- #1
HJ Farnsworth
- 128
- 1
Greetings,
This question makes reference to the stat mech book, “Fundamentals of Statistical and Thermal Physics”, by Reif, so people who have that book will probably understand where I am coming from most easily. However, the main points/questions of this post are independent of the book, so I would very much appreciate contributions from anyone.
In section 3.3, pages 98-99, Reif derives the energy at which P(E) reaches a maximum value, where E is the energy of one system which is thermally interacting with another. He states,
“To locate the position of the maximum of P(E), or equivalently, of the maximum of its logarithm,…”
He then continues by setting the derivative of ln(P) with respect to E equal to 0, rather than simply setting the derivative of P with respect to E equal to 0.
He also says, in a footnote on page 99,
“…The reason that it is somewhat more convenient to work with ln P instead of P itself is that the logarithm is a much more slowly varying function of the energy E, and that it involves the numbers Ω and Ω' as a simple sum rather than as a product.”
I think Reif’s textbook is pretty good overall – however, I dislike it when derivations in textbooks involve steps that seem pointless, and the switch to natural logarithms, as presented in this derivation, seems pointless. Additionally, the reason given in the footnote for switching to natural logarithms seems weak to me. It wouldn’t bother me except for the fact that it seems to needlessly add an extra level of abstraction to the quantities being dealt with.
In other words, probability P and number of states Ω are simple and un-abstract quantities, and I’m not satisfied with the explanations that I have heard for switching to logarithms of those quantities. It’s not that I find the math hard – it’s that it is not clear to me why it is necessary, or why it is worth the cost adding more levels of abstraction.
The best justification that I can think of is that natural logarithms relate more easily to other statistical quantities, like temperature, as well as various state variables. However, this doesn't fully satisfy me either, so I was wondering – what do other people think, and does anyone have any concise reasons/ways of thinking about it that justify the use of natural logarithms more convincingly than the ones that I have?
Thanks very much for any thoughts.
-HJ Farnsworth
This question makes reference to the stat mech book, “Fundamentals of Statistical and Thermal Physics”, by Reif, so people who have that book will probably understand where I am coming from most easily. However, the main points/questions of this post are independent of the book, so I would very much appreciate contributions from anyone.
In section 3.3, pages 98-99, Reif derives the energy at which P(E) reaches a maximum value, where E is the energy of one system which is thermally interacting with another. He states,
“To locate the position of the maximum of P(E), or equivalently, of the maximum of its logarithm,…”
He then continues by setting the derivative of ln(P) with respect to E equal to 0, rather than simply setting the derivative of P with respect to E equal to 0.
He also says, in a footnote on page 99,
“…The reason that it is somewhat more convenient to work with ln P instead of P itself is that the logarithm is a much more slowly varying function of the energy E, and that it involves the numbers Ω and Ω' as a simple sum rather than as a product.”
I think Reif’s textbook is pretty good overall – however, I dislike it when derivations in textbooks involve steps that seem pointless, and the switch to natural logarithms, as presented in this derivation, seems pointless. Additionally, the reason given in the footnote for switching to natural logarithms seems weak to me. It wouldn’t bother me except for the fact that it seems to needlessly add an extra level of abstraction to the quantities being dealt with.
In other words, probability P and number of states Ω are simple and un-abstract quantities, and I’m not satisfied with the explanations that I have heard for switching to logarithms of those quantities. It’s not that I find the math hard – it’s that it is not clear to me why it is necessary, or why it is worth the cost adding more levels of abstraction.
The best justification that I can think of is that natural logarithms relate more easily to other statistical quantities, like temperature, as well as various state variables. However, this doesn't fully satisfy me either, so I was wondering – what do other people think, and does anyone have any concise reasons/ways of thinking about it that justify the use of natural logarithms more convincingly than the ones that I have?
Thanks very much for any thoughts.
-HJ Farnsworth