Differential operator in multivariable fundamental theorem

In summary: The first step is to apply the linear operator ##D## to both sides:$$(DF)(x)=\sum_{i=1}^n\big[(x^i-a^i).(DH_i)(x)+H_i(x).D(x^i-a^i)\big]$$Edit: I missed out ##a^i## in the second term. Fixed now.Although, to really clarify what is going on we could introduce coordinate functions ##X^i(x) = x^i##. That allows us to avoid something like ##Dx^i## and...
  • #1
Shirish
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I'm referring to this result:

If ##F:\mathbb{R}^n\to\mathbb{R}## is ##C^{\infty}##, then for each ##a\in\mathbb{R}^n##, there exist ##C^{\infty}## functions ##H_i## such that for all ##x\in\mathbb{R}^n##, $$F(x)=F(a)+\sum_{i=1}^n(x^i-a^i)H_i(x)$$

But I'm not sure what happens if I apply a linear differential operator to both sides (like a derivation ##D##) - more specifically I'm not sure at what point should each term be evaluated. Acting ##D## on both sides I'll get $$DF=\sum_{i=1}^n\big[(x^i-a^i).DH_i+H_i.Dx^i\big]$$

If I try evaluating the non-differentiated RHS terms at ##a##, like this $$DF=\sum_{i=1}^n\big[(x^i-a^i)|_{x=a}.DH_i+H_i(a).Dx^i\big]$$
I can't just bring the ##x=a## thing out of thin air, can I? Should the LHS also be evaluated at ##x=a##? i.e. $$DF|_{x=a}=\sum_{i=1}^n\big[(x^i-a^i)|_{x=a}.DH_i|_{x=a}+\sum_{i=1}^nH_i(a).Dx^i|_{x=a}=\sum_{i=1}^nH_i(a).Dx^i|_{x=a}$$
And then finally, if ##H_i=X_i(F)## for some operator ##X_i##, can we say that ##H_i(x)=X_i(F)(x)## for all ##x\in\mathbb{R}^n##, and thus conclude from the above equation that $$DF|_{x=a}=\sum_{i=1}^nDx^i|_{x=a}.X_i(F)(a)=\bigg[\sum_{i=1}^nDx^i.X_i(F)\bigg]_{x=a}$$
Now since both sides are equal for arbitrary ##a\in\mathbb{R}^n##, ##D=\sum_{i=1}^nDx^i.X_i##

Is this fine? I'm not sure at all since there are so many steps and I don't know where I might have made a wrong assumption or step.
 
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  • #2
Shirish said:
But I'm not sure what happens if I apply a differential operator to both sides (like a derivation ##D##) - more specifically I'm not sure at what point should each term be evaluated. Acting ##D## on both sides I'll get $$DF=\sum_{i=1}^n\big[(x^i-a^i).DH_i+H_i.Dx^i\big]$$
I don't understand what you are doing here? You have dropped some function arguments but not others, so formally the equation cannot be right.
 
  • #3
PeroK said:
I don't understand what you are doing here? You have dropped some function arguments but not others, so formally the equation cannot be right.
Since ##F(a)## is constant, acting ##D## on it will give zero. The remaining stuff is applying the product rule to the 2nd RHS term in the very first equation (in quote block).
 
  • #4
Shirish said:
Since ##F(a)## is constant, acting ##D## on it will give zero. The remaining stuff is applying the product rule to the 2nd RHS term in the very first equation (in quote block).
My point is not that you misapplied the product rule, but you played fast and loose with functional arguments. So, it's not suprising that your calculations thereafter go from bad to worse. Your next equation is effectively a total mish-mash of notation:
Shirish said:
If I try evaluating the non-differentiated RHS terms at ##a##, like this $$DF=\sum_{i=1}^n\big[(x^i-a^i)|_{x=a}.DH_i+H_i(a).Dx^i\big]$$
 
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  • #5
PeroK said:
My point is not that you misapplied the product rule, but you played fast and loose with functional arguments. So, it's not suprising that your calculations thereafter go from bad to worse. Your next equation is effectively a total mish-mash of notation:
The thread's intention is for me to get a better understanding, hence I stated
Shirish said:
But I'm not sure what happens if I apply a linear differential operator to both sides (like a derivation ##D##)

I'm certain I've made mistakes in several steps. Could you help with those? (The motivation for the thread is to try and understand Theorem 2.2.1 from Wald's book)

Also you're right about this equation being wrong $$DF=\sum_{i=1}^n\big[(x^i-a^i)|_{x=a}.DH_i+H_i(a).Dx^i\big]$$
But immediately after that I acknowledge:
Shirish said:
I can't just bring the ##x=a## thing out of thin air, can I? Should the LHS also be evaluated at ##x=a##? i.e. $$DF|_{x=a}=\sum_{i=1}^n\big[(x^i-a^i)|_{x=a}.DH_i|_{x=a}+\sum_{i=1}^nH_i(a).Dx^i|_{x=a}=\sum_{i=1}^nH_i(a).Dx^i|_{x=a}$$
Is the new equation correct? If not, could you help me understand the proper way to apply the ##D## operator and evaluate at a specific point ##a##?
 
