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I am currently working on this. More specifically my question is about Problem 2.5 b). In the solution they get from $$ Nd\mu=-SdT+VdP $$ to $$ N\Big(\frac{\partial\mu}{\partial N}\Big)_{T,V}=V\Big(\frac{\partial P}{\partial N}\Big)_{T,V} $$ which I dont fully understand. I get that the $dT$ term is gone because $T$ is constant and so $dT=$. And because $V$ is constant there is no $\frac{\partial V}{\partial N}$. But I not yet came up with a mathmatical proof. My Problem is that the only way I know to start is to take the partial derivative over $N$ on both sides and let $T,V$ be fixed. Then on the right side I get the right thing but on the left side I get $$ \frac{\partial}{\partial N}\Big(Nd\mu\Big)_{T,V}=\Big(\frac{\partial N}{\partial N}d\mu\Big)_{T,V}+\Big(N\frac{\partial\mu}{\partial N}\Big)_{T,V}=\Big(d\mu\Big)_{T,V}+N\Big(\frac{\partial\mu}{\partial N}\Big)_{T,V} $$ The $d\mu$ should not be there. Can someone help me?

Qmechanic
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    The infinitesimal term $d\mu$ is far smaller than the other terms and can be ignored. This is true for all expressions containing a mix of finite and infinitesimal terms. – Chemomechanics Jul 31 '23 at 16:40
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    I don't think Chemomechanics comment is accurate, $d\mu$ is not just physically a small quantity, it is mathematically a differential and not a function. Therefore, deriving it doesn't make sense from a mathematical point of view. It's not that $d\mu$ can be ignored because it's small, it's that the calculation that OP did in the ending of their question is incorrect. – P. C. Spaniel Jul 31 '23 at 17:15
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    Yes, it's very likely a lie to children that works in this context and obviates the better analyses given in the answers. Your answer fits nicely between the extremes of mathematical abuse and the need to learn a new branch of math. – Chemomechanics Jul 31 '23 at 20:43
  • One minor nit: What you are calling a "mathematical proof" is actually a "mathematical derivation" (that's deri-vay-tion, no connection to deriv-ah-tives per se) which is a sequence of mathematically valid transformations and reductions. Whereas a mathematic proof is a series of strict, formal logical transformations and reductions from the axioms and theorems of a mathematical system. Physicists and others who apply mathematics rarely encounter them outside of high school geometry, but the distinction is important to some of us who do use them. – RBarryYoung Aug 02 '23 at 11:57

2 Answers2

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I will try to provide an answer without using differential geometry. In thermodynamics, the state of the system can be fully determined by knowing some thermodynamical variables. In most cases, we need three (This depends on how complex the system is). The most common ones are usually the total energy $E$, the total volume $V$ and the total number of particles $N$. Since there is an equation of state for the system, where the different quantities are related to each other, one can always switch them around and describe the system with another set of variables, for example $N$, $T$ and $V$. The important thing is that we need to consider three of the thermodynamical variables as independent and all other variables as functions of them.

It is also important to notice that $d\mu$ is not on the same footing as $\mu$. $\mu$ is a thermodynamical function of $N$, $T$ and $V$ while $d\mu$ represents a small variation on $\mu$ when you do a small variation on $N$, $T$ and $V$.

Ok, so now let's move on to answer the question. On one hand, we have a relation between small variations of thermodynamical variables

\begin{equation} N d\mu = -S dT+VdP \end{equation}

This equations tells you how $d\mu$ changes if you change temperature or pressure. On the other hand, the variation of any quantity can be written in terms of variations of $N$, $T$ and $V$, since those are our thermodynamical variables. We get

\begin{equation} d\mu = \big(\frac{\partial \mu}{\partial N}\big)_{T,V} dN + \big(\frac{\partial \mu}{\partial T}\big)_{N,V}dT+ \big(\frac{\partial \mu}{\partial V}\big)_{N,T}dV \end{equation}

and

\begin{equation} dP = \big(\frac{\partial P}{\partial N}\big)_{T,V} dN + \big(\frac{\partial P}{\partial T}\big)_{N,V}dT+ \big(\frac{\partial P}{\partial V}\big)_{N,T}dV \end{equation}

