def generate_rb_sequence(
self,
depth: int,
gateset: Sequence[Gate],
seed: Optional[int] = None,
interleaver: Optional[Program] = None,
) -> List[Program]:
"""
Construct a randomized benchmarking experiment on the given qubits, decomposing into
gateset. If interleaver is not provided, the returned sequence will have the form
C_1 C_2 ... C_(depth-1) C_inv ,
where each C is a Clifford element drawn from gateset, C_{< depth} are randomly selected,
and C_inv is selected so that the entire sequence composes to the identity. If an
interleaver G (which must be a Clifford, and which will be decomposed into the native
gateset) is provided, then the sequence instead takes the form
C_1 G C_2 G ... C_(depth-1) G C_inv .
The JSON response is a list of lists of indices, or Nones. In the former case, they are the
index of the gate in the gateset.
:param depth: The number of Clifford gates to include in the randomized benchmarking
experiment. This is different than the number of gates in the resulting experiment.
:param gateset: A list of pyquil gates to decompose the Clifford elements into. These
must generate the clifford group on the qubits of interest. e.g. for one qubit
[RZ(np.pi/2), RX(np.pi/2)].
:param seed: A positive integer used to seed the PRNG.
:param interleaver: A Program object that encodes a Clifford element.
:return: A list of pyquil programs. Each pyquil program is a circuit that represents an
element of the Clifford group. When these programs are composed, the resulting Program
will be the randomized benchmarking experiment of the desired depth. e.g. if the return
programs are called cliffords then `sum(cliffords, Program())` will give the randomized
benchmarking experiment, which will compose to the identity program.
"""
# Support QubitPlaceholders: we temporarily index to arbitrary integers.
# `generate_rb_sequence` handles mapping back to the original gateset gates.
gateset_as_program = address_qubits(sum(gateset, Program()))
qubits = len(gateset_as_program.get_qubits())
gateset_for_api = gateset_as_program.out().splitlines()
interleaver_out: Optional[str] = None
if interleaver:
assert isinstance(interleaver, Program)
interleaver_out = interleaver.out(calibrations=False)
depth = int(depth) # needs to be jsonable, no np.int64 please!
request = GenerateRandomizedBenchmarkingSequenceRequest(
depth=depth,
num_qubits=qubits,
gateset=gateset_for_api,
seed=seed,
interleaver=interleaver_out,
)
response = self._compiler_client.generate_randomized_benchmarking_sequence(request)
programs = []
for clifford in response.sequence:
clifford_program = Program()
if interleaver:
clifford_program._calibrations = interleaver.calibrations
# Like below, we reversed the order because the API currently hands back the Clifford
# decomposition right-to-left.
for index in reversed(clifford):
clifford_program.inst(gateset[index])
programs.append(clifford_program)
# The programs are returned in "textbook style" right-to-left order. To compose them into
# the correct pyquil program, we reverse the order.
return list(reversed(programs))
