Example #1
0
def B(matriz):
    E = mp.eig(matriz, left=False, right=False)
    E = mp.eig_sort(E)
    bd = matriz
    a = 0
    for y in range(5):
        a = a + 1
        d = np.identity(100)
        d[d == 1.0] = np.abs(mp.re(E[y]))
        d1 = mp.matrix(d)
        bd = bd + d1
        o = mp.eig(bd, left=False, right=False)
        o = mp.eig_sort(o)
        if mp.re(o[0]) > 0.001:
            break
    B1 = mp.cholesky(bd)
    return B1, a
Example #2
0
        print("L=" + str(L))
        print(v)
        print("................................")
        #the following cicle takes care of the staggered hopping
        for i in range(END):
            j = (i + 1) % L
            if i % 2 == 0:
                H[i, j] = -v
                H[j, i] = H[i, j]
            elif j % 2 == 0:
                H[i, j] = -1
                H[j, i] = H[i, j]

        #find its eigenvalues and vectors
        eigval, eigvec = mp.eigsy(H)
        eigval, eigvec = mp.eig_sort(eigval, eigvec)

        Cij = Cij_0(eigvec, Np)

        #From now on I will use the Free Fermions technique to calculate the entanglement entropies of the subsistems in units of log2

        SB = FreeFermions(B, Cij) / mp.log(mp.mpf(2.0))

        SAB = FreeFermions(A + B, Cij) / mp.log(mp.mpf(2.0))

        SBC = FreeFermions(B + C, Cij) / mp.log(mp.mpf(2.0))

        SABC = FreeFermions(D, Cij) / mp.log(mp.mpf(2.0))

        #In the end I calculate Sqtopo ad proposed by Wen
        Sq = (SAB + SBC - SB - SABC)
Example #3
0
# estimar M0 yM1

M0_act = ((Y * Y.T) / 100)
M0_in = (M0_act**-1)
MP = (M0_act * M0_in)
o = MP[0:5, 0:5]
o0 = M0_in[0:5, 0:5]
M1_act = ((Y * X.T) / 100)
M0_ant = ((X * X.T) / 100)
A = M1_act * (M0_ant**-1)
BBT = M0_act - (A * M1_act.T)

####
E = mp.eig(BBT, left=False, right=False)
E = mp.eig_sort(E)
# reajuste 0

d = np.identity(100)
d[d == 1.0] = abs(-24.7174268506955680247383180094514)
d1 = mp.matrix(d)
BBT0 = BBT + d1
E0 = mp.eig(BBT0, left=False, right=False)
E0 = mp.eig_sort(E0)

# reajuste 0
d0 = np.identity(100)
d0[d0 == 1.0] = abs(-0.00000062521499573893501604735293439538)
d2 = mp.matrix(d0)
BBT1 = BBT0 + d2
E1 = mp.eig(BBT1, left=False, right=False)