Notice that the identity of the factor in frond of any small variation is always the rate of change of $\mu$ respect to the variation of that variable while keeping everything else fixed. Now, we can plug these equations into the first one to get

\begin{equation} N\Big\{\big(\frac{\partial \mu}{\partial N}\big)_{T,V} dN + \big(\frac{\partial \mu}{\partial T}\big)_{N,V}dT+ \big(\frac{\partial \mu}{\partial V}\big)_{N,T}dV \Big\}=-SdT+V\Big\{\big(\frac{\partial P}{\partial N}\big)_{T,V} dN + \big(\frac{\partial P}{\partial T}\big)_{N,V}dT+ \big(\frac{\partial P}{\partial V}\big)_{N,T}dV\Big\} \end{equation}

Now, this long equation is a bit like a vector equation where you have three orthonormal vectors for your basis. We said in the beginning that we would consider $N$, $T$ and $V$ to be our independent variables. That means that a small variation on the number of particles $N$ can't really affect or be caused by a small variation on the temperature $T$. That means that we can group each of those terms and actually get three equations from this lengthy mess. The first one is

\begin{equation} N\big(\frac{\partial \mu}{\partial N}\big)_{T,V}=V\big(\frac{\partial P}{\partial N}\big)_{T,V} \end{equation}

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    good point. Perhaps one thing I should mention to clarify for OP the link between our presentations is that the purpose of my “evaluating both sides of the equation on $\xi_{(x),1}$” (i.e $\left(\frac{\partial}{\partial N}\right){(N,T,V)}$) is simply to extract and equate the coefficients of $dN$ on both sides of the penultimate equation here (this is the ‘dual basis’ stuff I mentioned initially). Likewise if I evaluated both sides on $\xi{(x),2}$, it amounts to equating coefficients of $dT$ on both sides of the penultimate equation here, and for $\xi_{(x),3}$, it is the coefficient of $dV$. – peek-a-boo Jul 31 '23 at 17:49
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    I understand, I agree that our answers are essentially the same, my intention was to provide an answer that didn't involve differential geometry since using forms notions of dual basis is too advanced for a thermodynamics class. Indeed, the OP didn't seem to understand that it is not mathematically correct to derive a differential, so I wanted to clarify some basic things instead of using more advanced math. – P. C. Spaniel Jul 31 '23 at 18:41
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    sure, and this is a great answer. My comment was merely to ‘provide a bridge’ between our two answers for OP/future readers who may think we’re talking completely different stuff. – peek-a-boo Jul 31 '23 at 18:44
  • Agreed! The bridge is that using a vector basis and contracting it with the differential forms (In your answer) is equivalent to expanding the differentials in any given basis of independent thermodynamical variables (in my answer). – P. C. Spaniel Jul 31 '23 at 18:46
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If you know a little differential geometry (vector fields and $1$-forms) and linear algebra (dual bases) then this question becomes almost a triviality/definition. At the outset, let me remark that the result is obtained, not by “differentiating” the equation given (because differentiating an equation of forms is only achieved by exterior derivatives), but rather by “evaluating” the given equation along a specific direction. Just in case this sounds mysterious, I’ll provide a rapid review.

Things like $d\mu,dT,dP$ etc are called $1$-forms, meaning they are objects which eat vector fields and produce a function. So, if $X$ is a vector field, and $f$ is a function, then $(df)(X)$ means the application of the $1$-form $df$ on the vector field $X$. What it measures is the directional derivative of $f$ along $X$. Now, consider the special case where you have a coordinate system $(x^1,\dots, x^n)$. This gives rise to $n$ different vector fields $\xi_{(x),1},\dots, \xi_{(x),n}$, where the $\xi_{(x),i}$ is the vector field which is tangent to the $x^i$ coordinate line (obtained by keeping the coordinates $x^1,\dots, x^{i-1},x^{i+1},\dots, x^n$ fixed). Pictorially, draw a ‘curvy grid’ if you wish, then along the coordinate liens, draw the tangent arrows. If you evaluate $df$ on this particular coordinate-induced vector field $\xi_{(x),i}$, then $df(\xi_{(x),i})$ gives the directional derivative of $f$ in the direction of the $x^i$ coordinate curve when all other coordinates are held fixed… I hope this sounds familiar; it is exactly the definition of the partial derivative $\frac{\partial f}{\partial x^i}$. One thing which I will emphasize (as hopefully you’ve already been told before), the $i^{th}$ vector field $\xi_{(x),i}$ depends on not just $x^i$, but it depends on the remaining coordinates $x^1,\dots, x^{i-1},x^{i+1},\dots, x^n$ as well, since we by definition have to keep them constant. This is why I’ve labored to write $\xi_{(x),i}$ rather than simply $\xi_i$, to emphasize that the definition of this object depends on the entire coordinate system $x=(x^1,\dots, x^n)$.

