I am trying to predict the exact solution for the mathieu's equation: y'' + (λ - 2 q cos(2x)) y = 0.
I have been able to get five eigenvalues for the equation using numerical approximation and I want to find for each eigenvalues a guessed exact solution. Below is one of the codes for the fourth Eigenvalue:
from scipy.integrate import solve_bvp
import numpy as np
import matplotlib.pyplot as plt
# Definition of Mathieu's Equation
q = 5.0
def func(x,u,p):
lambd = p[0]
# y'' + (lambda - 2qcos(2x))y = 0
ODE = [u[1],-(lambd - 2.0*q*np.cos(2.0*x))*u[0]]
return np.array(ODE)
# Definition of Boundary conditions(BC)
def bc(ua,ub,p):
return np.array([ua[0]-1., ua[1], ub[1]])
# A guess solution of the mathieu's Equation
def guess(x):
return np.cos(4*x-6)
Nx = 100
x = np.linspace(0, np.pi, Nx)
u = np.zeros((2,x.size))
u[0] = -x
res = solve_bvp(func, bc, x, u, p=[16], tol=1e-7)
sol = guess(x)
print res.p[0]
x_plot = np.linspace(0, np.pi, Nx)
u_plot = res.sol(x_plot)[0]
plt.plot(x_plot, u_plot, 'r-', label='u')
plt.plot(x, sol, color = 'black', label='Guess')
plt.legend()
plt.xlabel("x")
plt.ylabel("y")
plt.title("Mathieu's Equation for Guess$= \cos(3x) \quad \lambda_4 = %g$" % res.p )
plt.grid()
plt.show()
To compute the first five eigenpairs, thus, pairs of eigenvalues and eigenfunctions, of the Mathieu's equation Y" + (λ − 2q cos(2x))y = 0, on the interval [0, π] with boundary conditions: y'(0) = 0, and y'(π) = 0 when q = 5. The solution is normalized so that y(0) = 1. Though all the initial values are known at x = 0, the problem requires finding a value for the parameters that allows the boundary condition y'(π) = 0 to be satisfied. Therefore the guess or exact solution of Mathieu's equation is cos(k*x) where k ∈ ℕ.
from scipy.integrate import solve_bvp
import numpy as np
import matplotlib.pyplot as plt
q = 5.0
# Definition of Mathieu's Equation
def func(x,u,p):
lambd = p[0]
# y'' + (lambda - 2qcos(2x))y = 0 can be rewritten as u2'= - (lambda - 2qcos(2x))u1
ODE = [u[1],-(lambd - 2.0*q*np.cos(2.0*x))*u[0]]
return np.array(ODE)
# Definition of Boundary conditions(BC)
def bc(ua,ub,p):
return np.array([ua[0]-1., ua[1], ub[1]])
# A guess solution of the mathieu's Equation
def guess(x):
return np.cos(5*x) # for k=5
Nx = 100
x = np.linspace(0, np.pi, Nx)
u = np.zeros((2,x.size))
u[0] = -x # initial guess
res = solve_bvp(func, bc, x, u, p=[20], tol=1e-9)
sol = guess(x)
print res.p[0]
x_plot = np.linspace(0, np.pi, Nx)
u_plot = res.sol(x_plot)[0]
plt.plot(x_plot, u_plot, 'r-', label='u')
plt.plot(x, sol, linestyle='--', color='k', label='Guess')
plt.legend(loc='best')
plt.xlabel("x")
plt.ylabel("y")
plt.title("Mathieu's Equation $\lambda_5 = %g$" % res.p)
plt.grid()
plt.savefig('Eigenpair_5v1.png')
plt.show()
