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In Problems \(1-8\), find the gradient of each function. $$ f(x, y)=\ln \left(\frac{x}{y}+\frac{y}{x}\right) $$

Short Answer

Expert verified
The gradient of the function is \(\nabla f = \left( \frac{1}{u} \left( \frac{1}{y} - \frac{y}{x^2} \right), \frac{1}{u} \left( -\frac{x}{y^2} + \frac{1}{x} \right) \right)\), where \(u = \frac{x}{y} + \frac{y}{x}\).

Step by step solution

01

Understand the Gradient Concept

The gradient of a function with two variables is a vector showing the direction of the steepest ascent. It consists of the partial derivatives of the function with respect to each variable.
02

Differentiate with Respect to x

To find the partial derivative of the function with respect to \(x\), use the chain rule and quotient rule as needed. Let \(u = \frac{x}{y} + \frac{y}{x}\), then \(\frac{\partial f}{\partial x} = \frac{1}{u} \times \left(\frac{\partial}{\partial x} \left( \frac{x}{y} + \frac{y}{x} \right) \right) = \frac{1}{u} \left( \frac{1}{y} - \frac{y}{x^2} \right)\).
03

Differentiate with Respect to y

Now, differentiate the function with respect to \(y\). Similarly to the previous step, \(\frac{\partial f}{\partial y} = \frac{1}{u} \times \left(\frac{\partial}{\partial y} \left( \frac{x}{y} + \frac{y}{x} \right) \right) = \frac{1}{u} \left( -\frac{x}{y^2} + \frac{1}{x} \right)\).
04

Write the Gradient as a Vector

Combine the partial derivatives to express the gradient. Therefore, the gradient of \(f\) is given by \( abla f = \left( \frac{1}{u} \left( \frac{1}{y} - \frac{y}{x^2} \right), \frac{1}{u} \left( -\frac{x}{y^2} + \frac{1}{x} \right) \right) \).

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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 crucial concept when dealing with multivariable functions. They help us understand how a function changes as we tweak one variable while keeping others constant. In essence, a partial derivative is like taking a slice through a multi-dimensional landscape, observing changes along one axis at a time.

In this exercise, when we calculate the partial derivative of the function \(f(x, y) = \ln \left(\frac{x}{y} + \frac{y}{x}\right)\) with respect to \(x\), we are isolating the changes due to variations in \(x\), assuming \(y\) remains constant. Similarly, differentiating with respect to \(y\) treats \(x\) as static, only examining changes as \(y\) varies.

This step-by-step approach ensures that we can accurately gauge the sensitivity of the function to changes in each of its inputs, ultimately allowing us to construct the gradient vector, which reveals the function's steepest path of ascent.
Chain Rule
When working with nested functions or compositions of functions, the chain rule becomes invaluable. It allows us to differentiate these complex entities by breaking them into manageable parts. Put simply, the chain rule is a formula for computing the derivative of the composition of two or more functions.

In our specific problem, we first set \(u = \frac{x}{y} + \frac{y}{x}\). Then, to differentiate \(f(x, y) = \ln(u)\) with respect to \(x\) or \(y\), we employ the chain rule. This involves differentiating \(f\) with respect to \(u\) and multiplying by the derivative of \(u\) with respect to the variable of interest. It breaks down the differentiation task into smaller, simpler pieces.

For instance, to find \(\frac{\partial f}{\partial x}\), we calculate \(\frac{d}{dx}(\ln(u)) = \frac{1}{u} \cdot \frac{\partial u}{\partial x}\). This cascading approach, made possible by the chain rule, simplifies the complex derivatives into neat segments.
Quotient Rule
The quotient rule is a fundamental tool for differentiating expressions that are divisions of two functions. It's especially crucial when the functions forming the quotient have variables and operations that complicate direct differentiation.

The rule states that for a quotient \(\frac{g(x)}{h(x)}\), its derivative is given by:\[\left(\frac{g}{h}\right)' = \frac{g'h - gh'}{h^2}\]where \(g'\) and \(h'\) are the derivatives of \(g\) and \(h\), respectively.

