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(a) Show that \(\phi(t)=e^{2 t}\) is a solution of \(y^{\prime}-2 y^{\prime}-2 y=0\) and that \(y=c \phi(t)\) is also a solution of this equatio for any value of the conntanct \(y^{2}=0\) for \(t>0\), but that \(y=c \phi(t)\) is (b) Show that \(\phi(t)=1 / t\) is a solution of \(y^{\prime}+y^{2}=0\) for \(t>0\), but that \(y=c \phi(t)\) is not solution of this equation anless \(c=0\) or \(c=1 .\) Note that the equation of part (b) is nonlinear, while that of part (a) is linear.

Short Answer

Expert verified
Question: Show that for the following differential equations, the given solutions are valid and find the general form. (a) Verify that \(y'=2y'-2y=0\) has solutions of the form \(y=c e^{2t}\), where c is any constant. (b) Verify that \(y'+y^2=0\) has a solution of the form \(y=\frac{1}{t}\) for \(t>0\), and find under which conditions there can be a solution of the form \(y=\frac{c}{t}\). Answer: (a) We have shown that \(y'=2y'-2y=0\) has a solution \(\phi(t)=e^{2t}\), and the general form of the solution is \(y=c e^{2t}\) for any constant c. (b) We have shown that \(y'+y^2=0\) has a solution \(\phi(t)=\frac{1}{t}\) for \(t>0\), and the general form of the solution is \(y=\frac{c}{t}\) with c only being 0 or 1.

Step by step solution

01

Part (a): Showing that \(\phi(t)=e^{2t}\) is a solution of the equation \(y'-2y'-2y=0\)

To show that \(\phi(t)=e^{2t}\) is a solution, we need to differentiate it with respect to \(t\) and plug it back into the equation. We have: \(\phi(t) = e^{2t}, \phi'(t) = 2e^{2t}\) Now, replace the \(y\) and its derivatives in the given differential equation by \(\phi(t)\) and \(\phi'(t)\), respectively: \(\phi'(t)-2\phi'(t)-2\phi(t) = 2e^{2t}-4e^{2t}-2e^{2t} = 0\) Since the equation holds, \(\phi(t)=e^{2t}\) is indeed a solution.
02

Part (a): Showing that \(y=c\phi(t)\) is a solution of the equation for any value of the constant

Now let's see if \(y=c\phi(t)\) is also a solution, where \(c\) is a constant. \(y(t) = c\phi(t) = ce^{2t}\) Now we will find the derivative: \(y'(t) = 2ce^{2t}\) Now, substitute this back into the equation: \(y'(t)-2y'(t)-2y(t) = 2ce^{2t}-4ce^{2t}-2ce^{2t} = 0\) We can observe that the equation holds for any value of the constant \(c\). Thus, \(y=c\phi(t)\) is also a solution of the given differential equation.
03

Part (b): Showing that \(\phi(t)=1/t\) is a solution of \(y'+y^2=0\) for \(t>0\)

To show that \(\phi(t)=1/t\) is a solution of the given equation, we need to differentiate it with respect to \(t\) and plug it back into the equation. We have: \(\phi(t) = 1/t, \phi'(t) = -1/t^2\) Now, let's plug these values into the equation: \(\phi'(t)+\phi^2(t) = -\frac{1}{t^2}+\frac{1}{t^2} = 0\) Since the equation holds for \(t>0\), \(\phi(t)=1/t\) is a solution of the given differential equation.
04

Part (b): Showing that \(y=c\phi(t)\) is not a solution for this equation unless \(c=0\) or \(c=1\)

Let's check if the scaling of this solution \(y(t)=c\phi(t)=c/t\) will also be a solution of this differential equation. Differentiating this expression with respect to \(t\) gives us: \(y'(t) = -c/t^2\) Now, let's plug this into the equation: \(y'(t) + y^2(t) = -\frac{c}{t^2} + \frac{c^2}{t^2} = \frac{c^2-c}{t^2}\) For this equation to hold, we only have two cases: 1. \(c^2-c=0 \Longrightarrow c(c-1)=0 \Longrightarrow c=0 \text{ or } c=1\) Thus, \(y=c\phi(t)\) is not a solution of this equation (given \(t>0\)) unless \(c=0\) or \(c=1\).

