Merge pull request #28 from Jij-Inc/hotfix/num_occurrences

Fixing the issue where num_occurences cannot be set at decoding

jijmodeling_transpiler_quantum/qiskit/minimal_encoding/cost_function.py

@@ -1,7 +1,9 @@
 from __future__ import annotations
-from collections.abc import Callable
+
 import itertools
 import typing as typ
+from collections.abc import Callable
+
 import numpy as np
 import qiskit as qk
 import qiskit.quantum_info as qk_info
@@ -36,7 +38,8 @@ def define_pauli_op(
     one_op = qk_info.SparsePauliOp(
         qk_info.PauliList.from_symplectic(z, x), coeffs=[1 / 2, -1 / 2]
     )
-    identity_op = qk_info.SparsePauliOp(qk_info.Pauli([0], [0]))
+
+    identity_op = qk_info.SparsePauliOp(qk_info.Pauli(([0], [0])))
 
     ancilla_operator = one_op if ancilla else identity_op
 

jijmodeling_transpiler_quantum/qiskit/minimal_encoding/to_minimal_encoding.py

@@ -1,16 +1,16 @@
 from __future__ import annotations
+
 import typing as typ
 from collections.abc import Callable, Sequence
+
+import jijmodeling as jm
+import jijmodeling_transpiler as jmt
 import numpy as np
 import qiskit as qk
 import qiskit.quantum_info as qk_info
 from qiskit.primitives import Estimator
-import jijmodeling as jm
-import jijmodeling_transpiler as jmt
-from .cost_function import (
-    initialize_cost_function,
-    define_pauli_op,
-)
+
+from .cost_function import define_pauli_op, initialize_cost_function
 
 
 class MinimalEncodingBuilder:
@@ -203,5 +203,15 @@ def _decode_from_binary_values(
                 self.minimal_encoding_builder.compiled_instance,
             )
         )
-        # decoded.record.num_occurrences = [[1]] * len(binary_results)
+
+        num_occurrences = [1] * len(binary_results)
+        decoded = jm.SampleSet(
+            record=jm.Record(
+                num_occurrences=num_occurrences,
+                solution=decoded.record.solution,
+            ),
+            evaluation=decoded.evaluation,
+            measuring_time=decoded.measuring_time,
+            metadata=decoded.metadata,
+        )
         return decoded

jijmodeling_transpiler_quantum/qiskit/qaoa/to_qaoa.py

@@ -1,10 +1,14 @@
 from __future__ import annotations
+
 import typing as typ
-import qiskit as qk
-import qiskit.quantum_info as qk_info
+
 import jijmodeling as jm
 import jijmodeling_transpiler as jmt
+import qiskit as qk
+import qiskit.quantum_info as qk_info
+
 from jijmodeling_transpiler_quantum.core import qubo_to_ising
+
 from .ising_hamiltonian import to_ising_operator_from_qubo
 
 
@@ -33,7 +37,9 @@ def get_hamiltonian(
         qubo, constant = self.pubo_builder.get_qubo_dict(
             multipliers=multipliers, detail_parameters=detail_parameters
         )
-        ising_operator, ising_const = to_ising_operator_from_qubo(qubo, self.num_vars)
+        ising_operator, ising_const = to_ising_operator_from_qubo(
+            qubo, self.num_vars
+        )
         return ising_operator, ising_const + constant
 
     def get_qaoa_ansatz(
@@ -52,19 +58,27 @@ def get_qaoa_ansatz(
 
     def decode_from_counts(self, counts: dict[str, int]) -> jm.SampleSet:
         samples = []
-        num_occurances = []
+        num_occurrences = []
         for binary_str, count_num in counts.items():
             binary_values = {idx: int(b) for idx, b in enumerate(binary_str)}
             samples.append(binary_values)
-            num_occurances.append(count_num)
+            num_occurrences.append(count_num)
 
         binary_encoder = self.pubo_builder.binary_encoder
         decoded: jm.SampleSet = (
             jmt.core.pubo.binary_decode.decode_from_dict_binary_result(
                 samples, binary_encoder, self.compiled_instance
             )
         )
-        decoded.record.num_occurrences = num_occurances
+        decoded = jm.SampleSet(
+            record=jm.Record(
+                num_occurrences=num_occurrences,
+                solution=decoded.record.solution,
+            ),
+            evaluation=decoded.evaluation,
+            measuring_time=decoded.measuring_time,
+            metadata=decoded.metadata,
+        )
         return decoded
 
     def decode_from_quasi_dist(
@@ -81,7 +95,9 @@ def decode_from_quasi_dist(
             else:
                 shots = 30000
 
