Derivatives in Higher Dimensions

In summary, according to Munkres, if a neighborhood of a point exists in an R^n space, then the function $f$ is differentiable there.
  • #1
joypav
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Looking at Munkres "Analysis on Manifolds", it says for $A\subset R^n, f: A \rightarrow R^m$ suppose that $A$ contains a neighborhood of $a$. Then $f$ is differentiable at $a$ if there exists an $n$ by $m$ matrix $B$ such that,

$\frac{f(a+h)-f(a)-Bh}{\left| h \right|}\rightarrow 0$ as $h\rightarrow 0$​
($B$ is called the derivative of $f$ at $a$)

The definition seems a-ok, but I am trying to just work a simple problem so that I can see it in action and I am stuck.

Say $f(x,y)=(xy, x^2)$. Obviously, $f: R^2 \rightarrow R^2$.
And let $B = \left[\begin{array}{c} a & b \\ c & d \end{array}\right]$
We are in $R^2$ so $h = \left[\begin{array}{c}h_1 \\ h_2 \end{array}\right]$.

$f(x+h_1, y+h_2) - f(x,y) = \left[\begin{array}{c}(x+h_1)(y+h_2) \\ (x+h_1)^2 \end{array}\right]-\left[\begin{array}{c}xy \\ x^2 \end{array}\right]=\left[\begin{array}{c}xh_2+yh_1+h_1h_2 \\ 2xh_1+h_1^2 \end{array}\right]$

$B\cdot h = \left[\begin{array}{c} a & b \\ c & d \end{array}\right]\cdot \left[\begin{array}{c}h_1 \\ h_2 \end{array}\right] = \left[\begin{array}{c} ah_1+bh_2 \\ ch_1+dh_2 \end{array}\right]$

$f(x+h_1, y+h_2) - f(x,y) - B\cdot h = \left[\begin{array}{c}xh_2+yh_1+h_1h_2-ah_1-bh_2 \\ 2xh_1+h_1^2-ch_1-dh_2 \end{array}\right]$

We need to choose $a, b, c, d$ so that,
$\frac{1}{\sqrt{h_1^2+h_2^2}} \cdot \left[\begin{array}{c}xh_2+yh_1+h_1h_2-ah_1-bh_2 \\ 2xh_1+h_1^2-ch_1-dh_2 \end{array}\right] \rightarrow 0$ as $(h_1, h_2) \rightarrow 0$

Meaning, we need,
$\frac{xh_2+yh_1+h_1h_2-ah_1-bh_2}{\sqrt{h_1^2+h_2^2}} \rightarrow 0$ as $(h_1, h_2) \rightarrow 0$
and
$\frac{2xh_1+h_1^2-ch_1-dh_2}{\sqrt{h_1^2+h_2^2}} \rightarrow 0$ as $(h_1, h_2) \rightarrow 0$

OKAY, now that that's all out there, I need help! First of all, is there a simple way to figure this out from what I have?
From previous things I've worked on, I believe I can just find $B$ with partial derivatives. So it should be
$B = \left[\begin{array}{c} y & x \\ 2x & 0 \end{array}\right]$

How do I go about getting this? Or do I just need to show that this $B$ will work?
 
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  • #2
Hey joypav,

We can write:
$$\lim_{(h_1,h_2)\to 0}\frac{xh_2+yh_1+h_1h_2-ah_1-bh_2}{\sqrt{h_1^2+h_2^2}}
=\lim_{(h_1,h_2)\to 0}\frac{(x-b)h_2+(y-a)h_1+h_1h_2}{\sqrt{h_1^2+h_2^2}} = 0$$
For the limit to be zero, it needs to be zero on any path that $(h_1,h_2)$ can take to zero.
So for instance along the path where $h_1=0$ and $h_2\to 0^+$.
Suppose $x-b\ne 0$. Then along that path, the limit is $x-b\ne 0$, which is a contradiction. Therefore we must have $b=x$.
Similarly we must have $a=y$.
We can prove that the remaining expression has indeed the limit $0$.

The same reasoning applies to the other limit.And yes, one might also show that the $B$ you found with partial derivatives just works.
Do note that it's possible that a partial derivative does not exist, even though we can still find the derivative of $f$ at a point.
And a matrix with partial derivatives is also not guaranteed to work in all cases, even if it exists.
In other words, the definition that Munkres gives is certainly relevant.Btw, I hope you don't mind, but I'd classify this as Calculus, so I've moved the thread there.
 
  • #3
That makes a lot more sense. Thank you!
 

FAQ: Derivatives in Higher Dimensions

What are derivatives in higher dimensions?

Derivatives in higher dimensions are a mathematical concept used to describe the rate of change of a function with respect to multiple variables. In simple terms, it is a way to measure how a function changes as its inputs change.

How are derivatives in higher dimensions different from single variable derivatives?

Unlike single variable derivatives, which only consider the change of a function with respect to one variable, derivatives in higher dimensions take into account the change of a function with respect to multiple variables simultaneously. This allows for a more comprehensive understanding of how a function behaves.

What is the notation for derivatives in higher dimensions?

The notation for derivatives in higher dimensions is similar to that of single variable derivatives, but with additional subscripts to indicate which variable the derivative is being taken with respect to. For example, the derivative of a function f(x,y) with respect to x would be denoted as ∂f/∂x.

What is the geometric interpretation of derivatives in higher dimensions?

In higher dimensions, derivatives can be interpreted as the slope of a tangent line or plane to a function at a specific point. This can be visualized as the instantaneous rate of change of the function at that point.

How are derivatives in higher dimensions used in real-world applications?

Derivatives in higher dimensions have a wide range of applications in fields such as physics, economics, and engineering. They are used to model and analyze complex systems, optimize functions, and make predictions about the behavior of a system. Examples include using derivatives to calculate the trajectory of a projectile, optimize a company's production process, or predict the stock market.

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