Directional & Partial Derivatives .... working from the definition

In summary, the conversation is about understanding and clarifying the definition of partial derivative as presented by Shmuel Kantorovitz in his book "Several Real Variables." The main focus is on equation (2.3) in the proof of Kantorovitz's Proposition on pages 61-62 and how it relates to the definition of partial derivative. The conversation also includes confusion about the use of a variable tending to zero in the definition and in equation (2.3).
  • #1
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I am reading the book "Several Real Variables" by Shmuel Kantorovitz ... ...

I am currently focused on Chapter 2: Derivation ... ...

I need help with an element of the proof of Kantorovitz's Proposition on pages 61-62 ...

Kantorovitz's Proposition on pages 61-62 reads as follows:

Kantorovitz - 1 - Proposition Page 61 ... PART 1 ... .png

Kantorovitz - 2 - Proposition Page 61 ... PART 2 ... .png
I am trying to understand the above proof in terms of the definitions of directional and partial derivatives (in terms of limits) ... but I am having trouble understanding equation (2.3) above ... specifically I am concerned regarding how (2.3) follows from Kantorovitz's definition of partial derivative ...

I will explain my difficulties in terms of Kantorovitz's definitions as he develops them on page 60 ... as follows:
Kantorovitz - Definition of directional and partial derivatives ... .png
Now ... I am trying to understand how the definition of partial derivative applies to equation (2.3) in the proof of the proposition ... so for equation (2.1) of the definition we put ##u = e^j## (because we are dealing with partial derivatives) ... ... and so (2.1) becomes:##F(t) = f( x + t e^j)##

so then for ##F_j## in the proof (see the expression that is above the expression (2.3)) ... we have

##F_j (t) = f ( x + h^{j-1} + te^j )##and we appear to be dealing (for some reason?) with ##( x + h^{j-1} )## instead of ##x## ...

... which is OK ... just put ##x = x + h^{j-1}## ...... BUT ...In Definition 2.1.1 Kantorovitz defines the partial derivative this way:##\frac { \partial f }{ \partial x_j } := F'(0) = \lim_{ t \rightarrow 0 } \frac{ F(t) - F(0) }{t}####= \lim_{ t \rightarrow 0 } \frac{ f ( x + h^{j-1} + te^j ) - f(x) }{t} ##... ... is the above correct?Now ... my question is as follows: (pertaining largely to equation (2.3) )

What is the definition of ## F_j'(t)## ... and working strictly and rigorously from the definition how do we obtain

##F'_j (t) = \frac { \partial f }{ \partial x_j } f ( x + h^{j-1} + te^j )##

Hope someone can help ...

Peter***NOTE***

I have to say I find it somewhat confusing in trying to work from the definition of partial derivative, that Kantorovitz gives the definition for partial and directional derivative in terms of expressions where ##t## tends to zero ... and then equation (2.3) above is a partial derivative with ##t## as a variable ... as in ##F'_J(t)## ... surely ##t \rightarrow 0## as per the definition ...
 

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  • #2
\begin{align*}
F'_j(t)
&=\frac d{dt}f(x+h^{j-1}+te^j)\\
&=\lim_{s\to 0}\left(
\frac{f(x+h^{j-1}+(t+s)e^j)-f(x+h^{j-1}+te^j)}{s}\right)\\
&=\lim_{s\to 0}\left(
\frac{f(x+h^{j-1}+te^j+se^j)-f(x+h^{j-1}+te^j)}{s}\right)\\
&=\lim_{s\to 0}\left(
\frac{f(x+h^{j-1}+te^j+se^j)-f(x+h^{j-1}+te^j)}{s}\right)\\
&=\lim_{s\to 0}\left(
\frac{f(y+se^j)-f(y)}{s}\right)
\quad\quad\textrm{[where $y=x+h^{j-1}+te^j$]}\\
&=\frac{\partial f}{\partial u}(y)
\quad\quad\textrm{[where $u=e^j$, and refer Definition 2.1.1]}\\
&=\frac{\partial f}{\partial x_j}(y)
\quad\quad\textrm{[just changing notation from Directional Derivative to Partial Derivative, per Definition 2.1.1]}\\
&=\frac{\partial f}{\partial x_j}(x+h^{j-1}+te^j)
\quad\quad\textrm{[substituting back for $y$]}
\end{align*}
 
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  • #3
andrewkirk said:
\begin{align*}
F'_j(t)
&=\frac d{dt}f(x+h^{j-1}+te^j)\\
&=\lim_{s\to 0}\left(
\frac{f(x+h^{j-1}+(t+s)e^j)-f(x+h^{j-1}+te^j)}{s}\right)\\
&=\lim_{s\to 0}\left(
\frac{f(x+h^{j-1}+te^j+se^j)-f(x+h^{j-1}+te^j)}{s}\right)\\
&=\lim_{s\to 0}\left(
\frac{f(x+h^{j-1}+te^j+se^j)-f(x+h^{j-1}+te^j)}{s}\right)\\
&=\lim_{s\to 0}\left(
\frac{f(y+se^j)-f(y)}{s}\right)
\quad\quad\textrm{[where $y=x+h^{j-1}+te^j$]}\\
&=\frac{\partial f}{\partial u}(y)
\quad\quad\textrm{[where $u=e^j$, and refer Definition 2.1.1]}\\
&=\frac{\partial f}{\partial x_j}(y)
\quad\quad\textrm{[just changing notation from Directional Derivative to Partial Derivative, per Definition 2.1.1]}\\
&=\frac{\partial f}{\partial x_j}(x+h^{j-1}+te^j)
\quad\quad\textrm{[substituting back for $y$]}
\end{align*}
Thanks Andrew ..

Just working through your post and reflecting on what you have written ...

Most grateful for the help ...

Peter
 

1. What is the definition of directional derivative?

The directional derivative is a measure of how much a function changes along a specific direction. It is calculated by taking the dot product of the gradient of the function and a unit vector in the desired direction.

2. How is the directional derivative related to partial derivatives?

The directional derivative is a generalization of partial derivatives. It can be thought of as the partial derivative in the direction of a unit vector. By taking the dot product of the gradient and a unit vector, we can calculate the directional derivative in any desired direction.

3. Can the directional derivative be negative?

Yes, the directional derivative can be negative. This indicates that the function is decreasing in the direction of the unit vector. A positive directional derivative indicates that the function is increasing in the given direction.

4. What is the difference between directional and partial derivatives?

The main difference between directional and partial derivatives is the direction in which they are calculated. Partial derivatives are calculated in the direction of the x and y axes, while directional derivatives can be calculated in any desired direction. Additionally, partial derivatives are used to find the rate of change of a function with respect to a specific variable, while directional derivatives measure the rate of change along a specific direction.

5. How are directional and partial derivatives used in real-world applications?

Directional and partial derivatives are used in many fields of science and engineering to solve optimization problems. They allow us to find the direction in which a function has the steepest increase or decrease, which is useful for finding maximum and minimum values of a function. They are also used in physics to calculate the rate of change of physical quantities, such as velocity and acceleration.

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