arXiv subjects

J. Settino

Publications and source records attributed to J. Settino.

10 recordsLinked to original sources

arXiv2025

Topology-Enhanced Superconducting Qubit Networks for In-Sensor Quantum Information Processing

We investigate the influence of topology on the magnetic response of inductively coupled superconducting flux-qubit networks. Using exact diagonalization methods and linear response theory, we compare the magnetic response of linear and cross-shaped array geometries, used as paradigmatic examples. We find that the peculiar coupling matrix in cross-shaped arrays yields a significant enhancement of the magnetic flux response compared to linear arrays, this network-topology effect arising from cooperative coupling among the central and the peripheral qubits. These results establish quantitative design criteria for function-oriented superconducting quantum circuits, with direct implications for advancing performance in both quantum sensing and quantum information processing applications. Concerning the latter, by exploiting the non-linear and high-dimensional dynamics of such arrays, we demonstrate their suitability for quantum reservoir computing technology. This dual functionality suggests a novel platform in which the same device serves both as a quantum-limited electromagnetic sensor and as a reservoir capable of signal processing, enabling integrated quantum sensing and processing architectures.

quant-ph↗

arXiv2025

Probing graph topology from local quantum measurements

We show that global properties of an unknown quantum network, such as the average degree, hub density, and the number of closed paths of fixed length, can be inferred from strictly local quantum measurements. In particular, we demonstrate that a malicious agent with access to only a small subset of nodes can initialize quantum states locally and, through repeated short-time measurements, extract sensitive structural information about the entire network. The intrusion strategy is inspired by extreme learning and quantum reservoir computing and combines short-time quantum evolution with a non-iterative linear readout with trainable weights. These results suggest new strategies for intrusion detection and structural diagnostics in future quantum Internet infrastructures.

quant-ph↗

arXiv2025

Forecasting Low-Dimensional Turbulence via Multi-Dimensional Hybrid Quantum Reservoir Computing

The prediction of complex dynamics remains an open problem across many domains of physics, where nonlinearities and multiscale interactions severely limit the reliability of conventional forecasting methods. Quantum reservoir computing (QRC) has emerged as a promising paradigm for information processing by exploiting the high dimensionality of the Hilbert space, where the dynamics of quantum systems take place. Here, we introduce a hybrid quantum-classical reservoir architecture capable of handling multivariate time series through quantum evolution combined with classical memory enhancement. Our model employs a five-qubit transverse-field Ising Hamiltonian with input-modulated dynamics and temporal multiplexing, enabling the encoding of input signals over multiple timescales. We apply this framework to two paradigmatic models of chaotic behavior in fluid dynamics, where multiscale dynamics and nonlinearities play a dominant role: a low-dimensional truncation of the two-dimensional Navier-Stokes equations and the Lorenz-63 system. By systematically scanning the quantum system's parameter space, we identify regions that maximize forecasting performance, as measured by the Valid Prediction Time. The observed robustness and reliable performances for both dynamical systems suggest that this hybrid quantum approach offers a flexible platform for modelling complex nonlinear time series.

quant-ph↗

arXiv2025

Harnessing Quantum Extreme Learning Machines for image classification

Interest in quantum machine learning is increasingly growing due to its potential to offer more efficient solutions for problems that are difficult to tackle with classical methods. In this context, the research work presented here focuses on the use of quantum machine learning techniques for image classification tasks. We exploit a quantum extreme learning machine by taking advantage of its rich feature map provided by the quantum reservoir substrate. We systematically analyse different phases of the quantum extreme learning machine process, from the dataset preparation to the image final classification. In particular, we have tested different encodings, together with Principal Component Analysis, the use of Auto-Encoders, as well as the dynamics of the model through the use of different Hamiltonians for the quantum reservoir. Our results show that the introduction of a quantum reservoir systematically improves the accuracy of the classifier. Additionally, while different encodings can lead to significantly different performances, Hamiltonians with varying degrees of connectivity exhibit the same discrimination rate, provided they are interacting.

quant-ph↗

arXiv2024

Memory-Augmented Hybrid Quantum Reservoir Computing

Reservoir computing (RC) is an effective method for predicting chaotic systems by using a high-dimensional dynamic reservoir with fixed internal weights, while keeping the learning phase linear, which simplifies training and reduces computational complexity compared to fully trained recurrent neural networks (RNNs). Quantum reservoir computing (QRC) uses the exponential growth of Hilbert spaces in quantum systems, allowing for greater information processing, memory capacity, and computational power. However, the original QRC proposal requires coherent injection of inputs multiple times, complicating practical implementation. We present a hybrid quantum-classical approach that implements memory through classical post-processing of quantum measurements. This approach avoids the need for multiple coherent input injections and is evaluated on benchmark tasks, including the chaotic Mackey-Glass time series prediction. We tested our model on two physical platforms: a fully connected Ising model and a Rydberg atom array. The optimized model demonstrates promising predictive capabilities, achieving a higher number of steps compared to previously reported approaches.

