scholarly journals Electrical confinement in a spectrum of two-dimensional Dirac materials with classically integrable, mixed, and chaotic dynamics

2020 ◽  
Vol 2 (1) ◽  
Author(s):  
Chen-Di Han ◽  
Hong-Ya Xu ◽  
Ying-Cheng Lai
Keyword(s):  
Chaotic Dynamics ◽  
Two Dimensional ◽  
Dirac Materials

scholarly journals Sommerfeld enhancement factor in two-dimensional Dirac materials

2021 ◽  
Vol 103 (23) ◽  
Author(s):  
N. V. Leppenen ◽  
L. E. Golub ◽  
E. L. Ivchenko
Keyword(s):  
Enhancement Factor ◽  
Two Dimensional ◽  
Dirac Materials ◽  
Sommerfeld Enhancement

scholarly journals Coulomb effects in the absorbance spectra of two-dimensional Dirac materials

2018 ◽  
Vol 98 (20) ◽  
Author(s):  
Leone Di Mauro Villari ◽  
Ian Galbraith ◽  
Fabio Biancalana
Keyword(s):  
Two Dimensional ◽  
Dirac Materials ◽  
Coulomb Effects ◽  
Absorbance Spectra

Relation between Topological Entropies and Fractal Dimensions of Chaotic Attractors of the Hénon Map

2012 ◽  
Vol 569 ◽  
pp. 447-450
Author(s):  
Xiao Zhou Chen ◽  
Liang Lin Xiong ◽  
Long Li
Keyword(s):  
Linear Relation ◽  
Chaotic Dynamics ◽  
Fractal Dimensions ◽  
Chaotic Attractors ◽  
Two Dimensional ◽  
Hénon Map ◽  
Henon Map ◽  
Efficient Approach ◽  
Integral Relationship

In two-dimensional chaotic dynamics, relationship between fractal dimensions and topological entropies is an important issue to understand the chaotic attractors of Hénon map. we proposed a efficient approach for the estimation of topological entropies through the study on the integral relationship between fractal dimensions and topological entropies. Our result found that there is an approximate linear relation between their topological entropies and fractal dimensions.

scholarly journals Magneto-optical Kerr effect in spin split two-dimensional massive Dirac materials

2D Materials ◽  
2020 ◽  
Vol 7 (2) ◽  
pp. 025011 ◽  
Author(s):  
G Catarina ◽  
N M R Peres ◽  
J Fernández-Rossier
Keyword(s):  
Kerr Effect ◽  
Optical Kerr Effect ◽  
Two Dimensional ◽  
Dirac Materials ◽  
Magneto Optical Kerr Effect

GENERATION OF SYMMETRICAL COLORED IMAGES VIA SOLUTION OF THE INVERSE PROBLEM OF CHEMICAL REACTIONS DISCRETE CHAOTIC DYNAMICS

2006 ◽  
Vol 16 (05) ◽  
pp. 1419-1434 ◽  
Author(s):  
V. GONTAR ◽  
O. GRECHKO
Keyword(s):  
Genetic Algorithm ◽  
Mathematical Model ◽  
Inverse Problem ◽  
Mathematical Models ◽  
Chemical Reactions ◽  
Chaotic Dynamics ◽  
Two Dimensional

An automatic procedure for generating colored two-dimensional symmetrical images based on the chemical reactions discrete chaotic dynamics (CRDCD) is proposed. The inverse problem of derivation of symmetrical images from CRDCD mathematical models was formulated and solved using a special type of genetic algorithm. Different symmetrical images corresponding to the solutions of a CRDCD mathematical model for which the parameters were obtained automatically by the proposed method are presented.

A Solution for Two-Dimensional Mazes with Use of Chaotic Dynamics in a Recurrent Neural Network Model

2004 ◽  
Vol 16 (9) ◽  
pp. 1943-1957 ◽  
Author(s):  
Yoshikazu Suemitsu ◽  
Shigetoshi Nara
Keyword(s):  
Neural Network ◽  
State Space ◽  
Network Model ◽  
Neural Network Model ◽  
Chaotic Dynamics ◽  
Dimensional Space ◽  
Dynamical Structure ◽  
Two Dimensional ◽  
Time Step ◽  
The Neural Network

Chaotic dynamics introduced into a neural network model is applied to solving two-dimensional mazes, which are ill-posed problems. A moving object moves from the position at t to t + 1 by simply defined motion function calculated from firing patterns of the neural network model at each time step t. We have embedded several prototype attractors that correspond to the simple motion of the object orienting toward several directions in two-dimensional space in our neural network model. Introducing chaotic dynamics into the network gives outputs sampled from intermediate state points between embedded attractors in a state space, and these dynamics enable the object to move in various directions. System parameter switching between a chaotic and an attractor regime in the state space of the neural network enables the object to move to a set target in a two-dimensional maze. Results of computer simulations show that the success rate for this method over 300 trials is higher than that of random walk. To investigate why the proposed method gives better performance, we calculate and discuss statistical data with respect to dynamical structure.

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