def apply_swap(self, wire_index1, wire_index2):
'''
Method applying the swap gate to the quantum state \n
@param wire_index1: Integer indicating location of gate \n
@param wire_index2: Integer indicating location of gate \n
@return: State changed via going through gate \n
'''
assert wire_index1 < self.qn or wire_index2 < self.qn, (
'Input argument should be between wire 0 to ' + str(self.qn - 1))
if self.qn == 2:
self.state = SparseMatrix.dot(QG.SWAP, self.state)
else:
if wire_index1 < wire_index2:
a = wire_index1
else:
a = wire_index2
gate_list = []
for i in range(self.qn - 1):
if i == a:
gate_list.append(QG.SWAP)
else:
gate_list.append(QG.eye)
gate_M = gate_list[0]
for i in range(1, self.qn - 1):
gate_M = SparseMatrix.tensordot(gate_M, gate_list[i])
self.state = SparseMatrix.dot(gate_M, self.state)
def apply_pauliZ(self, wire_index):
'''
Method applying the Pauli Z gate to the quantum state \n
@param wire_index: Integer indicating location of gate \n
@return: State changed via going through gate \n
'''
assert -1 < wire_index < self.qn, (
'Input argument should be between wire 0 to ' + str(self.qn - 1))
if self.qn == 1:
self.state = SparseMatrix.dot(QG.PZ, self.state)
else:
gate_list = []
for i in range(self.qn):
if i == wire_index:
gate_list.append(QG.PZ)
else:
gate_list.append(QG.eye)
gate_M = gate_list[0]
for i in range(1, self.qn):
gate_M = SparseMatrix.tensordot(gate_M, gate_list[i])
self.state = SparseMatrix.dot(gate_M, self.state)
def apply_amplification(self):
'''
Method applying amplitude amplification of marked item \n
@return: Changed qubit state via amplification of marked item \n
'''
s = np.zeros(2**self.qn)
s[0] = 1
s = SparseMatrix.sparsify(s.reshape(len(s), 1))
gate_list = []
for i in range(self.qn):
gate_list.append(QG.H)
H = gate_list[0]
for i in range(1, self.qn):
H = SparseMatrix.tensordot(H, gate_list[i])
s = SparseMatrix.dot(H, s)
s_T = SparseMatrix.transpose(s)
s_s = SparseMatrix.tensordot(s, s_T)
s_s_2 = SparseMatrix.multiply(s_s, 2)
eye = SparseMatrix.sparsify(np.eye(2**self.qn))
diffuser = SparseMatrix.minus(s_s_2, eye)
self.state = SparseMatrix.dot(diffuser, self.state)
def apply_grover_oracle(self, marks):
'''
Method to apply grover oracle \n
@param marks: Integer or list of location for oracle \n
@return: Changed qubit state with grover oracle \n
'''
eye = np.eye(2**self.qn)
oracle = eye
if isinstance(marks, int):
oracle[marks][marks] = -1
else:
for mark in marks:
oracle[mark][mark] = -1
oracle = SparseMatrix.sparsify(oracle)
self.state = SparseMatrix.dot(oracle, self.state)