Matrices
A 3×3 matrix is a matrix of the form: (a,b,c|d,e,f|g,h,i)
The determinant of a 3×3 matrix can be found by Sarrus’ Method: (aei+bfg+cdh)-(ceg+fha+ibd)
To find the inverse M^-1 of a 3×3 matrix M, a number of steps have to be followed:
- Find the determinant
- Find the cofactors of every cell in the matrix (This means the determinant of the 2×2 matrix left after eliminating the row and column of the cell of which the cofactor is being found)
- Alter the signs of the cofactors according to the matrix (+,-,+|-,+,-|+,-,+)
- Transpose the matrix so that each row becomes a column and vice versa, so (a,b,c|d,e,f|g,h,i) becomes (a,d,g|b,e,h|c,f,i).
- Divide the resultant matrix by the determinant of the original matrix
The matrix M-(lamda)I = (a-lamba,b,c|d,e-lamda,f|g,h,i-lamda). The characteristic equation of a matrix is equating the determinant to 0, ending up with an equation in terms of lamda.
Eigenvalues are values of lamda for which det(M-(lamda)I)=0.
To obtain eigenvectors, first obtain simultaneous equations as follows:
ax+by+cz=(lamda)x
dx+ey+fz=(lamda)y
gx+hy+iz=(lamda)z
These can be solved to find the relationship between x, y, and z, and this can be put into the form of a 3×1 eigenvector.
To verify if a matrix is an eigenvector of a matrix, postmultiply the matrix by the eigenvector. If the output is a scalar multiple of the eigenvector, then it is valid.
Once eigenvalues and eigenvectors are known, it is possible to combine them together like so:
Eigenvectors (a,b,c) (d,e,f) (g,h,i)
Eigenvalues j, k, l respectively
P = (a,d,g|b,e,h|c,f,i)
D = (j,0,0|0,k,0|0,0,l)
Now the matrix M can be written as PDP^-1. This is useful for finding powers of M as M^n = PD^nP^-1 and D is a diagonal matrix so D^n = (j^n,0,0|0,k^n,0|0,0,l^n)
Cayley Hamilton theorem states that every square matrix satisfies its own characteristic equation.