def long_time_entropy(phi2, t):
#create MPs
def A_up(theta, phi):
return np.array([[0, 1j * np.exp(-1j * phi)], [0, 0]])
def A_down(theta, phi):
return np.array([[np.cos(theta), 0], [np.sin(theta), 0]])
theta1 = 0.9
theta2 = 2.985
phi1 = 0.188
# phi2 = 1.3
A_ups = dict()
A_downs = dict()
A_ups[0] = A_up(theta1, phi1)
A_ups[1] = A_up(theta2, phi2)
A_downs[0] = A_down(theta1, phi1)
A_downs[1] = A_down(theta2, phi2)
tensors = dict()
K = 2
for n in range(0, K):
tensors[n] = np.zeros(
(2, np.size(A_ups[0], axis=0), np.size(A_ups[0], axis=1)),
dtype=complex)
tensors[0][0] = A_downs[0]
tensors[0][1] = A_ups[0]
tensors[1][0] = A_downs[1]
tensors[1][1] = A_ups[1]
from MPS import periodic_MPS
psi = periodic_MPS(N)
for n in range(0, N, 1):
psi.set_entry(n, tensors[int(n % 2)], "both")
#convert MPS -> wf array
wf = np.zeros(system.dim, dtype=complex)
for n in range(0, np.size(system.basis_refs, axis=0)):
bits = system.basis[n]
coef = psi.node[0].tensor[bits[0]]
for m in range(1, np.size(bits, axis=0)):
coef = np.dot(coef, psi.node[m].tensor[bits[m]])
coef = np.trace(coef)
wf[n] = coef
psi_energy = np.dot(np.conj(np.transpose(u)), wf)
evolved_state = time_evolve_state(psi_energy, e, t)
evolved_state_comp = np.dot(np.conj(np.transpose(u)), evolved_state)
S = ent.eval(evolved_state_comp)
print(phi2, S)
return S
def mps_uc3_angles2wf(thetas, system):
def A_up(theta, phi):
return np.array([[0, 1j * np.exp(-1j * phi)], [0, 0]])
def A_down(theta, phi):
return np.array([[np.cos(theta), 0], [np.sin(theta), 0]])
#create MPs
theta3 = thetas[2]
theta2 = thetas[1]
theta1 = thetas[0]
A_ups = dict()
A_downs = dict()
A_ups[0] = A_up(theta1, 0)
A_ups[1] = A_up(theta2, 0)
A_ups[2] = A_up(theta3, 0)
A_downs[0] = A_down(theta1, 0)
A_downs[1] = A_down(theta2, 0)
A_downs[2] = A_down(theta3, 0)
tensors = dict()
K = 3
for n in range(0, K):
tensors[n] = np.zeros(
(2, np.size(A_ups[0], axis=0), np.size(A_ups[0], axis=1)),
dtype=complex)
tensors[0][0] = A_downs[0]
tensors[0][1] = A_ups[0]
tensors[1][0] = A_downs[1]
tensors[1][1] = A_ups[1]
tensors[2][0] = A_downs[2]
tensors[2][1] = A_ups[2]
from MPS import periodic_MPS
psi = periodic_MPS(system.N)
for n in range(0, system.N, 1):
psi.set_entry(n, tensors[int(n % 3)], "both")
wf = np.zeros(system.dim, dtype=complex)
for n in range(0, np.size(system.basis_refs, axis=0)):
bits = system.basis[n]
coef = psi.node[0].tensor[bits[0]]
for m in range(1, np.size(bits, axis=0)):
coef = np.dot(coef, psi.node[m].tensor[bits[m]])
coef = np.trace(coef)
wf[n] = coef
return wf
def TT_wf(theta1, phi1, theta2, phi2):
def A_up(theta, phi):
return np.array([[0, 1j * np.exp(-1j * phi)], [0, 0]])
def A_down(theta, phi):
return np.array([[np.cos(theta), 0], [np.sin(theta), 0]])
A_ups = dict()
A_downs = dict()
A_ups[0] = A_up(theta1, phi1)
A_ups[1] = A_up(theta2, phi2)
A_downs[0] = A_down(theta1, phi1)
A_downs[1] = A_down(theta2, phi2)
tensors = dict()
K = 2
for n in range(0, K):
tensors[n] = np.zeros(
(2, np.size(A_ups[0], axis=0), np.size(A_ups[0], axis=1)),
dtype=complex)
tensors[0][0] = A_downs[0]
tensors[0][1] = A_ups[0]
tensors[1][0] = A_downs[1]
tensors[1][1] = A_ups[1]
# tensors[2][0] = A_downs[2]
# tensors[2][1] = A_ups[2]
from MPS import periodic_MPS
psi = periodic_MPS(N)
for n in range(0, N, 1):
psi.set_entry(n, tensors[int(n % 2)], "both")
#convert MPS -> wf array
wf = np.zeros(system.dim, dtype=complex)
for n in range(0, np.size(system.basis_refs, axis=0)):
bits = system.basis[n]
coef = psi.node[0].tensor[bits[0]]
for m in range(1, np.size(bits, axis=0)):
coef = np.dot(coef, psi.node[m].tensor[bits[m]])
coef = np.trace(coef)
wf[n] = coef
return wf
tensors = dict()
K = 3
for n in range(0,K):
tensors[n] = np.zeros((2,np.size(A_ups[0],axis=0),np.size(A_ups[0],axis=1)),dtype=complex)
tensors[0][0] = A_downs[0]
tensors[0][1] = A_ups[0]
tensors[1][0] = A_downs[1]
tensors[1][1] = A_ups[1]
tensors[2][0] = A_downs[2]
tensors[2][1] = A_ups[2]
from MPS import periodic_MPS
psi = periodic_MPS(N)
for n in range(0,N,1):
psi.set_entry(n,tensors[int(n%3)],"both")
#convert MPS -> wf array
system = unlocking_System([0],"periodic",d,N)
system.gen_basis()
wf = np.zeros(system.dim,dtype=complex)
for n in range(0,np.size(system.basis_refs,axis=0)):
bits = system.basis[n]
coef = psi.node[0].tensor[bits[0]]
for m in range(1,np.size(bits,axis=0)):
coef = np.dot(coef,psi.node[m].tensor[bits[m]])
coef = np.trace(coef)
wf[n] = coef
np.save("z3,entangled_MPS_coef,"+str(system.N),wf)