Proving Limits in Multivariable Calculus: A Closer Look

In summary: This is because there are different norms in each space. So, for example, in Rn, the norm corresponding to the norm in \ell ^{2} is different from the norm corresponding to the norm in \ell ^{1}. So the answer to your question is that it depends on the space in question.
  • #1
ak416
122
0
Just wondering if anyone can prove these to me:

lim (x,y)->(a,b) f(x) * g(y) = lim x->a f(x) * lim y->b g(x) (As well as the n dimensional case)

Also, why when you try to show that a limit doesn't exist you can keep a variable constant, or do something like y=x, or approach from some other path and show that one path of approach doesn't give the same limit as another path of approach. This statement seems kind of ambiguous to me. Is there a rigorous way of proving this using the definition of the limit in Rn?

These are'nt specific questions of the textbook just things i am curious about and want to gain a better understanding
 
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  • #2
ak416 said:
Just wondering if anyone can prove these to me:
lim (x,y)->(a,b) f(x) * g(y) = lim x->a f(x) * lim y->b g(x) (As well as the n dimensional case)
Also, why when you try to show that a limit doesn't exist you can keep a variable constant, or do something like y=x, or approach from some other path and show that one path of approach doesn't give the same limit as another path of approach. This statement seems kind of ambiguous to me. Is there a rigorous way of proving this using the definition of the limit in Rn?
These are'nt specific questions of the textbook just things i am curious about and want to gain a better understanding

The definition of limit, [itex]lim\x\rightarrow a f(x)= L[/itex] in the ndimensional case is (f: Rn-> Rm, x and a are n-vectors, L is an m-vector):
Given [itex]\epsilon> 0[/itex] there exist a number [itex]\delta> 0[/itex] such that if ||x- a||< [itex]\delta[/itex] then [itex]||f(x)- L||< \epsilon[/itex]. "|| ||" is, of course, some norm in Rn. One of the nice things about finite dimensional space, Rn, is that the norm, [itex]||v||= max{|x_1|, |x_2|, ..., |x_n|}[/itex] gives exactly the same "topology" (i.e. limits, etc.) properties as the "usual norm" [itex]||v||= \sqrt{x_0^2+ x_1^2+ ...+ x_n^2}[/itex]. That means that you can look at the x and y components separately. That's why
[itex]lim_{(x,y)\rightarrow (a,b)}f(x)g(y)= \left(lim_{x\rightarrowa}f(x)\right)\left(lim_{x\rightarrowb}g(y)[/itex]

The point of showing that a limit, as x-> a of f(x), does NOT exist by showing that limits taken in two different ways do NOT give the same result is due to the fact that saying the limit is, say, L, means that for any x sufficiently close to the a, f(x) is "close" to L.

If, by taking the limits in two different paths, you get two different limits, say L1 and L2, that means that there are points, x, y, as close as you wish to a, on each path, such that f(x) is close to L1 and f(y) is close to L2. Taking, say, [itex]\epsilon= \frac{L_1-L2}{3}, shows that either x or y is does not give a value within [itex]\epsilon[/itex].
 
  • #3
thanks for the reply, i feel somewhat more confident now.
 
  • #4
but does this mean that the limit exists if it is exists on at least one norm or it must exist for all norms? I am guessing if it exists on at least one norm it will exist on all norms..
 
  • #5
If your space is finite dimensional, you can show that the various norms:
[tex]||<x_1, x_2, ..., x_n>|| = \sqrt{x_1^2+ x_2^2+ ...+ x_n^2}[/tex]
[tex]||<x_1, x_2, ..., x_n>|| = |x_1|+ |x_2|+ ... + |x_n|[/tex]
[tex]||<x_1, x_2, ..., x_n>|| = max{|x_1|, |x_2|, ..., |x_n|}[/itex]
Then, yes, a sequnce converges in all of those norms if and only if it converges in anyone of them (and converges to the same thing in all norms.)

However, there are norms corresponding to those in infinite dimensional spaces (such as function spaces) that give very different results.

Even in finite dimensional spaces (even in R itself) one could use the "discrete" norm (||v||= 0 if v= 0, 1 otherwise) which gives the result that only constant sequences converge.
 
