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In this unique book, the reader is invited to experience the joy of appreciating something which has eluded understanding for many years - entropy and the Second Law of Thermodynamics. The book has a two-pronged message: first, that the second law is not infinitely incomprehensible as commonly stated in most textbooks on thermodynamics, but can, in fact, be comprehended through sheer common sense; and second, that entropy is not a mysterious quantity that has resisted understanding but a simple, familiar and easily comprehensible concept. Written in an accessible style, the book guides the reader through an abundance of dice games and examples from everyday life. The author paves the way for readers to discover for themselves what entropy is, how it changes, and, most importantly, why it always changes in one direction in a spontaneous process. In this new edition, seven simulated games are included so that the reader can actually experiment with the games described in the book. These simulated games are meant to enhance the readers' understanding and sense of joy upon discovering the Second Law of Thermodynamics.
- Sales Rank: #1151146 in Books
- Brand: Brand: World Scientific Publishing Company
- Published on: 2008-06-18
- Released on: 2008-06-18
- Original language: English
- Number of items: 1
- Dimensions: 9.00" h x .62" w x 6.00" l, .90 pounds
- Binding: Paperback
- 250 pages
- Used Book in Good Condition
Review
This book makes very good reading for all students of thermodynamics, as well as for more-advanced people who do (or do not) feel comfortable with the fascinating concept of entropy. -- CERN Courier "CERN Courier"
Most helpful customer reviews
94 of 108 people found the following review helpful.
Basic
By Scott Davies
After seeing nothing but five-star reviews for this book, I figured I'd pick it up despite having little feel for what its target audience was since none of it was actually viewable on Amazon.
In a nutshell, this is very much a book for laymen. If you want an intuitive grasp of what entropy's about in the context of everyday physics without getting bogged down in math, then this may be a great book for you. The book uses as little math as possible in its explanations, and effectively assumes you're unfamiliar with or have forgotten high-school-level math operations such as factorials and logarithms. It manages to pound its point home reasonably well using lots and lots of fairly simple thought experiments that only differ from each other by little incremental steps.
On the other hand, if you already know anything at all about the information-theoretic formulation of entropy, already have an appreciation for the Law of Large Numbers, and have heard the words "macrostates" and "microstates" before, then there's nothing in this book you aren't likely to understand already. If you've taken a course on statistical mechanics and finished it without being horrendously confused, but maybe were hoping for a useful refresher on how different formulations of entropy are related, you should pass on this book. If you were hoping for illumination about the aspects of entropy that are actually at all "interesting" to modern physicists, such as black hole entropy (or the bizarre theories it's spawned such as the holographic principle), this is definitely not the book you're looking for.
Also, the book has no index. This is less annoying than it would be in a book that had more meat to it, but still, any 200+ page nonfiction book with no index should be taken out and shot as a matter of principle.
46 of 52 people found the following review helpful.
Another way to enjoy fundamental physics!
By Diego Casadei
Arieh Ben-Naim, professor at the Hebrew University of Jerusalem, taught
thermodynamics and statistical mechanics for many years and is well
aware that students learn the second law but do not understand it,
simply because it can not be explained in the framework of classical
thermodynamics, in which it was first formulated by Lord Kelvin (i.e.
William Thomson, 1824-1907) and Rudolf Julius Emanuel Clausius
(1822-1888). Hence, this law and the connected concept of entropy are
usually surrounded by some mysterious halo: there is something (the
entropy), defined as the ratio between heat and temperature, that is
always increasing. The students not only do not understand _why_ it is
always increasing (it is left as a principle in classical
thermodynamics), but also ask themselves what is the _source_ of such
ever increasing quantity.
We feel comfortable with the first law, that is the principle of energy conservation, because our experience always
suggests that if we use some resource (the energy) to perform any work,
then we are left with less available energy for further tasks. The
first law simply tells us that the heat is
another form of energy so that nothing is actually lost, something which
we can accept without pain. In addition, the second law says that,
though the total energy is constant, we can not always recycle 100% of
it because there is a limit on the efficiency of conversion of heat into
work (the highest efficiency being given by the Carnot cycle, named
after Nicolas Léonard Sadi Carnot, 1796-1832). Again, we can accept it
quite easily, because it sounds natural, i.e. in accordance with our
common sense: we do not know any perpetual engine. But our daily
experience is not sufficient to make us understand what entropy is, and
why it must always increase.
The author shows that, if we identify the entropy with the concept of
"missing information" of the system at equilibrium, following the work
done by Claude Elwood Shannon (1916-2001) in 1948, we obtain a well
defined and (at least in principle) measurable quantity. This quantity,
apart from a multiplicative constant, has the same behavior as the
entropy: for every spontaneous process of an isolated system, it must
increase until the equilibrium state is reached. The missing
information, rather than the disorder (not being a well defined
quantity), is the key concept to understand the second law.
I should say here that the identity of entropy and missing
information is not a widespread idea among physicists, so that many
people may not appreciate this point. However, the arguments of this
book are quite convincing, and different opinions are also taken into
account and commented.
In addition, Ben-Naim thinks that the entropy should be taught as an
dimensionless quantity, being defined as the ratio between heat, that is
energy, and temperature, that is a measure of the average kinetic energy
of the atoms and molecules. The only difference with the missing
information, again dimensionless, is the scale: because the missing
information can be defined as the number of binary questions (with
answer "yes" on "no" only) which are necessary to identify the
microscopic state of the system, this number comes out to be incredibly
large for ordinary physical systems, involving a number of constituents
of the order of the Avogadro's number. This numerical difference makes
me think about the difference between mass and energy, connected by the
Einstein's most famous equation E = m c^2: they could be measured using
the same units (as it is actually done in high-energy physics), the sole
difference being that even a very small mass amounts to a huge quantity
of energy.
The mystery of the ever increasing entropy can be explained once (and
only if) we realize that the matter is not continue, but discrete. The
author basically follows the work of Josiah Willard Gibbs (1839-1903),
who developed the statistical mechanical theory of matter based on a
purely probabilistic approach. First, one has to accept the fact that
macroscopic measurements are not sensitive enough to distinguish
microscopic configurations when they differ for thousands or even
millions of atoms, just because the total number of particles is usually
very large (usually of the order of 10^23 at least). Then, under the
hypothesis that each microscopic state is equally probable, i.e. that
the system will spend almost the same time in each micro-state, one can
group indistinguishable micro-states into macro-states. The latter are
the only thing we can monitor with macroscopic measurements. Under the
commonly accepted hypothesis that all microscopic configurations are
equally probable, macro-states composed by larger numbers of
micro-states will be more probable, i.e. the system will spend more time
in such macro-states.
As a naive example, one could start with a system prepared in such a way
that all its constituents are in the same microscopic configuration.
One could think about a sample of N dices, all of them showing the same
face, say the first one. The questions could be: (1) "Are all dices
showing the same face?"--Yes--; (2) "Is the face value larger or equal
than 3?"--No--; (3) "Is the face value larger or equal than 2?"--No--;
at this point we know that the value is 1. In general, the number of
binary questions is proportional to the logarithm in base 2 of the
number C of possible configurations, that is O(log_2 C). Now imagine to
randomly mix the dice by throwing all of them. The answer to the first
question would be "No", so that a completely different series of
questions has to be asked to find the microscopic configurations.
First, one may procede by finding how many dice show the value 1, for
example, asking O(log_2 N) questions. Suppose that the answer is M
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