Quantum annealing is a quantum computing approach widely used for optimization and
probabilistic sampling problems. It is an alternative approach designed due to the limitations …

Quantum annealing is a computing paradigm that has the ambitious goal of efficiently
solving large-scale combinatorial optimization problems of practical importance. However …

Transparent radiative coolers can be used as window materials to reduce cooling energy
needs for buildings and automobiles, which may contribute significantly to addressing …

Future communication networks will require increased flexibility, scalability, and data
computation capabilities to adequately respond to the growing number of service demands …

Quantum computing is important for science and industry as it offers the potential to solve
certain complex problems and perform calculations significantly faster than classical …

This research examines the energy efficiency of city districts through the Malmquist–DEA
model and investigates the spatial effects of the service trade and the digital economy on …

Multilayers composed of two or more materials enable the regulation of transmission,
reflection, and absorption spectra across one or multiple bands. While analytic formulas …

The homogeneous Bethe-Salpeter equation (hBSE), describing a bound system in a
genuinely relativistic quantum-field theory framework, was solved for the first time by using a …

This book is based on the lecture notes of the course Quantum Machine Learning for the
Master's degree in Computer Science that I gave at the University of Trento in the academic …

The computational requirements of future large scale radio telescopes are expected to scale
well beyond the capabilities of conventional digital resources. Current and planned …