updated eigvalue solvers

doc/Programs/EigenvaluesDeepLearning/MatrixRNN.py

@@ -0,0 +1,44 @@
+import scipy as scipy
+import scipy.special as special
+import numpy as np
+import itertools as it
+from pandas import *
+import matplotlib.pylab as plt
+from scipy.integrate import ode
+import time
+
+def unique_rows(a):
+    a = np.ascontiguousarray(a)
+    unique_a = np.unique(a.view([('', a.dtype)]*a.shape[1]))
+    return unique_a.view(a.dtype).reshape((unique_a.shape[0], a.shape[1]))
+
+def hamiltonian(n_pairs,n_basis,delta,g):
+	"""
+	n_pairs - Number of electron pairs
+	n_basis - Number of spacial basis states
+	Returns - The hamiltonian and the reference energy
+	"""
+	n_SD = int(special.binom(n_basis,n_pairs))
+	H_mat = np.zeros((n_SD,n_SD))
+	S = stateMatrix(n_pairs,n_basis)
+	for row in range(n_SD):
+		bra = S[row,:]
+		for col in range(n_SD):
+			ket = S[col,:]
+			if np.sum(np.equal(bra,ket)) == bra.shape:
+				H_mat[row,col] += 2*delta*np.sum(bra - 1) - 0.5*g*n_pairs
+			if n_pairs - np.intersect1d(bra,ket).shape[0] == 1:
+				H_mat[row,col] += -0.5*g
+	return(H_mat,H_mat[0,0])
+
+
+def stateMatrix(n_pairs,n_basis):
+	L = []
+	states = range(1,n_basis+1)
+	for perm in it.permutations(states,n_pairs):
+		L.append(perm)
+	L = np.array(L)
+	L.sort(axis=1)
+	L = unique_rows(L)
+	return(L)
+