/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 44 The discriminant \(f_{x x} f_{y ... [FREE SOLUTION] | 91Ó°ÊÓ

91Ó°ÊÓ

The discriminant \(f_{x x} f_{y y}-f_{x y}^{2}\) is zero at the origin for each of the following functions, so the Second Derivative Test fails there. Determine whether the function has a maximum, a minimum, or neither at the origin by imagining what the surface \(z=f(x, y)\) looks like. Describe your reasoning in each case. $$\text { a. } f(x, y)=x^{2} y^{2}$$ $$\text { b. } f(x, y)=1-x^{2} y^{2}$$ $$\text { c. }f(x, y)=x y^{2}$$ $$\text { d. } f(x, y)=x^{3} y^{2}$$ $$\text { e. } f(x, y)=x^{3} y^{3}$$ $$f(x, y)=x^{4} y^{4}$$

Short Answer

Expert verified
a, c, e: neither; b: max; d, f: neither

Step by step solution

01

Calculate Partial Derivatives

For each function, calculate the first and second partial derivatives with respect to \(x\) and \(y\). For example, for \(f(x, y) = x^2 y^2\), the first derivatives are \(f_x = 2xy^2\) and \(f_y = 2x^2y\), and the second derivatives are \(f_{xx} = 2y^2\), \(f_{yy} = 2x^2\), and \(f_{xy} = 4xy\).
02

Compute the Discriminant

Use the second derivatives to compute the discriminant \(D = f_{xx}f_{yy} - (f_{xy})^2\) at the origin (\(x = 0, y = 0\)). For \(f(x, y) = x^2 y^2\), we find \(f_{xx}(0,0) = 0\), \(f_{yy}(0,0) = 0\), \(f_{xy}(0,0) = 0\), which gives \(D = 0\).
03

Assess the Function's Surface at the Origin

For each function, analyze the behavior of \(f(x, y)\) near the origin to determine whether there is a max, min, or neither. For \(f(x, y) = x^2 y^2\), at the origin, all points nearby increase or decrease depending on the combination of x and y signs, indicating neither a max nor a min.
04

Repeat for Each Function

Repeat Steps 1 to 3 for functions \(f(x, y) = 1-x^2 y^2\), \(f(x, y) = xy^2\), \(f(x, y) = x^3 y^2\), \(f(x, y) = x^3 y^3\), and \(f(x, y) = x^4 y^4\). Analyze the resulting surface behavior at the origin for each to determine their respective types: max, min, or neither.

Unlock Step-by-Step Solutions & Ace Your Exams!

  • Full Textbook Solutions

    Get detailed explanations and key concepts

  • Unlimited Al creation

    Al flashcards, explanations, exams and more...

  • Ads-free access

    To over 500 millions flashcards

  • Money-back guarantee

    We refund you if you fail your exam.

Over 30 million students worldwide already upgrade their learning with 91Ó°ÊÓ!

Key Concepts

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

Understanding the Discriminant in the Context of Surface Analysis
The discriminant is a crucial tool in multivariable calculus, especially when applying the Second Derivative Test. It helps determine the type of critical point a function has at a particular location. The discriminant is calculated using second partial derivatives: \[ D = f_{xx}f_{yy} - (f_{xy})^2 \] At the origin, this measures how spread out the surface is in a way similar to the quadratic formula's discriminant in single-variable calculus. When \(D > 0\), the function might have a local max or min. If \(D < 0\), the point is a saddle point, indicating neither a max nor min. When \(D = 0\), as in this exercise, the test is inconclusive, requiring other analytical methods to make a determination.
Calculating and Interpreting Partial Derivatives
Partial derivatives represent how a function changes as each variable is varied independently. For a function \(f(x, y)\), the partial derivative with respect to \(x\), written as \(f_x\), considers how \(f\) changes with small changes in \(x\) while \(y\) remains constant. Conversely, \(f_y\) does the same for changes in \(y\) with \(x\) constant.These derivatives help describe the function's local behavior and are essential for calculating the discriminant. Second partial derivatives, such as \(f_{xx}\), \(f_{yy}\), and \(f_{xy}\), provide further insights into the curvature of the surface formed by \(f(x, y)\). By analyzing these, one can deduce whether the surface at a point is bowl-shaped, saddle-shaped, or flat.
Surface Analysis for Visualizing Function Behavior
Surface analysis involves envisioning the graph of a function \(z = f(x, y)\) to understand its geometric properties around critical points. The challenge arises when the discriminant is zero, as it does not directly indicate whether a point is a maximum, minimum, or saddle point.In these cases, imagining the surface helps. For instance, with \(f(x,y) = x^2y^2\), the surface resembles a cone, with its tip at the origin. This shape indicates neither a maximum nor a minimum since it flattens at the origin. Different functions will produce various shapes like troughs, ridges, or flat planes near the origin, guiding us to understand the function's local behavior more intuitively.
Identifying Local Extrema through Alternative Analysis
Local extrema are points where a function reaches a local maximum or minimum value. When the discriminant fails, as it does with \(D = 0\), it becomes essential to explore alternatives for locating these extrema.To probe further, one can analyze higher-order derivatives or assess the function's behavior along specific paths, like lines or curves intersecting the origin. For example, examining the cross-sections of the surface along these paths can reveal whether the function dips down or arches up, helping identify maxima or minima not apparent through the discriminant alone. This approach ensures a more comprehensive analysis beyond the limitations of straightforward derivative tests, opening broader insights into the function's behavior.

