Chapter 12: Problem 6
Find the directional derivative of \(f\) at the point \(\mathbf{p}\) in the direction of \(\mathbf{a}\). \(f(x, y)=e^{-x y} ; \mathbf{p}=(1,-1) ; \mathbf{a}=-\mathbf{i}+\sqrt{3} \mathbf{j}\)
Short Answer
Expert verified
The directional derivative is \(-\frac{e}{2}(1+\sqrt{3})\).
Step by step solution
01
Find the Gradient of the Function
The gradient of a function \( f(x, y) \) is given by the vector of partial derivatives: \( abla f(x, y) = \left( \frac{\partial f}{\partial x}, \frac{\partial f}{\partial y} \right) \). For our function \( f(x, y) = e^{-xy} \), we find: \[ \frac{\partial f}{\partial x} = -y e^{-xy} \] \[ \frac{\partial f}{\partial y} = -x e^{-xy} \] Thus, the gradient is \( abla f(x, y) = (-y e^{-xy}, -x e^{-xy}) \).
02
Evaluate the Gradient at the Point \(\mathbf{p}\)
Substitute the point \( \mathbf{p} = (1, -1) \) into the gradient equation: \[ abla f(1, -1) = (-(-1) e^{-(1)(-1)}, -(1) e^{-(1)(-1)}) = (e, -e) \] So, the gradient at point \( (1, -1) \) is \( (e, -e) \).
03
Normalize the Direction Vector
The given direction vector is \( \mathbf{a} = -\mathbf{i} + \sqrt{3} \mathbf{j} \) or \( \mathbf{a} = (-1, \sqrt{3}) \). First, we find the magnitude of \( \mathbf{a} \): \[ \| \mathbf{a} \| = \sqrt{(-1)^2 + (\sqrt{3})^2} = \sqrt{1 + 3} = 2 \] The unit vector in the direction of \( \mathbf{a} \) is: \[ \mathbf{a}_u = \left( \frac{-1}{2}, \frac{\sqrt{3}}{2} \right) \]
04
Calculate the Directional Derivative
The directional derivative of \( f \) at \( \mathbf{p} \) in the direction of \( \mathbf{a} \) is given by the dot product of the gradient \( abla f(1, -1) \) and the unit vector \( \mathbf{a}_u \): \[ D_{\mathbf{a}}f = abla f(1, -1) \cdot \mathbf{a}_u = (e, -e) \cdot \left( \frac{-1}{2}, \frac{\sqrt{3}}{2} \right) \] \[ D_{\mathbf{a}}f = e \cdot \frac{-1}{2} + (-e) \cdot \frac{\sqrt{3}}{2} = -\frac{e}{2} - \frac{\sqrt{3}e}{2} = -\frac{e}{2}(1 + \sqrt{3}) \]
05
State the Result
The directional derivative of \( f(x, y) = e^{-xy} \) at the point \( \mathbf{p} = (1, -1) \) in the direction of \( \mathbf{a} = -\mathbf{i} + \sqrt{3}\mathbf{j} \) is \( -\frac{e}{2}(1 + \sqrt{3}) \).
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Gradient
A gradient is a fundamental concept in multivariable calculus. It provides important information about the rate and direction of change in a function. For a function \(f(x, y)\), the gradient is represented by a vector. This vector consists of the function's partial derivatives with respect to each variable.
- Finding gradients will help you understand how a function changes at any given point.
- Gradients point in the direction of the steepest ascent of a function.
Partial Derivatives
Partial derivatives reveal how a function changes as one of the input variables changes, while the others are held constant. In multivariable calculus, these derivatives extend the concept of a derivative to functions of several variables.
- Allow you to focus on how change in one direction impacts the function.
- Useful in obtaining the gradient vector.
Unit Vector
A unit vector is a vector with a magnitude of 1. It’s often used to specify a direction without contributing to changes in magnitude. To find a unit vector in the direction of any vector \(\mathbf{a}\), you need to divide \(\mathbf{a}\) by its magnitude.
- The unit vector keeps the direction of \(\mathbf{a}\) but with a standardized length.
- Used to analyze the direction of the function's rate of change.
Dot Product
The dot product is a mathematical operation between two vectors that returns a scalar. It is also known as the scalar product and is essential in finding a directional derivative.
- Calculates how much one vector goes in the direction of another.
- Combines magnitude and direction information of the vectors involved.