000 04414nam a22005415i 4500
001 978-3-662-48410-4
003 DE-He213
005 20190213151235.0
007 cr nn 008mamaa
008 160303s2016 gw | s |||| 0|eng d
020 _a9783662484104
_9978-3-662-48410-4
024 7 _a10.1007/978-3-662-48410-4
_2doi
050 4 _aQC174.7-175.36
072 7 _aPBWR
_2bicssc
072 7 _aSCI012000
_2bisacsh
072 7 _aPBWR
_2thema
072 7 _aPHDT
_2thema
082 0 4 _a621
_223
245 1 0 _aChaos Detection and Predictability
_h[electronic resource] /
_cedited by Charalampos (Haris) Skokos, Georg A. Gottwald, Jacques Laskar.
264 1 _aBerlin, Heidelberg :
_bSpringer Berlin Heidelberg :
_bImprint: Springer,
_c2016.
300 _aXI, 269 p. 122 illus., 44 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aLecture Notes in Physics,
_x0075-8450 ;
_v915
505 0 _aEstimating Lyapunov exponents from time series -- Theory and applications of the fast Lyapunov Indicator (FLI) method -- Theory and applications of the Orthogonal Fast Lyapunov Indicator (OFLI and OFLI2) methods -- Theory and applications of the Mean Exponential Growth factor of Nearby Orbits (MEGNO) method -- The Smaller (SALI) and the Generalized (GALI) Alignment Indices: Efficient Methods of Chaos Detection -- The Relative Lyapunov Indicators: Theory and Application to Dynamical Astronomy -- The 0-1 Test for Chaos: A review.
520 _aDistinguishing chaoticity from regularity in deterministic dynamical systems and specifying the subspace of the phase space in which instabilities are expected to occur is of utmost importance in as disparate areas as astronomy, particle physics and climate dynamics. To address these issues there exists a plethora of methods for chaos detection and predictability. The most commonly employed technique for investigating chaotic dynamics, i.e. the computation of Lyapunov exponents, however, may suffer a number of problems and drawbacks, for example when applied to noisy experimental data. In the last two decades, several novel methods have been developed for the fast and reliable determination of the regular or chaotic nature of orbits, aimed at overcoming the shortcomings of more traditional techniques. This set of lecture notes and tutorial reviews serves as an introduction to and overview of modern chaos detection and predictability techniques for graduate students and non-specialists. The book covers theoretical and computational aspects of traditional methods to calculate Lyapunov exponents, as well as of modern techniques like the Fast (FLI), the Orthogonal (OFLI) and the Relative (RLI) Lyapunov Indicators, the Mean Exponential Growth factor of Nearby Orbits (MEGNO), the Smaller (SALI) and the Generalized (GALI) Alignment Index and the ‘0-1’ test for chaos.
650 0 _aMathematical physics.
650 0 _aAstrophysics.
650 1 4 _aApplications of Nonlinear Dynamics and Chaos Theory.
_0http://scigraph.springernature.com/things/product-market-codes/P33020
650 2 4 _aMathematical Methods in Physics.
_0http://scigraph.springernature.com/things/product-market-codes/P19013
650 2 4 _aMathematical Applications in the Physical Sciences.
_0http://scigraph.springernature.com/things/product-market-codes/M13120
650 2 4 _aSpace Sciences (including Extraterrestrial Physics, Space Exploration and Astronautics).
_0http://scigraph.springernature.com/things/product-market-codes/P22030
650 2 4 _aEarth System Sciences.
_0http://scigraph.springernature.com/things/product-market-codes/G35000
700 1 _aSkokos, Charalampos (Haris).
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aGottwald, Georg A.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
700 1 _aLaskar, Jacques.
_eeditor.
_4edt
_4http://id.loc.gov/vocabulary/relators/edt
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9783662484081
776 0 8 _iPrinted edition:
_z9783662484098
830 0 _aLecture Notes in Physics,
_x0075-8450 ;
_v915
856 4 0 _uhttps://doi.org/10.1007/978-3-662-48410-4
912 _aZDB-2-PHA
912 _aZDB-2-LNP
999 _c9995
_d9995