-        binary_counts = {key: int(prob * shots) for key, prob in binary_prob.items()}
+        binary_counts = {
+            key: int(prob * shots) for key, prob in binary_prob.items()
+        }
 
         return self.decode_from_counts(binary_counts)
 

jijmodeling_transpiler_quantum/qiskit/qrao/to_qrac.py

@@ -51,7 +51,17 @@ def decode_from_binary_values(
                 binary_results, binary_encoder, self.compiled_instance
             )
         )
-        decoded.record.num_occurrences = [[1]] * len(binary_results)
+
+        num_occurrences = [1] * len(binary_results)
+        decoded = jm.SampleSet(
+            record=jm.Record(
+                num_occurrences=num_occurrences,
+                solution=decoded.record.solution,
+            ),
+            evaluation=decoded.evaluation,
+            measuring_time=decoded.measuring_time,
+            metadata=decoded.metadata,
+        )
         return decoded
 
 

jijmodeling_transpiler_quantum/quri_parts/qaoa/ising_hamiltonian.py

@@ -1,7 +1,9 @@
 from __future__ import annotations
+
 import numpy as np
+from quri_parts.core.operator import PAULI_IDENTITY, Operator, pauli_label
+
 from jijmodeling_transpiler_quantum.core import qubo_to_ising
-from quri_parts.core.operator import pauli_label, PAULI_IDENTITY, Operator
 
 
 def to_ising_operator_from_qubo(

jijmodeling_transpiler_quantum/quri_parts/qaoa/to_qaoa.py

@@ -1,11 +1,14 @@
 from __future__ import annotations
+
+from math import pi
+
 import jijmodeling as jm
 import jijmodeling_transpiler as jmt
-from jijmodeling_transpiler_quantum.core import qubo_to_ising
-from .ising_hamiltonian import to_ising_operator_from_qubo
+import numpy as np
 from quri_parts.circuit import LinearMappedUnboundParametricQuantumCircuit
 from quri_parts.core.operator import Operator
-from math import pi
+
+from .ising_hamiltonian import to_ising_operator_from_qubo
 
 
 class QAOAAnsatzBuilder:
@@ -47,15 +50,17 @@ def get_hamiltonian(
         qubo, constant = self.pubo_builder.get_qubo_dict(
             multipliers=multipliers, detail_parameters=detail_parameters
         )
-        ising_operator, ising_const = to_ising_operator_from_qubo(qubo, self.num_vars)
+        ising_operator, ising_const = to_ising_operator_from_qubo(
+            qubo, self.num_vars
+        )
         return ising_operator, ising_const + constant
 
     def get_qaoa_ansatz(
         self,
         p: int,
         multipliers: dict = None,
         detail_parameters: dict = None,
-    ) -> tuple[UnboundParametricQuantumCircuit, operator, float]:
+    ) -> tuple[LinearMappedUnboundParametricQuantumCircuit, Operator, float]:
         """Get the QAOA ansatz.
 
         Args:
@@ -64,7 +69,7 @@ def get_qaoa_ansatz(
             detail_parameters (dict, optional): Detailed parameters for the Ising Hamiltonian. Defaults to None.
 
         Returns:
-            tuple[UnboundParametricQuantumCircuit, operator, float]: The QAOA ansatz, the Ising operator, and the constant offset.
+            tuple[LinearMappedUnboundParametricQuantumCircuit, Operator, float]: The QAOA ansatz, the Ising operator, and the constant offset.
         """
         ising_operator, constant = self.get_hamiltonian(
             multipliers=multipliers, detail_parameters=detail_parameters
@@ -73,12 +78,15 @@ def get_qaoa_ansatz(
         keys = list(ising_operator.keys())
         items = list(ising_operator.items())
         num_terms = ising_operator.n_terms - 1
-        pauli_terms = [keys[i].index_and_pauli_id_list[0] for i in range(num_terms)]
+        pauli_terms = [
+            keys[i].index_and_pauli_id_list[0] for i in range(num_terms)
+        ]
         coeff_terms = [items[i][1] for i in range(num_terms)]
         QAOAAnsatz = LinearMappedUnboundParametricQuantumCircuit(self.num_vars)
         pauli_z_terms = pauli_terms[: self.num_vars]
         pauli_zz_terms = [
-            sorted(sublist, reverse=True) for sublist in pauli_terms[self.num_vars :]
+            sorted(sublist, reverse=True)
+            for sublist in pauli_terms[self.num_vars :]
         ]
 
         for term in pauli_z_terms:
@@ -88,7 +96,9 @@ def get_qaoa_ansatz(
             Gamma = QAOAAnsatz.add_parameters(f"gamma{p_level}")
             Beta = QAOAAnsatz.add_parameters(f"beta{p_level}")
 
