Chapter 6: Problem 242
Use \(r=|\mathbf{r}|\) and \(\mathbf{r}=(x, y, z)\). Let \(\mathbf{F}(x, y)=\frac{-y \mathbf{i}+x \mathbf{j}}{x^{2}+y^{2}}, \quad\) where \(\mathbf{F}\) is defined on \(\\{(x, y) \in \mathbb{R} \mid(x, y) \neq(0,0)\\} .\) Find \(\operatorname{curl} \mathbf{F}\)
Short Answer
Expert verified
The curl of \( \mathbf{F} \) is zero everywhere except at the origin.
Step by step solution
01
Understand the Components of the Vector Field
The given vector field is \( \mathbf{F}(x, y) = \frac{-y \mathbf{i} + x \mathbf{j}}{x^2 + y^2} \). This means the components of \( \mathbf{F} \) are \( M(x, y) = \frac{-y}{x^2 + y^2} \) and \( N(x, y) = \frac{x}{x^2 + y^2} \).
02
Recall the Curl in 2D
In two dimensions, the curl of a vector field \( \mathbf{F} = M \mathbf{i} + N \mathbf{j} \) is given by \( \operatorname{curl} \mathbf{F} = \frac{\partial N}{\partial x} - \frac{\partial M}{\partial y} \). We need to calculate these partial derivatives for \( N \) and \( M \).
03
Compute \( \frac{\partial N}{\partial x} \)
Start by calculating \( \frac{\partial}{\partial x} \left( \frac{x}{x^2 + y^2} \right) \). Use the quotient rule: \( \frac{f}{g} \rightarrow \frac{g \cdot f' - f \cdot g'}{g^2} \), where \( f(x) = x \) and \( g(x) = x^2 + y^2 \). The derivative becomes:\[ \frac{(x^2 + y^2) \cdot 1 - x \cdot 2x}{(x^2 + y^2)^2} = \frac{(x^2 + y^2) - 2x^2}{(x^2 + y^2)^2} = \frac{y^2 - x^2}{(x^2 + y^2)^2} \]
04
Compute \( \frac{\partial M}{\partial y} \)
Next, calculate \( \frac{\partial}{\partial y} \left( \frac{-y}{x^2 + y^2} \right) \). Again apply the quotient rule. Here, \( f(y) = -y \) and \( g(y) = x^2 + y^2 \), giving the derivative:\[ \frac{(x^2 + y^2)(-1) - (-y)\cdot 2y}{(x^2 + y^2)^2} = \frac{-(x^2 + y^2) + 2y^2}{(x^2 + y^2)^2} = \frac{2y^2 - x^2 - y^2}{(x^2 + y^2)^2} = \frac{y^2 - x^2}{(x^2 + y^2)^2} \]
05
Calculate the Curl
Substitute the values from steps 3 and 4 into the formula for the curl: \( \operatorname{curl} \mathbf{F} = \frac{y^2 - x^2}{(x^2 + y^2)^2} - \frac{y^2 - x^2}{(x^2 + y^2)^2} \).This simplifies to zero, as both terms are identical and cancel each other out.
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Vector Fields
Imagine a vector field as a map of invisible forces in a given space. These forces can influence objects within that space without physically touching them. In a 2D plane, a vector field assigns a vector to every point, which describes both the direction and strength of this force at that point.
- For example, wind over a field can be represented as a vector field, where each vector shows the wind's speed and direction.
- Mathematically, a vector field can be expressed in terms of coordinate functions; in two dimensions, it often looks like \(\mathbf{F}(x, y) = M(x, y)\mathbf{i} + N(x, y)\mathbf{j}\).
Curl of a Vector Field
The curl of a vector field helps us understand how much the field rotates or "twists" around a point. This concept is crucial in physics when studying fields related to rotation, like magnetic fields.
- In a 2D vector field, the curl is a scalar value that resembles the amount of rotation at each point.
- The mathematical formula to find the curl in 2D is \( \text{curl} \mathbf{F} = \frac{\partial N}{\partial x} - \frac{\partial M}{\partial y}\).
Partial Derivatives
Partial derivatives are a cornerstone of vector calculus. When a function involves several variables, like \(x\) and \(y\) in our vector field \(\mathbf{F}\), a partial derivative measures how the function changes as one variable changes while others remain constant.
- The partial derivative of \(N(x, y)\) with respect to \(x\) tells us the rate of change of \(N\) as \(x\) shifts.
- Similarly, \(\frac{\partial M}{\partial y}\) explores how \(M(x, y)\) changes as \(y\) varies.
Quotient Rule
Handling derivatives of functions that are fractions is where the quotient rule comes into play. It's a technique used in differentiation when dealing with ratios, crucial for computing the derivatives in vector calculus.
- The quotient rule is given by: if \(u(x)\) and \(v(x)\) are function components, then the derivative \( \frac{d}{dx} \left( \frac{u}{v} \right) = \frac{v(x) \cdot u'(x) - u(x) \cdot v'(x)}{v(x)^2}\).
- In our exercise, it helps us differentiate the component functions \( \frac{x}{x^2 + y^2}\) and \( \frac{-y}{x^2 + y^2}\).