Born in 1940 in Moscow, USSR, Valery I. Klyatskin received his secondary education at school in Tbilisi, Georgia, finishing in 1957. Seven years later he graduated from Moscow Institute of Physics and Technology (FIZTEX), whereupon he took up postgraduate studies at the Institute of Atmospheric Physics USSR Academy of Sciences, Moscow gaining the degree of Candidate of Physical and Mathematical Sciences (Ph.D) in 1968. He then continued at the Institute as a researcher, until 1978, when he was appointed as Head of the Wave Process Department at the Pacific Oceanological Institute of the USSR Academy of Sciences, based in Vladivostok. In 1992 Valery I. Klyatskin returned to Institute of Atmospheric Physics Russian Academy of Sciences, Moscow when he was appointed to his present position as Chief Scientist. At the same time he is Chief Scientific Consultant of Pacific Oceanological Institute Russian Academy of Sciences, Vladivostok. In 1977 he obtained a doctorate in Physical and Mathematical Sciences and in 1988 became Research Professor of Theoretical and Mathematical Physics, Russian Academy of Science.
Fluctuating parameters appear in a variety of physical systems and phenomena. They typically come either as random forces/sources, or advecting velocities, or media (material) parameters, like refraction index, conductivity, diffusivity, etc. The well known example of Brownian particle suspended in fluid and subjected to random molecular bombardment laid the foundation for modern stochastic calculus and statistical physics. Other important examples include turbulent transport and diffusion of particle-tracers (pollutants), or continuous densities (''oil slicks''), wave propagation and scattering in randomly inhomogeneous media, for instance light or sound propagating in the turbulent atmosphere.
Such models naturally render to statistical description, where the input parameters and solutions are expressed by random processes and fields. The fundamental problem of stochastic dynamics is to identify the essential characteristics of system (its state and evolution), and relate those to the input parameters of the system and initial data.
This raises a host of challenging mathematical issues. One could rarely solve such systems exactly (or approximately) in a closed analytic form, and their solutions depend in a complicated implicit manner on the initial-boundary data, forcing and system's (media) parameters . In mathematical terms such solution becomes a complicated "nonlinear functional" of random fields and processes.
Part I gives mathematical formulation for the basic physical models of transport, diffusion, propagation and develops some analytic tools.
Part II and III sets up and applies the techniques of variational calculus and stochastic analysis, like Fokker-Plank equation to those models, to produce exact or approximate solutions, or in worst case numeric procedures. The exposition is motivated and demonstrated with numerous examples.
Part IV takes up issues for the coherent phenomena in stochastic dynamical systems, described by ordinary and partial differential equations, like wave propagation in randomly layered media (localization), turbulent advection of passive tracers (clustering), wave propagation in disordered 2D and 3D media.
For the sake of reader I provide several appendixes (Part V) that give many technical mathematical details needed in the book.
I Dynamical description of stochastic systems 1 Examples, basic problems, peculiar features of solutions 2 Indicator function and Liouville equation II Stochastic equations 3 Random quantities, processes and fields 4 Correlation splitting5 General approaches to analyzing stochastic dynamic systems6 Stochastic equations with the Markovian fluctuations of parameters III Asymptotic and approximate methods for analyzing stochastic equations7 Gaussian random field delta-correlated in time (ordinary differential equations) 8 Methods for solving and analyzing the Fokker-Planck equation 9 Gaussian delta-correlated random field (causal integral equations)10 Diffusion approximationIV Coherent phenomena in stochastic dynamic systems 11 Passive tracer clustering and diffusion in random hydrodynamic flows12 Wave localization in randomly layered media13 Wave propagation in random inhomogeneous medium 14 Some problems of statistical hydrodynamics A Variation (functional) derivatives B Fundamental solutions of wave problems in empty and layered mediaB.1 The case of empty spaceB.2 The case of layered spaceC Imbedding method in boundary-value wave problems C.1 Boundary-value problems for ordinary differential equations C.2 Stationary boundary-value wave problems C.2.1 One-dimensional stationary boundary-value wave problems
