38 citations · 107 across the 7 of their papers we have counts for
7 papers
Efficient Variational Quantum Algorithms for the Generalized Assignment Problem
Carlo Mastroianni, Francesco Plastina, Jacopo Settino +1
Quantum algorithms offer a compelling new avenue for addressing difficult NP-complete optimization problems, such as the Generalized Assignment Problem (GAP). Given the operational…
Assessing Projected Quantum Kernels for the Classification of IoT Data
Francesco D'Amore, Luca Mariani, Carlo Mastroianni +4
The use of quantum computing for machine learning is among the most promising applications of quantum technologies. Quantum models inspired by classical algorithms are developed to…
Variational Quantum Algorithms for the Allocation of Resources in a Cloud/Edge Architecture
Carlo Mastroianni, Francesco Plastina, Jacopo Settino +1
Modern Cloud/Edge architectures need to orchestrate multiple layers of heterogeneous computing nodes, including pervasive sensors/actuators, distributed Edge/Fog nodes, centralized…
Assessing Quantum Computing Performance for Energy Optimization in a Prosumer Community
Carlo Mastroianni, Francesco Plastina, Luigi Scarcello +2
The efficient management of energy communities relies on the solution of the "prosumer problem", i.e., the problem of scheduling the household loads on the basis of the user needs,…
Variational Gibbs State Preparation on NISQ devices
Mirko Consiglio, Jacopo Settino, Andrea Giordano +6
The preparation of an equilibrium thermal state of a quantum many-body system on noisy intermediate-scale quantum (NISQ) devices is an important task in order to extend the range o…
Quantum Computing Approach for Energy Optimization in a Prosumer Community
Carlo Mastroianni, Luigi Scarcello, Jacopo Settino
This paper presents a quantum approach for the formulation and solution of the prosumer problem, i.e., the problem of minimizing the energy cost incurred by a number of users in an…
A hybrid classical-quantum approach to speed-up Q-learning
A. Sannia, A. Giordano, N. Lo Gullo +2
We introduce a classical-quantum hybrid approach to computation, allowing for a quadratic performance improvement in the decision process of a learning agent. In particular, a quan…