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Key Concepts

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

Linear Differential Equations
Linear differential equations have a defining characteristic: all terms involving the unknown function and its derivatives are linear. A linear differential equation takes the form \( a_n(t)\frac{d^n y}{dt^n} + a_{n-1}(t)\frac{d^{n-1} y}{dt^{n-1}} + \ldots + a_1(t)\frac{dy}{dt} + a_0(t)y = g(t) \) where each term is linear with respect to \( y \). In simpler terms, if we have unknowns like \( y \) or its derivatives, they always appear to the first power and are not multiplied by each other.
This makes the equations easier to solve, as solutions can often be found using integration or substitution. These types of equations often represent systems with a constant or time-varying proportionality and superposition. For the linear equation presented in the exercise, \( y' - 2y' - 2y = 0 \), substituting solutions like \( \phi(t) = ce^{2t} \) keeps the equation balanced for any constant \( c \).
Linear differential equations are common in physics and engineering, describing systems like circuits or oscillations.
Nonlinear Differential Equations
Nonlinear differential equations, in contrast to their linear counterparts, include terms that are nonlinear functions of the unknown function or its derivatives. This could be in the form of powers (other than first power), products of the function and its derivatives, or any other non-linear operation. The essence of a nonlinear differential equation can make them more complex and challenging to solve.
Consider the equation given in the exercise: \( y' + y^2 = 0 \). Unlike linear equations, the term \( y^2 \) introduces nonlinearity. Solving nonlinear problems often requires specific methods or numerical techniques and may not guarantee a closed-form solution.
These equations more accurately reflect real-world processes with complexities such as turbulence, chaotic systems, or biological phenomena where small changes can lead to large-scale effects. The specific nature of the solutions can depend heavily on initial conditions, leading to potential sensitivity or multiple solution branches.
Solution to Differential Equations
Finding a solution to a differential equation involves identifying a function (or a set of functions) that satisfies the equation across a specific domain. There are generally two types of solutions:
  • Particular Solution: This satisfies the differential equation with specific initial and/or boundary conditions.
  • General Solution: Represents all possible solutions to the differential equation and often involves arbitrary constants.
For example, for the linear differential equation in the exercise, \( y = c\phi(t) \) is the general solution, with \( \phi(t) = e^{2t} \). This solution works for any \( c \) value given the equation's form, showing its validity as a general solution for linear cases.
In contrast, for nonlinear equations like \( y' + y^2 = 0 \), the solution \( \phi(t) = \frac{1}{t} \) only holds unless modified by constants, leading to \( c \) being restricted to specific values. Thus, understanding how constants impact solutions is key to fully comprehending differential equations.
Differential Calculus
Differential calculus is a fundamental branch of mathematics that focuses on the concept of the derivative, which represents change. It's a critical tool for solving differential equations as it allows for understanding rates of change within a system.
When working with differential equations, calculus aids in:
  • Finding derivatives: By determining the gradient of functions, which is integral in forming an equation.
  • Initial and Boundary Conditions: Using derivatives to meet specified conditions at the start or endpoints shaping particular solutions.
  • Integration: Provides the means to revert derivatives back to functions, revealing potential solutions.
In the exercise, differentiation allowed for forming the equation's expressions, checking potential solutions like \( \phi'(t) \), and integrating when necessary to find general solutions or specific conditions.
Overall, differential calculus is a foundational tool that offers the methodology needed to unravel differential equations, understanding how quantities dynamically evolve.

