# Example Polynomial Roots

From Efficient Java Matrix Library

Eigenvalue decomposition can be used to find the roots in a polynomial by constructing the so called companion matrix. While faster techniques do exist for root finding, this is one of the most stable and probably the easiest to implement.

Because the companion matrix is not symmetric a generalized eigenvalue [MatrixDecomposition decomposition] is needed. The roots of the polynomial may also be complex.

External Resources:

# Example Code

```
public class PolynomialRootFinder {
/**
* <p>
* Given a set of polynomial coefficients, compute the roots of the polynomial. Depending on
* the polynomial being considered the roots may contain complex number. When complex numbers are
* present they will come in pairs of complex conjugates.
* </p>
*
* <p>
* Coefficients are ordered from least to most significant, e.g: y = c[0] + x*c[1] + x*x*c[2].
* </p>
*
* @param coefficients Coefficients of the polynomial.
* @return The roots of the polynomial
*/
public static Complex_F64[] findRoots( double... coefficients ) {
int N = coefficients.length - 1;
// Construct the companion matrix
DMatrixRMaj c = new DMatrixRMaj(N, N);
double a = coefficients[N];
for (int i = 0; i < N; i++) {
c.set(i, N - 1, -coefficients[i]/a);
}
for (int i = 1; i < N; i++) {
c.set(i, i - 1, 1);
}
// use generalized eigenvalue decomposition to find the roots
EigenDecomposition_F64<DMatrixRMaj> evd = DecompositionFactory_DDRM.eig(N, false);
evd.decompose(c);
Complex_F64[] roots = new Complex_F64[N];
for (int i = 0; i < N; i++) {
roots[i] = evd.getEigenvalue(i);
}
return roots;
}
}
```