diff --git "a/documents/\345\215\225\346\265\213\346\226\207\344\273\266.py" "b/documents/\345\215\225\346\265\213\346\226\207\344\273\266.py" index a9961316c4dc6c1389af8c79851b512c7a0409f1..c589510214ae7af4009c5030c2e2087a0bd49b5a 100644 --- "a/documents/\345\215\225\346\265\213\346\226\207\344\273\266.py" +++ "b/documents/\345\215\225\346\265\213\346\226\207\344\273\266.py" @@ -1,4 +1,83 @@ from paddle_quantum.circuit import UAnsatz +from paddle_quantum.utils import Hamiltonian,NKron, gate_fidelity,SpinOps,dagger +from paddle_quantum.trotter import construct_trotter_circuit, get_1d_heisenberg_hamiltonian +from paddle import matmul, transpose, trace +import paddle +import numpy as np +import scipy +from scipy import linalg +import matplotlib.pyplot as plt + +def get_evolve_op(t,h): return scipy.linalg.expm(-1j * t * h.construct_h_matrix()) + +def test(h,n): + t = 2 + r = 1 + cir = UAnsatz(n) + construct_trotter_circuit(cir, h, tau=t/r, steps=r) + print('系统的哈密顿量为：') + print(h) + print('电路的酉矩阵与正确的演化算符之间的保真度为：%.2f' % gate_fidelity(cir.U.numpy(), get_evolve_op(t,h))) + print(cir) + + +print('--------------test1------------') +h1 = get_1d_heisenberg_hamiltonian(length=2, j_x=1, j_y=1, j_z=2,h_z=2 * np.random.rand(2) - 1,periodic_boundary_condition=False)# +test(h1,2) +print('--------------test2------------') +h2 = Hamiltonian([[1., 'X0, X1'], [1., 'Z2, Z3'], [1., 'Y0, Y1'], [1., 'X1, X2'], [1., 'Y2, Y3'], [1., 'Z0, Z1']]) +test(h2,4) +print('--------------test3------------') +h3 = Hamiltonian([ [1, 'Y0, Y1'], [1, 'X1, X0'],[1, 'X0, Y1'],[1, 'Z0, Z1']]) +test(h3,2) + +""" + +运行耗时: 130毫秒 +--------------test1------------ +([1.0, 1.0, 2.0, 0.8812020131972615, 0.7453483155128535], ['XX', 'YY', 'ZZ', 'Z', 'Z'], [[0, 1], [0, 1], [0, 1], [0], [1]]) +系统的哈密顿量为： +1.0 X0, X1 +1.0 Y0, Y1 +2.0 Z0, Z1 +0.8812020131972615 Z0 +0.7453483155128535 Z1 +电路的酉矩阵与正确的演化算符之间的保真度为：0.99 +---------------x----Rz(6.429)----*-----------------x----Rz(-1.57)----Rz(3.525)-- + | | | +--Rz(1.571)----*----Ry(-3.85)----x----Ry(3.854)----*----Rz(2.981)--------------- + +--------------test2------------ +([1.0, 1.0, 1.0, 1.0, 1.0, 1.0], ['XX', 'YY', 'ZZ', 'ZZ', 'XX', 'YY'], [[0, 1], [0, 1], [0, 1], [2, 3], [1, 2], [2, 3]]) +系统的哈密顿量为： +1.0 X0, X1 +1.0 Z2, Z3 +1.0 Y0, Y1 +1.0 X1, X2 +1.0 Y2, Y3 +1.0 Z0, Z1 +电路的酉矩阵与正确的演化算符之间的保真度为：0.51 +-------------------x--------Rz(2.429)--------*---------------------x----Rz(-1.57)------------------------------------------------------------------------------- + | | | +--Rz(1.571)--------*--------Ry(-3.85)--------x--------Ry(3.854)----*--------H--------*-----------------*----H--------------------------------------------------- + | | +------*-------------------------*------------H---------------------------------------x----Rz(4.000)----x----H----Rx(1.571)----*-----------------*----Rx(-1.57)-- + | | | | +------x--------Rz(4.000)--------x--------Rx(1.571)----------------------------------------------------------------------------x----Rz(4.000)----x----Rx(-1.57)-- + +--------------test3------------ +([1.0, 1.0, 1.0, 1.0], ['YY', 'XX', 'ZZ', 'XY'], [[0, 1], [1, 0], [0, 1], [0, 