Linewidth Enhancement Factor Impact on Optical Feedback Mutual Coupled Quantum Dot Lasers

In this article, we numerically study and analyse the roles of linewidth enhancement factor (α) in the dynamic operation of the mutual regime of the transmitter and receiver quantum dot laser lasers supported by optical feedback. A set model of adequate rate equations describing the overall dynamics in a quantum dot system subjected to optical feedback were solved numerically. The results reveal a clear chaotic regime between the receiver and the transmitter lasers at α = 3, which is incredibly advantageous for secure optical communications and encoding decoding data transmission. Moreover, at the other value of linewidth enhancement factors, namely 2, 2.5, 3.5 and 4, the optical regime works in high synchronisation with either periodic or steady state forms.

DYNAMICAL AND TOPOLOGICAL INVARIANTS OF NONLINEAR DYNAMICS OF THE CHAOTIC LASER DIODES WITH AN ADDITIONAL OPTICAL INJECTION

Nonlinear chaotic dynamics of the of the chaotic laser diodes with an additional optical injection is computed within rate equations model, based on the a set of rate equations for the slave laser electric complex amplitude and carrier density. To calculate the system dynamics in a chaotic regime the known chaos theory and non-linear analysis methods such as a correlation integral algorithm, the Lyapunov’s exponents and Kolmogorov entropy analysis are used. There are listed the data of computing dynamical and topological invariants such as the correlation, embedding and Kaplan-Yorke dimensions, Lyapunov’s exponents, Kolmogorov entropy etc. New data on topological and dynamical invariants are computed and firstly presented.

Chaos in the Bose-Hubbard model and Random Two-Body Hamiltonians

We investigate the chaotic phase of the Bose-Hubbard model [L. Pausch et al, Phys. Rev. Lett. 126, 150601 (2021)] in relation to the bosonic embedded random matrix ensemble, which mirrors the dominant few-body nature of many-particle interactions, and hence the Fock space sparsity of quantum many-body systems. The energy dependence of the chaotic regime is well described by the bosonic embedded ensemble, which also reproduces the Bose-Hubbard chaotic eigenvector features, quantified by the expectation value and eigenstate-to-eigenstate fluctuations of fractal dimensions. Despite this agreement, in terms of the fractal dimension distribution, these two models depart from each other and from the Gaussian orthogonal ensemble as Hilbert space grows. These results provide further evidence of a way to discriminate among different many-body Hamiltonians in the chaotic regime.

Complexity Collapse, Fluctuating Synchrony, and Transient Chaos in Neural Networks With Delay Clusters

Neural circuits operate with delays over a range of time scales, from a few milliseconds in recurrent local circuitry to tens of milliseconds or more for communication between populations. Modeling usually incorporates single fixed delays, meant to represent the mean conduction delay between neurons making up the circuit. We explore conditions under which the inclusion of more delays in a high-dimensional chaotic neural network leads to a reduction in dynamical complexity, a phenomenon recently described as multi-delay complexity collapse (CC) in delay-differential equations with one to three variables. We consider a recurrent local network of 80% excitatory and 20% inhibitory rate model neurons with 10% connection probability. An increase in the width of the distribution of local delays, even to unrealistically large values, does not cause CC, nor does adding more local delays. Interestingly, multiple small local delays can cause CC provided there is a moderate global delayed inhibitory feedback and random initial conditions. CC then occurs through the settling of transient chaos onto a limit cycle. In this regime, there is a form of noise-induced order in which the mean activity variance decreases as the noise increases and disrupts the synchrony. Another novel form of CC is seen where global delayed feedback causes “dropouts,” i.e., epochs of low firing rate network synchrony. Their alternation with epochs of higher firing rate asynchrony closely follows Poisson statistics. Such dropouts are promoted by larger global feedback strength and delay. Finally, periodic driving of the chaotic regime with global feedback can cause CC; the extinction of chaos can outlast the forcing, sometimes permanently. Our results suggest a wealth of phenomena that remain to be discovered in networks with clusters of delays.

Critical transition to a non-chaotic regime in isotropic turbulence

We study the properties of homogeneous and isotropic turbulence in higher spatial dimensions through the lens of chaos and predictability using numerical simulations. We employ both direct numerical simulations and numerical calculations of the eddy damped quasi-normal Markovian closure approximation. Our closure results show a remarkable transition to a non-chaotic regime above the critical dimension, $d_c$ , which is found to be approximately 5.88. We relate these results to the properties of the energy cascade as a function of spatial dimension in the context of the idea of a critical dimension for turbulence where Kolmogorov's 1941 theory becomes exact.

