public void runSymHelium()
{
double E0 = double.PositiveInfinity;
int size = 30;
List <matrix> basis = generateTestFunctions(size);
List <Permutation> p = new List <Permutation>();
List <int> l1 = new List <int>(); l1.Add(0); l1.Add(1); l1.Add(2);
List <int> l2 = new List <int>(); l2.Add(1); l2.Add(0); l2.Add(2);
p.Add(new Permutation(l1, 1, 1));
p.Add(new Permutation(l2, -1, 1));
perms = p;
for (int k = 0; k < 1000; k++)
{
for (int i = 0; i < size; i++)
{
for (int j = 0; j < 100; j++)
{
List <matrix> tmpbasis = new List <matrix>(basis);
tmpbasis[i] = generateA();
if (validateB(generateB2(tmpbasis)))
{
vector v = new vector(tmpbasis.Count);
matrix L = new CholeskyDecomposition(generateB2(tmpbasis)).L;
matrix inv = new QRdecomposition(L).inverse();
matrix inv_T = new QRdecomposition(L.transpose()).inverse();
matrix h = generateH2(tmpbasis);
matrix m = inv * h * inv_T;
jacobi.eigen(m, v);
double low = v[0];
if (low < E0)
{
E0 = low;
basis = tmpbasis;
Console.WriteLine(E0);
if (E0 < -2.2)
{
h.print();
}
}
}
}
}
}
}
// Calculate eigen values of system as specified in problem
public vector eigenValues(List <matrix> testFunctions)
{
vector v = new vector(testFunctions.Count);
/* try { */
matrix H = generateH(testFunctions);
matrix B = generateB(testFunctions);
matrix L = new CholeskyDecomposition(B).L;
matrix inv = new QRdecomposition(L).inverse();
matrix inv_T = new QRdecomposition(L.transpose()).inverse();
matrix p = inv * H * inv_T;
jacobi.eigen(p, v);
/* } catch (CholeskyException ce) { */
/* Console.WriteLine(ce); */
/* } */
return(v);
}