Zobrazeno 1 - 10
of 801
pro vyhledávání: '"Foulkes, W."'
This paper investigates interaction-induced symmetry breaking in circular quantum dots. We explain that the anisotropic static Wigner molecule ground states frequently observed in simulations are created by interference effects that occur even in the
Externí odkaz:
http://arxiv.org/abs/2410.01652
Quantum chemical calculations of the ground-state properties of positron-molecule complexes are challenging. The main difficulty lies in employing an appropriate basis set for representing the coalescence between electrons and a positron. Here, we ta
Externí odkaz:
http://arxiv.org/abs/2310.05607
Classical models of spin-lattice coupling are at present unable to accurately reproduce results for numerous properties of ferromagnetic materials, such as heat transport coefficients or the sudden collapse of the magnetic moment in hcp-Fe under pres
Externí odkaz:
http://arxiv.org/abs/2308.03130
Autor:
Lou, Wan Tong, Sutterud, Halvard, Cassella, Gino, Foulkes, W. M. C., Knolle, Johannes, Pfau, David, Spencer, James S.
Publikováno v:
Phys. Rev. X 14, 021030 (2024)
Understanding superfluidity remains a major goal of condensed matter physics. Here we tackle this challenge utilizing the recently developed Fermionic neural network (FermiNet) wave function Ansatz [D. Pfau et al., Phys. Rev. Res. 2, 033429 (2020).]
Externí odkaz:
http://arxiv.org/abs/2305.06989
Autor:
Hermann, Jan, Spencer, James, Choo, Kenny, Mezzacapo, Antonio, Foulkes, W. M. C., Pfau, David, Carleo, Giuseppe, Noé, Frank
Machine learning and specifically deep-learning methods have outperformed human capabilities in many pattern recognition and data processing problems, in game playing, and now also play an increasingly important role in scientific discovery. A key ap
Externí odkaz:
http://arxiv.org/abs/2208.12590
Autor:
Cassella, G., Sutterud, H., Azadi, S., Drummond, N. D., Pfau, D., Spencer, J. S., Foulkes, W. M. C.
Deep neural networks have been extremely successful as highly accurate wave function ans\"atze for variational Monte Carlo calculations of molecular ground states. We present an extension of one such ansatz, FermiNet, to calculations of the ground st
Externí odkaz:
http://arxiv.org/abs/2202.05183
Publikováno v:
Phys. Rev. Lett. 127, 086401 (2021)
According to Landau's Fermi liquid theory, the main properties of the quasiparticle excitations of an electron gas are embodied in the effective mass $m^*$, which determines the energy of a single quasiparticle, and the Landau interaction function, w
Externí odkaz:
http://arxiv.org/abs/2105.09139
The Fermionic Neural Network (FermiNet) is a recently-developed neural network architecture that can be used as a wavefunction Ansatz for many-electron systems, and has already demonstrated high accuracy on small systems. Here we present several impr
Externí odkaz:
http://arxiv.org/abs/2011.07125
Autor:
Fagerholm, Erik D., Foulkes, W. M. C., Gallero-Salas, Yasir, Helmchen, Fritjof, Friston, Karl J., Moran, Rosalyn J., Leech, Robert
In contrast to the symmetries of translation in space, rotation in space, and translation in time, the known laws of physics are not universally invariant under transformation of scale. However, the action can be invariant under change of scale in th
Externí odkaz:
http://arxiv.org/abs/1911.00775
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