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(a) Find all the first partial derivatives of the following functions \(f(x, y)\) : (i) \(x^{2} y\), (ii) \(x^{2}+y^{2}+4\), (iii) \(\sin (x / y)\), (iv) \(\tan ^{-1}(y / x)\), (v) \(r(x, y, z)=\left(x^{2}+y^{2}+z^{2}\right)^{1 / 2}\). (b) For (i), (ii) and (v), find \(\partial^{2} f / \partial x^{2}, \partial^{2} f / \partial y^{2}\) and \(\partial^{2} f / \partial x \partial y\). (c) For (iv) verify that \(\partial^{2} f / \partial x \partial y=\partial^{2} f / \partial y \partial x\).

Short Answer

Expert verified
First partial derivatives and second partial derivatives are calculated as shown. Mixed partial derivatives for given functions are equal.

Step by step solution

01

Compute First Partial Derivatives

To compute the first partial derivatives, take the derivative of each function with respect to each variable. (i) For the function \( f(x,y) = x^2 y \):\[ \frac{\partial f}{\partial x} = 2xy \; \text{and} \; \frac{\partial f}{\partial y} = x^2 \](ii) For the function \( f(x,y) = x^2 + y^2 + 4 \):\[ \frac{\partial f}{\partial x} = 2x \; \text{and} \; \frac{\partial f}{\partial y} = 2y \](iii) For the function \( f(x,y) = \sin(x/y) \):\[ \frac{\partial f}{\partial x} = \frac{1}{y} \cos{\frac{x}{y}} \; \text{and} \; \frac{\partial f}{\partial y} = -\frac{x}{y^2} \cos{\frac{x}{y}} \](iv) For the function \( f(x,y) = \tan^{-1}(y/x) \):\[ \frac{\partial f}{\partial x} = \frac{-y}{x^2 + y^2} \; \text{and} \; \frac{\partial f}{\partial y} = \frac{x}{x^2 + y^2} \](v) For the function \( r(x,y,z) = \sqrt{x^2 + y^2 + z^2} \):\[ \frac{\partial r}{\partial x} = \frac{x}{\sqrt{x^2 + y^2 + z^2}} \; \frac{\partial r}{\partial y} = \frac{y}{\sqrt{x^2 + y^2 + z^2}} \; \frac{\partial r}{\partial z} = \frac{z}{\sqrt{x^2 + y^2 + z^2}} \]
02

Compute Second Partial Derivatives for (i)

For \( f(x,y) = x^2 y \):\[ \frac{\partial^2 f}{\partial x^2} = \frac{\partial(2xy)}{\partial x} = 2y \]\[ \frac{\partial^2 f}{\partial y^2} = \frac{\partial(x^2)}{\partial y} = 0 \]\[ \frac{\partial^2 f}{\partial x \partial y} = \frac{\partial(x^2)}{\partial x} = 2x \]
03

Compute Second Partial Derivatives for (ii)

For \( f(x,y) = x^2 + y^2 + 4 \):\[ \frac{\partial^2 f}{\partial x^2} = \frac{\partial(2x)}{\partial x} = 2 \]\[ \frac{\partial^2 f}{\partial y^2} = \frac{\partial(2y)}{\partial y} = 2 \]\[ \frac{\partial^2 f}{\partial x \partial y} = 0 \]
04

Compute Second Partial Derivatives for (v)

For \( r(x,y,z) = (x^2 + y^2 + z^2)^{1/2} \):\[ \frac{\partial^2 r}{\partial x^2} = \frac{\partial}{\partial x} \left( \frac{x}{\sqrt{x^2 + y^2 + z^2}} \right) = \frac{y^2 + z^2}{(x^2 + y^2 + z^2)^{3/2}} \]\[ \frac{\partial^2 r}{\partial y^2} = \frac{\partial}{\partial y} \left( \frac{y}{\sqrt{x^2 + y^2 + z^2}} \right) = \frac{x^2 + z^2}{(x^2 + y^2 + z^2)^{3/2}} \]\[ \frac{\partial^2 r}{\partial x \partial y} = \frac{\partial}{\partial y} \left( \frac{x}{\sqrt{x^2 + y^2 + z^2}} \right) = -\frac{xy}{(x^2 + y^2 + z^2)^{3/2}} \]
05

Verify Mixed Partial Derivatives for (iv)

