Information entropy and temperature of binary Markov chains.

We propose two different approaches for introducing the information temperature of binary Nth-order Markov chains. The first approach is based on a comparison of Markov sequences with equilibrium Ising chains at given temperatures. The second approach uses probabilities of finite-length subsequences of symbols occurring, which determine their entropies.

Continuous stochastic processes with nonlocal memory.

We study the non-Markovian random continuous processes described by the Mori-Zwanzig equation. As a starting point, we use the Markovian Gaussian Ornstein-Uhlenbeck process and introduce an integral memory term depending on the past of the process into an expression for the higher-order transition probability function and the stochastic differential equation. We show that the proposed processes can be considered as continuous-time interpolations of discrete-time higher-order autoregressive sequences.

Decomposition of conditional probability for high-order symbolic Markov chains.

The main goal of this paper is to develop an estimate for the conditional probability function of random stationary ergodic symbolic sequences with elements belonging to a finite alphabet. We elaborate on a decomposition procedure for the conditional probability function of sequences considered to be high-order Markov chains. We represent the conditional probability function as the sum of multilinear memory function monomials of different orders (from zero up to the chain order).

Interaction between a tubular beam of charged particles and a dispersive metamaterial of cylindrical configuration.

The interaction between a tubular beam of charged particles and a dispersive metamaterial of cylindrical configuration has been investigated theoretically. This metamaterial may have negative permittivity and negative permeability simultaneously over a certain frequency range where it behaves like a left-handed metamaterial. The dispersion equation for the eigenmodes spectra of a metamaterial and the coupled modes spectra of the system have been derived and numerically analyzed.

Entropy and long-range memory in random symbolic additive Markov chains.

The goal of this paper is to develop an estimate for the entropy of random symbolic sequences with elements belonging to a finite alphabet. As a plausible model, we use the high-order additive stationary ergodic Markov chain with long-range memory. Supposing that the correlations between random elements of the chain are weak, we express the conditional entropy of the sequence by means of the symbolic pair correlation function.

Textures on the surface of BSA films with different concentrations of sodium halides and water state in solution.

The formation of the textures on the surface of the films from the solutions of bovine serum albumin (BSA) with sodium halides (NaF, NaCl, and NaBr) of various concentrations was studied. The formation of symmetric zigzag textures on the surface of BSA films (Cryst Eng 3:173-194, 2000) in the presence of sodium halides depends on the conformational state of the protein globule. Thermal denaturation of BSA also did not allow to form zigzag textures on the surface of the films.

Iterative method for generating correlated binary sequences.

We propose an efficient iterative method for generating random correlated binary sequences with a prescribed correlation function. The method is based on consecutive linear modulations of an initially uncorrelated sequence into a correlated one. Each step of modulation increases the correlations until the desired level has been reached.

Entropy of finite random binary sequences with weak long-range correlations.

We study the N-step binary stationary ergodic Markov chain and analyze its differential entropy. Supposing that the correlations are weak we express the conditional probability function of the chain through the pair correlation function and represent the entropy as a functional of the pair correlator. Since the model uses the two-point correlators instead of the block probability, it makes it possible to calculate the entropy of strings at much longer distances than using standard methods.

Entropy and long-range correlations in DNA sequences.

We analyze the structure of DNA molecules of different organisms by using the additive Markov chain approach. Transforming nucleotide sequences into binary strings, we perform statistical analysis of the corresponding "texts". We develop the theory of N-step additive binary stationary ergodic Markov chains and analyze their differential entropy.

Lamb-Dicke spectroscopy of atoms in a hollow-core photonic crystal fibre.

Unlike photons, which are conveniently handled by mirrors and optical fibres without loss of coherence, atoms lose their coherence via atom-atom and atom-wall interactions. This decoherence of atoms deteriorates the performance of atomic clocks and magnetometers, and also hinders their miniaturization. Here we report a novel platform for precision spectroscopy.

Conversion of terahertz wave polarization at the boundary of a layered superconductor due to the resonance excitation of oblique surface waves.

We predict a complete TM↔TE transformation of the polarization of terahertz electromagnetic waves reflected from a strongly anisotropic boundary of a layered superconductor. We consider the case when the wave is incident on the superconductor from a dielectric prism separated from the sample by a thin vacuum gap. The physical origin of the predicted phenomenon is similar to the Wood anomalies known in optics and is related to the resonance excitation of the oblique surface waves.

Design of specific gratings operating under surface plasmon-polariton resonance.

We present a productive method of designing specific diffraction gratings that ensure some predetermined energy redistributions between outgoing waves. It is based on the analytical solution of the direct and reverse diffraction problems under surface plasmon-polariton resonance and is supported by strict numerical calculations.

Extremely short-length surface plasmon resonance devices.

The impact of the system design on the control of coupling between planar waveguide modes and surface plasmon polaritons (SPP) is analyzed. We examine how the efficiency of the coupling can be enhanced by an appropriate dimensioning of a multi-layer device structure without using additional gratings. We demonstrate that by proper design the length of the device can be dramatically reduced through fabrication a surface plasmon resonance sensor based on the SPP-photon transformation rather then on SPP dissipation.

Rank distributions of words in correlated symbolic systems and the Zipf law.

The binary many-step Markov chain with the step-like memory function is considered as a model for the analysis of rank distributions of words in correlated stochastic symbolic systems. We prove that this distribution obeys the power law with the exponent of the order of unity in the case of rather strong persistent correlations. The Zipf law is shown to be valid for the rank distribution of words with lengths about and shorter than the correlation length in the Markov sequence.

Competition between two kinds of correlations in literary texts.

A theory of additive Markov chains with long-range memory is used to describe the correlation properties of coarse-grained literary texts. The complex structure of the correlations in the texts is revealed. Anti-persistent correlations at small distances, L approximately < 300, and persistent ones at L approximately > 300 define this non-trivial structure.

Symbolic stochastic dynamical systems viewed as binary N-step Markov chains.

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In the model, the conditional probability that the ith symbol in the chain equals zero (or unity) is a linear function of the number of unities among the preceding N symbols. The correlation and distribution functions as well as the variance of the number of symbols in the words of arbitrary length L are obtained analytically and numerically.

Binary N-step Markov chains and long-range correlated systems.

A theory of systems with long-range correlations based on the consideration of binary N-step Markov chains is developed. In our model, the conditional probability that the ith symbol in the chain equals zero (or unity) is a linear function of the number of unities among the preceding N symbols. The correlation and distribution functions as well as the variance of number of symbols in the words of arbitrary length L are obtained analytically and numerically.