Quantum Computer
Quantum computers aim to leverage quantum mechanics for computations exceeding classical capabilities, primarily focusing on optimization and machine learning tasks. Current research emphasizes developing efficient quantum algorithms and architectures, including variational quantum circuits, quantum neural networks (both hybrid and fully quantum), and quantum-enhanced versions of classical algorithms like Grover's search. These advancements are being tested on noisy intermediate-scale quantum (NISQ) devices and cloud platforms, addressing challenges like error mitigation, data security, and efficient circuit design to demonstrate practical applications in diverse fields such as finance, materials science, and drug discovery.
Papers
Towards Feature Selection for Ranking and Classification Exploiting Quantum Annealers
Maurizio Ferrari Dacrema, Fabio Moroni, Riccardo Nembrini, Nicola Ferro, Guglielmo Faggioli, Paolo Cremonesi
Quantum neural network autoencoder and classifier applied to an industrial case study
Stefano Mangini, Alessia Marruzzo, Marco Piantanida, Dario Gerace, Daniele Bajoni, Chiara Macchiavello