7 papers
A Tensor Network Framework for Interpretable Graph Analysis of Brain Networks
Domenico Pomarico, Giuseppe Magnifico, Alessandro Grecucci +10
Identifying robust neurobiological signatures of brain disorders requires machine learning approaches that combine predictive performance with interpretable representations of feat…
Multipartite entanglement of random states of qubits
Giorgia Trotta, Paolo Scarafile, Paolo Facchi +5
We investigate multipartite entanglement via the statistical properties of pure quantum states of n-qubits. By analyzing the distribution of purity among balanced bipartitions, we…
Superradiant decay in non-Markovian Waveguide Quantum Electrodynamics
Rosa Lucia Capurso, Giuseppe Calajó, Simone Montangero +5
An array of initially excited emitters coupled to a one-dimensional waveguide exhibits superradiant decay under the Born-Markov approximation, manifested as a coherent burst of pho…
Dynamical cluster-based strategy for improving tensor network algorithms in quantum circuit simulations
Andrea De Girolamo, Paolo Facchi, Peter Rabl +3
We optimize matrix-product state-based algorithms for simulating quantum circuits with finite fidelity, specifically the time-evolving block decimation (TEBD) and the density-matri…
Non-Markovian dynamics of generation of bound states in the continuum via single-photon scattering
Giuseppe Magnifico, Maria Maffei, Domenico Pomarico +4
The excitation of bound states in the continuum (BICs) in two- or multi-qubit systems lies at the heart of entanglement generation and harnessing in Waveguide Quantum Electrodynami…
Transfer entropy and O-information to detect grokking in tensor network multi-class classification problems
Domenico Pomarico, Roberto Cilli, Alfonso Monaco +10
Quantum-enhanced machine learning, encompassing both quantum algorithms and quantum-inspired classical methods such as tensor networks, offers promising tools for extracting struct…