Partial Derivatives: Find $\frac{\partial^2{w}}{\partial{u}\partial{v}}$

In summary, we have a two variable function $w=f(x, y)$ with $x=u+v$ and $y=u-v$. Using the chain rule, we can show that $\frac{\partial^2{w}}{\partial{u}\partial{v}}=\frac{\partial^2{w}}{\partial{x^2}}-\frac{\partial^2{w}}{\partial{y^2}}$. The formulation appears to be correct and no improvements are needed.
  • #1
mathmari
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Hey! :eek:

Let $w=f(x, y)$ a two variable function and $x=u+v$, $y=u-v$.
Show that $$\frac{\partial^2{w}}{\partial{u}\partial{v}}=\frac{\partial^2{w}}{\partial{x^2}}-\frac{\partial^2{w}}{\partial{y^2}}$$

I have done the following:

We have $w(x(u,v), y(u, v))$.

From the chain rule we have: $$\frac{\partial{w}}{\partial{v}}=\frac{\partial{w}}{\partial{x}}\frac{\partial{x}}{\partial{v}}+\frac{\partial{w}}{\partial{y}}\frac{\partial{y}}{\partial{v}}=\frac{\partial{w}}{\partial{x}} \cdot 1+\frac{\partial{w}}{\partial{y}} \cdot (-1)=\frac{\partial{w}}{\partial{x}}-\frac{\partial{w}}{\partial{y}}$$

We apply again the chain rule, so:
$$\frac{\partial}{\partial{u}}\left (\frac{\partial{w}}{\partial{v}}\right )=\frac{\partial}{\partial{x}}\left (\frac{\partial{w}}{\partial{v}}\right ) \frac{\partial{x}}{\partial{u}}+\frac{\partial}{\partial{y}}\left (\frac{\partial{w}}{\partial{v}}\right )\frac{\partial{y}}{\partial{u}}=\frac{\partial}{\partial{x}}\left (\frac{\partial{w}}{\partial{x}}-\frac{\partial{w}}{\partial{y}}\right ) \cdot 1+\frac{\partial}{\partial{y}}\left (\frac{\partial{w}}{\partial{x}}-\frac{\partial{w}}{\partial{y}}\right ) \cdot 1\\ =\frac{\partial^2{w}}{\partial{x^2}}-\frac{\partial^2{w}}{\partial{x}\partial{y}}+\frac{\partial^2{w}}{\partial{x}\partial{y}}-\frac{\partial^2{w}}{\partial{y^2}}=\frac{\partial^2{w}}{\partial{x^2}}-\frac{\partial^2{w}}{\partial{y^2}}$$

Is it correct?? (Wondering)

Could I improve something at the formulation?? (Wondering)
 
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  • #2
Looks good to me. (Yes)
 

FAQ: Partial Derivatives: Find $\frac{\partial^2{w}}{\partial{u}\partial{v}}$

What is the purpose of finding partial derivatives?

The purpose of finding partial derivatives is to calculate the rate of change of a function with respect to one of its variables while holding all other variables constant. It allows us to study the behavior of a function in multiple dimensions and is often used in fields such as physics, engineering, and economics.

How is the notation for partial derivatives interpreted?

The notation for partial derivatives, such as $\frac{\partial{w}}{\partial{u}}$, is interpreted as the derivative of the function $w$ with respect to the variable $u$, while holding all other variables constant. It is a way of specifying which variables are being treated as constants in the differentiation process.

What is the difference between a partial derivative and a regular derivative?

A partial derivative is a derivative of a multivariable function with respect to one of its variables, while holding all other variables constant. A regular derivative, on the other hand, is the derivative of a single-variable function with respect to its input. In other words, a partial derivative takes into account the effect of only one variable on the function, while a regular derivative considers the effect of all variables.

Can we find higher order partial derivatives?

Yes, just like regular derivatives, we can find higher order partial derivatives by taking the partial derivative of the previous partial derivatives. For example, to find $\frac{\partial^2{w}}{\partial{u}^2}$, we would take the partial derivative of $\frac{\partial{w}}{\partial{u}}$ with respect to $u$.

How do we use partial derivatives to find maximum or minimum points of a function?

To find maximum or minimum points of a function using partial derivatives, we first find the critical points by setting all partial derivatives equal to 0 and solving for the variables. Then, we use the second derivative test to determine whether the critical points are maximum, minimum, or saddle points. This involves taking the second partial derivative and evaluating it at the critical point. If the result is positive, the point is a minimum, if it is negative, the point is a maximum, and if it is 0, the test is inconclusive.

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