In our exercise, it comes into play when differentiating terms like \(\frac{x}{y}\) and \(\frac{y}{x}\). To find \(\frac{\partial}{\partial x}\) or \(\frac{\partial}{\partial y}\), each part is treated as a separate application of the quotient rule. This allows us to handle each function slab within the larger expression, ensuring accuracy in the derivative's computation.

Application of the quotient rule helps in navigating through these fractions, allowing for precise and structured differentiation required to solve these types of problems.

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Most popular questions from this chapter

Morphogenesis Most embryos start out as lumps of cells. Cells in these lumps are initially undifferentiated-that is, they start out all in the same state. Over time cells then commit to different functions, e.g., to becoming legs, eyes, and so on. To do this chemicals called morphogens are distributed unequally through the embryo, allowing each cell to tell where in the embryo it is located. How are unequal distributions of morphogens achieved? One model for how morphogens can be distributed through the embryo is that morphogens are continuously produced at one end (also called pole) of the embryo. From there they diffuse through the embryo. As the morphogens diffuse, they are constantly broken down by the cells in the embryo. First let's ignore the process of morphogen degradation, and focus only on diffusion. We will assume that the pole at which the morphogen is produced is located at \(x=0 ;\) and for simplicity's sake the cell occupies the interval \(x \geq 0\). Then our partial differential equation model for the distribution of morphogen becomes: $$ \frac{\partial c}{\partial t}=D \frac{\partial^{2} c}{\partial x^{2}} \quad \text { for } \quad x>0 $$ with $$ -D \frac{\partial c}{\partial x}(0, t)=Q \quad \text { and } \quad c(x, t) \rightarrow 0 \text { as } x \rightarrow \infty $$ where \(Q\) is the rate of morphogen production. (a) Let's try to find a steady state distribution of morphogen. That is, we will assume that over time the morphogen concentration reaches some state that does not change with time, i.e., the concentration is given by a function \(C(x) .\) Then \(C(x)\) will satisfy the partial differential equation if and only if: $$ \begin{aligned} 0 &=D \frac{d^{2} C}{d x^{2}} \quad \text { for } \quad x>0 \\ -D C^{\prime}(0) &=Q \quad \text { and } \quad C(x) \rightarrow 0 \text { as } x \rightarrow \infty \end{aligned} $$ Show that there is no function \(C(x)\) that satisfies this differential equation. [Hint: Start by integrating once \((10.48)\) to find \(d C / d x\) and then again to find \(\mathcal{C}(x)\), then try to impose the constraints at \(x=0\), and as \(x \rightarrow \infty\) on your solution.] (b) Now let's incorporate morphogen degradation into our model. We will assume that the breakdown of morphogen has first order kinetics (see Section \(5.9\) for a discussion of the different kinds of kinetics that chemical reactions may have). This means that in one unit of time a fraction \(r\) of the morphogen contained in each region of the embryo is degraded. Then our partial differential equation must be altered to: $$ \frac{\partial c}{\partial t}=D \frac{\partial^{2} c}{\partial x^{2}}-r c \quad \text { for } \quad x>0 $$ with $$ -D \frac{\partial c}{\partial x}(0, t)=Q \quad \text { and } \quad c(x, t) \rightarrow 0 \text { as } x \rightarrow \infty $$ Show that this partial differential equation does have a steady state solution of the form: $$ C(x)=Q \sqrt{\frac{1}{D r}} \exp \left(-\sqrt{\frac{r}{D}} x\right) $$ That is, check that this function \(C(x)\) satisfies both the steady state form of \((10.49)\) as well as the constraints at \(x=0\) and as \(x \rightarrow \infty\).

(a) Write $$h(x, y)=\sqrt{x+y}$$ as a composition of two functions.

Find the range of each function \(f(x, y)\), when defined on the specified domain \(D\). \(\left.f(x, y)=x^{2} y ; D=(x, y):-2 \leq x \leq 1,0 \leq y \leq 1, y

Give a geometric interpretation of the set $$A=\left\\{(x, y) \in \mathbf{R}^{2}: \sqrt{x^{2}+6 x+y^{2}-2 y+10}<2\right\\}$$

Find the range of each function \(f(x, y)\), when defined on the specified domain \(D\). \(f(x, y)=\frac{x}{y} ; D=\\{(x, y): 0 \leq x \leq 1,1 \leq y \leq 2\\}\)

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