Chapter 12: Problem 13
find the gradient vector of the given function at the given point \(\mathbf{p}\). Then find the equation of the tangent plane at \(\mathbf{p}\) \((\) see Example 1). $$ f(x, y)=\cos \pi x \sin \pi y+\sin 2 \pi y, \mathbf{p}=\left(-1, \frac{1}{2}\right) $$
Short Answer
Expert verified
Gradient: \((0, -2\pi)\), Tangent Plane: \(z = 1 + \pi - 2\pi y\)."
Step by step solution
01
Calculate Partial Derivatives
To find the gradient vector, we first need to calculate the partial derivatives of the function with respect to both variables, \(x\) and \(y\). For \(f(x, y) = \cos(\pi x) \sin(\pi y) + \sin(2\pi y)\):- The partial derivative with respect to \(x\) is: \(f_x(x, y) = \frac{d}{dx}[\cos(\pi x) \sin(\pi y)] = -\pi \sin(\pi x)\sin(\pi y)\).- The partial derivative with respect to \(y\) is: \(f_y(x, y) = \frac{d}{dy}[\cos(\pi x) \sin(\pi y) + \sin(2\pi y)] = \pi \cos(\pi x)\cos(\pi y) + 2\pi \cos(2\pi y)\).
02
Evaluate the Gradients at Point p
Now, substitute the coordinates of point \(\mathbf{p} = (-1, \frac{1}{2})\) into the partial derivatives to find the gradient vector at this point.- For \(f_x\): \(f_x(-1, \frac{1}{2}) = -\pi \sin(-\pi) \sin\left(\frac{\pi}{2}\right) = 0\) because \(\sin(\pi) = 0\).- For \(f_y\): \(f_y(-1, \frac{1}{2}) = \pi \cos(-\pi)\cos\left(\frac{\pi}{2}\right) + 2\pi \cos(\pi) = 0 + 2\pi(-1) = -2\pi\).
03
Construct the Gradient Vector
The gradient vector \(abla f\) at point \(\mathbf{p}\) is \(abla f(-1, \frac{1}{2}) = (0, -2\pi)\). This vector will guide us to find the tangent plane in the next step.
04
Equation of the Tangent Plane
The equation for the tangent plane at a point \((x_0, y_0)\) is given by:\[ z = f(x_0, y_0) + abla f(x_0, y_0) \cdot \begin{bmatrix} (x - x_0) \ (y - y_0) \end{bmatrix}.\]Substitute \((x_0, y_0) = (-1, \frac{1}{2})\) and \(abla f(-1, \frac{1}{2}) = (0, -2\pi)\):- First, compute \(f(-1, \frac{1}{2}) = \cos(-\pi)\sin\left(\frac{\pi}{2}\right) + \sin(\pi) = 1\cdot 1 + 0 = 1\).- Plug into the plane equation: \[ z = 1 + 0(x + 1) - 2\pi(y - \frac{1}{2}) \].- Simplify the equation to \[ z = 1 - 2\pi y + \pi \].
05
Simplify Tangent Plane Equation
Simplify the tangent plane equation further:- Combine like terms: \[ z = 1 + \pi - 2\pi y \].- Therefore, the equation of the tangent plane is: \[ z = 1 - 2\pi y + \pi = 1 + \pi - 2\pi y \].
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Partial Derivatives
Partial derivatives are a fundamental concept in multivariable calculus. They involve taking the derivative of a function with respect to one variable, while keeping all other variables constant. This is crucial for understanding how changes in one variable affect the overall behavior of a function.
For functions in two variables like \(f(x, y)\), the partial derivative with respect to \(x\), denoted as \(f_x(x, y)\), indicates the rate of change of \(f\) as \(x\) changes while \(y\) is held constant. Similarly, the partial derivative with respect to \(y\), denoted as \(f_y(x, y)\), shows the rate of change of \(f\) with changing \(y\) while \(x\) remains fixed.
For functions in two variables like \(f(x, y)\), the partial derivative with respect to \(x\), denoted as \(f_x(x, y)\), indicates the rate of change of \(f\) as \(x\) changes while \(y\) is held constant. Similarly, the partial derivative with respect to \(y\), denoted as \(f_y(x, y)\), shows the rate of change of \(f\) with changing \(y\) while \(x\) remains fixed.
- Notation: \(f_x(x, y)\) and \(f_y(x, y)\) are the common notations for partial derivatives, regardless of the function's complexity.
- Calculation: Use standard differentiation rules, treating other variables as constants.
- Purpose: Helps find the gradient vector and understand the function's behavior and slope.
Tangent Plane Equation
The equation of the tangent plane is a key element in multivariable calculus, providing a linear approximation of a surface at a given point. This equation helps to simplify the examination of complex surfaces by replacing the surface around a small region with a plane.
The general formula for the tangent plane to a surface \(z = f(x, y)\) at a point \((x_0, y_0, z_0)\) is:
\[ z = z_0 + f_x(x_0, y_0)(x - x_0) + f_y(x_0, y_0)(y - y_0). \]
The general formula for the tangent plane to a surface \(z = f(x, y)\) at a point \((x_0, y_0, z_0)\) is:
\[ z = z_0 + f_x(x_0, y_0)(x - x_0) + f_y(x_0, y_0)(y - y_0). \]
- Point of tangency: \((x_0, y_0, z_0)\) is the point where the plane is tangent to the surface.
- Gradient vector: \((f_x(x_0, y_0), f_y(x_0, y_0))\) directs the slope and orientation of the tangent plane.
- Linear approximation: Provides a simple approach to analyze changes near the tangent point.
Multivariable Calculus
Multivariable calculus extends the principles of single-variable calculus to functions of multiple variables. It allows us to understand and analyze scenarios where more than one variable influences the outcome, such as physical systems and geometrical surfaces.
Some key concepts include:
Some key concepts include:
- Function of multiple variables: For example, \(f(x, y)\) can represent a surface where \(x\) and \(y\) are independent variables.
- Partial derivatives: As discussed, these are derivatives with respect to one variable at a time.
- Gradient vector: A vector composed of partial derivatives, pointing towards the direction of the steepest ascent of the function.
- Tangent planes and surfaces: Local linear approximations to better understand and manipulate 3D surfaces.