38 citations · 144 across the 22 of their papers we have counts for
10 papers · 1 filter
A weighted quantum ensemble of homogeneous quantum classifiers
Emiliano Tolotti, Enrico Blanzieri, Davide Pastorello
Ensemble methods in machine learning aim to improve prediction accuracy by combining multiple models. This is achieved by ensuring diversity among predictors to capture different d…
Enhancing Expressivity of Quantum Neural Networks Based on the SWAP test
Sebastian Nagies, Emiliano Tolotti, Davide Pastorello +1
Quantum neural networks (QNNs) based on parametrized quantum circuits are promising candidates for machine learning applications, yet many architectures lack clear connections to c…
Scalable quantum neural networks by few quantum resources
Davide Pastorello, Enrico Blanzieri
This paper focuses on the construction of a general parametric model that can be implemented executing multiple swap tests over few qubits and applying a suitable measurement proto…
Evaluating the Convergence of Tabu Enhanced Hybrid Quantum Optimization
Enrico Blanzieri, Davide Pastorello, Valter Cavecchia +2
In this paper we introduce the Tabu Enhanced Hybrid Quantum Optimization metaheuristic approach useful for optimization problem solving on a quantum hardware. We address the theore…
A quantum binary classifier based on cosine similarity
Davide Pastorello, Enrico Blanzieri
We introduce the quantum implementation of a binary classifier based on cosine similarity between data vectors. The proposed quantum algorithm evaluates the classifier on a set of…
Geometric viewpoint on the quantization of a fuzzy logic
Davide Pastorello
Within the Hamiltonian framework, the propositions about a classical physical system are described in the Borel σ-algebra of a symplectic manifold (the phase space) where logical c…
Bell inequality violation by entangled single photon states generated from a laser, a LED or a Halogen lamp
M. Pasini, N. Leone, S. Mazzucchi +3
In single-particle or intraparticle entanglement, two degrees of freedom of a single particle, e.g., momentum and polarization of a single photon, are entangled. Single-particle en…
Learning adiabatic quantum algorithms for solving optimization problems
Davide Pastorello, Enrico Blanzieri
An adiabatic quantum algorithm is essentially given by three elements: An initial Hamiltonian with known ground state, a problem Hamiltonian whose ground state corresponds to the s…
Quantum Annealing Learning Search for solving QUBO problems
Enrico Blanzieri, Davide Pastorello
In this paper we present a novel strategy to solve optimization problems within a hybrid quantum-classical scheme based on quantum annealing, with a particular focus on QUBO proble…
A quantum key distribution scheme based on tripartite entanglement and violation of CHSH inequality
Davide Pastorello
Entanglement is a well-known resource in quantum information, in particular it can be exploited for quantum key distribution (QKD). In this paper we define a two-way QKD scheme emp…