The leaking soft stadium

We soften the non zero y-boundary on a Bunimovich like quarter-stadium. The smoothing procedure is performed via an exponent monomial potential, the system becomes partially reflective, preserving the particle’s translation and rotational motion. By increasing the exponent value, the stadium’s boundaries become rigid and the system’s dynamics reaches a chaotic regime. We set a leaking soft stadium family by opening a limited region located at some place of its basis’s boundary, throughout which the particles can leak out. This work is an extension of our recently reported paper on this matter. We chase the particle’s trajectory and focus on the stadium transient behavior by means of the statistical analysis of the survival probability on the marginal orbits that never leave the system, the so called bouncing ball orbits. We compare these family orbits with the billiard’s transient chaos orbits.

Onset of universality in the dynamical mixing of a pure state

We study the time dynamics of random density matrices generated by evolving the same pure state using a Gaussian orthogonal ensemble (GOE) of Hamiltonians. We show that the spectral statistics of the resulting mixed state is well described by random matrix theory (RMT) and undergoes a crossover from the Gaussian orthogonal ensemble to the Gaussian unitary ensemble (GUE) for short and large times, respectively. Using a semi-analytical treatment relying on a power series of the density matrix as a function of time, we find that the crossover occurs in a characteristic time that scales as the inverse of the dimension. The RMT results are contrasted with a paradigmatic model of many-body localization in the chaotic regime, where the GUE statistics is reached at large times, while for short times the statistics strongly depends on the peculiarity of the considered subspace.

Dynamics of a DC Motor-Driving Arm with a Circular Periodic Potential and DC/AC Voltage Input

In this paper, we investigate the dynamics of an electromechanical system consisting of a DC motor-driving arm within a circular periodic potential created by three permanent magnets. Two configurations of the circular potential appear when one varies the positions of the magnets and the length of the DC motor, respectively. Two different forms of input signal are used: DC and AC voltage sources. For each case, conditions under which the mechanical arm can perform a complete rotation are obtained. Under the DC voltage excitation, the arm oscillates and then is stabilized at an equilibrium position for a DC voltage lower than a critical value [Formula: see text]. When the DC voltage is higher than the critical value [Formula: see text], the arm performs large amplitude motions (complete rotation). Submitted to an AC voltage with amplitude lower than a critical value, the mechanical arm exhibits sinusoidal oscillations around the equilibrium position [Formula: see text] with amplitudes less than one turn. Angular oscillations with amplitudes greater than one turn are observed when the voltage amplitude is higher than the critical value. Bifurcation diagrams show that the simple system can enter chaotic regime with the amplitudes of angular oscillations varying erratically from small to high values.

From chaos to stability in soliton mode-locked fibre laser system

Intracavity energy rate in a soliton mode-locked fibre laser is derived by solving the Haus master equation. The influence of net gain, absorber response, saturation energy, nonlinearity and absorption are investigated on stable/unstable states. Intracavity modes include the zeroth, first and higher order solitons. Accordingly, chaotic regime as well as breather modes is recognized as a conventional intracavity state. However, tuning the control parameters also results in a reverse bifurcation and thus returning to a stable state. Accordingly, a chaos-based encryption/decryption system is proposed taking the advantage of using a single-side control process; both the encryption and decryption procedures can be achieved by one of the actions of increasing/decreasing the control parameters.

Investigating the Cocaine-induced Reduction of Potassium Current on the Generation of Action Potentials Using a Computational Model

Introduction: Drugs of abuse, including cocaine, affect different brain regions and lead to pathological memories. These abnormal memories may occur due to the changes in synaptic transmissions or variations in synaptic properties of neurons. It has been shown that cocaine inhibits delayed rectifying potassium currents in affected regions of the brain and can have a role in the formation of pathological memories. Purpose: This study investigates how the change in the conductance of delayed rectifying potassium channels can affect the produced action potentials using a computational model. Methods: We present a computational model with different channels and receptors, including sodium, potassium, calcium, NMDARs, and AMPARs, which can produce burst-type action potentials. In the simulations, by changing the delayed rectifying potassium conductance bifurcation diagram is calculated. Conclusion: Results show that for a specific range of potassium conductance, a chaotic regime emerges in produced action potentials. These chaotic oscillations may play a role in inducing abnormal memories.