Merge branch 'master' into task80

paddle_quantum/circuit.py

@@ -26,7 +26,7 @@ from paddle import imag, real, reshape, kron, matmul, trace
 from paddle_quantum.utils import partial_trace, dagger, pauli_str_to_matrix
 from paddle_quantum import shadow
 from paddle_quantum.intrinsic import *
-from paddle_quantum.state import density_op
+from paddle_quantum.state import density_op,vec
 
 __all__ = [
     "UAnsatz",
@@ -60,6 +60,29 @@ class UAnsatz:
         # Record history of adding gates to the circuit
         self.__history = []
 
+    def expand(self,new_n):
+        """
+        为原来的量子电路进行比特数扩展
+
+        Args：
+            new_n(int):扩展后的量子比特数
+        """
+        assert new_n>=self.n,'扩展后量子比特数要大于原量子比特数'
+        diff = new_n-self.n
+        dim = 2**diff
+        if self.__state is not None:
+            if self.__run_mode=='density_matrix':
+                shape = (dim,dim)
+                _state = paddle.to_tensor(density_op(diff))
+            elif self.__run_mode=='state_vector':
+                shape = (dim,)
+                _state = paddle.to_tensor(vec(0,diff))
+            
+            _state= paddle.reshape(_state,shape)
+            _state = kron(self.__state,_state)
+            self.__state = _state
+        self.n = new_n
+
     def __add__(self, cir):
         r"""重载加法 ‘+’ 运算符，用于拼接两个维度相同的电路
 

paddle_quantum/utils.py

@@ -33,6 +33,7 @@ from scipy import sparse
 import matplotlib as mpl
 from paddle_quantum import simulator
 import matplotlib.animation as animation
+import matplotlib.image
 
 __all__ = [
     "partial_trace",
@@ -59,6 +60,7 @@ __all__ = [
     "plot_n_qubit_state_in_bloch_sphere",
     "plot_state_in_bloch_sphere",
     "plot_rotation_in_bloch_sphere",
+    "img_to_density_matrix",
 ]
 
 
@@ -915,17 +917,21 @@ class Hamiltonian:
             pass
         return self.coefficients, self.__pauli_words
 
-    def construct_h_matrix(self):
+    def construct_h_matrix(self, n_qubit=None):
         r"""构建 Hamiltonian 在 Z 基底下的矩阵。
 
         Returns:
             np.ndarray: Z 基底下的哈密顿量矩阵形式
         """
         coefs, pauli_words, sites = self.decompose_with_sites()
-        n_qubit = 1
-        for site in sites:
-            if type(site[0]) is int:
-                n_qubit = max(n_qubit, max(site) + 1)
+        if n_qubit is None:
+            n_qubit = 1
+            for site in sites:
+                if type(site[0]) is int:
+                    print(n_qubit,(site))
+                    n_qubit = max(n_qubit, max(site) + 1)
+        else:
+            assert n_qubit>=self.n_qubits,"输入的量子数不小于哈密顿量表达式中所对应的量子比特数"
         h_matrix = np.zeros([2 ** n_qubit, 2 ** n_qubit], dtype='complex64')
         spin_ops = SpinOps(n_qubit, use_sparse=True)
         for idx in range(len(coefs)):
@@ -1719,3 +1725,24 @@ def decompose(matrix):
         pauli_form.append(pauli_site)
 
     return pauli_form
+
+def img_to_density_matrix(img_file):
+    r"""将图片编码为密度矩阵
+    Args:
+        img_file: 图片文件
+
+    Return:
+        rho:密度矩阵 ``
+    """
+    img_matrix = matplotlib.image.imread(img_file)
+    
+    #将图片转为灰度图
+    img_matrix = img_matrix.mean(axis=2)
+    
+    #填充矩阵,使其变为[2**n,2**n]的矩阵
+    length = int(2**np.ceil(np.log2(np.max(img_matrix.shape))))
+    img_matrix = np.pad(img_matrix,((0,length-img_matrix.shape[0]),(0,length-img_matrix.shape[1])),'constant')
+    #trace为1的密度矩阵
+    rho = img_matrix@img_matrix.T
+    rho = rho/np.trace(rho)
+    return rho

test_and_documents/readme.md

+通过在UAnsatz类中添加新的成员函数expand来实现扩展

test_and_documents/test.py

+from paddle_quantum.circuit import UAnsatz
+from paddle import kron
+from paddle_quantum.state import vec,density_op
+import paddle
+
+
+#density_matrix
+def test_density_matrix():
+    cir = UAnsatz(1)
+    cir.ry(paddle.to_tensor(1,dtype='float64'),0)
+    state = cir.run_density_matrix()
+    cir.expand(3)
+    print(cir.get_state())
+
+    cir2 = UAnsatz(3)
+    cir2.ry(paddle.to_tensor(1,dtype='float64'),0)
+    cir2.run_density_matrix()
+    print(cir2.get_state())
+
+#state_vector
+def test_state_vector():
+    cir = UAnsatz(1)
+    cir.ry(paddle.to_tensor(1,dtype='float64'),0)
+    state = cir.run_state_vector()
+    cir.expand(3)
+    print(cir.get_state())
+
+    cir2 = UAnsatz(3)
+    cir2.ry(paddle.to_tensor(1,dtype='float64'),0)
+    cir2.run_state_vector()
+    print(cir2.get_state())
+
+test_density_matrix()
+test_state_vector()

test_documents/test.py

+from paddle_quantum.utils import img_to_density_matrix
+import paddle
+import matplotlib.image
+import numpy as np
+
+
+img_file = '/home/aistudio/f1.jpeg'
+rho = (img_to_density_matrix(img_file))
+
+#半正定
+w,_=np.linalg.eig(rho)
+print(all(w>=0))
+#迹为1
+print(np.trace(rho))
+#shape为[2**n,2**n]
+print(rho.shape)

test_documents/test_construct_h_matrix.py

+from paddle_quantum.utils import Hamiltonian
+
+h = Hamiltonian([(1, 'Z0, Z1')])
+
+print(h.construct_h_matrix())
+print(h.construct_h_matrix(4))