  • #6
Shirish said:
The thread's intention is for me to get a better understanding, hence I statedI'm certain I've made mistakes in several steps. Could you help with those? (The motivation for the thread is to try and understand Theorem 2.2.1 from Wald's book)

Also you're right about this equation being wrong $$DF=\sum_{i=1}^n\big[(x^i-a^i)|_{x=a}.DH_i+H_i(a).Dx^i\big]$$
But immediately after that I acknowledge:

Is the new equation correct? If not, could you help me understand the proper way to apply the ##D## operator and evaluate at a specific point ##a##?
The first step is to apply the linear operator ##D## to both sides:
$$(DF)(x)=\sum_{i=1}^n\big[(x^i-a^i).(DH_i)(x)+H_i(x).D(x^i-a^i)\big]$$Edit: I missed out ##a^i## in the second term. Fixed now.

Although, to really clarify what is going on we could introduce coordinate functions ##X^i(x) = x^i##. That allows us to avoid something like ##Dx^i## and have:
$$(DF)(x)=\sum_{i=1}^n\big[X^i(x-a).(DH_i)(x)+H_i(x).(DX^i)(x-a)\big]$$
 
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  • #7
PeroK said:
The first step is to apply the linear operator ##D## to both sides:
$$(DF)(x)=\sum_{i=1}^n\big[(x^i-a^i).(DH_i)(x)+H_i(x).Dx^i\big]$$Although, to really clarify what is going on we could introduce coordinate functions ##X^i(x) = x^i##. That allows us to avoid something like ##Dx^i## and have:
$$(DF)(x)=\sum_{i=1}^n\big[X^i(x-a).(DH_i)(x)+H_i(x).(DX^i)(x-a)\big]$$
Thanks! Understood so far. How does the rest of the treatment after that look? (i.e. evaluating both sides at some point ##x=a## and reaching the conclusion ##D=\sum_{i=1}^n dx^i.X_i##)
 
  • #8
Shirish said:
Thanks! Understood so far. How does the rest of the treatment after that look? (i.e. evaluating both sides at some point ##x=a## and reaching the conclusion ##D=\sum_{i=1}^n dx^i.X_i##)
##a## is already the point about which the expansion was taken. I.e. ##x-a = 0##. The only question is how the differential operator ##D## acts on the coordinate functions. That depends on the details of ##D##. In any case, we have:
$$(DF)(a)=\sum_{i=1}^n\big[H_i(a).(DX^i)(0)\big]$$If you are asking about another point that is not ##a##, then ##x## does just as well, although you might want to use ##x = b##.
$$(DF)(b)=\sum_{i=1}^n\big[X^i(b-a).(DH_i)(b)+H_i(b).(DX^i)(b-a)\big]$$Note these notations are equivalent:$$F(a) \equiv F(x) \big |_{x = a}$$
 
  • #9
PeroK said:
The first step is to apply the linear operator ##D## to both sides:
$$(DF)(x)=\sum_{i=1}^n\big[(x^i-a^i).(DH_i)(x)+H_i(x).Dx^i\big]$$Although, to really clarify what is going on we could introduce coordinate functions ##X^i(x) = x^i##. That allows us to avoid something like ##Dx^i## and have:
$$(DF)(x)=\sum_{i=1}^n\big[X^i(x-a).(DH_i)(x)+H_i(x).(DX^i)(x-a)\big]$$
Sorry I didn't notice before, but why is there ##x-a## in the very last term in the 2nd equation? I'm guessing it should be ##DX^i(x)##?
 
  • #10
Shirish said:
Sorry I didn't notice before, but why is there ##x-a## in the very last term in the 2nd equation? I'm guessing it should be ##DX^i(x)##?
It right as it is. It's true that for a differential operator the two will (probably) be equal. But, I was keeping the action of ##D## as general as possible until we have a specific operator in mind. The point of the exercise was to emphasise the formal structure of the equation of functions, acted on by an operator. You had a number of (often confusing) short cuts in your OP. I was trying to avoid that scenario.
 
  • #11
PS the assumption you want to make is that
$$D(X^i(x - a)) = D(X^i(x))$$If, for example, ##D \equiv \frac{\partial}{\partial x^j}##, then:
$$D(X^i(x - a)) = D(X^i(x)) = \frac{\partial x^i}{\partial x^j}= \delta^i_j$$
 
  • #12
PeroK said:
It right as it is. It's true that for a differential operator the two will (probably) be equal. But, I was keeping the action of ##D## as general as possible until we have a specific operator in mind. The point of the exercise was to emphasise the formal structure of the equation of functions, acted on by an operator. You had a number of (often confusing) short cuts in your OP. I was trying to avoid that scenario.
So a problematic case could be if ##D## is non-linear? If ##D## is linear, then $$D(X^i(x-a))=D(X^i(x))-D(X^i(a))=D(X^i(x))$$ since ##X^i## is also linear, and ##X^i(a)=a^i## is just a constant, so ##D(\text{constant})=0##. It didn't occur to me that there can be operators ##D## such that ##Dx^i\neq DX^i(x)##
 
