Source code for braket.program_sets.circuit_binding

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from __future__ import annotations

import warnings
from collections import defaultdict
from collections.abc import Mapping, Sequence

from braket.ir.openqasm import Program

from braket.circuits import Circuit, Gate, Observable
from braket.circuits.observable import euler_angle_parameter_names
from braket.circuits.observables import Sum
from braket.circuits.serialization import IRType
from braket.program_sets.parameter_sets import ParameterSets, ParameterSetsLike
from braket.pulse import PulseSequence
from braket.quantum_information import PauliString
from braket.registers import QubitSet


[docs] class CircuitBinding: def __init__( self, circuit: Circuit, input_sets: ParameterSetsLike | None = None, observables: Sequence[Observable | PauliString | str] | Sum | None = None, ): """ A single parametrized circuit and multiple parameter sets and observables. In other words, running a circuit binding means running the circuit with each set of input parameters specified. Furthermore, observables are encoded as input parameters by way of Euler angle representation. If both input parameters and observables are provided, then each combination is executed, resulting in a total number of runs equal to the product of the two. For example, if there are 3 input sets and 4 parameters (or a Hamiltonian with 4 terms), the circuit will be run 12 times. Note: Circuits cannot have result types attached. Args: circuit (Circuit): The parametrized circuit input_sets (ParameterSetsLike | None): The inputs to the circuit, if specified. observables (Sequence[Observable | PauliString | str] | Sum | None): The observables or Hamiltonian to measure, if specified. Examples: >>> circuit = Circuit().rx(0, FreeParameter("theta")).cnot(0, 1) >>> observable = 2.1 * X(0) @ Z(1) - 4.5 * Z(0) @ Y(1) # Sum Hamiltonian >>> # observable = [X(0) @ Z(1), Z(0) @ Y(1)] # Or a list of single-term observables >>> binding = CircuitBinding(circuit, {"theta": [1.23, 1.73, 0.73]}, observable) """ if not input_sets and not observables: raise ValueError("At least one of input_sets and observables must be specified") if ( observables and not isinstance(observables, Sum) and any(isinstance(obs, Sum) for obs in observables) ): raise TypeError("Cannot have Sum Hamiltonian in list of observables") if circuit.result_types: raise ValueError("Circuit cannot have result types") self._circuit = circuit self._input_sets = ParameterSets(input_sets) if input_sets else None self._observables = CircuitBinding._to_observables(observables) @staticmethod def _to_observables( observables: Sequence[Observable | PauliString | str] | Sum | None, ) -> Sequence[Observable] | Sum | None: if not observables: return None if isinstance(observables, Sum): return observables obs = [] for o in observables: if isinstance(o, Observable): obs.append(o) elif isinstance(o, PauliString): obs.append(o.phase * o.to_unsigned_observable(include_trivial=True)) else: pauli = PauliString(o) obs.append(pauli.phase * pauli.to_unsigned_observable(include_trivial=True)) return obs @property def circuit(self) -> Circuit: """ Circuit: The parametrized circuit """ return self._circuit @property def input_sets(self) -> ParameterSets | None: """ ParameterSets | None: The inputs to the circuit, if specified. """ return self._input_sets @property def observables(self) -> Sequence[Observable] | Sum | None: """ Sequence[Observable] | Sum | None: The observables or qubit Hamiltonian to measure, if specified. """ return self._observables
