True or false: Differentiability with vectors

In summary: False. Differentiability of a vector valued function of three variables is determined by the following equation: \lim_{(\Delta x, \Delta y)\rightarrow\ (0,0)}\frac {\Delta f - f_x (x_0, y_0)\Delta x - f_y(x_0,y_0) \Delta y}{\sqrt{(\Delta x)^2 + (\Delta y)^2}} = 0
  • #1
Justhanging
18
0
If all the first partial derivatives of f exist at [tex]\vec{x}[/tex], and if [tex]
\lim_{\vec{h}\rightarrow\vec{0}}\frac {f(\vec{x})-(\nabla f(\vec{x}))\cdot\vec{h}}{||\vec{h}||} = 0
[/tex]

Then f is differentiable at [tex]\vec{x}[/tex]

Note: Its the magnitude of h on the bottom.

First of all, I don't exactly understand what a function of a vector is like f([tex]\vec{x}[/tex]). Does it mean that this function is evaluated at the terminal point of this vector?
 
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  • #2
Just guessing trying to fix your TeX for you:

[tex]\lim_{\vec{h}\rightarrow\vec{0}}\frac {f(\vec{x})-(\nabla f(\vec{x}))\cdot\vec{h}}{|\vec{h}|} = 0 [/tex]

Click on it to see it.
 
  • #3
LCKurtz said:
Just guessing trying to fix your TeX for you:

[tex]\lim_{\vec{h}\rightarrow\vec{0}}\frac {f(\vec{x})-(\nabla f(\vec{x}))\cdot\vec{h}}{|\vec{h}|} = 0 [/tex]

Click on it to see it.

You sure know your latex, sorry its my first time and it was late. Everything is right except its the magnitude of h on the bottom not the absolute value. I don't if the notation is the same.
 
  • #4
Yes, say the vector x has components (1,-4,3). Then f(x) = f(1,-4,3). And yes, the absolute value notation, |h|, is often used instead of ||h|| to mean the magnitude of a vector.
 
  • #5
First, do you understand what [itex]\nabla\vec{f}[/itex] means?

And what is your definition of "differentiable" for a vector valued function of 3 variables?
 
  • #6
HallsofIvy said:
First, do you understand what [itex]\nabla\vec{f}[/itex] [means?

And what is your definition of "differentiable" for a vector valued function of 3 variables?

Yes it means the gradient of f evaluated at the terminal point of the vector.

My equation for differentiability taken from the book is:

[tex]
\lim_{(\Delta x, \Delta y)\rightarrow\ (0,0)}\frac {\Delta f - f_x (x_0, y_0)\Delta x - f_y(x_0,y_0) \Delta y}{\sqrt{(\Delta x)^2 + (\Delta y)^2}} = 0
[/tex]

If [tex] \vec{h} [/tex] is taken to be [tex] (\Delta x, \Delta y) [/tex] than the dot product of h and the gradient evaluated at the vector x is:

[tex]
f_x (\vec{x}) \Delta x + f_y(\vec{x}) \Delta y
[/tex]

Then

[tex]
\lim_{(\Delta x, \Delta y)\rightarrow\ (0,0)}\frac {f(\vec{x}) - f_x (\vec{x})\Delta x - f_y(\vec{x}) \Delta y}{\sqrt{(\Delta x)^2 + (\Delta y)^2}} = 0

[/tex]

I distributed the minus from the original problem but am not exactly sure if I can. It looks very similar to the definition with the exception of deltaF being missing. Is this the only reason why the statement is false? I don't exactly understand the deltaF concept as being approximately [tex] f_x (\vec{x}) \Delta x + f_y(\vec{x}) \Delta y [/tex]
 
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FAQ: True or false: Differentiability with vectors

1. What is the definition of differentiability with vectors?

Differentiability with vectors refers to the ability to take the derivative of a vector-valued function. It is a measure of how smooth and continuous a function is at a particular point.

2. How is differentiability with vectors related to the concept of continuity?

Differentiability is a stronger condition than continuity. A function must be continuous in order to be differentiable, but not all continuous functions are differentiable. Differentiability with vectors takes into account both the magnitude and direction of change in a vector-valued function, whereas continuity only considers the magnitude.

3. What is the significance of differentiability with vectors in real-world applications?

Differentiability with vectors is essential in many fields, particularly in physics and engineering. It allows for the analysis of how a vector-valued quantity changes over time, and is crucial in understanding motion, forces, and other physical phenomena.

4. Can a function be differentiable with vectors but not continuous?

No, a function must be continuous in order to be differentiable. However, a function can be continuous but not differentiable if it has a sharp point or corner at a certain point.

5. How is the concept of differentiability with vectors extended to higher dimensions?

In higher dimensions, differentiability with vectors is known as differentiability with multivariate functions. It involves taking partial derivatives in each direction of a multi-dimensional space, and the concept remains the same as in two or three dimensions.

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