未验证 提交 dfa2b163 编写于 作者: Y yangguohao 提交者: GitHub

Update utils.py

上级 71a17d57
...@@ -56,6 +56,7 @@ __all__ = [ ...@@ -56,6 +56,7 @@ __all__ = [
"haar_state_vector", "haar_state_vector",
"haar_density_operator", "haar_density_operator",
"Hamiltonian", "Hamiltonian",
"plot_n_qubit_state_in_bloch_sphere",
"plot_state_in_bloch_sphere", "plot_state_in_bloch_sphere",
"plot_rotation_in_bloch_sphere", "plot_rotation_in_bloch_sphere",
] ]
...@@ -1281,6 +1282,67 @@ def __plot_bloch_sphere( ...@@ -1281,6 +1282,67 @@ def __plot_bloch_sphere(
) )
def plot_n_qubit_state_in_bloch_sphere(
state,
show_qubits=None,
**args
):
r"""将输入的多量子比特的量子态展示在 Bloch 球面上
Args:
state (list(numpy.ndarray or paddle.Tensor)): 输入的量子态列表,可以支持态矢量和密度矩阵,
该函数下,列表内每一个量子态对应一张单独的图片
show_qubits(list(list)):若为多量子比特,则给出要展示的量子比特,默认为 None,表示全展示
show_arrow (bool): 是否展示向量的箭头,默认为 ``False``
save_gif (bool): 是否存储 gif 动图,默认为 ``False``
filename (str): 存储的 gif 动图的名字
view_angle (list or tuple): 视图的角度,
第一个元素为关于 xy 平面的夹角 [0-360],第二个元素为关于 xz 平面的夹角 [0-360], 默认为 ``(30, 45)``
view_dist (int): 视图的距离,默认为 7
set_color (str): 若要设置指定的颜色,请查阅 ``cmap`` 表。默认为红色到黑色的渐变颜色
"""
assert type(state) == list or type(state) == paddle.Tensor or type(state) == np.ndarray, \
'the type of "state" must be "list" or "paddle.Tensor" or "np.ndarray".'
if type(state) == paddle.Tensor or type(state) == np.ndarray:
state = [state]
state_len = len(state)
assert state_len >= 1, '"state" is NULL.'
for i in range(state_len):
assert type(state[i]) == paddle.Tensor or type(state[i]) == np.ndarray, \
'the type of "state[i]" should be "paddle.Tensor" or "numpy.ndarray".'
if show_qubits is None:
show_qubits = [None]*state_len
else:
assert len(show_qubits)==state_len,'show_qubits大小需要和state相同'
for i in range(state_len):
assert type(show_qubits[i])==list,'the type of show_qubits should be None or list'
# Convert Tensor to numpy
for i in range(state_len):
if type(state[i]) == paddle.Tensor:
state[i] = state[i].numpy()
# Convert state_vector to density_matrix
for i in range(state_len):
if state[i].size == 2:
state_vector = state[i]
state[i] = np.outer(state_vector, np.conj(state_vector))
for i in range(state_len):
if state[i].shape[0]>2:
s = []
if show_qubits[i] is None:
qubits_list = [*range(int(np.log2(state[i].shape[0])))]
else:
qubits_list = show_qubits[i]
rho = paddle.to_tensor(state[i])
for q in qubits_list:
s.append(partial_trace_discontiguous(rho,[q]))
plot_state_in_bloch_sphere(s,**args)
else:
plot_state_in_bloch_sphere(state[i],**args)
def plot_state_in_bloch_sphere( def plot_state_in_bloch_sphere(
state, state,
show_arrow=False, show_arrow=False,
......
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