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Homogeneous Differential Equations: Definition: Homogeneous Equations: A differential equation is said to be homogeneous if there is no isolated constant term in the equation, e.g., each term in a differential equation for y has y or some derivative of y in each term. Ordinary differential equation A differential equation is an equation which contains the derivatives of a variable, such as the equation here x is the variable and the derivatives are with respect to a second variable t. The letters a, b, c and d are taken to be constants here. This equation would be described as a second order, linear differential equation with constant coefficients. It is second order because of the highest order derivative present, linear because none of the derivatives are raised to a power, and the multipliers of the derivatives are constant. If x were the position of an object and t the time, then the first derivative is the velocity, the second the acceleration, and this would be an equation describing the motion of the object. As shown, this is also said to be a non-homogeneous equation, and in solving physical problems, one must also consider the homogeneous equation. Let y be an unknown function in x with y(n) the nth derivative of y, then an equation of the form is called an ordinary differential equation (ODE) of order n; for vector valued functions, , it is called a system of ordinary differential equations of dimension m. When a differential equation of order n has the form it is called an implicit differential equation whereas the form is called an explicit differential equation. A differential equation not depending on x is called autonomous. A differential equation is said to be linear if F can be written as a linear combination of the derivatives of y with ai(x) and r(x) continuous functions in x. The function r(x) is called the source term; if r(x)=0 then the linear differential equation is called homogeneous, otherwise it is called non-homogeneous or inhomogeneous. Explanation: First Order Homogeneous DE A first order homogeneous differential equation involves only the first derivative of a function and the function itself, with constants only as multipliers. The equation is of the form and can be solved by the substitution The solution which fits a specific physical situation is obtained by substituting the solution into the equation and evaluating the various constants by forcing the solution to fit the physical boundary conditions of the problem at hand. Substituting gives Applications: Homogeneous Linear Equations with Constant Coefficients A second order homogeneous equation with constant coefficients is written as Where a, b and c are constant. This type of equation is very useful in many applied problems (physics, electrical engineering, etc..). Let us summarize the steps to follow in order to find the general solution: (1) Write down the characteristic equation This is a quadratic equation. Let and be its roots we have ; (2) If and are distinct real numbers (this happens if general solution is ), then the (3) If (which happens if ), then the general solution is (4) If and are complex numbers (which happens if general solution is Where ), then the , That is, Example: Find the solution to the IVP Solution: Let us follow the steps: 1 Characteristic equation and its roots Since 4-8 = -4<0, we have complex roots . Therefore, and ; 2 General solution ; 3 In order to find the particular solution we use the initial conditions to determine and . First, we have . Since we get , From these two equations we get , Which implies? Homogeneous equations with constant coefficients The first method of solving linear ordinary differential equations with constant coefficients is due to Euler, who realized that solutions have the form ezx, for possiblycomplex values of z. The exponential function is one of the few functions that keep its shape even after differentiation. In order for the sum of multiple derivatives of a function to sum up to zero, the derivatives must cancel each other out and the only way for them to do so is for the derivatives to have the same form as the initial function. Thus, to solve we set y = ezx, leading to Division by e zx gives the nth-order polynomial This equation F(z) = 0, is the "characteristic" equation considered later by Monge and Cauchy. Formally, the terms of the original differential equation are replaced by zk. Solving the polynomial gives n values of z, z1, ..., zn. Substitution of any of those values for z into e zx gives a solution e zix. Since homogeneous linear differential equations obey the superposition principle, any linear combination of these functions also satisfies the differential equation. When these roots are all distinct, we have n distinct solutions to the differential equation. It can be shown that these are linearly independent, by applying the Vandermonde determinant, and together they form a basis of the space of all solutions of the differential equation. Examples has the characteristic equation This has zeroes, i, −i, and 1 (multiplicity 2). The solution basis is then This corresponds to the real-valued solution basis The preceding gave a solution for the case when all zeros are distinct, that is, each has multiplicity 1. For the general case, if z is a (possibly complex) zero (or root) of F(z) having multiplicity m, then, for , is a solution of the