One App. One Place for Learning.

All the tools & learning materials you need for study success - in one app.

Get started for free

Most popular questions from this chapter

Find three positive numbers whose sum is 3 and whose product is a maximum.

If you cannot make any headway with \(\lim _{(x, y) \rightarrow(0,0)} f(x, y)\) in rectangular coordinates, try changing to polar coordinates. Substitute \(x=r \cos \theta, y=r \sin \theta,\) and investigate the limit of the resulting expression as \(r \rightarrow 0 .\) In other words, try to decide whether there exists a number \(L\) satisfying the following criterion: $$|r|<\delta \Rightarrow|f(r, \theta)-L|<\epsilon$$ If such an \(L\) exists, then $$\lim _{(x, y) \rightarrow(0,0)} f(x, y)=\lim _{r \rightarrow 0} f(r \cos \theta, r \sin \theta)=L$$ For instance, $$\lim _{(x, y) \rightarrow(0,0)} \frac{x^{3}}{x^{2}+y^{2}}=\lim _{r \rightarrow 0} \frac{r^{3} \cos ^{3} \theta}{r^{2}}=\lim _{r \rightarrow 0} r \cos ^{3} \theta=0$$ To verify the last of these equalities, we need to show that Equation (1) is satisfied with \(f(r, \theta)=r \cos ^{3} \theta\) and \(L=0 .\) That is, we need to show that given any \(\epsilon>0,\) there exists a \(\delta>0\) such that for all \(r\) and \(\theta\) $$|r|<\delta \Rightarrow\left|r \cos ^{3} \theta-0\right|<\epsilon$$ since $$\left|r \cos ^{3} \theta\right|=|r|\left|\cos ^{3} \theta\right| \leq|r| \cdot 1=|r|$$ the implication holds for all \(r\) and \(\theta\) if we take \(\delta=\epsilon\) In contrast, $$\frac{x^{2}}{x^{2}+y^{2}}=\frac{r^{2} \cos ^{2} \theta}{r^{2}}=\cos ^{2} \theta$$takes on all values from 0 to 1 regardless of how small \(|r|\) is, so that \(\lim _{(x, y) \rightarrow(0,0)} x^{2} /\left(x^{2}+y^{2}\right)\) does not exist. In each of these instances, the existence or nonexistence of the limit as \(r \rightarrow 0\) is fairly clear. Shifting to polar coordinates does not always help, however, and may even tempt us to false conclusions. For example, the limit may exist along every straight line (or ray) \(\theta=\) constant and yet fail to exist in the broader sense. Example 5 illustrates this point. In polar coordinates, \(f(x, y)=\left(2 x^{2} y\right) /\left(x^{4}+y^{2}\right)\) becomes $$f(r \cos \theta, r \sin \theta)=\frac{r \cos \theta \sin 2 \theta}{r^{2} \cos ^{4} \theta+\sin ^{2} \theta}$$for \(r \neq 0 .\) If we hold \(\theta\) constant and let \(r \rightarrow 0,\) the limit is \(0 .\) On the path \(y=x^{2},\) however, we have \(r \sin \theta=r^{2} \cos ^{2} \theta\) and $$\begin{aligned} f(r \cos \theta, r \sin \theta) &=\frac{r \cos \theta \sin 2 \theta}{r^{2} \cos ^{4} \theta+\left(r \cos ^{2} \theta\right)^{2}} \\ &=\frac{2 r \cos ^{2} \theta \sin \theta}{2 r^{2} \cos ^{4} \theta}=\frac{r \sin \theta}{r^{2} \cos ^{2} \theta}=1 \end{aligned}$$ Find the limit of \(f\) as \((x, y) \rightarrow(0,0)\) or show that the limit does not exist. $$f(x, y)=\frac{2 x}{x^{2}+x+y^{2}}$$

Find the point on the plane \(3 x+2 y+z=6\) that is nearest the origin.

Use a CAS to plot the implicitly defined level surfaces. $$x^{2}+z^{2}=1$$

The Sandwich Theorem for functions of two variables states that if \(g(x, y) \leq f(x, y) \leq h(x, y)\) for all \((x, y) \neq\left(x_{0}, y_{0}\right)\) in a disk centered at \(\left(x_{0}, y_{0}\right)\) and if \(g\) and \(h\) have the same finite limit \(L\) as \((x, y) \rightarrow\left(x_{0}, y_{0}\right)\) then$$\lim _{(x, y) \rightarrow\left(x_{0}, y_{0}\right)} f(x, y)=L$$ Use this result to support your answers to the questions. Does knowing that $$1-\frac{x^{2} y^{2}}{3}<\frac{\tan ^{-1} x y}{x y}<1$$ tell you anything about $$\lim _{(x, y) \rightarrow(0,0)} \frac{\tan ^{-1} x y}{x y} ?$$ Give reasons for your answer.

See all solutions

Recommended explanations on Math Textbooks

View all explanations

What do you think about this solution?

We value your feedback to improve our textbook solutions.

Study anywhere. Anytime. Across all devices.