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The availability of large data sets has allowed researchers to
uncover complex properties such as large-scale fluctuations and
heterogeneities in many networks, leading to the breakdown of
standard theoretical frameworks and models. Until recently these
systems were considered as haphazard sets of points and
connections. Recent advances have generated a vigorous research
effort in understanding the effect of complex connectivity patterns
on dynamical phenomena. This book presents a comprehensive account
of these effects. A vast number of systems, from the brain to
ecosystems, power grids and the internet, can be represented as
large complex networks. This book will interest graduate students
and researchers in many disciplines, from physics and statistical
mechanics to mathematical biology and information science. Its
modular approach allows readers to readily access the sections of
most interest to them, and complicated maths is avoided so the text
can be easily followed by non-experts in the subject.
This book provides a complete introduction into spatial networks.
It offers the mathematical tools needed to characterize these
structures and how they evolve in time and presents the most
important models of spatial networks. The book puts a special
emphasis on analyzing complex systems which are organized under the
form of networks where nodes and edges are embedded in space. In
these networks, space is relevant, and topology alone does not
contain all the information. Characterizing and understanding the
structure and the evolution of spatial networks is thus crucial for
many different fields, ranging from urbanism to epidemiology. This
subject is therefore at the crossroad of many fields and is of
potential interest to a broad audience comprising physicists,
mathematicians, engineers, geographers or urbanists. In this book,
the author has expanded his previous book ("Morphogenesis of
Spatial Networks") to serve as a textbook and reference on this
topic for a wide range of students and professional researchers.
With over half of the world's population now living in urban areas,
the ability to model and understand the structure and dynamics of
cities is becoming increasingly valuable. Combining new data with
tools and concepts from statistical physics and urban economics,
this book presents a modern and interdisciplinary perspective on
cities and urban systems. Both empirical observations and
theoretical approaches are critically reviewed, with particular
emphasis placed on derivations of classical models and results,
along with analysis of their limits and validity. Key aspects of
cities are thoroughly analyzed, including mobility patterns, the
impact of multimodality, the coupling between different
transportation modes, the evolution of infrastructure networks,
spatial and social organisation, and interactions between cities.
Drawing upon knowledge and methods from areas of mathematics,
physics, economics and geography, the resulting quantitative
description of cities will be of interest to all those studying and
researching how to model these complex systems.
The availability of large data sets has allowed researchers to
uncover complex properties such as large-scale fluctuations and
heterogeneities in many networks, leading to the breakdown of
standard theoretical frameworks and models. Until recently these
systems were considered as haphazard sets of points and
connections. Recent advances have generated a vigorous research
effort in understanding the effect of complex connectivity patterns
on dynamical phenomena. This book presents a comprehensive account
of these effects. A vast number of systems, from the brain to
ecosystems, power grids and the internet, can be represented as
large complex networks. This book will interest graduate students
and researchers in many disciplines, from physics and statistical
mechanics to mathematical biology and information science. Its
modular approach allows readers to readily access the sections of
most interest to them, and complicated maths is avoided so the text
can be easily followed by non-experts in the subject.
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