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Determine whether the statement is true or false. If it is true, explain why. If it is false, explain why or give an example that shows it is false. If \(P\) is the solution of the initial-value problem \(P^{\prime}=0.02 P\left(1-\frac{P}{1000}\right), P(0)=1000\), then \(\lim _{t \rightarrow \infty} P(t)=1000\).

Short Answer

Expert verified
The statement is true. The reason for this is that the given initial condition lies exactly at the equilibrium point \(P=1000\). Thus, the solution remains at this equilibrium point, and the limit of \(P(t)\) as \(t\) approaches infinity equals 1000.

Step by step solution

01

Identify the given equation and initial condition

We are given the initial-value problem: \[P'=0.02P\left(1-\frac{P}{1000}\right), \quad P(0)=1000\]
02

Analyzing equilibrium points

To find the equilibrium points, we need to set \(P'=0\) and solve for \(P\): \begin{align*} 0 &= 0.02P\left(1-\frac{P}{1000}\right) \\ 0 &= P\left(1-\frac{P}{1000}\right) \end{align*} This equation is satisfied when \(P=0\) or \(P=1000\). These are our two equilibrium points.
03

Solve the given differential equation

The given differential equation is separable, so we can rearrange the terms and integrate both sides: \[\frac{dP}{P\left(1-\frac{P}{1000}\right)}=0.02\,dt\] Now, integrate both sides of the equation: \[\int\frac{dP}{P\left(1-\frac{P}{1000}\right)} = \int0.02\,dt\] Use the partial fraction decomposition for the left side of the equation: \[\frac{A}{P}+\frac{B}{1-\frac{P}{1000}} = \frac{A(1-\frac{P}{1000})+BP}{P\left(1-\frac{P}{1000}\right)}\] Comparing the numerators, we see that \(A=1\) and \(B=-1\). The left side now becomes: \[\frac{1}{P}-\frac{1}{1-\frac{P}{1000}}\] Integrate both sides: \[\int \left(\frac{1}{P}-\frac{1}{1-\frac{P}{1000}}\right) dP = \int 0.02\,dt\] \[\ln\left|P\right|-\ln\left|1-\frac{P}{1000}\right| =0.02t+C\] Applying exponentials to both sides the equation becomes: \[\frac{P}{1-\frac{P}{1000}}=k e^{0.02t}\] Where \(k=e^C\). Now, use the initial condition \(P(0) = 1000\) to find the value of \(k\): \[\frac{1000}{1-\frac{1000}{1000}}=ke^{0.02(0)} \Rightarrow \frac{1000}{0}=k\] This situation implies that the solution is not possible. This means that the initial condition lies exactly on the equilibrium point \(P=1000\). Therefore, the solution remains at the equilibrium point.
04

Compute the limit and compare with the statement

Since we found that the solution remains at the equilibrium point, we can conclude that: \[\lim_{t \to \infty} P(t) = 1000\] The given statement is true, and the explanation is that the initial condition is at the equilibrium point.

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Key Concepts

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

Equilibrium Points
Equilibrium points in differential equations are fundamental because they represent values where the system is in balance. For a differential equation, these are points where the rate of change is zero, meaning there is no growth or decline at that moment.

To find equilibrium points, set the derivative (or the expression for rate of change) equal to zero and solve for the variable. In this exercise, for the function \(P' = 0.02P\left(1 - \frac{P}{1000}\right)\), setting \(P'=0\) leads us to solve \(P\left(1 - \frac{P}{1000}\right) = 0\). This results in two solutions: \(P=0\) and \(P=1000\).

These solutions indicate the population levels where no change occurs, meaning if the population starts at one of these points, it will remain constant over time. Understanding equilibrium points is crucial for predicting long-term behavior of dynamic systems.
Initial-Value Problem
Initial-value problems in differential equations involve finding a particular solution that fits a given initial condition. The goal is to solve the differential equation and then apply the specific conditions to find a unique solution.

In the exercise, the initial-value problem is defined by \(P'=0.02P\left(1-\frac{P}{1000}\right)\) with the initial condition \(P(0)=1000\). The initial condition means that at time \(t=0\), the value of \(P\) is 1000. This specific information helps determine the constant of integration when solving the differential equation, ensuring that the solution matches the initial starting point.

The challenge is to ensure that any solution to the differential equation satisfies this initial condition, thereby providing a complete understanding of how the system evolves over time starting from that particular initial scenario.
Separable Equations
Separable equations are a powerful tool in solving simple differential equations. These types of equations can be rewritten so that all terms containing one variable are on one side and all terms containing another variable, along with their differential, are on the other side.

In the provided exercise, the differential equation \(P'=0.02P\left(1-\frac{P}{1000}\right)\) can be manipulated into a separable form by rearranging terms:
\[\frac{dP}{P\left(1-\frac{P}{1000}\right)} = 0.02\,dt\]

Now, each side of the equation can be integrated separately. This is useful because it simplifies the process of finding the general solution to the differential equation. After integrating both sides, you can solve for \(P\) in terms of \(t\), incorporating any initial conditions provided, like \(P(0)=1000\), to find the particular solution.
Partial Fraction Decomposition
Partial fraction decomposition is a mathematical technique used to break down complex rational expressions into simpler components, making them easier to integrate. This method is especially useful in solving separable differential equations.

In the case of our exercise, the expression \(\frac{1}{P\left(1-\frac{P}{1000}\right)}\) needs to be integrated, which is challenging in its current form. By decomposing it into partial fractions:
\[\frac{A}{P} + \frac{B}{1-\frac{P}{1000}}\]
we identify values for \(A\) and \(B\) (in this case, \(A=1\) and \(B=-1\)). Substituting these values,
the expression becomes much simpler: \(\frac{1}{P} - \frac{1}{1-\frac{P}{1000}}\).

Each part can now be integrated with more ease, thanks to this decomposition. The process shows us how calculus operates with algebraic techniques to solve problems that initially seem computationally intensive.

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