  • #6
Those norms are finite dimensional analogs of the norms in [tex]\ell ^{2},\ell ^{1},\mbox{ and }\ell ^{\infty},[/tex] correct? Do similar results apply to those spaces and, say [tex]\ell ^{p},L^{p},..[/tex]? How about Hilbert or Banach spaces in general? I'm just learning about these spaces so that I am curious enough to ask (but should these have obvious answers, just tell me to go study harder.)
 
  • #7
benorin said:
Those norms are finite dimensional analogs of the norms in [tex]\ell ^{2},\ell ^{1},\mbox{ and }\ell ^{\infty},[/tex] correct? Do similar results apply to those spaces and, say [tex]\ell ^{p},L^{p},..[/tex]? How about Hilbert or Banach spaces in general? I'm just learning about these spaces so that I am curious enough to ask (but should these have obvious answers, just tell me to go study harder.)
Yes those are the "infinite" dimensional spaces I was talking about. But notice that I said "However, there are norms corresponding to those in infinite dimensional spaces (such as function spaces) that give very different results."

In particular, L0(C) is defined as the set of all continuous function on compact set C with norm |f|= max|f(x)|, maximum taken over all x in C. That corresponds directly to the [itex]|||| = max{|x_1|, |x_2|, ..., |x_n|}[/itex] norm on Rn.

L1(C) is the set of (Lebesque) integrable functions on C with norm [tex]|f|= \int_C|f(x)|dx. That corresponds directly to the [itex]|||| = |x_1|+ |x_2|+ ... + |x_n|[/itex] norm.

L2(C) is the set function whose square is (Lebesque) integrable on C with norm [tex]|f|= \sqrt{\int_C f^2(x)dx}[/tex]. That corresponds directly to the "usual" norm[tex]|||| = \sqrt{x_1^2+ x_2^2+ ...+ x_n^2}[/tex]

In general, Lp(c) is the set of functions whose pth power is (Lebesque) integrable on C with norm [tex]|f|= ^p\sqrt{\int_C f^p(x)dx}[/tex]. There is the obvious analog on Rn but I've never seen it used except for p= 2.


However, while all three norms give exactly the same topology and so the same convergence on Rn, that is not true for their infinite dimensional analogs. The Lp spaces are quite different for different p.

As far as Hilbert and Banach spaces in general are concerned, the inner product and norm are part of the definition. Exactly the same set with different norms defined will, in general, be different Banach spaces.
 
  • #8
Thanx Ivy.
 

Related to Proving Limits in Multivariable Calculus: A Closer Look

1. What is the purpose of proving limits in multivariable calculus?

The purpose of proving limits in multivariable calculus is to determine the behavior of a function as it approaches a specific point in a multi-dimensional space. This is important in understanding the continuity and differentiability of a function, and is a fundamental concept in multivariable calculus.

2. How are limits in multivariable calculus different from limits in single variable calculus?

Limits in multivariable calculus involve multiple variables, whereas limits in single variable calculus only involve one variable. In multivariable calculus, the function approaches a specific point in a multi-dimensional space, whereas in single variable calculus, the function approaches a specific value on a one-dimensional number line.

3. What are some common techniques used to prove limits in multivariable calculus?

Some common techniques used to prove limits in multivariable calculus include the epsilon-delta definition, the squeeze theorem, and the use of polar or spherical coordinates. These techniques involve manipulating the function and its variables in different ways to show that the limit exists.

4. What are some challenges that may arise when proving limits in multivariable calculus?

One of the main challenges in proving limits in multivariable calculus is visualizing and understanding the behavior of a function in multiple dimensions. This can become increasingly complex as the number of variables and dimensions increases. Additionally, the use of different coordinate systems and techniques can also add to the difficulty of proving limits.

5. How are limits in multivariable calculus applied in real-world situations?

Limits in multivariable calculus are commonly used in physics, engineering, and other fields to model and understand the behavior of systems with multiple variables. For example, in fluid dynamics, limits can be used to determine the velocity of a fluid at a specific point in a three-dimensional space. In economics, limits can be used to analyze the behavior of markets with multiple variables, such as supply and demand.

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