Next, if we still fix a coordinate system $x=(x^1,\dots, x^n)$ then taking $f$ to be one of the coordinate functions $f=x^j$, we can consider its exterior derivative $dx^j$. This can of course act on the various coordinate vector fields $\xi_{(x),i}$. The result is then $dx^j(\xi_{(x),i})=\delta^j_i$.

Ok, so for your question specifically, we have a $3$-dimensional system, and we consider a coordinate system $x=(x^1,x^2,x^3)=(N,T,V)$. We thus have three coordinate-induced vector fields $\xi_{(x),1},\xi_{(x),2},\xi_{(x),3}$. Now, we consider the equality $N\,d\mu=-S\,dT+V\,dP$, and we evaluate both sides on the vector field $\xi_{(x),1}$. This gives \begin{align} N\,(d\mu)(\xi_{(x),1})&=-S(dT)(\xi_{(x),1})+V(dP)(\xi_{(x),1}).\\ &=0+V(dP)(\xi_{(x),1}), \end{align} where the $0$ is because $(dT)(\xi_{(x),1})=(dx^2)(\xi_{(x),1})=0$, since by definition $x^2$ is kept constant along the vector field $\xi_{(x),1}$. So, this equality can now be written (by definition/notation!) as \begin{align} N\frac{\partial \mu}{\partial x^1}&=V\frac{\partial P}{\partial x^1}. \end{align} Or, what means the same thing, but in more traditional notation, \begin{align} N\left(\frac{\partial \mu}{\partial N}\right)_{T,V}&=V\left(\frac{\partial P}{\partial N}\right)_{T,V}. \end{align}


Notational Remark.

What I called $\xi_{(x),i}$ is more traditionally written simply as $\frac{\partial}{\partial x^i}$, or $\left(\frac{\partial}{\partial x^i}\right)_{(x^1,\dots, x^n)}$ if we wish to emphasize the entire coordinate system (so we know which other coordinates to keep fixed!), and we have the equation (a definition really) $\frac{\partial f}{\partial x^i}:=(df)\left(\frac{\partial}{\partial x^i}\right)$. So I could have simply said that “the equality you asked for follows immediately by evaluating both sides of $N\,d\mu=-S\,dT+V\,dP$ on the coordinate-induced vector field $\left(\frac{\partial}{\partial N}\right)_{(N,T,V)}$.”

peek-a-boo
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    This answer is vastly too technical for an introductory thermodynamics question. It is not mathematically wrong to my eye, but it is missing the point. – Matt Hanson Jul 31 '23 at 18:00
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    @MattHanson I disagree. In fact I would double down :) and go even further to say that despite intimidating words like 1-form and duality and the DG lingo, everything here is elementary and belongs at the level of basic linear algebra and multivariable calculus, not differential geometry. I’m only using two things. First is that differential calculus is the study of “local linear approximation”: $df$ gives us the linear approximation of a function, and $df(X)$ gives the linear approximation when moving in a given direction (this is what makes tangent lines and planes go round afterall). – peek-a-boo Jul 31 '23 at 18:32
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    Second is that a coordinate system gives us vector fields; a fact which we’re all familiar with from simple examples like spherical coordinates. The rest of my answer is just a precise math-speak way of writing things (definitions), because I like having things written down precisely with little notational abuse (on a first pass). Here I’m willing to concede that it may be a little tough to read (depending on individual’s backgrounds/training) due to a math vs physics communication/cultural barrier (eg. I personally find it a little more challenging to read a physics text than a math text). – peek-a-boo Jul 31 '23 at 18:32
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    It is not familiar to all that coordinate systems give vector fields. There are biology students, even engineering students that learn about thermodynamics without ever getting deep into linear algebra, vector basis, etc. Even basic physics courses might not cover this. I agree that this answer is great for advanced readers, but I provided a simpler answer for people without this background. – P. C. Spaniel Jul 31 '23 at 18:43
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    Again, we will have to agree to disagree. I quite love giving mathematics its due, and I think that being properly rigorous can be extremely helpful to put concepts on their proper footing. But in this context I think the mathematical abstraction serves more to confuse than to clarify, particularly in the context of a beginner to the subject. For more advanced students (I.e. graduate students), your approach would be extremely valuable, however. – Matt Hanson Aug 01 '23 at 11:34