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This book covers analysis on fractals, a developing area of mathematics that focuses on the dynamical aspects of fractals, such as heat diffusion on fractals and the vibration of a material with fractal structure. The book provides a self-contained introduction to the subject, starting from the basic geometry of self-similar sets and going on to discuss recent results, including the properties of eigenvalues and eigenfunctions of the Laplacians, and the asymptotical behaviors of heat kernels on self-similar sets. Requiring only a basic knowledge of advanced analysis, general topology and measure theory, this book will be of value to graduate students and researchers in analysis and probability theory. It will also be useful as a supplementary text for graduate courses covering fractals.
The aim of these lecture notes is to propose a systematic framework
for geometry and analysis on metric spaces. The central notion is a
partition (an iterated decomposition) of a compact metric space.
Via a partition, a compact metric space is associated with an
infinite graph whose boundary is the original space. Metrics and
measures on the space are then studied from an integrated point of
view as weights of the partition. In the course of the text: It is
shown that a weight corresponds to a metric if and only if the
associated weighted graph is Gromov hyperbolic. Various relations
between metrics and measures such as bilipschitz equivalence,
quasisymmetry, Ahlfors regularity, and the volume doubling property
are translated to relations between weights. In particular, it is
shown that the volume doubling property between a metric and a
measure corresponds to a quasisymmetry between two metrics in the
language of weights. The Ahlfors regular conformal dimension of a
compact metric space is characterized as the critical index of
p-energies associated with the partition and the weight function
corresponding to the metric. These notes should interest
researchers and PhD students working in conformal geometry,
analysis on metric spaces, and related areas.
This book covers analysis on fractals, a developing area of
mathematics which focuses on the dynamical aspects of fractals,
such as heat diffusion on fractals and the vibration of a material
with fractal structure. The book provides a self-contained
introduction to the subject, starting from the basic geometry of
self-similar sets and going on to discuss recent results, including
the properties of eigenvalues and eigenfunctions of the Laplacians,
and the asymptotical behaviors of heat kernels on self-similar
sets. Requiring only a basic knowledge of advanced analysis,
general topology and measure theory, this book will be of value to
graduate students and researchers in analysis and probability
theory. It will also be useful as a supplementary text for graduate
courses covering fractals.
In this paper, time changes of the Brownian motions on generalized
Sierpinski carpets including $n$-dimensional cube $[0, 1]^n$ are
studied. Intuitively time change corresponds to alteration to
density of the medium where the heat flows. In case of the Brownian
motion on $[0, 1]^n$, density of the medium is homogeneous and
represented by the Lebesgue measure. The author's study includes
densities which are singular to the homogeneous one. He establishes
a rich class of measures called measures having weak exponential
decay. This class contains measures which are singular to the
homogeneous one such as Liouville measures on $[0, 1]^2$ and
self-similar measures. The author shows the existence of time
changed process and associated jointly continuous heat kernel for
this class of measures. Furthermore, he obtains diagonal lower and
upper estimates of the heat kernel as time tends to $0$. In
particular, to express the principal part of the lower diagonal
heat kernel estimate, he introduces ``protodistance'' associated
with the density as a substitute of ordinary metric. If the density
has the volume doubling property with respect to the Euclidean
metric, the protodistance is shown to produce metrics under which
upper off-diagonal sub-Gaussian heat kernel estimate and lower near
diagonal heat kernel estimate will be shown.
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