def is_gate_executable(self, gate: Gate, qubit_mapping: dict) -> bool:
"""Determines if a 2 qubut gate is executable, i.e., whether the gate acts on qubits which are connected in
the coupling graph
Args:
gate (Gate): input 2 qubit gate
qubit_mapping (dict): logical to physical qubit mapping
Returns:
bool: True if the input gate acts on connected qubits. False otherwise
"""
gate_qubits = list(gate.get_qubits())
logical_qubit_1, logical_qubit_2 = gate_qubits[0], gate_qubits[1]
physical_qubit_1, physical_qubit_2 = qubit_mapping.get(
logical_qubit_1), qubit_mapping.get(logical_qubit_2)
return self.coupling_graph.has_edge(physical_qubit_1, physical_qubit_2)
def update_decay_parameter(self, min_score_swap_gate: Gate,
decay_parameter: list) -> list:
"""Updates decay parameters for qubits on which SWAP gate with the minimum heuristic score is applied
Args:
min_score_swap_gate (Gate): SWAP gate with the minimum heuristic score
decay_parameter (list): decay parameter list to be updated
Returns:
list: updated decay parameter list
"""
min_score_swap_qubits = list(min_score_swap_gate.get_qubits())
decay_parameter[min_score_swap_qubits[0]] = decay_parameter[
min_score_swap_qubits[0]] + 0.001
decay_parameter[min_score_swap_qubits[1]] = decay_parameter[
min_score_swap_qubits[1]] + 0.001
return decay_parameter
def update_initial_mapping(self, swap_gate: Gate,
qubit_mapping: dict) -> dict:
"""Update qubit mapping between logical and physical if a SWAP gate is inserted in the program
Args:
swap_gate (Gate): a pyquil SWAP gate
qubit_mapping (dict): a dictionary containing logical to physical qubit mapping
Returns:
dict: updated qubit mapping
"""
temp_mapping = qubit_mapping.copy()
swap_qubits = list(swap_gate.get_qubits())
p_qubit_1, p_qubit_2 = qubit_mapping.get(
swap_qubits[0]), qubit_mapping.get(swap_qubits[1])
p_qubit_1, p_qubit_2 = p_qubit_2, p_qubit_1
temp_mapping.update({
swap_qubits[0]: p_qubit_1,
swap_qubits[1]: p_qubit_2
})
return temp_mapping
def heuristic_function(F: list, circuit_dag: DiGraph, initial_mapping: dict,
distance_matrix: np.matrix, swap_gate: Gate,
decay_parameter: list) -> float:
"""Computes a heuristic cost function that is used to rate a candidate SWAP to determine whether the SWAP gate can be inserted in a program to resolve
qubit dependencies
Args:
F (list): list of gates that have no unexecuted predecessors in the DAG
circuit_dag (DiGraph): a directed acyclic graph representing qubit dependencies between
gates
initial_mapping (dict): a dictionary containing logical to physical qubit mapping
distance_matrix (np.matrix): represents qubit connections from given coupling graph
swap_gate (Gate): candidate SWAP gate
decay_parameter (list): decay parameters for each logical qubit in the mapping
Returns:
float: heuristic score for the candidate SWAP gate
"""
E = create_extended_successor_set(F, circuit_dag)
min_score_swap_qubits = list(swap_gate.get_qubits())
size_E = len(E)
size_F = len(F)
W = 0.5
max_decay = max(decay_parameter[min_score_swap_qubits[0]],
decay_parameter[min_score_swap_qubits[1]])
f_distance = 0
e_distance = 0
for gate_details in F:
f_distance += calculate_distance(gate_details, distance_matrix,
initial_mapping)
for gate_details in E:
e_distance += calculate_distance(gate_details, distance_matrix,
initial_mapping)
f_distance = f_distance / size_F
e_distance = W * (e_distance / size_E)
H = max_decay * (f_distance + e_distance)
return H