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19922026
most citedMachine Learning in Automated Text Categorization

8k citations

Showing 2023 · quant-phShow all

12 papers · 2 filters

quant-ph2023★ 38 cited

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,…

quant-ph2023★ 31 cited

Experimental certification of contextuality, coherence and dimension in a programmable universal photonic processor

Taira Giordani, Rafael Wagner, Chiara Esposito +11

Quantum superposition of high-dimensional states enables both computational speed-up and security in cryptographic protocols. However, the exponential complexity of tomographic pro…

quant-ph2023★ 37 cited

Observation of first- and second-order dissipative phase transitions in a two-photon driven Kerr resonator

Guillaume Beaulieu, Fabrizio Minganti, Simone Frasca +4

In open quantum systems, first- and second-order dissipative phase transitions (DPTs) can emerge in the thermodynamic limit from the competition between unitary evolution, driving…

quant-ph2023★ 11 cited

Rydberg atomtronic devices

Philip Kitson, Tobias Haug, Antonino La Magna +2

Networks of Rydberg atoms provide a powerful basis for quantum simulators and quantum technologies. Inspired by matter-wave atomtronics, here we engineer switches, diodes and unive…

quant-ph2023★ 2 cited

Routing in Quantum Repeater Networks with Mixed Efficiency Figures

Vinay Kumar, Claudio Cicconetti, Marco Conti +1

This study explores an approach to routing in quantum networks, which targets practical scenarios for quantum networks, mirroring real-world classical networks. By addressing pract…

quant-ph2023★ 29 cited

Variational quantum algorithm for experimental photonic multiparameter estimation

Valeria Cimini, Mauro Valeri, Simone Piacentini +5

Variational quantum metrology represents a powerful tool for optimizing generic estimation strategies, combining the principles of variational optimization with the techniques of q…