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Merge pull request #28 from yangguohao/task81
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【PaddlePaddle Hackathon】81 时间演化电路的性能优化
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@Quleaf
Quleaf authored Nov 24, 2021
2 parents 34bb545 + cc9c9e7 commit 99dee56
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80 changes: 80 additions & 0 deletions documents/单测文件.py
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Original file line number Diff line number Diff line change
@@ -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
Expand All @@ -19,3 +98,4 @@
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)

73 changes: 69 additions & 4 deletions paddle_quantum/trotter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,7 @@

from paddle_quantum.utils import Hamiltonian
from paddle_quantum.circuit import UAnsatz
from collections import defaultdict
import warnings
import numpy as np
import re
Expand Down Expand Up @@ -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 <len(coeffs):
if term_index+3<=len(coeffs) and \
len(set(y for x in sites[term_index:term_index+3] for y in x ))==2 and\
set(pauli_words[term_index:term_index+3])=={'XX','YY','ZZ'}:
optimal_circuit(circuit,[tau*i for i in coeffs[term_index:term_index+3]],sites[term_index])
term_index+=3
else:
# 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+=1
# in the reverse mode, if the Hamiltonian is a single element list, reverse the order its each term
else:
if len(grouped_hamiltonian) == 1:
Expand Down Expand Up @@ -361,7 +403,30 @@ def add_n_pauli_gate(circuit, theta, pauli_word, which_qubits):
circuit.h(which_qubits[qubit_index])
elif re.match(r'Y', pauli_word[qubit_index], flags=re.I):
circuit.rx(- PI / 2, which_qubits[qubit_index])

def optimal_circuit(circuit,theta,which_qubits):
r""" 添加一个优化电路，哈密顿量为'XXYYZZ'`
Args:
circuit (UAnsatz): 需要添加门的电路
theta list(tensor or float): 旋转角度需要传入三个参数
which_qubits (list or np.ndarray): ``pauli_word`` 中的每个算符所作用的量子比特编号
"""
p = np.pi/2
x,y,z = theta
alpha = paddle.to_tensor(3*p-4*x*p+2*x,dtype='float64')
beta = paddle.to_tensor(-3*p+4*y*p-2*y,dtype='float64')
gamma = paddle.to_tensor(2*z-p,dtype='float64')
which_qubits.sort()
a,b = which_qubits
circuit.rz(paddle.to_tensor(p,dtype='float64'),b)
circuit.cnot([b,a])
circuit.rz(gamma,a)
circuit.ry(alpha,b)
circuit.cnot([a,b])
circuit.ry(beta,b)
circuit.cnot([b,a])
circuit.rz(paddle.to_tensor(-p,dtype='float64'),a)

def __group_hamiltonian_xyz(hamiltonian):
r""" 将哈密顿量拆分成 X、Y、Z 以及剩余项四个部分，并返回由他们组成的列表
Expand Down

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