1]]) +系统的哈密顿量为： +1.0 Y0, Y1 +1.0 X1, X0 +1.0 X0, Y1 +1.0 Z0, Z1 +电路的酉矩阵与正确的演化算符之间的保真度为：0.46 +---------------x----Rz(2.429)----*-----------------x----Rz(-1.57)----H----*-----------------*--------H------ + | | | | | +--Rz(1.571)----*----Ry(-3.85)----x----Ry(3.854)----*----Rx(1.571)---------x----Rz(4.000)----x----Rx(-1.57)-- +""" + from paddle_quantum.utils import partial_trace,plot_state_in_bloch_sphere,partial_trace_discontiguous,NKron,plot_n_qubit_state_in_bloch_sphere from mpl_toolkits.mplot3d import Axes3D import numpy as np @@ -19,3 +98,4 @@ state = rho plot_n_qubit_state_in_bloch_sphere(state,show_arrow=True) plot_n_qubit_state_in_bloch_sphere(cir2.run_density_matrix(),show_arrow=True) plot_n_qubit_state_in_bloch_sphere(cir1.run_state_vector(),show_arrow=True) + diff --git a/paddle_quantum/trotter.py b/paddle_quantum/trotter.py index ef68ec387e7ad9bc4f0371692d480c4dbc3f4127..2220d788b652698809b471313d2352a84cb30e1a 100644 --- a/paddle_quantum/trotter.py +++ b/paddle_quantum/trotter.py @@ -18,6 +18,7 @@ Trotter Hamiltonian time evolution circuit module from paddle_quantum.utils import Hamiltonian from paddle_quantum.circuit import UAnsatz +from collections import defaultdict import warnings import numpy as np import re @@ -257,13 +258,54 @@ def __add_first_order_trotter_block(circuit, tau, grouped_hamiltonian, reverse=F if not reverse: for hamiltonian in grouped_hamiltonian: assert isinstance(hamiltonian, Hamiltonian) + + #将原哈密顿量中相同site的XX，YY，ZZ组合到一起 + grouped_hamiltonian = [] + coeffs, pauli_words, sites = hamiltonian.decompose_with_sites() + grouped_terms_indices = [] + left_over_terms_indices = [] + d = defaultdict(list) + #合并相同site的XX,YY,ZZ + for term_index in range(len(coeffs)): + site = sites[term_index] + pauli_word = pauli_words[term_index] + for pauli in ['XX', 'YY', 'ZZ']: + assert isinstance(pauli_word, str), "Each pauli word should be a string type" + if (pauli_word==pauli or pauli_word==pauli.lower()): + key = tuple(sorted(site)) + d[key].append((pauli,term_index)) + if len(d[key])==3: + terms_indices_to_be_grouped = [x[1] for x in d[key]] + grouped_terms_indices.extend(terms_indices_to_be_grouped) + grouped_hamiltonian.append(hamiltonian[terms_indices_to_be_grouped]) + #其他的剩余项 + for term_index in range(len(coeffs)): + if term_index not in grouped_terms_indices: + left_over_terms_indices.append(term_index) + if len(left_over_terms_indices): + for term_index in left_over_terms_indices: + grouped_hamiltonian.append(hamiltonian[term_index]) + #得到新的哈密顿量 + res = grouped_hamiltonian[0] + for i in range(1,len(grouped_hamiltonian)): + res+=grouped_hamiltonian[i] + hamiltonian = res + # decompose the Hamiltonian into 3 lists coeffs, pauli_words, sites = hamiltonian.decompose_with_sites() # apply rotational gate of each term - for term_index in range(len(coeffs)): - # get the sorted pauli_word and site (an array of qubit indices) according to their qubit indices - pauli_word, site = __sort_pauli_word(pauli_words[term_index], sites[term_index]) - add_n_pauli_gate(circuit, 2 * tau * coeffs[term_index], pauli_word, site) + term_index = 0 + while term_index