Chapter 9: Problem 12
Fix two real numbers \(a\) and \(b, 0
Short Answer
Expert verified
b) What is the set of all points in the range K where \(\nabla f_3 = 0\)?
c) What are the types of critical points for the four points found in part (a)?
d) What is the square of the magnitude of \(\mathbf{g}'(t)\) for the mapping \(g(t)=\mathbf{f}(t,\lambda t)\), where \(\lambda\) is an irrational number?
Step by step solution
01
Define the given mapping and its components
We are given a mapping \(\mathbf{f} = (f_1, f_2, f_3)\) of \(\mathbb{R}^2\) into \(\mathbb{R}^3\), where
$$
\begin{array}{l}
f_1(s,t) = (b + a\cos{s})\cos{t},\\
f_2(s,t) = (b + a\cos{s})\sin{t},\\
f_3(s,t) = a\sin{s}.
\end{array}
$$
02
Calculate the gradients \(\nabla f_1\) and \(\nabla f_3\)
First, find the partial derivatives of \(f_1\) and \(f_3\) with respect to \(s\) and \(t\). For \(f_1\), we have
$$
\frac{\partial f_1}{\partial s} = -a\sin{s}\cos{t},\ \frac{\partial f_1}{\partial t} = -(b+a\cos{s})\sin{t},
$$
so the gradient of \(f_1\) is
$$
\nabla f_1 = \left(-a\sin{s}\cos{t}, -(b+a\cos{s})\sin{t}\right).
$$
Similarly, for \(f_3\) we have
$$
\frac{\partial f_3}{\partial s} = a\cos{s},\ \frac{\partial f_3}{\partial t} = 0,
$$
and the gradient of \(f_3\) is
$$
\nabla f_3 = \left(a\cos{s}, 0\right).
$$
03
Find points where \(\nabla f_1 = 0\)
In order to find the 4 points where \((\nabla f_1)\left(\mathbf{f}^{-1}(\mathbf{p})\right) = \mathbf{0}\), we need to solve the following system of equations:
$$
\begin{cases}
-a\sin{s}\cos{t}=0,\\
-(b+a\cos{s})\sin{t}=0.
\end{cases}
$$
From the first equation, we can see that either \(\sin s = 0\) or \(\cos t = 0\). If \(\sin s = 0\), then \(s=0\) or \(s=\pi\). If \(\cos t = 0\), then \(t=\pi/2\) or \(t=3\pi/2\). Combining these conditions, we get four points \((s,t)\): \((0,\pi/2)\), \((0,3\pi/2)\), \((\pi,\pi/2)\), and \((\pi,3\pi/2)\).
04
Find points in the range K corresponding to the points found in Step 3
Now apply the mapping to the points found in Step 3 to get the points in the range K:
$$
\begin{aligned}
\mathbf{p}_1 &= \mathbf{f}(0,\pi/2) = (a, b, 0),\\
\mathbf{p}_2 &= \mathbf{f}(0,3\pi/2) = (a, -b, 0),\\
\mathbf{p}_3 &= \mathbf{f}(\pi,\pi/2) = (-a, b, 0),\\
\mathbf{p}_4 &= \mathbf{f}(\pi,3\pi/2) = (-a, -b, 0).
\end{aligned}
$$
05
Determine set of \(\mathbf{q}\in\mathbb{K}\) where \(\nabla f_3 = 0\)
In order to find the set of points, we need to solve \(a\cos{s} = 0\). This occurs when \(s=\pi/2\) or \(s=3\pi/2\). Hence, for these two values of \(s\), the points in the range K will be
$$
\mathbf{q} = (0, (b+a\cos{s})\sin{t}, 0),
$$
and the set of all \(\mathbf{q}\) will be a circle in the xy-plane with radii \(b-a\) and \(b+a\).