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Most popular questions from this chapter

Harvesting a Renewable Resource. Suppose that the population \(y\) of a certain species of fish (for example, tuna or halibut) in a given area of the ocean is described by the logistic equation $$ d y / d t=r(1-y / K) y . $$ While it is desirable to utilize this source of food, it is intuitively clear that if too many fish are caught, then the fish population may be reduced below a useful level, and possibly even driven to extinction. Problems 20 and 21 explore some of the questions involved in formulating a rational strategy for managing the fishery. At a given level of effort, it is reasonable to assume that the rate at which fish are caught depends on the population \(y:\) The more fish there are, the easier it is to catch them. Thus we assume that the rate at which fish are caught is given by \(E y,\) where \(E\) is a positive constant, with units of \(1 /\) time, that measures the total effort made to harvest the given species of fish. To include this effect, the logistic equation is replaced by $$ d y / d t=r(1-y / K) y-E y $$ This equation is known as the Schaefer model after the biologist, M. B. Schaefer, who applied it to fish populations. (a) Show that if \(E0 .\) (b) Show that \(y=y_{1}\) is unstable and \(y=y_{2}\) is asymptotically stable. (c) A sustainable yield \(Y\) of the fishery is a rate at which fish can be caught indefinitely. It is the product of the effort \(E\) and the asymptotically stable population \(y_{2} .\) Find \(Y\) as a function of the effort \(E ;\) the graph of this function is known as the yield-effort curve. (d) Determine \(E\) so as to maximize \(Y\) and thereby find the maximum sustainable yield \(Y_{m}\).

let \(\phi_{0}(t)=0\) and use the method of successive approximations to approximate the solution of the given initial value problem. (a) Calculate \(\phi_{1}(t), \ldots, \phi_{4}(t),\) or (if necessary) Taylor approximations to these iterates. Keep tems up to order six. (b) Plot the functions you found in part (a) and observe whether they appear to be converging. Let \(\phi_{n}(x)=x^{n}\) for \(0 \leq x \leq 1\) and show that $$ \lim _{n \rightarrow \infty} \phi_{n}(x)=\left\\{\begin{array}{ll}{0,} & {0 \leq x<1} \\ {1,} & {x=1}\end{array}\right. $$

Show that if \(\left(N_{x}-M_{y}\right) / M=Q,\) where \(Q\) is a function of \(y\) only, then the differential equation $$ M+N y^{\prime}=0 $$ has an integrating factor of the form $$ \mu(y)=\exp \int Q(y) d y $$

Find the value of \(b\) for which the given equation is exact and then solve it using that value of \(b\). $$ \left(x y^{2}+b x^{2} y\right) d x+(x+y) x^{2} d y=0 $$

Convergence of Euler's Method. It can be shown that, under suitable conditions on \(f\) the numerical approximation generated by the Euler method for the initial value problem \(y^{\prime}=f(t, y), y\left(t_{0}\right)=y_{0}\) converges to the exact solution as the step size \(h\) decreases. This is illustrated by the following example. Consider the initial value problem $$ y^{\prime}=1-t+y, \quad y\left(t_{0}\right)=y_{0} $$ (a) Show that the exact solution is \(y=\phi(t)=\left(y_{0}-t_{0}\right) e^{t-t_{0}}+t\) (b) Using the Euler formula, show that $$ y_{k}=(1+h) y_{k-1}+h-h t_{k-1}, \quad k=1,2, \ldots $$ (c) Noting that \(y_{1}=(1+h)\left(y_{0}-t_{0}\right)+t_{1},\) show by induction that $$ y_{n}=(1+h)^{x}\left(y_{0}-t_{0}\right)+t_{n} $$ for each positive integer \(n .\) (d) Consider a fixed point \(t>t_{0}\) and for a given \(n\) choose \(h=\left(t-t_{0}\right) / n .\) Then \(t_{n}=t\) for every \(n .\) Note also that \(h \rightarrow 0\) as \(n \rightarrow \infty .\) By substituting for \(h\) in \(\mathrm{Eq}\). (i) and letting \(n \rightarrow \infty,\) show that \(y_{n} \rightarrow \phi(t)\) as \(n \rightarrow \infty\). Hint: \(\lim _{n \rightarrow \infty}(1+a / n)^{n}=e^{a}\).

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