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Prove Theorem 9.7 .2 by completing the following argument. According to Green's theorem in the plane, if \(C\) is a sufficiently smooth simple closed curve, and if \(F\) and \(G\) are continuous and have continuous first partial derivatives, then $$ \int_{C}[F(x, y) d y-G(x, y) d x]=\iint_{R}\left[F_{x}(x, y)+G_{y}(x, y)\right] d A $$ where \(C\) is traversed counterclockwise and \(R\) is the region enclosed by \(C .\) Assume that \(x=\phi(t), y=\psi(t)\) is a solution of the system ( 15) that is periodic with period \(T\). Let \(C\) be the closed curve given by \(x=\phi(t), y=\psi(t)\) for \(0 \leq t \leq T\). Show that for this curve the line integral is zero. Then show that the conclusion of Theorem 9.7 .2 must follow.

Short Answer

Expert verified
#tag_title#Step 2: Show that the line integral is zero#tag_content# To show that the line integral is zero, we need to show that the given parameterized solution satisfies: $$ \int_{0}^{T}\left[F(\phi(t), \psi(t))\frac{d\psi(t)}{dt}-G(\phi(t), \psi(t))\frac{d\phi(t)}{dt}\right] dt = 0 $$ We know that the parameterized solution $(x, y) = (\phi(t), \psi(t))$ is a periodic solution to the system. Thus, we have: $$ \begin{cases} \frac{d\phi}{dt} = F(\phi(t), \psi(t)) \\ \frac{d\psi}{dt} = G(\phi(t), \psi(t)) \end{cases} $$ Substituting this into the integral, we get: $$ \int_{0}^{T}\left[F(\phi(t), \psi(t))G(\phi(t), \psi(t))-G(\phi(t), \psi(t))F(\phi(t), \psi(t))\right] dt $$ Simplifying the integrand gives: $$ \int_{0}^{T}\left[F(\phi(t), \psi(t))G(\phi(t), \psi(t))-F(\phi(t), \psi(t))G(\phi(t), \psi(t))\right] dt = 0 $$ Since the integrand is identically zero, the line integral is indeed zero. #tag_title#Step 3: Show the conclusion of Theorem 9.7.2 follows#tag_content# Since the line integral of our parameterized periodic solution is zero, we can now attempt to show how this demonstrates the conclusion of Theorem 9.7.2. Theorem 9.7.2 states that if a sufficiently smooth simple closed curve C and two continuous functions, F and G, are given with continuous first partial derivatives, then the line integral of F and G along curve C is zero. We have already shown that the line integral of our parameterized periodic solution is zero. By Green's theorem, the double integral over the region R enclosed by curve C is zero as well: $$ \iint_{R}\left[F_{x}(x, y)+G_{y}(x, y)\right] d A = 0 $$ The zero line integral implies that the contribution to the total integral from all points inside the region R balances out. This means that there must be some equal and opposite contributions within the region, proving the conclusion of Theorem 9.7.2.

Step by step solution

01

Compute the line integral using Green's theorem

Using Green's theorem, the integral along the curve C can be written as: $$ \int_{C}[F(x, y) d y-G(x, y) d x]=\iint_{R}\left[F_{x}(x, y)+G_{y}(x, y)\right] d A $$ We are given a parameterized solution for the system \((x, y) = (\phi(t), \psi(t))\). So, let's transform the integral in terms of t: $$ \int_{0}^{T}\left[F(\phi(t), \psi(t))\frac{d\psi(t)}{dt}-G(\phi(t), \psi(t))\frac{d\phi(t)}{dt}\right] dt $$

