1.2 Order - order of the highest derivative
of the dependent variable with respect
to the independent variable
1.3 Linear - only if the unknown function and its derivatives
appear to the power 1 Non-linear - otherwise
1.4 Homogeneous - If f(x) is a solution, so is cf(x), where c is an arbitrary
(non-zero) constant. Note that in order for this condition to hold, each term in
a linear differential equation of the dependent variable y must contain y or
any derivative of y. Simply said, the are no constant terms in the equation.
They are usually recognized because the RHS is 0
1.5 Degree - the power to which one of the derivatives is raised
2 First Order Linear ODEs
2.1 Example: a falling object subject to linear
air resistance
2.2 Solution Method
2.2.1 1) Multiply through by integrating factor
"IF", which can be always found
2.2.1.1 2)Recall the formula for calculating the
integrating factor : IF = e^(int f(x)dx )
2.3 NOTE
2.3.1 Some non-linear equations can be
transformed into linear ones by change of
variable
2.4 y' + f(x)y = g(x)
3 2nd and higher order - Linear ODEs
with constant coefficients
3.1 Solution Method
3.1.1 The general solution is the sum of the complementary function and the
particular integral. i.e. GS = CF + PI
3.1.1.1 Complementary function
3.1.1.1.1 General solution to the corresponding
homogeneous equation
3.1.1.2 Particular Integral
3.1.1.2.1 Any solution of the
inhomogeneous equation
3.1.1.2.2 Educated Guess
3.1.1.2.2.1 The trial solutions used to find the PI are usually of the
same form of the Complementary Function: most
commonly constants, polynomials, sine/cosine and
exponentials
3.2 The Wronskian
3.2.1 If the wronskian of n functions f1(x),
f2(x) ... fn(x) is zero, then the functions
are linearly indipendent
3.2.2 The wronskian is the determinant of the matrix which has f1(x), f2(x) ...
fn(x) has elements of the first row, the first derivative of the functions in the
second raw, the second derivative in the third raw and so on up to the
(n-1)th derivative of the functions in the last raw
4 Series Solutions of ODEs
4.1 We can use a power series solution if the function is analytic at
that point - i.e. if the function is locally given by a convergent
power series
4.2 Method
4.2.1 Write each term as a power series
in terms of the independent variable
4.2.1.1 Find the recurrence relation between the
coefficients equating the sum of the power series to
zero
5 Legendre's Equation
5.1 Equation which is often met when solving PDEs (particularly ones which
involve the Laplacian) in spherical polar coordinates when seeking a
separable solution of form u(r,θ,φ) = R(r)T(θ)F(φ)
5.2 Can be solved with
the "series solution"
technique
5.2.1 Power series only converge if k, which is the
coefficient of y in the equation, is equal to
L(L+1), where L = 0,1,2,3 and so k = 0,2,6,12
5.2.1.1 Legendre polynomials
5.2.1.1.1 The solutions are Legendre
polynomials, which are defined
recursively - important for Quantum
Mechanics
5.3 The equation has regular singular points at x = ±1 so, in general, a
series solution about the origin will only converge for |x| < 1.
6 Frobenius Method
(Generalised power
series)
6.1 Technique to find an infinite series solution for a second-order ordinary
differential equation of the form z^2u''+p(z)zu'+q(z)u=0
6.1.1 p(z) and q(z) have to be analytic at 0
6.1.2 Use y = sum Cn(x-x0)^(r+n) to find ...
6.1.2.1 ... Indicial Equation
6.1.2.1.1 recurrence equation
6.1.2.1.2 The general solution
will be y = A_pJ_p
+A_-pJ_-p
6.1.2.1.2.1 Jp is Bessel's function of first kind
6.1.2.1.2.2 four classes of solutions
7 Three important linear PDEs
7.1 Laplace's equation (see
Legendre's equation and
separation of variables)
7.2 Wave equation
7.3 Diffusion equation
8 Solution of PDEs by separation of variables
8.1 Define boundary and initial conditions
8.1.1 Use separation of variable to reduce to ODE eigenvalue problem.
For example, to solve Laplace's equation in 2 dimensions, use the
trial solution T(x,y) = X(x)Y(y) and generate two couples ODEs:
X"=SX and Y"=SY
8.1.1.1 Use homogeneous boundary conditions to find eigenvectors and eigenfunctions
8.1.1.1.1 Apply initial conditions and other boundary conditions