000			03962cam a22003254a 4500
001			16805820
005			20191116165745.0
008			110602s2012 enka b 001 0 eng
010			_a 2011023678
020			_a9780521853354 (hardback)
040			_aDLC
042			_apcc
050	0	0	_aQC174.85.S34 _bP78 2012
082	0	0	_a003 _223
084			_aSCI040000 _2bisacsh
100	1		_aPruessner, Gunnar, _d1973-
245	1	0	_aSelf-organised criticality : _btheory, models, and characterisation / _cGunnar Pruessner.
260			_aCambridge ; _aNew York : _bCambridge University Press, _c2012.
300			_axxii, 494 p. : _bill. ; _c26 cm.
504			_aIncludes bibliographical references (p. 398-458) and indexes.
505	8		_aMachine generated contents note: 1. Introduction; 2. Scaling; 3. Experiments and observations; 4. Deterministic sandpiles; 5. Dissipative models; 6. Stochastic sandpiles; 7. Numerical methods and data analysis; 8. Analytical results; 9. Mechanisms of SOC; 10. Summary and discussion; Index.
520			_a"Giving a detailed overview of the subject, this book takes in the results and methods that have arisen since the term 'self-organised criticality' was coined twenty years ago. Providing an overview of numerical and analytical methods, from their theoretical foundation to the actual application and implementation, the book is an easy access point to important results and sophisticated methods. Starting with the famous Bak-Tang-Wiesenfeld sandpile, ten key models are carefully defined, together with their results and applications. Comprehensive tables of numerical results are collected in one volume for the first time, making the information readily accessible to readers. Written for graduate students and practising researchers in a range of disciplines, from physics and mathematics to biology, sociology, finance, medicine and engineering, the book gives a practical, hands-on approach throughout. Methods and results are applied in ways that will relate to the reader's own research"-- _cProvided by publisher.
520			_a"When Bak, Tang, and Wiesenfeld (1987) coined the term Self-Organised Criticality (SOC), it was an explanation for an unexpected observation of scale invariance and at the same time, a programme of further research. Over the years it developed into a subject area which is concerned mostly with the analysis of computer models that display a form of generic scale invariance. The primacy of the computer model is manifest in the first publication and throughout the history of SOC, which evolved with and revolved around such computer models. That has led to a plethora of computer 'models', many of which are not intended to model much except themselves (also Gisiger, 2001), in the hope that they display a certain aspect of SOC in a particularly clear way. The question whether SOC exists is empty if SOC is merely the title for a certain class of computer models. In the following, the term SOC will therefore be used in its original meaning (Bak et al, 1987), to be assigned to systems with spatial degrees of freedom [which] naturally evolve into a self-organized critical point. Such behaviour is to be juxtaposed to the traditional notion of a phase transition, which is the singular, critical point in a phase diagram, where a system experiences a breakdown of symmetry and long-range spatial and in non-equilibrium, also temporal correlations, generally summarised as (power law) scaling (Widom, 1965a,b; Stanley, 1971)"-- _cProvided by publisher.
650		0	_aScaling laws (Statistical physics) _xComputer simulation.
650		0	_aSystem analysis.
650		7	_aSCIENCE / Mathematical Physics _2bisacsh.
906			_a7 _bcbc _corignew _d1 _eecip _f20 _gy-gencatlg
942			_2udc _cBK
999			_c27220 _d27220