Differentiable multivariable functions

In summary, local linearity is defined as the existence of partial derivatives and the tendency of the difference between function values and the linear approximation to approach zero faster than the distance between the input and the point of evaluation. This may seem counterintuitive, as one may expect both the difference between function values and the distance between the input and the point of evaluation to approach zero at the same rate. However, this is not always the case and can be seen in the function f(x)=x^2 and its derivative f'(a)>0. The reasoning for this is still under discussion and may vary depending on different perspectives.
  • #1
hholzer
37
0
Defining differentiability for multivariable functions we want not only
for the partial derivatives to exist but also local linearity.

Because my question is the same also for the single variable
case, I'll pose it with a single variable function.

In one variable we have that local linearity at a point is
such that E(x) = f(x) - L(x) tends to zero faster than
|x - a| as x -> a does.

My question is how can the difference between function values
tend to zero faster than the distance between |x-a|? My current,
and broken intuition, expects them to tend to zero at the same
time. Why is this not the case?
 
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  • #2
Consider the function [tex]f(x)=x^2[/tex]. How close to f(0)=0 is f(x), when x is 0.5? 0.1? 0.001?
 
  • #3
if the derivative is f'(a)>0, then it means that the ratio (f(x)-f(x))/(x-a) "stabilizes" to f'(a) as x-->a.. so wouldn't you say this implies that f(x)-f(x) and x-a to go 0 "at the same rate"?
 
  • #4
Tinyboss: I understand where you are going with that but why is that the case? What is the reasoning?

Quasar987: I would agree with that but my book is saying that |x-a| as x->a goes to zero faster than f(x) - L(x). Which is different than what you are saying.
 

What is a differentiable multivariable function?

A differentiable multivariable function is a mathematical function that takes multiple input variables and produces a single output value, and is continuously differentiable at each point in its domain. This means that the function has a well-defined derivative at every point, allowing for the calculation of its slope or rate of change.

How is differentiability defined for multivariable functions?

Differentiability for multivariable functions is defined using partial derivatives, which represent the rate of change of the function with respect to each individual input variable. If all of these partial derivatives exist and are continuous, then the function is considered differentiable.

What is the significance of differentiability for multivariable functions?

Differentiability is important for multivariable functions because it allows for the calculation of their gradients, which represent the direction and magnitude of the function's steepest ascent. This information is useful in optimization problems, where the goal is to find the input values that maximize or minimize the function's output.

Can a function be differentiable but not continuous?

No, a function cannot be differentiable if it is not continuous. This is because differentiability requires the existence of a well-defined derivative at every point in the function's domain, and a function cannot have a derivative at a point where it is not continuous.

What are some common applications of differentiable multivariable functions?

Differentiable multivariable functions have numerous applications in fields such as physics, economics, and engineering. They are used to model complex systems and phenomena, and their derivatives provide valuable information for making predictions and optimizing outcomes in these systems.

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