ODE. Applying this to all roots gives a collection of n distinct and linearly independent functions, where n is the degree of F(z). As before, these functions make up a basis of the solution space. If the coefficients Ai of the differential equation are real, then real-valued solutions are generally preferable. Since non-real roots z then come in conjugate pairs, so do their corresponding basis functions xkezx, and the desired result is obtained by replacing each pair with their real-valued linear combinations Re(y) and Im(y), where y is one of the pair. A case that involves complex roots can be solved with the aid of Euler's formula. Examples Given . The characteristic equation is which has zeroes 2+i and 2−i. Thus the solution basis {y1,y2} is a solution if and only if for Because the coefficients are real, we are likely not interested in the complex solutions our basis elements are mutual conjugates . Now y is . The linear combinations and will give us a real basis in {u1,u2}. Application: Simple harmonic oscillator The second order differential equation D2y = − k2y, which represents a simple harmonic oscillator, can be restated as (D2 + k2)y = 0. The expression in parenthesis can be factored out, yielding (D + ik)(D − ik)y = 0, which has a pair of linearly independent solutions, one for (D − ik)y = 0 and another for (D + ik)y = 0. The solutions are, respectively, y0 = A0eikx and y1 = A1e − ikx. These solutions provide a basis for the two-dimensional "solution space" of the second order differential equation: meaning that linear combinations of these solutions will also be solutions. In particular, the following solutions can be constructed and These last two trigonometric solutions are linearly independent, so they can serve as another basis for the solution space, yielding the following general solution: yH = A0cos(kx) + A1sin(kx). Damped harmonic oscillator Given the equation for the damped harmonic oscillator: the expression in parentheses can be factored out: first obtain the characteristic equation by replacing D with λ. This equation must be satisfied for all y, thus: Solve using the quadratic formula: Use these data to factor out the original differential equation: This implies a pair of solutions, one corresponding to and another to The solutions are, respectively, and where ω = b / 2m. From this linearly independent pair of solutions can be constructed another linearly independent pair which thus serve as a basis for the two-dimensional solution space: However, if |ω| < |ω0| then it is preferable to get rid of the consequential imaginaries, expressing the general solution as This latter solution corresponds to the underdamped case, whereas the former one corresponds to the overdamped case: the solutions for the underdamped case oscillate whereas the solutions for the overdamped case do not. Fredholm Theory: Homogeneous equations Much of Fredholm theory concerns itself with finding solutions for the integral equation This equation arises naturally in many problems in physics and mathematics, as the inverse of a differential equation. That is, one is asked to solve the differential equation Lg(x) = f(x) where the function f is given and g is unknown. Here, L stands for a linear differential operator. For example, one might take L to be an elliptic operator, such as in which case the equation to be solved become the Poisson equation. A general method of solving such equations is by means of Green's functions, namely, rather than a direct attack, one instead attempts to solve the equation LK(x,y) = δ(x − y) where δ(x) is the Dirac delta function. The desired solution to the differential equation is then written as This integral is written in the form of a Fredholm integral equation. The function K(x,y) is variously known as a Green's function, or the kernel of an integral. It is sometimes called the nucleus of the integral, whence the term nuclear operator arises. In the general theory, x and y may be points on any manifold; the real number line or mdimensional Euclidean space in the simplest cases. The general theory also often requires that the functions belong to some given function space: often, the space of squareintegrable functions is studied, and Sobolev spaces appear often. The actual function space used is often determined by the solutions of the eigenvalue problem of the differential operator; that is, by the solutions to Lψn(x) = ωnψn(x) where the ωn are the eigenvalues, and the ψn(x) are the eigenvectors. The set of eigenvectors form a Banach space, and, when there is a natural inner product, then the eigenvectors form a Hilbert space, at which point the Riesz representation theorem is applied. Examples of such spaces are the orthogonal polynomials, which occur as the solutions to a class of second-order ordinary differential equations. Given a Hilbert space as above, the kernel may be written in the form where is the dual to ψn. In this form, the object K(x,y) is often called the Fredholm operator or the Fredholm kernel. That this is the same kernel as before follows from the completeness of the basis of the Hilbert space, namely, that one has Since the ωn are generally increasing, the resulting eigenvalues of the operator K(x,y) are thus seen to be decreasing towards zero. Non Homogeneous differential equations: Definition: An equation which is not homogeneous is called non homogeneous. Explanation: First Order Non-homogeneous