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pro vyhledávání: '"Dragoni, Daniele"'
The advent of quantum computers has justified the development of quantum machine learning algorithms , based on the adaptation of the principles of machine learning to the formalism of qubits. Among such quantum algorithms, anomaly detection represen
Externí odkaz:
http://arxiv.org/abs/2408.11047
Using drones to perform human-related tasks can play a key role in various fields, such as defense, disaster response, agriculture, healthcare, and many others. The drone delivery packing problem (DDPP) arises in the context of logistics in response
Externí odkaz:
http://arxiv.org/abs/2406.08430
The optimization of the power consumption of antenna networks is a problem with a potential impact in the field of telecommunications. In this work, we investigate the application of the quantum approximate optimization algorithm (QAOA) and the quant
Externí odkaz:
http://arxiv.org/abs/2311.11621
Publikováno v:
In Future Generation Computer Systems October 2024 159:105-113
Akademický článek
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Publikováno v:
Phys. Rev. Materials 2, 013808 (2018)
We show that the Gaussian Approximation Potential machine learning framework can describe complex magnetic potential energy surfaces, taking ferromagnetic iron as a paradigmatic challenging case. The training database includes total energies, forces,
Externí odkaz:
http://arxiv.org/abs/1706.10229
A comprehensive, critical study of the vibrational, thermodynamic and thermoelastic properties of bcc iron is presented, using well established semi-empirical embedded-atom method potentials available in the literature. Classical molecular dynamics s
Externí odkaz:
http://arxiv.org/abs/1605.03334
We calculate the thermomechanical properties of $\alpha$-iron, and in particular its isothermal and adiabatic elastic constants, using first-principles total-energy and lattice-dynamics calculations, minimizing the quasi-harmonic vibrational free ene
Externí odkaz:
http://arxiv.org/abs/1502.01534
Publikováno v:
In Computational Materials Science September 2018 152:99-106
Autor:
Cecchi, Stefano, Momand, Jamo, Dragoni, Daniele, Abou El Kheir, Omar, Fagiani, Federico, Kriegner, Dominik, Rinaldi, Christian, Arciprete, Fabrizio, Holý, Vaclav, Kooi, Bart J., Bernasconi, Marco, Calarco, Raffaella
Publikováno v:
Advanced Science; 1/5/2024, Vol. 11 Issue 1, p1-11, 11p