arXiv subjects

Nadia Milazzo

Publications and source records attributed to Nadia Milazzo.

7 recordsLinked to original sources

arXiv2026

Engineered Learning Problems on Noisy Quantum Processors

Despite quantum machine learning being an active topic of research, demonstrations of algorithms run on quantum hardware beating classical methods remain rare. In this work, we demonstrate a significant performance gap using a projected quantum kernel for $n=15,30$ and $45$ qubits over classical methods on an engineered classification problem, and show reproducibility of the results over different quantum processor units. We also demonstrate how error mitigation can widen this gap, both by improving hardware performance but also by increasing the classical difficulty, with different techniques contributing unequally to these phenomena. This work provides strong evidence that superior empirical performance of quantum hardware over all classical techniques is an achievable goal in quantum machine learning, albeit for an artificial problem. However, as with any application relying on observables, beating state-of-the-art simulation methods remains the primary challenge, as our matrix product state results here show.

quant-ph↗

arXiv2026

Pareto-optimal quantum kernel selection for unsupervised anomaly detection on real malware beaconing data

Quantum kernel methods are leading candidates for a practical quantum advantage in machine learning, but assessing that potential requires two quantities usually reported separately: how well a kernel performs on the task, and how far its geometry departs from the classical kernels available for the same problem. We introduce a fully unsupervised, multi-objective protocol that optimises simultaneously the normalised pseudo discrepancy (NPD), a label-free proxy for anomaly detection quality, and the geometric difference (GD) to a tuned classical reference kernel, selecting models from the resulting Pareto front. We apply it to malware beaconing detection in real network traffic, using a one-class support vector machine with fidelity and projected quantum kernels over four data encodings, on simulators and on IQM's 20-qubit Garnet processor. NPD-guided selection alone finds a fidelity kernel that beats the tuned classical baseline, but with a geometric difference too small to certify the gain as quantum. Projected kernels reach far larger geometric differences; the Pareto-selected one only marginally exceeds the baseline (AUC $0.782$ versus $0.765$, $g_{C\to Q}\approx 89>\sqrt{N}$ relative to that reference kernel), still below the NPD-selected fidelity kernel ($0.840$).

quant-ph↗

arXiv2025

H-DES: a Quantum-Classical Hybrid Differential Equation Solver

In this article, we introduce an original hybrid quantum-classical algorithm based on a variational quantum algorithm for solving systems of differential equations. The algorithm relies on a spectral decomposition of the trial functions that are encoded directly in the quantum states generated by different parametrized circuits, and transforms the task of solving the differential equations into an optimization problem. We first describe the principle of the algorithm from a theoretical point of view. We provide a detailed pseudo-code of the algorithm, on which we elaborate preliminary elements for a complexity analysis to highlight some of its scaling properties. We apply our algorithm to a set of examples, running on emulators and real hardware showcasing its applicability across diverse sets of differential equations. We discuss the advantages of our method and potential avenues for further exploration and refinement.

quant-ph↗

arXiv2022

Principles of quantum functional testing

With increasing commercial availability of quantum information processing devices the need for testing them efficiently for their specified functionality will arise. Complete quantum channel characterization is out of the question for anything more than the simplest quantum channels for one or two qubits. Quantum functional testing leads to a decision problem with outcomes corresponding to rejection or acceptance of the claim of the producer that the device parameters are within certain specifications. In this context, we introduce and analyse three ingredients that can speed up this decision problem: iteration of the channel, efficient decision criteria, and non-greedy adaptive experimental design.

quant-ph↗

arXiv2021

Bipartite and tripartite entanglement in a Bose-Einstein acoustic black hole

We investigate quantum entanglement in an analogue black hole realized in the flow of a Bose-Einstein condensate. The system is described by a three-mode Gaussian state and we construct the corresponding covariance matrix at zero and finite temperature. We study associated bipartite and tripartite entanglement measures and discuss their experimental observation. We identify a simple optical setup equivalent to the analogue Bose-Einstein black hole which suggests a new way of determining the Hawking temperature and grey-body factor of the system.

cond-mat.quant-gas↗

arXiv2020

Truncated moment sequences and a solution to the channel separability problem

We consider the problem of separability of quantum channels via the Choi matrix representation given by the Choi-Jamiołkowski isomorphism. We explore three classes of separability across different cuts between systems and ancillae and we provide a solution based on the mapping of the coordinates of the Choi state (in a fixed basis) to a truncated moment sequence (tms) $y$. This results in an algorithm which gives a separability certificate using semidefinite programming. The computational complexity and the performance of it depend on the number of variables $n$ in the tms and on the size of the moment matrix $M_t(y)$ of order $t$. We exploit the algorithm to numerically investigate separability of families of 2-qubit and single-qutrit channels; in the latter case we can provide an answer for examples explored earlier through the criterion based on the negativity $N$, a criterion which remains inconclusive for Choi matrices with $N=0$.

quant-ph↗

arXiv2019

The role of information back-flow in the emergence of quantum Darwinism

Quantum Darwinism attempts to explain the emergence of objective reality of the state of a quantum system in terms of redundant information about the system acquired by independent non interacting fragments of the environment. The consideration of interacting environmental elements gives rise to a rich phenomenology, including the occurrence of non-Markovian features, whose effects on objectification {\it a' la} quantum Darwinism needs to be fully understood. We study a model of local interaction between a simple quantum system and a multi-mode environment that allows for a clear investigation of the interplay between information trapping and propagation in the environment and the emergence of quantum Darwinism. We provide strong evidence of the correlation between non-Markovianity and quantum Darwinism in such a model, thus providing strong evidence of a potential link between such fundamental phenomena.

quant-ph↗