Adiabatic nonlinear waves with trapped particles: II. Wave dispersion

A general nonlinear dispersion relation is derived in a nondifferential form for an adiabatic sinusoidal Langmuir wave in collisionless plasma, allowing for an arbitrary distribution of trapped electrons. The linear dielectric function is generalized, and the nonlinear kinetic frequency shift $\omega_{\rm NL}$ is found analytically as a function of the wave amplitude $a$. Smooth distributions yield $\omega_{\rm NL} \propto \sqrt{a}$, as usual. However, beam-like distributions of trapped electrons result in different power laws, or even a logarithmic nonlinearity, which are derived as asymptotic limits of the same dispersion relation. Such beams are formed whenever the phase velocity changes, because the trapped distribution is in autoresonance and thus evolves differently from the passing distribution. Hence, even adiabatic $\omega_{\rm NL}(a)$ is generally nonlocal.Comment: submitted together with Papers I and II

Axiomatic geometrical optics, Abraham-Minkowski controversy, and photon properties derived classically

By restating geometrical optics within the field-theoretical approach, the classical concept of a photon (and, more generally, any elementary excitation) in arbitrary dispersive medium is introduced, and photon properties are calculated unambiguously. In particular, the canonical and kinetic momenta carried by a photon, as well as the two corresponding energy-momentum tensors of a wave, are derived from first principles of Lagrangian mechanics. As an example application of this formalism, the Abraham-Minkowski controversy pertaining to the definitions of these quantities is resolved for linear waves of arbitrary nature, and corrections to the traditional formulas for the photon kinetic energy-momentum are found. Several other applications of axiomatic geometrical optics to electromagnetic waves are also presented

Interpretation of the Veiling of the Photospheric Spectrum for T Tauri Stars in Terms of an Accretion Model

The problem on heating the atmospheres of T Tauri stars by radiation from an accretion shock has been solved. The structure and radiation spectrum of the emerging so-called hot spot have been calculated in the LTE approximation. The emission not only in continuum but also in lines has been taken into account for the first time when calculating the spot spectrum. Comparison with observations has shown that the strongest of these lines manifest themselves as narrow components of helium and metal emission lines, while the weaker ones decrease significantly the depth of photospheric absorption lines, although until now, this effect has been thought to be due to the emission continuum alone. The veiling by lines changes the depth of different photospheric lines to a very different degree even within a narrow spectral range. Therefore, the nonmonotonic wavelength dependence of the degree of veiling r found for some CTTS does not suggest a nontrivial spectral energy distribution of the veiling continuum. In general, it makes sense to specify the degree of veiling r only by providing the set of photospheric lines from which this quantity was determined. We show that taking into account the contribution of lines to the veiling of the photospheric spectrum can cause the existing estimates of the accretion rate onto T Tauri stars to decrease by several times, with this being also true for stars with a comparatively weakly veiled spectrum. Neglecting the contribution of lines to the veiling can also lead to appreciable errors in determining the effective temperature, interstellar extinction, radial velocity, and vsin(i)

Post-AGB candidate IRAS 02143+5852: Cepheid-like variability, three-layer circumstellar dust envelope and spectral features

We present the results of multicolour $UBVR_{\text{C}}I_{\text{C}}JHK$ photometry, spectroscopic analysis and spectral energy distribution (SED) modelling for the post-AGB candidate IRAS 02143+5852. We detected Cepheid-like light variations with the full peak-to-peak amplitude $\Delta V\sim0.9$ mag and the pulsation period of about 24.9 d. The phased light curves appeared typical for the W Vir Cepheids. The period-luminosity relation for the Type II Cepheids yielded the luminosity $\log L/L_{\odot}\sim2.95$. From a low-resolution spectrum, obtained at maximum brightness, the following atmospheric parameters were determined: $T_\text{eff}\sim7400$ K and $\log g\sim1.38$. This spectrum contains the emission lines H$\alpha$, BaII $\lambda$6496.9, HeI $\lambda$10830 and Pa$\beta$. Spectral monitoring performed in 2019-2021 showed a significant change in the H$\alpha$ profile and appearance of CH and CN molecular bands with pulsation phase. The metal lines are weak. Unlike typical W Vir variables, the star shows a strong excess of infrared radiation associated with the presence of a heavy dust envelope around the star. We modelled the SED using our photometry and archival data from different catalogues and determined the parameters of the circumstellar dust envelope. We conclude that IRAS~02143+5852 is a low-luminosity analogue of dusty RV Tau stars.Comment: 21 pages, 19 figures, 9 tables, accepted for publication in MNRA

Time-dependent ARMA modeling of genomic sequences

<p>Abstract</p> <p>Background</p> <p>Over the past decade, many investigators have used sophisticated time series tools for the analysis of genomic sequences. Specifically, the correlation of the nucleotide chain has been studied by examining the properties of the power spectrum. The main limitation of the power spectrum is that it is restricted to stationary time series. However, it has been observed over the past decade that genomic sequences exhibit non-stationary statistical behavior. Standard statistical tests have been used to verify that the genomic sequences are indeed not stationary. More recent analysis of genomic data has relied on time-varying power spectral methods to capture the statistical characteristics of genomic sequences. Techniques such as the evolutionary spectrum and evolutionary periodogram have been successful in extracting the time-varying correlation structure. The main difficulty in using time-varying spectral methods is that they are extremely unstable. Large deviations in the correlation structure results from very minor perturbations in the genomic data and experimental procedure. A fundamental new approach is needed in order to provide a stable platform for the non-stationary statistical analysis of genomic sequences.</p> <p>Results</p> <p>In this paper, we propose to model non-stationary genomic sequences by a time-dependent autoregressive moving average (TD-ARMA) process. The model is based on a classical ARMA process whose coefficients are allowed to vary with time. A series expansion of the time-varying coefficients is used to form a generalized Yule-Walker-type system of equations. A recursive least-squares algorithm is subsequently used to estimate the time-dependent coefficients of the model. The non-stationary parameters estimated are used as a basis for statistical inference and biophysical interpretation of genomic data. In particular, we rely on the TD-ARMA model of genomic sequences to investigate the statistical properties and differentiate between coding and non-coding regions in the nucleotide chain. Specifically, we define a quantitative measure of randomness to assess how far a process deviates from white noise. Our simulation results on various gene sequences show that both the coding and non-coding regions are non-random. However, coding sequences are "whiter" than non-coding sequences as attested by a higher index of randomness.</p> <p>Conclusion</p> <p>We demonstrate that the proposed TD-ARMA model can be used to provide a stable time series tool for the analysis of non-stationary genomic sequences. The estimated time-varying coefficients are used to define an index of randomness, in order to assess the statistical correlations in coding and non-coding DNA sequences. It turns out that the statistical differences between coding and non-coding sequences are more subtle than previously thought using stationary analysis tools: Both coding and non-coding sequences exhibit statistical correlations, with the coding regions being "whiter" than the non-coding regions. These results corroborate the evolutionary periodogram analysis of genomic sequences and revoke the stationary analysis' conclusion that coding DNA behaves like random sequences.</p