The European Physical Journal Plus最新文献

In this paper, we report the dynamical evolution of a second-order non-autonomous electronic circuit, namely, the Murali-Lakshmanan-Chua (MLC) circuit subjected to square wave excitation. The dynamics of the circuit is studied by varying the amplitude, duty cycle of the square wave and the DC offset voltage through phase-portraits, power spectrum, one-parameter bifurcation diagrams, Lyapunov exponents and two-phase diagrams. Experimentally observed oscilloscope images and power spectra are presented to confirm the numerical studies. With the amplitude, duty cycle of the square wave and DC offset voltage as control parameters, a rich variety of dynamical phenomena such as chaos, dynamical symmetry, hysteresis, period-doubling structures are observed and reported. Finally, analytical solutions are developed for the square wave forced system and the multistability behavior observed through numerical and experimental studies are validated using the analytical results.

Formation of a diurnal ocean mixed layer (OML) as one of the nonlinear dynamic processes has been investigated by using large eddy simulation (LES) in previous studies, but the effect of different terms of heat fluxes on the OML has not been discussed separately so far. In this paper, the effect of air–sea interaction on the OML was evaluated by large eddy simulation (LES) in the presence or absence of Langmuir circulation (LC), wave breaking (WB), sensible heat flux (SHF), long wave radiation (LWR), latent heat flux, and insolation or short wave radiation for the first time. We used average climatic parameters for the Arabian Sea during the summer monsoon to define the ideal case of simulation. The area was simulated for 33.5 h, and the results of the first 9.5 h were ignored. The variation of different simulated parameters was investigated during a 24-h period. The results of the present study showed that since the SHF and LWR values were omissible, the effects of these two fluxes on many OMD properties are negligible. We also observed that SHF had a reversible effect because of its positive and negative values during the defined timeframe of the simulation. In addition, the maximum impression of heat fluxes was seen in the presence of evaporation and insolation. However, the evaporation in the absence of LC and WB caused a slight decrease in velocity shear and shear production and an increase in the dissipation rate (approximately double), pressure transport, and TKE transport. Moreover, in the presence of evaporation, the presence or absence of LC and WB did not affect the profile of turbulent heat flux. Evaporation did not change the Stokes production as well. The results of this study show that the effect of solar insolation on OML is significant and even more effective than surface evaporation. It reduced TKE and causes most of the diurnal variation in TKE. Furthermore, significant changes in the TKE profile are controlled by the shear production profile.

In this article, I demonstrate a new method to derive Jacobi metrics from Randers–Finsler metrics by introducing a more generalised approach to Hamiltonian mechanics for such spacetimes and discuss the related applications and properties. I introduce Hamiltonian mechanics with the constraint for relativistic momentum, including a modification for null curves and two applications as exercises: derivation of a relativistic harmonic oscillator and analysis of Schwarzschild Randers–Finsler metric. Then I describe the main application for constraint mechanics in this article: a new derivation of Jacobi metric for time-like and null curves, comparing the latter with optical metrics. After that, I discuss frame dragging with the Jacobi metric and two applications for Randers–Finsler metrics: an alternative to Eisenhart lift, and different metrics that share the same Jacobi metric.

This study explores the application of random matrix theory (RMT) and machine learning (ML) in the analysis of financial time-series data and market volatility. RMT is used to quantify the level of chaos in financial data, while ML enhances prediction accuracy. We analyze financial data from Bank of America, Bank of China, and Royal Bank of Canada, focusing on spectral statistics and the nearest-neighbor spacing distribution. Using maximum likelihood estimation, we measure the degree of chaos and predict market volatility across daily, weekly, and monthly scales. Our results show that the spectral characteristics of Bank of America and Bank of China align with a Poisson distribution, while the Royal Bank of Canada exhibits a mix of regularity and chaos. Incorporating unfolded prices into the ML model significantly improves predictive accuracy, with the lowest root-mean-square error observed in the Bank of China dataset. Finally, the Cramer–Rao lower bound is applied to minimize estimator variance, confirming the effectiveness of our combined RMT and ML approach. This method bridges statistical physics and advanced data-driven modeling for improved financial predictions.

Factorizing multiparameter densities are proposed for the analytic continuum modeling of human life tables. The formalism is developed based on mortality data of the female, male, and total population of France for the year 2021. The data sets cover the age range from birth up to 110 years. The cumulative hazard function is a multiply broken exponential density, admitting a differential hazard rate capable of describing the observed late-life mortality deceleration and exhibiting exponential asymptotic increase rather than a mortality plateau. The nonlinear least-squares regression is performed with the survival function, which admits double-exponential decay in the high-age limit. The minimization of the multiparametric least-squares functional is facilitated by invoking the product structure of the cumulative hazard, the number of factors and fitting parameters being adapted to the data set. More generally, new techniques are developed to deal with probability densities exhibiting a nonlinear multiparameter dependence. Such densities are increasingly needed to represent extended data sets, as exemplified by recent mortality data across the tree of life. In the case of the mentioned human life tables, the residual deviations of the regressed survival functions and cumulative distributions from the data points are within at most two percent, uniformly over the entire empirical age range. The analytic probability density and age-conditioned survival probabilities are calculated for the total population and the female and male cohorts. The lifetime evolution of the cumulative and differential female/male hazard ratios is studied, from birth up to the asymptotic high-age regime.

In a twisted graphene on hexagonal boron nitride, the presence of a gap and the breaking of the symmetry between carbon sublattices lead to multicomponent fractional quantum Hall effect (FQHE) due to the electrons’ correlation. Here we report on the FQHE at filling factors ν = k/2 and ν = k/3 with ν > 1, and on the composite fermions at in the ν < 1 lowest Landau level ν = 4/5, 5/7 and 2/3. These fractional states can be described with a partons model, in which the electron is broken down into sub-particles each one residing in an integer quantum Hall effect state; partons are fictitious particles that, glued back together, recover the physical electrons. The parton states host exotic anyons that could potentially form building blocks of a fault-tolerant topological quantum computer.

We numerically investigate a geographical d-dimensional ((d=1,2,3,4)) Bianconi–Barabási-like model, characterized by preferential attachment growth mechanisms influenced by Euclidean distances and weighted edges. The weights of the edges follow a predetermined random probability distribution. This model is implemented through a straightforward energy-driven dynamics and exhibits the distribution of ’energy’ per site in its quasi-stationary state. Across all networks generated by this model, we observe q-exponential energy distributions over the entire parameter space, which exhibits that this model belongs to the realm of nonadditive q-entropies. Additionally, the time evolution of the site energies, characterized by the dynamic (beta _{varepsilon }-)exponent, is analyzed.

The paper aims to establish diverse types of the soliton solutions for the integrable Kuralay equations to discuss the integrable motion of the induced space curves by these equations. The solitons arising from the integrable Kuralay equations are considered by tall superiority and qualitative studies for many effective phenomena in various fields such as ferromagnetic materials, nonlinear optics and optical fibers. There are two various schemes are suggested to establish these diverse types of solitons that arise from this model, namely the extended simple equation method and the Paul-Painleve approach method. New diverse types of the soliton solutions that appear in forms of periodic trigonometric function soliton solutions, parabolic function soliton solutions, singular soliton solutions, W-like soliton solutions and M-like soliton solutions have been documented. The suggested techniques are used for the first time for this target. The achieved soliton solutions will offer a rich podium to study the nonlinear spin dynamics in magnetic materials. Moreover, we will construct the numerical solutions for all achieved soliton solutions by using the differential transform methods. The comparison between the new achieved soliton solutions with its consistent numerical solutions has been documented.