  • #13
Shirish said:
So a problematic case could be if ##D## is non-linear?
We don't need a non-linear operator. Only an operator that does not map a constant function to the zero function. If ##D## were the identity operator, for example. Ironically, then it could be seen as the zeroth derivative!
Shirish said:
If ##D## is linear, then ##D(X^i(x-a))=D(X^i(x))-D(X^i(a))=D(X^i(x))## is what I think.
This does not hold for all operators. See above.
Shirish said:
It didn't occur to me that there can be operators ##D## such that ##Dx^i\neq DX^i(x)##
That's not what we are saying. We are saying that for some operators ##D(X^i(x)) \ne D(X^i(x - a))##.
 
  • #14
I'm sure I'm probably trying your patience by now, but please bear with me since I'm not very bright. You mentioned this:
PeroK said:
The first step is to apply the linear operator ##D## to both sides:
$$(DF)(x)=\sum_{i=1}^n\big[(x^i-a^i).(DH_i)(x)+H_i(x).Dx^i\big]$$
Call the above equation 1. All perfectly fine so far. Then you mention:
PeroK said:
Although, to really clarify what is going on we could introduce coordinate functions ##X^i(x) = x^i##. That allows us to avoid something like ##Dx^i## and have:
$$(DF)(x)=\sum_{i=1}^n\big[X^i(x-a).(DH_i)(x)+H_i(x).(DX^i)(x-a)\big]$$
Call this equation 2. What I'm trying to understand is - what's the pitfall of writing equation 1 in terms of coordinate functions like this: $$(DF)(x)=\sum_{i=1}^n\big[X^i(x-a).(DH_i)(x)+H_i(x).(DX^i)(x)\big]$$ Call the above equation 3. Equation 3 will be the wrong way to write only if ##(DX^i)(x)## is not the correct way to write ##Dx^i##, right? i.e. there is some operator ##D## for which ##Dx^i\neq DX^i(x)##
 
  • #15
Shirish said:
I'm sure I'm probably trying your patience by now, but please bear with me since I'm not very bright. You mentioned this:

Call the above equation 1. All perfectly fine so far. Then you mention:

Call this equation 2. What I'm trying to understand is - what's the pitfall of writing equation 1 in terms of coordinate functions like this: $$(DF)(x)=\sum_{i=1}^n\big[X^i(x-a).(DH_i)(x)+H_i(x).(DX^i)(x)\big]$$ Call the above equation 3. Equation 3 will be the wrong way to write only if ##(DX^i)(x)## is not the correct way to write ##Dx^i##, right? i.e. there is some operator ##D## for which ##Dx^i\neq DX^i(x)##
In post #6, I missed out the ##a^i## in the second term. I've fixed that now. The only question is whether we simplify the equation using ##D(x-a) = D(x)## or ##D(x^i - a^i) = D(x^i)## or ##D(X^i(x-a)) = D(X^i(x))##.
 

FAQ: Differential operator in multivariable fundamental theorem

What is a differential operator in the context of multivariable calculus?

A differential operator in multivariable calculus is an operator that acts on functions to produce derivatives. Common examples include the gradient, divergence, and curl. These operators are crucial for analyzing the behavior of multivariable functions and are foundational in fields such as physics and engineering.

What is the fundamental theorem of calculus for multivariable functions?

The fundamental theorem of calculus for multivariable functions connects the concept of differentiation and integration. It states that under certain conditions, the integral of a differential operator applied to a function over a region can be related to the values of the function on the boundary of that region, thereby linking local properties (derivatives) to global properties (integrals).

How does the fundamental theorem apply to vector fields?

The fundamental theorem of calculus for vector fields, often referred to as Green's Theorem, Stokes' Theorem, or the Divergence Theorem, states that the integral of a vector field over a surface can be expressed in terms of the integral of its curl or divergence over the volume bounded by that surface. This illustrates the relationship between a field's behavior in a region and its behavior on the boundary of that region.

What are the conditions for applying the fundamental theorem in multivariable calculus?

To apply the fundamental theorem of calculus in multivariable contexts, the functions involved typically need to be continuously differentiable over the domain. Additionally, the region of integration should have a well-defined boundary, and the vector fields should satisfy the necessary conditions such as continuity and differentiability to ensure the theorems hold true.

Can you provide an example of the fundamental theorem applied to a specific problem?

Consider a vector field F(x, y) = (y, x) defined over a region R in the xy-plane. By applying Green's Theorem, we can compute the line integral of F around the boundary of R by evaluating a double integral of the curl of F over the region R. This effectively illustrates how the local behavior of the field (its curl) relates to the global behavior (the line integral around the boundary).

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