06
Evaluate the second partial derivatives and analyze the critical points
Compute the second partial derivatives of \(f_1\):
$$
\frac{\partial^2 f_1}{\partial s^2} = -a\cos{s}\cos{t},\ \frac{\partial^2 f_1}{\partial t^2} = -(b+a\cos{s})\cos{t},\ \frac{\partial^2 f_1}{\partial s\partial t} = a\sin{s}\sin{t}.
$$
For points \((s,t)\) found in Step 3, we can compute the determinant of the Hessian matrix:
$$
\begin{aligned}
D(0,\pi/2) &= \left(-a\cos{(0)}\cos{(\pi/2)}\right)\left(-(b+a\cos{(0)})\cos{(\pi/2)}\right) - \left(a\sin{(0)}\sin{(\pi/2)}\right)^2 = 0,\\
D(0,3\pi/2) &= 0,\\
D(\pi,\pi/2) &= -a(b-a) > 0,\\
D(\pi,3\pi/2) &= a(b+a) > 0.
\end{aligned}
$$
From these results, we can conclude that \(\mathbf{p}_1\) and \(\mathbf{p}_2\) are saddle points, \(\mathbf{p}_3\) corresponds to a local minimum, and \(\mathbf{p}_4\) corresponds to a local maximum.
For the points \(\mathbf{q}\) found in Step 5, we have \(f_3=0\). Since \(f_3\) does not depend on \(t\), its critical points will be along the circles found in the xy-plane (without any maxima or minima).
07
Define \(g(t)\) and analyze its properties
We are given a new function \(g(t)=\mathbf{f}(t,\lambda t)\) where \(\lambda\) is an irrational number. Compute the derivative of \(\mathbf{g}\) with respect to \(t\):
$$
\mathbf{g}'(t) = \frac{d\mathbf{f}(t,\lambda t)}{dt} = \left(-a\sin t\cos (\lambda t)+\lambda(b+a\cos t)(-\sin(\lambda t)), -(b+a\cos t)\sin(\lambda t)-\lambda a\sin t\sin(\lambda t), a\cos t\right).
$$
Compute the square of the magnitude of \(\mathbf{g}'(t)\):
$$
\left|\mathbf{g}'(t)\right|^2=(-a\sin t\cos (\lambda t)+\lambda(b+a\cos t)(-\sin(\lambda t)))^2+(-(b+a\cos t)\sin(\lambda t)-\lambda a\sin t\sin(\lambda t))^2+(a\cos t)^2
$$
Simplify expression:
$$
\left|\mathbf{g}'(t)\right|^2 = a^{2} + \lambda^{2}(b+a\cos{t})^{2}.
$$
Since \(g(t)\) is a mapping of \(\mathbb{R}\) onto a subset of K, it is a one-to-one mapping onto a dense subset of K.
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Key Concepts
These are the key concepts you need to understand to accurately answer the question.
Gradient
In differential calculus, the gradient is a vector that represents the direction and rate of fastest increase of a function. For functions of several variables, the gradient is the counterpart of the derivative in single-variable calculus. Here, the gradient is denoted as \( abla f \) and is a vector containing all the partial derivatives of a function.
- The gradient \( abla f_1 = (-a\sin{s}\cos{t}, -(b+a\cos{s})\sin{t}) \) describes how the function \( f_1(s, t) \) changes in the \( s \) and \( t \) directions.
- Similarly, \( abla f_3 = (a\cos{s}, 0) \) shows change in the \( s \) direction with no change in the \( t \) direction.
Compact Sets
A compact set is a fundamental concept in topology, particularly in the field of real analysis. It is a set that is both closed and bounded.
- A set is closed if it contains all its limit points.
- A set is bounded if it can fit within a ball of finite radius.
Hessian Matrix
The Hessian matrix is a square matrix of second-order partial derivatives of a scalar-valued function. It is used to study the local curvature of functions and can indicate the nature of critical points found from the gradient.
- The determinant of the Hessian, denoted as \( D \), can help identify whether a critical point is a local max, min, or saddle point.
- For the given problem, critical points were evaluated using the Hessian to determine their nature: \( \mathbf{p}_3 \) is a local minimum and \( \mathbf{p}_4 \) is a local maximum, while \( \mathbf{p}_1 \) and \( \mathbf{p}_2 \) are saddle points.
One-to-One Mapping
A one-to-one (1-1) mapping means each element of one set is paired with a unique element of another set, and vice versa.
- In this context, the function \( g(t) = \mathbf{f}(t, \lambda t) \) describes such a mapping.
- When \( \lambda \) is irrational, it ensures that \( g(t) \) maps \( \mathbb{R}^1 \) densely onto a subset of \( K \).