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Key Concepts

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

Line Integral
A line integral is a technique to integrate a function along a curve. Imagine tracing a path through a field where each point has a value. The line integral accumulates the values along this path. It's key in physics for calculating work done by a force along a path.
In the context of Green's Theorem, a line integral relates to the circulation of a vector field around a closed curve. You evaluate it over a curve defined by two functions, say \(F(x, y)\) and \(G(x, y)\). The integral then becomes: \[ \int_{C}[F(x, y) d y-G(x, y) d x] \] Here, "C" is a curve in the plane, and "dy" and "dx" represent small changes along y and x. Green's Theorem connects this line integral with a region's area, simplifying many calculations.
Parameterized Solution
A parameterized solution lets us express a curve using parameters. Typically, these parameters can be a single variable, such as \(t\), to represent multiple variables \( (x, y)\). This is especially useful in calculus and physics when describing complex paths.
For example, a curve might be represented as \(x = \phi(t)\) and \(y = \psi(t)\). Here, \(\phi(t)\) and \(\psi(t)\) describe how "x" and "y" change over time. It turns a two-variable problem into a single-variable one, which simplifies analysis and integrations. \[ \int_{0}^{T}\left[F(\phi(t), \psi(t))\frac{d\psi(t)}{dt}-G(\phi(t), \psi(t))\frac{d\phi(t)}{dt}\right] dt \] This specific transformation allows us to solve the line integral along the parameterized curve.
Partial Derivatives
Partial derivatives measure how a function changes as one variable changes, while keeping others constant. In multivariable calculus, they are foundational for analyzing functions with several variables. They're like a flashlight showing how one dimension varies at a time.
For a function \(F(x, y)\), the partial derivative with respect to "x" would be \(F_x(x, y)\) and with respect to "y" would be \(F_y(x, y)\).
These derivatives form a key part of Green's Theorem. They help bridge changes along the curve to changes over the area: \[ \iint_{R}\left[F_x(x, y) + G_y(x, y)\right] dA \] Understanding partial derivatives enables analysis over curves and surfaces, crucial in physics and engineering applications.
Closed Curve
A closed curve is a loop that starts and ends at the same point without crossing itself. Think of it as a rubber band layed on a plane. Closed curves are fundamental for applying Green's Theorem.
They enclose an area (like a circle or an ellipse) that makes it possible to explore the relationship between a line integral around the curve and a double integral over the region it encloses.
In Green's Theorem, such closed curves allow us to derive the equivalence between the circulation around "C" and the area "R" it outlines: \[ \int_{C}[...] = \iint_{R}[...] \] Traversing the curve counterclockwise is standard, maintaining consistency in calculations, particularly in physics.

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Most popular questions from this chapter

For certain \(r\) intervals, or windows, the Lorenz equations exhibit a period- doubling property similar to that of the logistic difference equation discussed in Section \(2.9 .\) Careful calculations may reveal this phenomenon. (a) One period-doubling window contains the value \(r=100 .\) Let \(r=100\) and plot the trajectory starting at \((5,5,5)\) or some other initial point of your choice. Does the solution appear to be periodic? What is the period? (b) Repeat the calculation in part (a) for slightly smaller values of \(r .\) When \(r \cong 99.98\), you may be able to observe that the period of the solution doubles. Try to observe this result by performing calculations with nearby values of \(r\). (c) As \(r\) decreases further, the period of the solution doubles repeatedly. The next period doubling occurs at about \(r=99.629 .\) Try to observe this by plotting trajectories for nearby values of \(r .\)

(a) Determine all critical points of the given system of equations. (b) Find the corresponding linear system near each critical point. (c) Find the eigenalues of each linear system. What conclusions can you then draw about the nonlinear system? (d) Draw a phase portrait of the nonlinear system to confirm your conclusions, or to extend them in those cases where the linear system does not provide definite information about the nonlinear system. $$ d x / d t=1-x y, \quad d y / d t=x-y^{3} $$

Determine the periodic solutions, if any, of the system $$ \frac{d x}{d t}=y+\frac{x}{\sqrt{x^{2}+y^{2}}}\left(x^{2}+y^{2}-2\right), \quad \frac{d y}{d t}=-x+\frac{y}{\sqrt{x^{2}+y^{2}}}\left(x^{2}+y^{2}-2\right) $$

Can be interpreted as describing the interaction of two species with population densities \(x\) and \(y .\) In each of these problems carry out the following steps. (a) Draw a direction field and describe how solutions seem to behave. (b) Find the critical points. (c) For each critical point find the corresponding linear system. Find the eigenvalues and eigenvectors of the linear system; classify each critical point as to type, and determine whether it is asymptotically stable, or unstable. (d) Sketch the trajectories in the neighborhood of each critical point. (e) Draw a phase portrait for the system. (f) Determine the limiting behavior of \(x\) and \(y\) as \(t \rightarrow \infty\) and interpret the results in terms of the populations of the two species. $$ \begin{array}{l}{d x / d t=x(1-0.5 x-0.5 y)} \\ {d y / d t=y(-0.25+0.5 x)}\end{array} $$

Can be interpreted as describing the interaction of two species with population densities \(x\) and \(y .\) In each of these problems carry out the following steps. (a) Draw a direction field and describe how solutions seem to behave. (b) Find the critical points. (c) For each critical point find the corresponding linear system. Find the eigenvalues and eigenvectors of the linear system; classify each critical point as to type, and determine whether it is asymptotically stable, or unstable. (d) Sketch the trajectories in the neighborhood of each critical point. (e) Draw a phase portrait for the system. (f) Determine the limiting behavior of \(x\) and \(y\) as \(t \rightarrow \infty\) and interpret the results in terms of the populations of the two species. $$ \begin{array}{l}{d x / d t=x(1.5-0.5 y)} \\ {d y / d t=y(-0.5+x)}\end{array} $$

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