an introduction to statistical mechanics and thermodynamics pdf
The disciplines of statistical mechanics and thermodynamics are very closely related, although their historical roots are separate. The founders of thermodynamics developed their theories without the advantage of contemporary understanding of the atomic structure of matter. Statistical mechanics, which is built on this understanding, makes predictions of system behavior that lead to thermodynamic rules. In other words, statistical mechanics is a conceptual precursor to thermodynamics, although it is an historical latecomer.
Unfortunately, despite their theoretical connection, statistical mechanics and thermodynamics are often taught as separate fields of study. Even worse, thermodynamics
is usually taught first, for the dubious reason that it is older than statistical mechanics.
All too often the result is that students regard thermodynamics as a set of highly
abstract mathematical relationships, the significance of which is not clear.
This book is an effort to rectify the situation. It presents the two complementary
aspects of thermal physics as a coherent theory of the properties of matter. My
intention is that after working through this text a student will have solid foundations
in both statistical mechanics and thermodynamics that will provide direct access to
In writing this book I have been guided by a number of principles, only some of which
are shared by other textbooks in statistical mechanics and thermodynamics.
• I have written this book for students, not professors. Many things that experts
might take for granted are explained explicitly. Indeed, student contributions have
been essential in constructing clear explanations that do not leave out ‘obvious’
steps that can be puzzling to someone new to this material.
• The goal of the book is to provide the student with conceptual understanding, and
the problems are designed in the service of this goal. They are quite challenging,
but the challenges are primarily conceptual rather than algebraic or computational.
• I believe that students should have the opportunity to program models themselves
and observe how the models behave under different conditions. Therefore, the
problems include extensive use of computation.
• The book is intended to be accessible to students at different levels of preparation.
I do not make a distinction between teaching the material at the advanced
undergraduate and graduate levels, and indeed, I have taught such a course many
times using the same approach and much of the same material for both groups. As
the mathematics is entirely self-contained, students can master all of the material
even if their mathematical preparation has some gaps. Graduate students with
previous courses on these topics should be able to use the book with self-study
to make up for any gaps in their training.
• After working through this text, a student should be well prepared to continue with more specialized topics in thermodynamics, statistical mechanics, and condensed-matter physics.