def test_z4_z2_u1_compute(self): ndim = 10 sign_array = np.random.randint(0, 2, ndim) sign_map = {0: "+", 1: "-"} pattern = "".join([sign_map[ix] for ix in sign_array]) na = np.random.randint(0, 10, ndim) z4arrs = [Z4(n) for n in na] z4out = Z4._compute(pattern, z4arrs) z2arrs = [Z2(n) for n in na] z2out = Z2._compute(pattern, z2arrs) u1arrs = [U1(n) for n in na] u1out = U1._compute(pattern, u1arrs) z4outn = 0 z2outn = 0 u1outn = 0 for p, n in zip(sign_array, na): if p == 0: z4outn += n z2outn += n u1outn += n else: z4outn -= n z2outn -= n u1outn -= n assert z4out.n == z4outn % 4 assert z2out.n == z2outn % 2 assert u1out.n == u1outn
def setUp(self): bond = BondInfo({Z2(0):5, Z2(1):7}) self.bond = bond self.T = rand((bond,)*4, pattern="++--", dq=Z2(1)) self.symmetry = Z2 self.skeleton_test_dq = Z2(1) self.contract_test_dq = (Z2(0),Z2(1)) self.svd_dq_iterator = [Z2(0), Z2(1)] self.shift = Z2(0) self.T1 = rand((bond,)*4, pattern="++--", dq=Z2(0))
def test_z4_z2_u1_flat(self): for z in range(-10, 10): z4a = Z4(z) z4b = Z4.from_flat(z4a.to_flat()) assert z4a == z4b z2a = Z2(z) z2b = Z2.from_flat(z2a.to_flat()) assert z2a == z2b u1a = U1(z) u1b = U1.from_flat(u1a.to_flat()) assert u1a == u1b
def test_z4_z2_u1_numerics(self): for za in range(-10, 10): z4a = Z4(za) z2a = Z2(za) u1a = U1(za) for zb in range(-5, 5): z4b = Z4(zb) z2b = Z2(zb) u1b = U1(zb) z4_add = z4a + z4b z2_add = z2a + z2b u1_add = u1a + u1b assert z4_add.n == (za + zb) % 4 assert z2_add.n == (za + zb) % 2 assert u1_add.n == (za + zb) z4_sub = z4a - z4b z2_sub = z2a - z2b u1_sub = u1a - u1b assert z4_sub.n == (za - zb) % 4 assert z2_sub.n == (za - zb) % 2 assert u1_sub.n == (za - zb)
def test_z4_z2_compute_flat(self): nblks = 30 ndim = 5 sign_array = np.random.randint(0, 2, ndim) sign_map = {0: "+", 1: "-"} pattern = "".join([sign_map[ix] for ix in sign_array]) na = np.random.randint(0, 10, nblks * ndim).reshape(nblks, ndim) z4lsts = [[Z4(na[nb, nd]) for nd in range(ndim)] for nb in range(nblks)] z4arrs = [[z4lsts[nb][nd].to_flat() for nd in range(ndim)] for nb in range(nblks)] z4arrs = np.asarray(z4arrs, dtype=int) z4out = Z4._compute(pattern, z4arrs) z4neg = Z4._compute(pattern, z4arrs, offset=("+", Z4(3)), neg=True) z2lsts = [[Z2(na[nb, nd]) for nd in range(ndim)] for nb in range(nblks)] z2arrs = [[z2lsts[nb][nd].to_flat() for nd in range(ndim)] for nb in range(nblks)] z2arrs = np.asarray(z2arrs, dtype=int) z2out = Z2._compute(pattern, z2arrs) z2neg = Z2._compute(pattern, z2arrs, offset=("-", Z2(1)), neg=True) u1lsts = [[U1(na[nb, nd]) for nd in range(ndim)] for nb in range(nblks)] u1arrs = [[u1lsts[nb][nd].to_flat() for nd in range(ndim)] for nb in range(nblks)] u1arrs = np.asarray(u1arrs, dtype=int) u1out = U1._compute(pattern, u1arrs) u1neg = U1._compute(pattern, u1arrs, offset=("-", U1(1)), neg=True) for i in range(nblks): z4outa = Z4._compute(pattern, z4lsts[i]) z4outb = Z4.from_flat(z4out[i]) assert z4outa == z4outb assert -(z4outa + Z4(3)) == Z4.from_flat(z4neg[i]) z2outa = Z2._compute(pattern, z2lsts[i]) z2outb = Z2.from_flat(z2out[i]) assert z2outa == z2outb assert -(z2outa - Z2(1)) == Z2.from_flat(z2neg[i]) u1outa = U1._compute(pattern, u1lsts[i]) u1outb = U1.from_flat(u1out[i]) assert u1outa == u1outb assert -(u1outa - U1(1)) == U1.from_flat(u1neg[i])
def setUp(self): self.t = 2 self.U = 4 self.tau = 0.1 self.mu = 0.2 self.symmetry = Z2 states = np.zeros([2, 2]) states[0, 0] = .5 ** .5 blocks = [SubTensor(reduced=states, q_labels=(Z2(0), Z2(1))), # 0+ SubTensor(reduced=states, q_labels=(Z2(1), Z2(0)))] # +0, eigenstate of hopping self.hop_psi = SparseFermionTensor(blocks=blocks, pattern="++") blocks = [] states = np.zeros([2, 2]) states[1, 0] = .5 blocks = [SubTensor(reduced=states, q_labels=(Z2(0), Z2(0))), SubTensor(reduced=states.T, q_labels=(Z2(0), Z2(0))), SubTensor(reduced=-states.T, q_labels=(Z2(1), Z2(1))), SubTensor(reduced=states, q_labels=(Z2(1), Z2(1)))] self.hop_exp_psi = SparseFermionTensor(blocks=blocks, pattern="++") psi0 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([1,0]), q_labels=(Z2(0),))], pattern="+") psi1 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([1,0]), q_labels=(Z2(1),))], pattern="+") psi2 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([0,1]), q_labels=(Z2(1),))], pattern="+") psi3 = SparseFermionTensor(blocks=[SubTensor(reduced=np.asarray([0,1]), q_labels=(Z2(0),))], pattern="+") self.psi_array = [psi0, psi1, psi2, psi3] self.sz_array = [0,1,-1,0] self.pn_array = [0,1,1,2] bond = BondInfo({Z2(0):2, Z2(1):2}) self.psi = SparseFermionTensor.random((bond,)*2, pattern="++", dq=Z2(0)) self.fac = (0.5, 0.3)