Deprecation of BaseSamplerV1 has a conflict with HamiltonianPhaseEstimation class

What is happening?

Since the release of the version Qiskit 1.2 the class Sampler is deprecated. With this choice we require that all implementations of the BaseSamplerV1 interface have been deprecated in favour of their V2 counterparts. The V2 alternative for the Sampler class is StatevectorSampler.

The class HamiltonianPhaseEstimation has not be modified to accommodate this modification and still uses the BaseSamplerV1 Sampler class. At the moment, the code is still working with the exception of printing a DeprecationWarning. However, once the Sampler class will be removed it will generate an error.

At the moment StatevectorSampler CANNOT be used as sampler for the HamiltonianPhaseEstimation. This is due to the implementation of the function estimate_from_pe_circuit in the module qiskit_algorithms/phase_estimators/phase_estimation.py.

How can we reproduce the issue?

Import required modules

import qiskit 
import qiskit_algorithms
from qiskit.primitives import Sampler, StatevectorSample
from qiskit.quantum_info import Statevector, SparsePauli
from qiskit_algorithms import HamiltonianPhaseEstimation

Use the Sampler class to run the HamiltonianPhaseEstimation

sampler = Sampler(options={"shots" : 10, "seed" : 0})
qpe = HamiltonianPhaseEstimation(num_evaluation_qubits=2, 
                                 sampler=sampler)

qpe_result = qpe.estimate(hamiltonian=SparsePauliOp('XZ'),
                          state_preparation=Statevector.from_label("01"))

/tmp/ipykernel_1033530/360718787.py:1: DeprecationWarning: The class qiskit.primitives.sampler.Sampler is deprecated ...

Use the StatevectorSampler leads to an error:

bound = 0.8
sampler = StatevectorSampler(default_shots=10, seed=0)
qpe = HamiltonianPhaseEstimation(num_evaluation_qubits=2, 
                                 sampler=sampler)

qpe_result = qpe.estimate(hamiltonian=SparsePauliOp('XZ'),
                          state_preparation=Statevector.from_label("01"))

--> 6 qpe_result = qpe.estimate(hamiltonian=SparsePauliOp('XZ'),

File ~/qiskit_algorithms/phase_estimators/hamiltonian_phase_estimation.py:173, in HamiltonianPhaseEstimation.estimate(self, hamiltonian, state_preparation, evolution, bound)

--> 173 phase_estimation_result = self._phase_estimation.estimate( 174 unitary=unitary, state_preparation=state_preparation)

File ~/qiskit_algorithms/phase_estimators/phase_estimation.py:230, in PhaseEstimation.estimate(self, unitary, state_preparation)

--> 230 return self.estimate_from_pe_circuit(pe_circuit)

File ~/qiskit_algorithms/phase_estimators/phase_estimation.py:199, in PhaseEstimation.estimate_from_pe_circuit(self, pe_circuit)

--> 199 phases = circuit_result.quasi_dists[0]

AttributeError: 'PrimitiveResult' object has no attribute 'quasi_dists'

The reason of the error arise because the BaseSamplerV1 provides a result that is a quasi distribution, while BaseSamplerV2 return a primitive unified blocs (PUB) results which is inconsistent with the actual implementation.

What should happen?

The estimate_from_pe_circuit function in phase_estimation.py should check which Sampler is passed on and allow back-compatibility, in case it is passed the BaseSamplerV1, and also allow the usage of the suggested BaseSamplerV2

Any suggestions?

I am happy to open a pull request to modify the code from the current implementation

phases = circuit_result.quasi_dists[0]
phases_bitstrings = {}
for key, phase in phases.items():
    bitstring_key = self._get_reversed_bitstring(self._num_evaluation_qubits, key)
    phases_bitstrings[bitstring_key] = phase
phases = phases_bitstrings
return PhaseEstimationResult(
    self._num_evaluation_qubits, circuit_result=circuit_result, phases=phases
)

To my suggested implementation:

phases_bitstrings = {}
if isinstance(self._sampler, BaseSampler): 
    print("sampler V1")
    phases = circuit_result.quasi_dists[0]
    for key, phase in phases.items():
        bitstring_key = self._get_reversed_bitstring(self._num_evaluation_qubits, key)
        phases_bitstrings[bitstring_key] = phase
elif isinstance(self._sampler, BaseSamplerV2): 
    phases = circuit_result[0].data.meas.get_counts()
    for key, phase in phases.items():
        phases_bitstrings[key[::-1]] = phase
else: 
    raise ValueError("Sampler does not belong to any known Sampler class")
phases = phases_bitstrings
return PhaseEstimationResult(
    self._num_evaluation_qubits, circuit_result=circuit_result, phases=phases
)

Further modification is the annotation of the classes as sampler: BaseSampler | BaseSamplerV2 | None = None. I am open to discuss wheatear the check of the Sampler type is more appropriate in the initialization of the PhaseEstimation object.

To address the issue of deprecating Sampler and ensuring compatibility with HamiltonianPhaseEstimation, we need to modify the estimate_from_pe_circuit function in the phase_estimation.py file to support both BaseSamplerV1 and BaseSamplerV2. Below are the suggested changes:

Changes to `phase_estimation.py`

Import Necessary Classes: Ensure that BaseSampler, BaseSamplerV2, and any other necessary classes are imported at the top of the file.
Modify estimate_from_pe_circuit: Update the function to handle both sampler versions.

from qiskit.primitives import BaseSampler, BaseSamplerV2

def estimate_from_pe_circuit(self, pe_circuit):
    phases_bitstrings = {}

    # Determine the type of sampler and process accordingly
    if isinstance(self._sampler, BaseSampler):
        # Handle BaseSamplerV1
        phases = circuit_result.quasi_dists[0]
        for key, phase in phases.items():
            bitstring_key = self._get_reversed_bitstring(self._num_evaluation_qubits, key)
            phases_bitstrings[bitstring_key] = phase

    elif isinstance(self._sampler, BaseSamplerV2):
        # Handle BaseSamplerV2
        phases = circuit_result[0].data.meas.get_counts()
        for key, phase in phases.items():
            bitstring_key = key[::-1]  # Reverse the bitstring
            phases_bitstrings[bitstring_key] = phase

    else:
        raise ValueError("Sampler does not belong to any known Sampler class")

    phases = phases_bitstrings
    return PhaseEstimationResult(
        self._num_evaluation_qubits, circuit_result=circuit_result, phases=phases
    )

Annotation Update: Update the class annotations to reflect the new sampler compatibility.

# Update the class to accept both types of samplers
class HamiltonianPhaseEstimation:
    def __init__(self, num_evaluation_qubits, sampler: BaseSampler | BaseSamplerV2 | None = None):
        self._num_evaluation_qubits = num_evaluation_qubits
        self._sampler = sampler

Reasoning

Backward Compatibility: By checking the instance type of the sampler, we ensure that existing code using BaseSamplerV1 continues to work without modification.
Forward Compatibility: Supporting BaseSamplerV2 prepares the code for future updates where Sampler is fully removed.
Error Handling: Adding a ValueError ensures that users get immediate feedback if an unsupported sampler type is passed.

Additional Considerations

Testing: Ensure that you have unit tests that cover both sampler versions to validate the changes.
Documentation: Update any documentation to reflect the changes in how samplers are handled within HamiltonianPhaseEstimation.

By implementing these changes, the HamiltonianPhaseEstimation class will be compatible with both deprecated and new samplers, ensuring a smooth transition for users as they upgrade to newer versions of Qiskit.

pdhoolia / qiskit