Continuity for Multivariable Functions

In summary, the conversation discusses how to define continuity for multivariate functions and the use of topological and set theoretical definitions. The concept is explained in terms of metrics, and the use of epsilon-delta proofs for continuity is suggested. The conversation also mentions the difficulty in proving continuity for functions with multiple variables and suggests using basic functions and theorems for proof. The conversation also mentions differentiability and the use of vectors in epsilon-delta proofs. Finally, it is stated that the addition of vectors implies continuity.
  • #1
brydustin
205
0
Just curious how to define continuity for mult dim. functions. I know that the topological and set theorectical definitions work in a very abstract setting; but I just don't know how to prove (for example) that f(x,y) = x + y or f(t,z) = t*z is continuous, other than saying something like: Well because f(t)=t is continuous and ..., therefore the composition of... and hence it is continuous. I was wondering if there is a generalization for delta-epsilon defition that would cover any (actual) function (as opposed to some abstract space,etc): R to R and R^n to R^m (where m,n are any positive integers and may or may not be equal). Can we possibly express epsilon-delta as a vector? A stretch maybe? Thanks for any help,... I'm teaching myself topology and more analysis right now! got to love it!
 
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  • #2
What do you mean an (actual) function as opposed to some abstract space? This doesn't seem to make much sense because we obviously need the point-set before we can define the function. In a metric space, we can define continuity in terms of the metric, and if we have a function f from R^n to R^m, we're just working with the usual topology. Thus continuity of f at a point a in R^n is just the same old "for every epsilon > 0 there exists a delta > 0 such that d(x, a) < delta implies d(f(x), f(a)) < epsilon" where x is in R^n and d is the standard euclidean distance.
 
  • #3
what are you reading? Isn't this explained in every book on several variable calculus? i like courant, volume 2, and wendell fleming's book. basically you define the length of a vector |(a,b,c)| = sqrt(a^2+b^2+c^2), and do all the epsilon delta in those terms, word for word the same as in one variable.

It's differentiability where you have to do something new, because you can't divide vectors.|x+y| ≤ |x| + |y|, implies continuity of addition.
 
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  • #4
brydustin said:
Just curious how to define continuity for mult dim. functions. I know that the topological and set theorectical definitions work in a very abstract setting; but I just don't know how to prove (for example) that f(x,y) = x + y or f(t,z) = t*z is continuous, other than saying something like: Well because f(t)=t is continuous and ..., therefore the composition of... and hence it is continuous. I was wondering if there is a generalization for delta-epsilon defition that would cover any (actual) function (as opposed to some abstract space,etc): R to R and R^n to R^m (where m,n are any positive integers and may or may not be equal). Can we possibly express epsilon-delta as a vector? A stretch maybe? Thanks for any help,... I'm teaching myself topology and more analysis right now! got to love it!

Of course, even with functions of one variable, nobody would use the epsilon-delta kind of argument for an "actual" function something like

[tex]f(x) = \frac{e^{\sin(x)}\sqrt{1+x^3}}{3x^2+7}[/tex]

You prove continuity for the basic functions and use the theorems about products, quotients, compositions etc. The same thing is true for functions of 2 variables.
 
  • #5
brydustin said:
but I just don't know how to prove (for example) that f(x,y) = x + y or f(t,z) = t*z is continuous, other than saying something like: Well because f(t)=t is continuous and ..., therefore the composition of...
Note that continuity along lines parallel to the z and t axes does not imply continuity of the function; consider
[tex]
f(z,t) = \left\{\begin{array}{ll}
\frac{|t|e^{-\frac{|t|}{z^2}}}{z^2} & z\neq 0 \\
0 & z=0 \end{array}
[/tex]
in the neighborhood of (0,0). Although the limits along the axes both exist and are equal to the value of the function at (0,0), [itex]\lim_{(z,t)\rightarrow (0,0)} f(z,t)[/itex] does not exist.
 
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  • #6
Actually the book I'm using is Real Analysis by Norman B Haaser and Joseph A Sullivan. It explains the concept of continuity on metric spaces but doesn't given any examples other than those of one variable however wants the reader to do examples of more than one variable as practice problems.

So I still don't have a clue how to prove that x+y is continuous. Any more help?


mathwonk said:
what are you reading? Isn't this explained in every book on several variable calculus? i like courant, volume 2, and wendell fleming's book. basically you define the length of a vector |(a,b,c)| = sqrt(a^2+b^2+c^2), and do all the epsilon delta in those terms, word for word the same as in one variable.

It's differentiability where you have to do something new, because you can't divide vectors.


|x+y| ≤ |x| + |y|, implies continuity of addition.
 

Related to Continuity for Multivariable Functions

What is continuity for multivariable functions?

Continuity for multivariable functions is the property that describes a function's behavior when its input variables change. It means that as the input variables approach a certain value, the output values also approach a certain value, without any abrupt or sudden changes in between.

How is continuity defined for multivariable functions?

The concept of continuity for multivariable functions is similar to the one-dimensional case. A function f(x, y) is continuous at a point (a, b) if the limit of the function as (x, y) approaches (a, b) is equal to the value of the function at (a, b).

What is the importance of continuity for multivariable functions?

Continuity for multivariable functions is important in many areas of mathematics, including calculus, differential equations, and optimization. It allows us to make predictions and analyze the behavior of functions in various contexts.

How is continuity different from differentiability for multivariable functions?

Continuity and differentiability are related concepts, but they are not the same. A function can be continuous but not differentiable, meaning that it is smooth and has no abrupt changes but does not have a defined slope at certain points. Differentiability requires not only continuity but also a defined slope at every point.

Can multivariable functions be discontinuous?

Yes, multivariable functions can be discontinuous. In general, a multivariable function can be discontinuous at a point if the limit of the function at that point does not exist, or if the limit exists but is not equal to the value of the function at that point. This can happen due to abrupt changes or jumps in the function, or because the function is not defined at that point.

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