For \( f(x,y) = \tan^{-1}(y/x) \):First compute \( \frac{\partial^2 f}{\partial x \partial y} \)\[ \frac{\partial}{\partial y} \left( \frac{-y}{x^2 + y^2} \right) = \frac{-x^2 + y^2}{(x^2 + y^2)^2} \]Then compute \( \frac{\partial^2 f}{\partial y \partial x} \)\[ \frac{\partial}{\partial x} \left( \frac{x}{x^2 + y^2} \right) = \frac{x^2 - y^2}{(x^2 + y^2)^2} \]Since \( \frac{\partial^2 f}{\partial x \partial y} = \frac{\partial^2 f}{\partial y \partial x} \), they are equal.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

first partial derivatives
First partial derivatives are the derivatives of a function taken with respect to one of its variables, while keeping the other variables constant. They provide the rate of change of the function with respect to a particular variable. For example, if we have a function of two variables, like \( f(x, y) \), the first partial derivatives are \( \frac{\partial f}{\partial x} \) and \( \frac{\partial f}{\partial y} \).

To compute these, we treat other variables as constants and differentiate accordingly:

1. For \( f(x, y) = x^2 y \):
\[ \frac{\partial f}{\partial x} = 2xy \; \text{and} \; \frac{\partial f}{\partial y} = x^2 \]
2. For \( f(x, y) = x^2 + y^2 + 4 \):
\[ \frac{\partial f}{\partial x} = 2x \; \text{and} \; \frac{\partial f}{\partial y} = 2y \]

First partial derivatives help us understand how the function changes along different axes in a multi-dimensional space.
second partial derivatives
Second partial derivatives are the derivatives of the first partial derivatives. They measure how the rate of change, given by the first partial derivatives, changes with respect to the variables. For instance, for a function \( f(x, y) \), there are several possible second partial derivatives, such as \( \frac{\partial^2 f}{\partial x^2} \), \( \frac{\partial^2 f}{\partial y^2} \), and mixed partial derivatives like \( \frac{\partial^2 f}{\partial x \partial y} \).

Here's how you compute them for some functions:

1. For \( f(x, y) = x^2 y \):
\[ \frac{\partial^2 f}{\partial x^2} = 2y \]
\[ \frac{\partial^2 f}{\partial y^2} = 0 \]

2. For \( f(x, y) = x^2 + y^2 + 4 \):
\[ \frac{\partial^2 f}{\partial x^2} = 2 \]
\[ \frac{\partial^2 f}{\partial y^2} = 2 \]

Second partial derivatives provide deeper insights into the curvature or concavity of the function's surface.
mixed partial derivatives
Mixed partial derivatives are the second partial derivatives where the differentiation is with respect to different variables. For a function of two variables \( f(x, y) \), this means, for example, taking the partial derivative of \( \frac{\partial f}{\partial x} \) with respect to \( y \), and vice versa.

Consider the following examples:

1. For \( f(x, y) = x^2 y \):
\[ \frac{\partial^2 f}{\partial x \partial y} = \frac{\partial (2xy)}{\partial y} = 2x \]
2. For \( f(x, y) = x^2 + y^2 + 4 \):
\[ \frac{\partial^2 f}{\partial x \partial y} = 0 \]

They highlight how the function changes as you simultaneously adjust multiple variables. Mixed partial derivatives are essential in multivariable calculus and have important applications, such as in optimization problems.
verification of mixed partial derivatives
Verification of mixed partial derivatives involves checking if different orders of mixed partial derivatives of a function are equal. According to Schwarz's theorem (also known as Clairaut's theorem), if the mixed partial derivatives are continuous, they are equal. That is:
\[ \frac{\partial^2 f}{\partial x \partial y} = \frac{\partial^2 f}{\partial y \partial x} \]

Let’s verify this for \( f(x, y) = \tan^{-1}(y/x) \):

1. Compute \( \frac{\partial^2 f}{\partial x \partial y} \):
\[ \frac{\partial}{\partial y} \left( \frac{-y}{x^2 + y^2} \right) = \frac{-x^2 + y^2}{(x^2 + y^2)^2} \]

2. Compute \( \frac{\partial^2 f}{\partial y \partial x} \):
\[ \frac{\partial}{\partial x} \left( \frac{x}{x^2 + y^2} \right) = \frac{x^2 - y^2}{(x^2 + y^2)^2} \]

Both mixed partial derivatives are equal, thus verifying Schwarz's theorem. This process ensures the consistency and correctness of calculating mixed partial derivatives in multivariable functions.

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