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The statistical properties of quantum transport through a chaotic cavity are encoded in the traces $\T={\rm Tr}(tt^\dag)^n$, where $t$ is the transmission matrix. Within the Random Matrix Theory approach, these traces are random variables…

Mesoscale and Nanoscale Physics · Physics 2008-08-04 Marcel Novaes

We study the chaos of travelling waves (TW) in unidirectional chains of bistable maps. Previous numerical results suggested that this property is selective, {\sl viz.}\ given the parameters, there is at most a single (non-trivial) velocity…

Cellular Automata and Lattice Gases · Physics 2018-11-21 Bastien Fernandez

We analyze the quantum dynamics of the fractional-time Jaynes-Cummings model using a recent unitary framework for the fractional-time Schr\"odinger equation. We examine how the fractional derivative order $\alpha$ influences non-classical…

Quantum Physics · Physics 2026-04-23 Thiago T. Tsutsui , Danilo Cius , Antonio S. M. de Castro , Fabiano M. Andrade

We consider critical curves -- conformally invariant curves that appear at critical points of two-dimensional statistical mechanical systems. We show how to describe these curves in terms of the Coulomb gas formalism of conformal field…

Statistical Mechanics · Physics 2007-05-23 I. Rushkin , E. Bettelheim , I. A. Gruzberg , P. Wiegmann

The time-dependent variational principle using generalized Gaussian trial functions yields a finite dimensional approximation to the full quantum dynamics and is used in many disciplines. It is shown how these 'semi-quantum' dynamics may be…

chao-dyn · Physics 2009-10-22 Arjendu K. Pattanayak , William C. Schieve

An approximate method based on adiabatic time dependent density functional theory (TDDFT) is presented, that allows for the description of the electron dynamics in nanoscale junctions under arbitrary time dependent external potentials. In…

Mesoscale and Nanoscale Physics · Physics 2015-05-27 Y. Wang , C. -Y. Yam , G. H. Chen , Th. Frauenheim , T. A. Niehaus

The main purpose of this paper is to study the fractional-order model with Caputo derivative associated to Lagrange system. For this fractional-order system we investigate the existence and uniqueness of solutions of initial value problem,…

Dynamical Systems · Mathematics 2022-11-22 Mihai Ivan

The long therm behavior of chaotic flows is investigated by means of time dependent frequency analysis. The system under test consists of an electrically conducting fluid, confined between two differentially rotating spheres. The spherical…

Fluid Dynamics · Physics 2021-02-24 Ferran Garcia , Martin Seilmayer , André Giesecke , Frank Stefani

In this paper we consider a generalized classical mechanics with fractional derivatives. The generalization is based on the time-clock randomization of momenta and coordinates taken from the conventional phase space. The fractional…

Classical Physics · Physics 2011-11-15 Aleksander Stanislavsky

Sensitive boundary condition dependence (BCD) is reported in a convectively unstable system with noise, where the amplitude of generated oscillatory dynamics in the downstream depends sensitively on the boundary value. This BCD is explained…

chao-dyn · Physics 2007-05-23 Koichi Fujimoto , Kunihiko Kaneko

The MHD flow driven by a travelling magnetic field (TMF) in an annular channel is investigated numerically. For sufficiently large magnetic Reynolds number Rm, or if a large enough pressure gradient is externally applied, the system…

Fluid Dynamics · Physics 2016-03-23 Christophe Gissinger , Paola Rodriguez-Imazio , Stephan Fauve

Quantum chaotic systems are conjectured to display a spectrum whose fine-grained features (gaps and correlations) are well described by Random Matrix Theory (RMT). We propose and develop a complementary version of this conjecture: quantum…

High Energy Physics - Theory · Physics 2023-12-08 Vijay Balasubramanian , Javier M. Magan , Qingyue Wu

A new method of symbolic analysis based on finite discretization of velocity-curvature space is proposed. A minimum alphabet is introduced in a natural way, and a number of initial analytic measures are defined that make it possible to…

Chaotic Dynamics · Physics 2012-03-20 A. V. Makarenko

Dynamical systems across the sciences, from electrical circuits to ecological networks, undergo qualitative and often catastrophic changes in behavior, called bifurcations, when their underlying parameters cross a threshold. Existing…

Machine Learning · Computer Science 2024-03-22 Noa Moriel , Matthew Ricci , Mor Nitzan

The Kowalevski gyrostat in two constant fields is known as the unique example of an integrable Hamiltonian system with three degrees of freedom not reducible to a family of systems in fewer dimensions and still having the clear mechanical…

Symplectic Geometry · Mathematics 2010-01-18 Mikhail P. Kharlamov

We consider model order reduction of parameterized Hamiltonian systems describing nondissipative phenomena, like wave-type and transport dominated problems. The development of reduced basis methods for such models is challenged by two main…

Numerical Analysis · Mathematics 2021-05-27 Cecilia Pagliantini

New fluctuation properties arise in problems where both spatial integration and energy summation are necessary ingredients. The quintessential example is given by the short-range approximation to the first order ground state contribution of…

Mesoscale and Nanoscale Physics · Physics 2009-11-13 Steven Tomsovic , Denis Ullmo , Arnd Baecker

A fundamental principle of chaotic quantum dynamics is that local subsystems eventually approach a thermal equilibrium state. Large subsystems thermalize slower: their approach to equilibrium is limited by the hydrodynamic build-up of…

Molecular dynamics simulations yield large amounts of trajectory data. For their durable storage and accessibility an efficient compression algorithm is paramount. State of the art domain-specific algorithms combine quantization, Huffman…

Distributed, Parallel, and Cluster Computing · Computer Science 2016-01-13 Jan Huwald , Stephan Richter , Peter Dittrich

Classification of sequence data is the topic of interest for dynamic Bayesian models and Recurrent Neural Networks (RNNs). While the former can explicitly model the temporal dependencies between class variables, the latter have a capability…

Machine Learning · Computer Science 2018-03-12 Son N. Tran , Srikanth Cherla , Artur Garcez , Tillman Weyde