酉矩阵

目录

• 应用
  • 量子线路的矩阵
• 获取内部数据
  • 获取 numpy.ndarray形式的数据中
• 判等

上一章: KL散度
下一章: 矩阵

---

应用

量子线路的矩阵

获取量子线路 QCircuit 的酉矩阵

API文档链接

Python

 
from pyqpanda3.core import QCircuit,X,CP,CNOT
from pyqpanda3.quantum_info import Unitary
 
# Building QCircuit
cir = QCircuit()
cir << X(0)<<CP(2,1,5.28)<<CNOT(1,0)
# Obtain the unitary matrix of QCircuit
matrix = Unitary(cir)
# Print result
print(matrix)
 

输出

[[0.        +0.j         1.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [1.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         1.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         1.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         1.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  0.53761923-0.84318774j 0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.53761923-0.84318774j]]

获取内部数据

获取 numpy.ndarray形式的数据中

获取内部数据，结果将作为 numpy.ndarray 对象返回

API文档链接

Python

 
from pyqpanda3.quantum_info import Unitary
from pyqpanda3.core import QCircuit,X,CP,CNOT
def test_ndarray():
    cir = QCircuit()
    cir << X(0)<<CP(2,1,5.28)<<CNOT(1,0)
    U = Unitary(cir)
    print("U",U)
    arr = U.ndarray()
    print("arr:",arr)
 
if __name__ == "__main__":
    test_ndarray()
 

输出

U [[0.        +0.j         1.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [1.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         1.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         1.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         1.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  0.53761923-0.84318774j 0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.53761923-0.84318774j]]
arr: [[0.        +0.j         1.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [1.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         1.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         1.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         1.        +0.j         0.        +0.j
  2.        +0.j         0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  0.53761923-0.84318774j 0.        +0.j        ]
 [0.        +0.j         0.        +0.j         0.        +0.j
  1.        +0.j         0.        +0.j         0.        +0.j
  2.        +0.j         0.53761923-0.84318774j]]

判等

判断两个 Unitary 对象的内部数据是否相等

API文档链接

Python

 
from pyqpanda3.quantum_info import Unitary
from pyqpanda3.core import QCircuit,X,CP,CNOT
def test_eq():
    cir = QCircuit()
    cir << X(0)<<CP(2,1,5.28)<<CNOT(1,0)
    U = Unitary(cir)
    U2 = U
    print("U2==U:",U2==U)
    return U2==U
 
if __name__ == "__main__":
    test_eq()
 

输出

U2==U: True