000 03754nam a22005295i 4500
001 vtls000541678
003 RU-ToGU
005 20210922082153.0
007 cr nn 008mamaa
008 160915s2014 xxu| s |||| 0|eng d
020 _a9781493913237
_9978-1-4939-1323-7
024 7 _a10.1007/978-1-4939-1323-7
_2doi
035 _ato000541678
040 _aSpringer
_cSpringer
_dRU-ToGU
050 4 _aQA273.A1-274.9
050 4 _aQA274-274.9
072 7 _aPBT
_2bicssc
072 7 _aPBWL
_2bicssc
072 7 _aMAT029000
_2bisacsh
082 0 4 _a519.2
_223
100 1 _aPavliotis, Grigorios A.
_eauthor.
_9309146
245 1 0 _aStochastic Processes and Applications
_helectronic resource
_bDiffusion Processes, the Fokker-Planck and Langevin Equations /
_cby Grigorios A. Pavliotis.
260 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2014.
300 _aXIII, 339 p. 29 illus., 23 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aTexts in Applied Mathematics,
_x0939-2475 ;
_v60
505 0 _aStochastic Processes -- Diffusion Processes -- Introduction to Stochastic Differential Equations -- The Fokker-Planck Equation -- Modelling with Stochastic Differential Equations -- The Langevin Equation -- Exit Problems for Diffusions -- Derivation of the Langevin Equation -- Linear Response Theory -- Appendix A Frequently Used Notations -- Appendix B Elements of Probability Theory.
520 _aThis book presents various results and techniques from the theory of stochastic processes that are useful in the study of stochastic problems in the natural sciences. The main focus is analytical methods, although numerical methods and statistical inference methodologies for studying diffusion processes are also presented. The goal is the development of techniques that are applicable to a wide variety of stochastic models that appear in physics, chemistry and other natural sciences. Applications such as stochastic resonance, Brownian motion in periodic potentials and Brownian motors are studied and the connection between diffusion processes and time-dependent statistical mechanics is elucidated.                 The book contains a large number of illustrations, examples, and exercises. It will be useful for graduate-level courses on stochastic processes for students in applied mathematics, physics and engineering. Many of the topics covered in this book (reversible diffusions, convergence to equilibrium for diffusion processes, inference methods for stochastic differential equations, derivation of the generalized Langevin equation, exit time problems) cannot be easily found in textbook form and will be useful to both researchers and students interested in the applications of stochastic processes.
650 0 _amathematics.
_9566183
650 0 _aDifferential equations, partial.
_9303599
650 0 _aDistribution (Probability theory).
_9303731
650 0 _aMechanics, applied.
_9304329
650 1 4 _aMathematics.
_9566184
650 2 4 _aProbability Theory and Stochastic Processes.
_9303734
650 2 4 _aPartial Differential Equations.
_9303602
650 2 4 _aTheoretical and Applied Mechanics.
_9304330
650 2 4 _aTheoretical, Mathematical and Computational Physics.
_9410498
710 2 _aSpringerLink (Online service)
_9143950
773 0 _tSpringer eBooks
830 0 _aTexts in Applied Mathematics,
_9298055
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4939-1323-7
912 _aZDB-2-SMA
999 _c399529