In this paper we report the result of a Monte Carlo study on the probability of chaos in large dynamical systems. We use neural networks as the basis functions for the system dynamics and choose parameter values for the networks randomly. Our results show that as the dimension of the system and the
Superconductivity in multi-orbital systems: A dynamical mean Monte Carlo study
β Scribed by Shiro Sakai; Ryotaro Arita; Hideo Aoki
- Publisher
- Elsevier Science
- Year
- 2005
- Tongue
- English
- Weight
- 178 KB
- Volume
- 359-361
- Category
- Article
- ISSN
- 0921-4526
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β¦ Synopsis
We have implemented the dynamical mean field ΓΎ quantum Monte Carlo method to study superconductivity in the double-orbital Hubbard model. The result shows that Hund's and pair-hopping terms enhance the spin-tripletorbitalantisymmetric pairing in a wide region around half-filling.
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## Abstract A simple cubic lattice model of the melt of 3βarm starβbranched polymers of various length dissolved in a matrix of long linear chains (__n__~1~ = 800 beads) is studied using a dynamic Monte Carlo method. The total polymer volume fraction is equal to 0,5, while the volume fraction of th