The book
presents an overwhelmingly rich display of deep ideas in the theory and
applications of invariant manifolds for dynamical systems, which appear in
physical and chemical kinetics, as well as in biology.
An example
of a result and exposition is provided by a stunningly beautiful treatment of
the systems with inheritance in Chapter 14, combining mathematical rigor with a
wide display of concrete applications.
The book
should become an all time classics.
Mikhail
Shubin,
Matthews
Distinguished University Professor
in
Northeastern University, Boston, USA.
This book
is a treasure box filled with a variety of ideas on the reduced description of
kinetics. The authors do not only summarize
their pioneering work --- at the heart of which is the "invariant
manifold method" --- but also put it nicely into perspective and add new
material (e.g., "invariant grids", "films") to compose a
well-balanced picture of physical and chemical kinetics. The elegant idea of
"films" consisting of macroscopically definable nonequilibrium states
offers new opportunities for a deeper understanding of irreversibility. 25
years of experience in the field are condensed into deep physical insight,
powerful mathematical techniques, and a wealth of illustrating examples and
useful references.
Hans
Christian ttinger,
Professor of
Polymer Physics, ETH Zrich
Statistical
mechanics is the branch of theoretical physics which endeavours to explain the macroscopic
behaviour of natural systems in terms of the fundamental interactions between
their microscopic constituents. It comes in two flavors: equilibrium and
non-equilibrium. At equilibrium, only time-asymptotic states are relevant to
the macroscopic description, and consequently the time-evolution
of the
system plays no role. As a result, many elegant and general
results can
be established, which place equilibrium statistical mechanics on a very solid
foundational and operational basis. The same is definitely not true for
non-equilibrium statistical mechanics, especially for systems far-off
equilibrium. For such systems, the dynamics does play a vital role and
consequently the task of establishing general principles appears much harder
and way less accomplished than for the equilibrium case.
One of the
few powerful and general ideas which help unravelling the complexities of
non-equilibrium systems is the notion of separation between 'slow' and 'fast'
degrees of freedom. Loosely speaking, the former describe the large-scale,
macroscopic dynamics, whereas the latter associate with microscopic
fluctuations around the slow modes.
Of course,
the 'slow/fast' dichotomy is a rather fuzzy notion, which necessitates
quantitative specification in order to acquire genuine scientific status.
Such
quantitative underpinning is provided by the theory of invariant manifolds,
that is subsets of the system phase-space which act as attractors of the
long-time dynamics of the system. Providing criteria to identify, construct and
classify the invariant manifolds of complex systems, thereby offering a
quantitative tool for the investigation of non-equilibrium statistical systems,
is a task of utmost importance in modern non-equilibrium statistical mechanics.
This task
makes the central core of the present monograph.
The authors
are highly reputed experts in the field and provide a very remarkable, and much
needed, self-contained introduction to this fascinating subject, along with a
systematic treatment of advanced topics which the authors themselves have
largely contributed to develop.
The
resulting monograph is a unique and very precious contribution to modern
non-equilibrium statistical mechanics. It will make a very useful and enjoyable
entry in the library of graduate students and professional in the very many
disciplines, such as applied math, physics, chemistry and biology, which share
non-equilibrium statistical mechanics as a common conceptual background.
Sauro Succi,
Professor,
Research Director
Istituto
Applicazioni Calcolo, CNR-IAC
Roma, Italy