Can I Prove the Chain Rule with the Definition of a Total Differential?

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Discussion Overview

The discussion revolves around the proof of the chain rule for partial derivatives, specifically whether it can be derived from the definition of a total differential. Participants explore various approaches to proving the chain rule, including the use of basic derivative definitions and the implications of different mathematical rigor.

Discussion Character

  • Exploratory
  • Technical explanation
  • Debate/contested
  • Homework-related

Main Points Raised

  • One participant proposes starting with the total differential definition to derive the chain rule, suggesting that dividing both sides by dt leads to the chain rule expression.
  • Another participant argues that the proof's rigor depends on the audience, indicating that mathematicians might reject the approach while physicists may find it acceptable.
  • A different viewpoint suggests proving the chain rule first using the basic definition of a derivative before deriving the total differential.
  • A participant recalls a historical presentation on derivatives and discusses the properties of linear maps in relation to the chain rule, emphasizing the beauty of the mathematical treatment.
  • Another participant mentions an equivalent way to state the existence of a derivative, which can simplify proving the chain rule for one-variable and multi-variable functions.
  • A participant indicates they used a simpler approach to meet an assignment deadline, expressing gratitude for the more complex explanations provided by others.
  • One participant notes that the simpler approach may not capture the depth of understanding and warns against the pressures of assignment deadlines influencing the learning process.

Areas of Agreement / Disagreement

Participants express differing opinions on the rigor required for the proof of the chain rule, with no consensus on a single approach being universally accepted. Multiple competing views on how to derive the chain rule remain present throughout the discussion.

Contextual Notes

Some participants highlight the limitations of their approaches, including the dependence on definitions and the varying levels of rigor expected in different academic contexts.

Icebreaker
If I was trying to prove the chain rule for partial derivatives, can I start with the definition of a total differential? What I mean is:

Let [tex]f(x,y)=z[/tex] where [tex]x=g(t)[/tex] and [tex]y=h(t)[/tex].

I'm looking for [tex]\frac{dz}{dt}[/tex].

By definition,

[tex]dz = \frac{\partial z}{\partial x}dx + \frac{\partial z}{\partial y}dy[/tex]

So, can I simply divide both sides by [tex]dt[/tex] and obtain,

[tex]\frac{dz}{dt} = \frac{\partial z}{\partial x}\frac{dx}{dt} + \frac{\partial z}{\partial y}\frac{dy}{dt}[/tex]

Which happens to be the partial derivate using chain rule, and thus proving it? Or must I go with the definitions of the derivatives ([tex]\Delta[/tex] and all)?
 
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Depends on how rigurous you want to be.A course on analysis for and by mathematicians would reject your proof.

As for us physicists,it's good enough.

Daniel.
 
Actually, I would do it almost the opposite way: first prove the chain rule by using the basic definition of "derivative" (as [itex]lim \frac{f(x+h)-f(x)}{h}[/itex]) THEN
show [itex]dz = \frac{\partial z}{\partial x}dx + \frac{\partial z}{\partial y}dy[/itex] from that!
 
I still remember the very clear presentation by Lynn Loomis in my advanced calc class in 1964.

The derivative of f:R^n-->R^m, at x is a linear map L such that the difference o(y) = f(x+y)-f(x) -L(y) is "little oh" as a function of y, i.e. |o(y)|/|y| approaches zero as y does.

A map O is "big oh" if the ratio |O(y)|/|y| remains bounded as y approaches zero. Then simply check (trivial) that the composition of two little oh maps is little oh, and the composition of a little oh and a big oh map is little oh, and that linear maps are big oh (in finite dimensions), and that the sum of big oh maps is big oh, and the sum of little oh maps is little oh.


Then it is trivial to prove that the derivative of a composition is the composition of the derivatives, in the sense of composing linear maps.

in particular the derivative wrt t of f(x(t),y(t)) is the matrix product of [df/dx,df/dy] with the column matrix [dx/dt, dy/dt].

this language mimics that in Hardy's classic calculus book, Pure mathematics.

I never get to teach this stuff, but seem to spend my life reteaching elementary calc over and over. this stuff is so beautiful.

this treatment works also in infinite dimensional banach spaces, where of course the derivative is assumed to be both continuous and linear.

this may seem odd today, but in 1964, most of the students in Loomis' banach space advanced calc course were freshmen.
 
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There's an equivalent way of stating the existence of a derivative.
A function f is differentiable at x=a iff there's a number f'(a), such that:

[itex]f(a+\Delta x)-f(a)=f'(a)\Delta x+\epsilon \Delta x[/itex]

with
[tex]\lim_{\Delta x \to 0}\epsilon=0[/tex].

Using this it's very easy to prove the one variable chain rule. The chain rule for a function R^n -> R can be proven similarly.
 
I did it using Galileo's suggestion. Thanks to everyone
 
i guess then you did not notice that galileo's suggestion was the same as mine.

i.e. the statement f(x+y)-f(x) -L(y) is "little oh" as a function of y, i.e. |o(y)|/|y| approaches zero as y does, means that

[f(x+y)-f(x) - f'(x).y]= e(y) |y|, where e(y)-->0 as y approaches zero.

here |y| = delta(x), in galileo's notation.

the way i stated it (and galileo's as well, suitably interpreted) was designed to work in all dimensions or even infinite dimensions.
 
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Well, I needed to hand in the assignment before the deadline, so I went with the simplest form. I do appreciate your extended help, mathwonk, and I will study it further.
 
thanks for your response. I know it is harder to assimilate but it is the better formulation.

another lesson that assignments are evil influences! do not be seduced by the darkness!
 

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