Introductory university-level calculus, linear algebra, abstract algebra, probability, statistics, and stochastic processes.
Special solution of inhomogeneous linear differential equations
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The general solution of an inhomogeneous linear differential equation can be obtained as the sum of a special solution and the general solution of the corresponding homogeneous differential equation. We study the method of variation of parameters in particular.
Consider the linear differential equation of the form
\[F(D)y = q(x)\]
where \(F(t)\) is a polynomial and \(q(x)\) is a function. When \(q(x) = 0\), this is a homogeneous linear differential equation. Here, we assume \(q(x) \neq 0\).
Suppose we can factorize \(F(t)\) as \(F(t) = G(t)H(t)\). If \(y = y(x)\) is a solution of \(F(D)y = q\), then \(z = H(D)y\) is a solution of \(G(D)z = q\). Thus, the given differential equation \(F(D)y = q\) is decomposed into two parts:
\(G(D)z = q\) (a linear differential equation of \(z\), given \(q\)),
\(H(D)y = z\) (a linear differential equation of \(y\), given \(z\)),
and we can process one after the other. Thus, by factorizing the polynomial \(F(D)\), we only need to consider the case where \(F(t) = t - \alpha\) (\(\alpha \in \mathbb{C}\)). That is, \(y' - \alpha y = q.\) This ODE can be readily solved by using the method of variation of parameters. The general solution of this ODE is obtained as
Note that \(F(t) = t^2 + t - 6 = (t - 2)(t + 3)\) so the given ODE is \((D - 2)(D+3)y = \cos x\). Solving the homogeneous ODE \((D - 2)(D + 3)y = 0\), we have
\(y = Ae^{2x} + Be^{-3x}\) where \(A, B\) are constants. Let \(z = (D+3)y\), then we have \((D-2)z = \cos x\) and its special solution is given by
\[z = e^{2x}\int e^{-2x}\cos x dx = -\frac{2}{5}\cos x + \frac{1}{5}\sin x.\]
Similarly, solving \((D+3)y = -\frac{2}{5}\cos x + \frac{1}{5}\sin x\), we have a special solution
\[y = e^{-3x}\int e^{3x}\left(-\frac{2}{5}\cos x + \frac{1}{5}\sin x\right)\,dx = -\frac{7}{50}\cos x + \frac{1}{50}\sin x.\]
Thus, the general solution is
\[y = -\frac{7}{50}\cos x + \frac{1}{50}\sin x + Ae^{2x} + Be^{-3x}\]
where \(A, B\) are constants. □
Let's consider the more general case where \(F(t) = t^2 + at + b = (t - \alpha)(t - \beta)\) with \(\alpha \neq \beta\). In particular, when \(a^2 - 4b < 0\), we have \(\beta = \bar{\alpha}\). We want to solve the following second-order ODE:
\[(D - \alpha)(D - \beta)y = q.\]
Let \(z = (D-\beta)y\), and we have
\[(D - \alpha)z = q.\tag{eq:odea}\]
We first solve the homogeneous case \((D - \alpha)z = 0\) which yields
\[z = Ae^{\alpha x}.\]
Now, regarding \(A\) as a function of \(x\), substitute it into (eq:odea), we have
Note the symmetry between the two terms on the right-hand side. This means that swapping \(\alpha\) and \(\beta\) does not change the result. This is expected as the differential operators are commutative: \((D-\alpha)(D - \beta) = (D -\beta)(D - \alpha)\).
Example. Let us solve
\[y'' + y = \frac{1}{\cos x}.\]
The corresponding homogeneous equation is \(y'' + y = 0\). Noting \(D^2 + 1 = (D -i)(D+i)\), its solution is
\[y = Ae^{ix} + Be^{-ix} \tag{eg:hom}\]
where \(A, B \in \mathbb{C}\) are constants. Now, we use the method of variation of parameters by regarding \(A\) and \(B\) as functions of \(x\). According to the above result, we have
Using Euler's formula (\(e^{\pm i x} = \cos x \pm i \sin x\)), this can be further "simplified" (exercise!) as
\[y = (\log|\cos x| + C)\cos x + (x + D)\sin x\]
where \(C\) and \(D\) are constants. Note that this is a real-valued function if \(C\) and \(D\) are real. □
Next, let's consider \((D-\alpha)^2y = q.\) Of course, \((t - \alpha)^2 = (t-\alpha)(t-\alpha)\) so that we can apply the technique above. Let \(y_1 = (D-\alpha)y\), and we solve \((D-\alpha)y_1 = q\). As we have seen above,
\[y_1 = e^{\alpha x}\int e^{-\alpha x}q(x)\,dx.\]
Next, we solve \((D-\alpha)y_2 = y_1\). This gives
We can continue the same process to solve \((D-\alpha)^my = q\) for any \(m = 3, 4, \cdots\). Let the solution of \((D-\alpha)^my = q\) be \(y_m\) for \(m = 0, 1, 2, \cdots\). We can see that
Open sets In \(\mathbb{R}\), we have the notion of an open interval such as \((a, b) = \{x \in \mathbb{R} | a < x < b\}\). We want to extend this idea to apply to \(\mathbb{R}^n\). We also introduce the notions of bounded sets and closed sets in \(\mathbb{R}^n\). Recall that the \(\varepsilon\)-neighbor of a point \(x\in\mathbb{R}^n\) is defined as \(N_{\varepsilon}(x) = \{y \in \mathbb{R}^n | d(x, y) < \varepsilon \}\) where \(d(x,y)\) is the distance between \(x\) and \(y\). Definition (Open set) A subset \(U\) of \(\mathbb{R}^n\) is said to be an open set if the following holds: \[\forall x \in U ~ \exists \delta > 0 ~ (N_{\delta}(x) \subset U).\tag{Eq:OpenSet}\] That is, for every point in an open set \(U\), we can always find an open ball centered at that point, that is included in \(U\). See the following figure. Perhaps, it is instructive to see what is not an open set. Negating (Eq:OpenSet), we have \[\exists x \in U ~ \forall \delta > 0 ~ (N_{\delta}(x) \not
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