[docs] def to_ir( self, *, gate_definitions: Mapping[tuple[Gate, QubitSet], PulseSequence] | None = None, ) -> Program: """Serializes the circuit binding into a form that can run on a Braket device. Observables are treated as input parameters via conversion to Euler angles. Args: gate_definitions (dict[tuple[Gate, QubitSet], PulseSequence] | None): The calibration data for the device. default: None. Returns: Program: An OpenQASM program containing the serialized circuit and input parameters. """ if not self._observables: return Program( source=self._circuit.to_ir( IRType.OPENQASM, gate_definitions=gate_definitions ).source, inputs=self._input_sets.as_dict() if self._input_sets else None, ) # with_euler_angles validates that the observable has valid Euler angle gates circuit_with_euler_angles = self._circuit.with_euler_angles(self._observables) euler_angles = self._get_euler_angles() return Program( source=circuit_with_euler_angles.to_ir( IRType.OPENQASM, gate_definitions=gate_definitions ).source, inputs=( self._input_sets * euler_angles if self._input_sets else ParameterSets(euler_angles) ).as_dict(), )
def _get_euler_angles(self) -> dict[str, float] | None: observables = self._observables return ( self._get_euler_angles_sum(observables) if isinstance(observables, Sum) else self._get_euler_angles_list(observables) ) def _get_euler_angles_sum(self, observables: Sum) -> dict[str, float]: euler_angles = defaultdict(list) summands = observables.summands if not observables.targets: targets = self._circuit.qubits for obs in summands: for param, angle in obs.get_euler_angles(targets).items(): euler_angles[param].append(angle) return euler_angles targets = QubitSet(q for obs in summands for q in obs.targets) for obs in summands: obs_euler_angles = obs.euler_angles for q in targets: for param in euler_angle_parameter_names(q): euler_angles[param].append(obs_euler_angles.get(param, 0)) return euler_angles def _get_euler_angles_list(self, observables: Sequence[Observable]) -> dict[str, float]: euler_angles = defaultdict(list) circuit_qubits = self._circuit.qubits targets = QubitSet(q for obs in observables for q in (obs.targets or circuit_qubits)) for obs in observables: if not obs.targets: for param, angle in obs.get_euler_angles(targets).items(): euler_angles[param].append(angle) else: obs_euler_angles = obs.euler_angles for q in targets: for param in euler_angle_parameter_names(q): euler_angles[param].append(obs_euler_angles.get(param, 0)) return euler_angles
[docs] def bind_observables_to_inputs( self, inplace: bool = True, add_measure: bool = True, ) -> CircuitBinding: """ Bind observables to input sets of parameters. Translates observables in a CircuitBinding to local measurement bases via a parameterized quantum circuit. The resulting composite input_set will be indexed to the same index in the CompositeEntry. entry.expectation will no longer work, and data will have to be processed as from a distribution. If using a Sum, information on the coefficients will be lost, as well as CompositeEntry.expectation. Kwargs: inplace (bool): whether or not to return a new circuit binding or use the same one add_measure (bool): whether or not to apply Measure instructions to the circuit Returns: CircuitBinding: A new circuit binding with the observables bound. """ measure = Circuit() parameters = self._input_sets.as_dict() if self._input_sets else None if observables := self._observables: if isinstance(observables, Sum): observables = observables.summands warnings.warn( "Binding a Sum discards information on observable weights; please " "distribute your observable in advance using observable.summands.", stacklevel=2, ) euler_angles = self._get_euler_angles() if add_measure: for target in {int(p.split("_")[-1]) for p in euler_angles}: measure.measure(target) measure = Circuit().with_euler_angles(observables) + measure parameters = self._input_sets * euler_angles if parameters else euler_angles if inplace: self._circuit.add_circuit(measure) self._observables = None self._input_sets = parameters return self return CircuitBinding(self._circuit + measure, input_sets=parameters)
def __len__(self): input_sets = self._input_sets observables = self._observables if input_sets and observables: return len(input_sets) * len(observables) if input_sets: return len(input_sets) return len(observables) def __eq__(self, other: CircuitBinding): if not isinstance(other, CircuitBinding): return False return ( self._circuit == other._circuit and self._input_sets == other._input_sets and self._observables == other._observables ) def __repr__(self): return ( f"CircuitBinding(circuit={self._circuit!r}, " f"input_sets={self._input_sets}, " f"observables={self._observables})" )