflectivity the intensity of the two strongly-coupled branches is essentially symmetric and well explained by their respective localized or propagative components, the second harmonic signal presents a strong asymmetry. Analyzing it in detail, we reveal the importance of interference effects between the nonlinear polarization terms originating in the bulk and in the phonon polariton modes, respectively.

cond-mat.mes-hall↗

arXiv2018

Complementary metal-oxide semiconductor compatible source of single photons at near-visible wavelengths

We demonstrate on chip generation of correlated pairs of photons in the near-visible spectrum using a CMOS compatible PECVD Silicon Nitride photonic device. Photons are generated via spontaneous four wave mixing enhanced by a ring resonator with high quality Q-factor of 320,000 resulting in a generation rate of 950,000 $\frac{pairs}{mW}$. The high brightness of this source offers the opportunity to expand photonic quantum technologies over a broad wavelength range and provides a path to develop fully integrated quantum chips working at room temperature.

quant-ph↗

arXiv2017

Four wave mixing in 3C SiC Ring Resonators

We demonstrate frequency conversion by four wave mixing at telecommunication wavelengths using an integrated platform in 3C SiC. The process was enhanced by high-Q and small modal volume ring resonators, allowing the use of mW-level CW powers to pump the nonlinear optical process. We retrieved the nonlinear refractive index $n_{2}=(5.31\pm 0.04)\times 10^{-19} m^{2}/W$ of 3C SiC and observed a signal attributed to Raman gain in the structure.

physics.optics↗

arXiv2015

Coherent coupling between localised and propagating phonon polaritons

Following the recent observation of localised phonon polaritons in user-defined silicon carbide nano-resonators, here we demonstrate coherent coupling between those localised modes and propagating phonon polaritons bound to the surface of the nano-resonator's substrate. In order to obtain phase-matching, the nano-resonators have been fabricated to serve the double function of hosting the localised modes, while also acting as grating for the propagating ones. The coherent coupling between long lived, optically accessible localised modes, and low-loss propagative ones, opens the way to the design and realisation of phonon-polariton based quantum circuits.

cond-mat.mes-hall↗