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Disrupted Networks: From Physics To Climate Change [Kõva köide]

(Duke Univ, Usa), (Army Research Office, Usa)
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This book provides a lens through which modern society is shown to depend on complex networks for its stability. One way to achieve this understanding is through the development of a new kind of science, one that is not explicitly dependent on the traditional disciplines of biology, economics, physics, sociology and so on; a science of networks. This text reviews, in non-mathematical language, what we know about the development of science in the twenty-first century and how that knowledge influences our world. In addition, it distinguishes the two-tiered science of the twentieth century, based on experiment and theory (data and knowledge) from the three-tiered science of experiment, computation and theory (data, information and knowledge) of the twenty-first century in everything from psychophysics to climate change.

This book is unique in that it addresses two parallel lines of argument. The first line is general and intended for a lay audience, but one that is scientifically sophisticated, explaining how the paradigm of science has been changed to accommodate the computer and large-scale computation. The second line of argument addresses what some consider the seminal scientific problem of climate change. The authors show how a misunderstanding of the change in the scientific paradigm has led to a misunderstanding of complex phenomena in general, and the causes of global warming in particular

This book provides a lens through which modern society is shown to depend on complex networks for its stability. One way to achieve this understanding is through the development of a new kind of science, one that is not explicitly dependent on the traditional disciplines of biology, economics, physics, sociology and so on; a science of networks. This text reviews, in non-mathematical language, what we know about the development of science in the twenty-first century and how that knowledge influences our world. In addition, it distinguishes the two-tiered science of the twentieth century, based on experiment and theory (data and knowledge) from the three-tiered science of experiment, computation and theory (data, information and knowledge) of the twenty-first century in everything from psychophysics to climate change.This book is unique in that it addresses two parallel lines of argument. The first line is general and intended for a lay audience, but one that is scientifically sophisticated, explaining how the paradigm of science has been changed to accommodate the computer and large-scale computation. The second line of argument addresses what some consider the seminal scientific problem of climate change. The authors show how a misunderstanding of the change in the scientific paradigm has led to a misunderstanding in complex phenomena in general, and the causes of global warming in particular.
Preface v
1 Why a Science of Networks?
1(68)
1.1 The science of data, information and knowledge
4(7)
1.2 The face of science
11(29)
1.2.1 Qualitative and quantitative
17(7)
1.2.2 What is a complex network?
24(3)
1.2.3 A taxonomy of complex networks
27(7)
1.2.4 The three-tiers of science
34(6)
1.3 Framing the climate change debate
40(29)
1.3.1 The Intergovernmental Panel on Climate Change
43(8)
1.3.2 Climate topologies in comparison
51(18)
2 Data
69(66)
2.1 Physics as a scientific paradigm
72(24)
2.1.1 Psychophysics quantifies individuals
78(5)
2.1.2 Sociophysics quantifies groups
83(6)
2.1.3 Econophysics quantifies exchange
89(5)
2.1.4 Biophysics quantifies life
94(2)
2.2 Time series
96(9)
2.2.1 Measures and data
97(3)
2.2.2 Representing the data
100(5)
2.3 Fractal statistics
105(7)
2.4 Solar and climate variability
112(23)
2.4.1 Solar data
115(10)
2.4.2 Temperature data
125(10)
3 Information
135(62)
3.1 Entropy
138(13)
3.1.1 Wiener-Shannon Information
143(3)
3.1.2 The Physicality of Information
146(5)
3.2 Pareto's Law
151(29)
3.2.1 Economic networks
157(5)
3.2.2 Science networks
162(8)
3.2.3 Information networks
170(2)
3.2.4 Social-communication networks
172(7)
3.2.5 Networks of neurons
179(1)
3.3 Entropy and data processing
180(14)
3.3.1 Diffusion of Information
182(6)
3.3.2 Diffusion entropy analysis
188(6)
3.4 Sun-climate complexity matching?
194(3)
4 Knowledge
197(56)
4.1 Mathematics enables knowledge
200(3)
4.2 The Pareto Principle: the 80/20 rule
203(3)
4.3 What we know about complex networks
206(20)
4.3.1 Random networks
211(4)
4.3.2 Scale-free networks and the STDs epidemic
215(7)
4.3.3 Scale-rich networks
222(4)
4.4 The Sun-climate linking: an ongoing debate
226(27)
4.4.1 The Hockey Stick graph and the climate models
228(9)
4.4.2 The 11-year solar cycle signature on climate: models vs. data
237(7)
4.4.3 The phenomenological reconstruction of the solar signature on climate
244(9)
5 A World of Disrupted Networks
253(10)
Glossary 263(8)
Bibliography 271(18)
Index 289