Quantum Information and Computing | Doctoral Program - Information Engineering and Computer Science

Quantum Information and Computing

We investigate the connections between foundations of Quantum Physics and Computer Science, our research focuses on information storing and processing by means of quantum physical systems (e.g. photons, electrons, trapped ions, superconducting circuits). The covered research topics range from fundamental aspects of Quantum Mechanics to technological applications.

We work on the following topics:

  • Hybrid quantum-classical algorithms combining quantum operations and classical computations for existing or near-term quantum machines.
  • Efficient procedures for storing large amount of classical data into quantum hardware.
  • Quantum Machine Learning.
  • Quantum communications and quantum key distribution.
  • Theoretical quantum information.
  • Quantum Annealing

We collaborate with Quantum Computing Group of the German Aerospace Center, Quantum Informatics Lab (University of Verona), Dept. of Mathematics and Dept. of Physics at University of Trento.



7 publications for 2 currently enrolled students

A general learning scheme for classical and quantum Ising machines
Schmid, Ludwig; Zardini, Enrico; Pastorello, Davide in SCIPOST PHYSICS CORE, v. 7, n. 1 (2024). - DOI: 10.21468/scipostphyscore.7.1.013

Ensembles of quantum classifiers
Tolotti, Emiliano; Zardini, Enrico; Blanzieri, Enrico; Pastorello, Davide in QUANTUM INFORMATION & COMPUTATION, v. 24, n. 3-4 (2024), p. 181-209. - Publication URL . - DOI: 10.26421/QIC24.3-4-1

Hybrid classical-quantum algorithms for optimization and machine learning

Implementation and empirical evaluation of a quantum machine learning pipeline for local classification
Zardini, Enrico; Blanzieri, Enrico; Pastorello, Davide in PLOS ONE, v. 18, n. 11 (2023), p. 1-28. - Publication URL . - DOI: 10.1371/journal.pone.0287869

Quantum annealing learning search implementations
Bonomi, Andrea; De Min, Thomas; Zardini, Enrico; Blanzieri, Enrico; Cavecchia, Valter; Pastorello, Davide in QUANTUM INFORMATION & COMPUTATION, v. 22, n. 3&4 (2022), p. 181-208. - Publication URL . - DOI: 10.26421/QIC22.3-4-1

Reconstructing Bayesian networks on a quantum annealer
Zardini, Enrico; Rizzoli, Massimo; Dissegna, Sebastiano; Blanzieri, Enrico; Pastorello, Davide in QUANTUM INFORMATION & COMPUTATION, v. 22, n. 15-16 (2022), p. 1320-1350. - Publication URL . - DOI: 10.26421/QIC22.15-16-4

Seeking quality diversity in evolutionary co-design of morphology and control of soft tensegrity modular robots
Zardini, E.; Zappetti, D.; Zambrano, D.; Iacca, G.; Floreano, D. in GECCO 2021 - Proceedings of the 2021 Genetic and Evolutionary Computation Conference, New York: Association for Computing Machinery, Inc, 2021, p. 189-197. - ISBN: 9781450383509. Proceedings of: 2021 Genetic and Evolutionary Computation Conference, GECCO 2021, Lille, 10-14 June, 2021. - Publication URL . - DOI: 10.1145/3449639.3459311



Vallero, Marziomarzio.vallero [at] unitn.itwebpage
Zardini, Enricoenrico.zardini [at] unitn.itwebpage