quant-ph↗

arXiv2020

Ballistic transport through quantum point contacts of multi-orbital oxides

Linear and non-linear transport properties through an atomic-size point contact based on oxides two-dimensional electron gas is examined using the tight-binding method and the $\mathbf{k\cdot p}$ approach. The ballistic transport is analyzed in contacts realized at the (001) interface between band insulators $LaAlO_3$ and $SrTiO_3$ by using the Landauer-Büttiker method for many sub-bands derived from three Ti 3d orbitals ($d_{yz}$, $d_{zx}$ and $d_{xy}$) in the presence of an out-of-plane magnetic field. We focus especially on the role played by the atomic spin-orbit coupling and the inversion symmetry breaking term pointing out three transport regimes: the first, at low energies, involving the first $d_{xy}$-like sub-bands, where the conductance quantization is robust; a second one, at intermediate energies, entailing further $d_{xy}$-like sub-bands, where the sub-band splitting induced by the magnetic field is quenched; the third one, where the mixing between light $d_{xy}$-like, heavy $d_{yz}$-like and $d_{zx}$-like sub-bands is so strong that the conductance plateaus turn out to be very narrow. Very good agreement is found with recent experiments exploring the transport properties at low energies.

cond-mat.mes-hall↗

arXiv2020

Spin-orbital polarization of Majorana edge states in oxides nanowires

We investigate a paradigmatic case of topological superconductivity in a one-dimensional nanowire with $d-$orbitals and a strong interplay of spin-orbital degrees of freedom due to the competition of orbital Rashba interaction, atomic spin-orbit coupling, and structural distortions. We demonstrate that the resulting electronic structure exhibits an orbital dependent magnetic anisotropy which affects the topological phase diagram and the character of the Majorana bound states (MBSs). The inspection of the electronic component of the MBSs reveals that the spin-orbital polarization generally occurs along the direction of the applied Zeeeman magnetic field, and transverse to the magnetic and orbital Rashba fields. The competition of symmetric and antisymmetric spin-orbit coupling remarkably leads to a misalignment of the spin and orbital moments transverse to the orbital Rashba fields, whose manifestation is essentially orbital dependent. The behavior of the spin-orbital polarization along the applied Zeeman field reflects the presence of multiple Fermi points with inequivalent orbital character in the normal state. Additionally, the response to variation of the electronic parameters related with the degree of spin-orbital entanglement leads to distinctive evolution of the spin-orbital polarization of the MBSs. These findings unveil novel paths to single-out hallmarks relevant for the experimental detection of MBSs.

cond-mat.supr-con↗

arXiv2020

Emergence of anomalous dynamics from the underlying singular continuous spectrum in interacting many-body systems

We investigate the dynamical properties of an interacting many-body system with a non-trivial energy potential landscape that may induce a singular continuous single-particle energy spectrum. Focusing on the Aubry-André model, whose anomalous transport properties in presence of interaction has recently been demonstrated experimentally in an ultracold gas setup, we discuss the anomalous slowing down of the dynamics it exhibits and show that it emerges from the singular-continuous nature of the single-particle excitation spectrum. Our study demonstrates that singular-continuous spectra can be found in interacting systems, unlike previously conjectured by treating the interactions in the mean-field approximation. This, in turns, also highlights the importance of the many-body correlations in giving rise to anomalous dynamics, which, in many-body systems, can result from a non-trivial interplay between geometry and interactions.

cond-mat.str-el↗

arXiv2020

Exact spectral function of a Tonks-Girardeau gas in a lattice

The single-particle spectral function of a strongly correlated system is an essential ingredient to describe its dynamics and transport properties. We develop a general method to calculate the exact spectral function of a strongly interacting one-dimensional Bose gas in the Tonks-Girardeau regime, valid for any type of confining potential, and apply it to bosons on a lattice to obtain the full spectral function, at all energy and momentum scales. We find that it displays three main singularity lines. The first two can be identified as the analogs of Lieb-I and Lieb-II modes of a uniform fluid; the third one, instead, is specifically due to the presence of the lattice. We show that the spectral function displays a power-law behaviour close to the Lieb-I and Lieb-II singularities, as predicted by the non-linear Luttinger liquid description, and obtain the exact exponents. In particular, the Lieb-II mode shows a divergence in the spectral function, differently from what happens in the dynamical structure factor, thus providing a route to probe it in experiments with ultracold atoms.

cond-mat.quant-gas↗

arXiv2016

Signatures of the single particle mobility edge in the ground state properties of Tonks-Girardeau and non-interacting Fermi gases in a bichromatic potential

We explore the ground state properties of cold atomic gases, loaded into a bichromatic lattice, focusing on the cases of non-interacting fermions and hard-core (Tonks-Girardeau) bosons, trapped by the combination of two potentials with incommensurate periods. For such systems, two limiting cases have been thoroughly established. In the tight-binding limit, the single-particle states in the lowest occupied band show a localization transition, as the strength of the second potential is increased above a certain threshold. In the continuous limit, when the tight-binding approximation does not hold anymore, a mobility edge is found, whose position in energy depends upon the strength of the second potential. Here, we study how the crossover from the discrete to the continuum behavior occurs, and prove that signatures of the localization transition and mobility edge clearly appear in the generic many-body properties of the systems. Specifically, we evaluate the momentum distribution, which is a routinely measured quantity in experiments with cold atoms, and demonstrate that, even in the presence of strong boson-boson interactions, the single particle mobility edge can be observed in the ground state properties.

cond-mat.quant-gas↗