Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Gedeon, Johannes"'
We present a density-based topology optimization scheme for locally optimizing the electric power dissipation in nanostructures made of lossy dispersive materials. By using the complex-conjugate pole-residue (CCPR) model, we can accurately model any
Externí odkaz:
http://arxiv.org/abs/2407.05994
In the last decades nanostructures have unlocked myriads of functionalities in nanophotonics by engineering light-matter interaction beyond what is possible with conventional bulk optics. The space of parameters available for design is practically un
Externí odkaz:
http://arxiv.org/abs/2305.00234
Autor:
Gedeon, Johannes, Schmidt, Jonathan, Hodgson, Matthew J. P., Wetherell, Jack, Benavides-Riveros, Carlos L., Marques, Miguel A. L.
Publikováno v:
Mach. Learn.: Sci. Technol. 3 015011 (2022)
Machine learning is a powerful tool to design accurate, highly non-local, exchange-correlation functionals for density functional theory. So far, most of those machine learned functionals are trained for systems with an integer number of particles. A
Externí odkaz:
http://arxiv.org/abs/2106.16075
Autor:
Ferranti, Francesco, Keshavarz Hedayati, Mehdi, Fratalocchi, Andrea, Gedeon, Johannes, Hassan, Emadeldeen, Evlyukhin, Andrey B., Calà Lesina, Antonio
Publikováno v:
Proceedings of SPIE; June 2024, Vol. 13017 Issue: 1 p130170G-130170G-3, 1171534p
Publikováno v:
ACS Photonics; 11/15/2023, Vol. 10 Issue 11, p3875-3887, 13p
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.