def _generate_cqasm_from_instructions(instructions,
number_of_qubits=2,
full_state_projection=True):
experiment_dict = {
'instructions': instructions,
'header': {
'n_qubits': number_of_qubits,
'number_of_clbits': number_of_qubits,
'compiled_circuit_qasm': ''
},
'config': {
'coupling_map': 'all-to-all',
'basis_gates':
'x,y,z,h,rx,ry,rz,s,cx,ccx,u1,u2,u3,id,snapshot',
'n_qubits': number_of_qubits
}
}
experiment = qiskit.qobj.QasmQobjExperiment.from_dict(experiment_dict)
for instruction in experiment.instructions:
if hasattr(instruction, 'params'):
# convert params to params used in qiskit instructions
qiskit_instruction = Instruction('dummy', 0, 0,
instruction.params)
instruction.params = qiskit_instruction.params
simulator = QuantumInspireBackend(Mock(), Mock())
result = simulator._generate_cqasm(experiment, full_state_projection)
return result
def test_generate_cqasm_with_entangle_algorithm(self):
q = QuantumRegister(2)
b = ClassicalRegister(2)
circuit = QuantumCircuit(q, b)
circuit.h(q[0])
circuit.cx(q[0], q[1])
circuit.measure(q[0], b[0])
circuit.measure(q[1], b[1])
backend = QuantumInspireBackend(Mock(), Mock())
# transpiling the circuits using the transpiler_config
new_circuits = transpile(circuit, backend)
run_config = RunConfig(shots=1024, max_credits=10, memory=False)
# assembling the circuits into a qobj to be run on the backend
qiskit_job = assemble(new_circuits, backend, run_config=run_config)
experiment = qiskit_job.experiments[0]
result = backend._generate_cqasm(experiment)
expected = "version 1.0\n" \
"# cQASM generated by QI backend for Qiskit\n" \
"qubits 2\n" \
"H q[0]\n" \
"CNOT q[0], q[1]\n"
self.assertEqual(result, expected)
def _generate_cqasm_from_circuit(circuit, full_state_projection=True):
run_config_dict = {'shots': 25, 'memory': True}
backend = QuantumInspireBackend(Mock(), Mock())
qobj = assemble(circuit, backend, **run_config_dict)
experiment = qobj.experiments[0]
simulator = QuantumInspireBackend(Mock(), Mock())
result = simulator._generate_cqasm(experiment, full_state_projection)
return result
def _generate_cqasm_from_instructions(instructions, number_of_qubits=2):
experiment_dict = {'instructions': instructions,
'header': {'n_qubits': number_of_qubits,
'number_of_clbits': number_of_qubits,
'compiled_circuit_qasm': ''},
'config': {'coupling_map': 'all-to-all',
'basis_gates': 'x,y,z,h,rx,ry,rz,s,cx,ccx,u1,u2,u3,id,snapshot',
'n_qubits': number_of_qubits}}
experiment = qiskit.qobj.QobjExperiment.from_dict(experiment_dict)
simulator = QuantumInspireBackend(Mock(), Mock())
result = simulator._generate_cqasm(experiment)
return result
def test_generate_cqasm_WithEntangleAlgorithm(self):
q = QuantumRegister(2)
b = ClassicalRegister(2)
circuit = QuantumCircuit(q, b)
circuit.h(q[0])
circuit.cx(q[0], q[1])
circuit.measure(q[0], b[0])
circuit.measure(q[1], b[1])
simulator = QuantumInspireBackend(Mock(), Mock())
qiskit_job = qiskit.compile(circuit, simulator)
experiment = qiskit_job.experiments[0]
result = simulator._generate_cqasm(experiment)
expected = "version 1.0\n" \
"# cQASM generated by QI backend for Qiskit\n" \
"qubits 2\n" \
"H q[0]\n" \
"CNOT q[0], q[1]\n"
self.assertEqual(result, expected)