Differential Equation An example of a first order linear non-homogeneous differential equation is Having a non-zero value for the constant c is what makes this equation nonhomogeneous, and that adds a step to the process of solution. The path to a general solution involves finding a solution to the homogeneous equation (i.e., drop off the constant c), and then finding a particular solution to the non-homogeneous equation (i.e., find any solution with the constant c left in the equation). The solution to the homogeneous equation is By substitution you can verify that setting the function equal to the constant value -c/b will satisfy the non-homogeneous equation. It is the nature of differential equations that the sum of solutions is also a solution, so that a general solution can be approached by taking the sum of the two solutions above. The final requirement for the application of the solution to a physical problem is that the solution fits the physical boundary conditions of the problem. The most common situation in physical problems is that the boundary conditions are the values of the function f(x) and its derivatives when x=0. Boundary conditions are often called "initial conditions". For the first order equation, we need to specify one boundary condition. For example: Substituting at x=0 gives: Inhomogenous equations The inhomogenous Fredholm integral equation may be written formally as f = (K − ω)φ which has the formal solution A solution of this form is referred to as the resolvent formalism, where the resolvent is defined as the operator Given the collection of eigenvectors and eigenvalues of K, the resolvent may be given a concrete form as with the solution being A necessary and sufficient condition for such a solution to exist is one of Fredholm's theorems. The resolvent is commonly expanded in powers of λ = 1 / ω, in which case it is known as the Liouville-Neumann series. In this case, the integral equation is written as and the resolvent is written in the alternate form as Applications: Fredholm determinant The Fredholm determinant is commonly defined as where and and so on. The corresponding zeta function is The zeta function can be thought of as the determinant of the resolvent. The zeta function plays an important role in studying dynamical systems. Note that this is the same general type of zeta function as the Riemann zeta function; however, in this case, the corresponding kernel is not known. The existence of such a kernel is known as the Hilbert-Polya conjecture. Applications: Charging a Capacitor An application of non-homogeneous differential equations A first order non-homogeneous differential equation has a solution of the form : . For the process of charging a capacitor from zero charge with a battery, the equation is . Using the boundary condition Q=0 at t=0 and identifying the terms corresponding to the general solution, the solutions for the charge on the capacitor and the current are: . In this example the constant B in the general solution had the value zero, but if the charge on the capacitor had not been initially zero, the general solution would still give an accurate description of the change of charge with time. The discharge of the capacitor is an example of application of the homogeneous differential equation Capacitor Discharge An application of homogeneous differential equations A first order homogeneous differential equation Has a solution of the form: . For the process of discharging a capacitor which is initially charged to the voltage of a battery, the equation is . Using the boundary condition and identifying the terms corresponding to the general solution, the solutions for the charge on the capacitor and the current are: . Since the voltage on the capacitor during the discharge is strictly determined by the charge on the capacitor, it follows the same pattern. Nonhomogeneous equation with constant coefficients To obtain the solution to the non-homogeneous equation (sometimes called inhomogeneous equation), find a particular solution yP(x) by either the method of undetermined coefficients or the method of variation of parameters; the general solution to the linear differential equation is the sum of the general solution of the related homogeneous equation and the particular solution. Suppose we face For later convenience, define the characteristic polynomial We find the solution basis as in the homogeneous (f=0) case. We now seek a particular solution yp by the variation of parameters method. Let the coefficients of the linear combination be functions of x: Using the "operator" notation D = d / dx and a broad-minded use of notation, the ODE in question is P(D)y = f; so With the constraints the parameters commute out, with a little "dirt": But P(D)yj = 0, therefore This, with the constraints, gives a linear system in the u'j. This much can always be solved; in fact, combining Cramer's rule with the Wronskian, The rest is a matter of integrating u'j. The particular solution is not unique; for any set of constants cj. also satisfies the ODE Example Suppose y'' − 4y' + 5y = sin(kx). We take the solution basis found above {e(2 + i)x,e(2 − i)x}. And so (Notice that u1 and u2 had factors that canceled y1 and y2; that is typical.) For interest's sake, this ODE has a physical interpretation as a driven damped harmonic oscillator; yp represents the steady state, and c1y1 + c2y2 is the transient. Equation with variable coefficients A linear ODE of order n with variable coefficients has the general form Examples A particular simple example is the Cauchy-Euler equation often used in engineering First order equation Examples with the initial condition Using the general solution method: The integration is done from 0 to x, giving: Then we can reduce to: Where κ is 2 from the initial condition. A linear ODE of order 1 with variable coefficients has the general form Dy(x) + f(x)y(x) = g(x). Equations of this form can be solved by multiplying the integrating factor throughout to obtain which simplifies due to the product rule to which, on integrating both sides, yields In other words: The solution of a first-order linear ODE y'(x) + f(x)y(x) = g(x), with coefficients that may or may not vary with x, is: where κ is the constant of integration, and Examples Consider a first order differential equation with constant coefficients: This equation is particularly relevant to first order systems such as RC circuits and massdamper systems. In this case, p(x) = b, r(x) = 1. Hence its solution Applications of homogeneous & Nonhmogeneous equations to matrices: You recall that a linear differential equation was called homogeneous if , and non-homogeneous or inhomogeneous otherwise. We use the same terminology for systems of linear equations and for matrix equations: A matrix equation is called homogeneous if is the zero vector (all entries are zero). A system of linear equations is called homogeneous if the equivalent matrix equation is homogeneous. Homogeneous matrix equations have some special properties: 1. The matrix equation Always has at least one solution, the zero solution (Here 0 stands for a column vector all of whose entries are zero.) 2. If the column vectors and are two solutions to the matrix equation Then so is any linear combination of them, . 3. The complete solution to a matrix equation Is always given in the form where , , ... are solutions and , , ..., are parameters. The number of parameters depends on the dimension of the ``solution space.'' You can see why property (1) holds; a system of linear equations like Will always be satisfied by setting all the variables equal to zero. (This is the same reason a homogeneous linear differential equation can always be satisfied by setting Property (2) depends on the linearity of multiplication by .) . If Then we have that Property (3) also really comes from the linearity, since if we have Then we have that This is the same reason that the general solution to a homogeneous linear differential equation is a linear combination of particular solutions, such as In the case of differential equations, the number of different particular solutions, or the number of constants in the general solution, depends on the order of the differential equation; one solution for a first order equation, two different solutions for a second order equation, etc. In the case of matrix equations, the number of particular solutions is the number of paramters in the general or complete solution, the dimension of the solution space. We can also see property (3) in action by solving a matrix equation. Here's the equation: The augmented matrix of this equation has the row echelon form So we can write down the complete general solution We can rewrite this as The particular solutions from which we can put together this complete solution are The really nice thing we get out of this is a method for finding solutions to nonhomogeneous systems of linear equations (or non-homogeneous matrix equations.) It works exactly the same way as solutions for linear differential equations: If the matrix equation Have one particular solution , and the associated homogeneous equation Has the complete solution homogeneous equation is , then the complete solution to the original non- Example: Has the complete solution (which we computed earlier) Which we can rewrite as This is the sum of the solution to the associated homogeneous system, which we wrote down in the previous example, And a particular solution to this inhomogeneous system Example: The homogeneous system of linear equations Has the complete solution The non-homogenous system Has one particular solution To get the complete solution to the non-homogeneous system We add these together: Exercise 1 Rewrite the systems of linear equations of Exercise 4 (in the last handout) as matrix equations. Exercise 2 Rewrite the following matrix equations as systems of linear equations. Exercise 3 Carry out the following matrix multiplications, or explain why they cannot be carried out. Exercise 4 Solve the following matrix equations using row-reduction. Exercise 5 What does it say about the set of solutions to a system of linear equations if it’s augmented matrix, when put into row-reduced form: (a.) Has a row whose leading entry is in the last column (the column corresponding to the constant terms)? (b.) has all zeroes in the last column? (c.) Has a column, other than the last column, in which no row has a leading entry? (d.) Has rows with leading entries in every column except the last one? Exercise 6 Write down the associated homogeneous matrix equations for the matrix equations in exercise 4. Now write down the complete solution to each of these homogeneous matrix equations. Exercise 7 The matrix equation has one solution given by Give the complete solution to this matrix equation. From Name To Roll.No.9022 Ahmad Sheeraz Sir Atif Firdous