-            for pauli_z_info, coeff in zip(pauli_z_terms, coeff_terms[: self.num_vars]):
+            for pauli_z_info, coeff in zip(
+                pauli_z_terms, coeff_terms[: self.num_vars]
+            ):
                 QAOAAnsatz.add_ParametricRZ_gate(
                     pauli_z_info[0], {Gamma[-1]: 2 * coeff}
                 )
@@ -97,11 +107,15 @@ def get_qaoa_ansatz(
                 pauli_zz_terms, coeff_terms[self.num_vars :]
             ):
                 QAOAAnsatz.add_ParametricPauliRotation_gate(
-                    pauli_zz_info, pauli_ids=(3, 3), angle={Gamma[-1]: 2 * coeff}
+                    pauli_zz_info,
+                    pauli_ids=(3, 3),
+                    angle={Gamma[-1]: 2 * coeff},
                 )
 
             for pauli_z_info in pauli_z_terms:
-                QAOAAnsatz.add_ParametricRX_gate(pauli_z_info[0], {Beta[-1]: 2})
+                QAOAAnsatz.add_ParametricRX_gate(
+                    pauli_z_info[0], {Beta[-1]: 2}
+                )
 
         return QAOAAnsatz, ising_operator, constant
 
@@ -115,19 +129,27 @@ def decode_from_counts(self, counts: dict[str, int]) -> jm.SampleSet:
             jm.SampleSet: The decoded sample set.
         """
         samples = []
-        num_occurances = []
+        num_occurrences = []
         for binary_str, count_num in counts.items():
             binary_values = {idx: int(b) for idx, b in enumerate(binary_str)}
             samples.append(binary_values)
-            num_occurances.append(count_num)
+            num_occurrences.append(count_num)
 
         binary_encoder = self.pubo_builder.binary_encoder
         decoded: jm.SampleSet = (
             jmt.core.pubo.binary_decode.decode_from_dict_binary_result(
                 samples, binary_encoder, self.compiled_instance
             )
         )
-        decoded.record.num_occurrences = num_occurances
+        decoded = jm.SampleSet(
+            record=jm.Record(
+                num_occurrences=num_occurrences,
+                solution=decoded.record.solution,
+            ),
+            evaluation=decoded.evaluation,
+            measuring_time=decoded.measuring_time,
+            metadata=decoded.metadata,
+        )
         return decoded
 
     def decode_from_probs(self, probs: np.array) -> jm.SampleSet:
@@ -140,8 +162,12 @@ def decode_from_probs(self, probs: np.array) -> jm.SampleSet:
             jm.SampleSet: The decoded sample set.
         """
         shots = 10000
-        z_basis = [format(i, "b").zfill(self.num_vars) for i in range(len(probs))]
-        binary_counts = {i: int(value * shots) for i, value in zip(z_basis, probs)}
+        z_basis = [
+            format(i, "b").zfill(self.num_vars) for i in range(len(probs))
+        ]
+        binary_counts = {
+            i: int(value * shots) for i, value in zip(z_basis, probs)
+        }
 
         return self.decode_from_counts(binary_counts)
 
@@ -150,7 +176,7 @@ def transpile_to_qaoa_ansatz(
     compiled_instance: jmt.core.CompiledInstance,
     normalize: bool = True,
     relax_method=jmt.core.pubo.RelaxationMethod.AugmentedLagrangian,
-) -> quriQAOAAnsatzBuilder:
+) -> QAOAAnsatzBuilder:
     """Transpile to a QAOA ansatz builder.
 
     Args:
@@ -159,10 +185,10 @@ def transpile_to_qaoa_ansatz(
         relax_method (jmt.core.pubo.RelaxationMethod, optional): The relaxation method to be used. Defaults to AugmentedLagrangian.
 
     Returns:
-        quriQAOAAnsatzBuilder: The QAOA ansatz builder.
+        QAOAAnsatzBuilder: The QAOA ansatz builder.
     """
     pubo_builder = jmt.core.pubo.transpile_to_pubo(
-        compiled_instance, normalize=True, relax_method=relax_method
+        compiled_instance, normalize=normalize, relax_method=relax_method
     )
     var_num = compiled_instance.var_map.var_num
     return QAOAAnsatzBuilder(pubo_builder, var_num, compiled_instance)

jijmodeling_transpiler_quantum/quri_parts/qrao/qrao21.py

@@ -1,8 +1,11 @@
 from __future__ import annotations
+
 import numpy as np
+from quri_parts.core.operator import PAULI_IDENTITY, Operator, pauli_label
+
 from jijmodeling_transpiler_quantum.core.ising_qubo import IsingModel
+
 from .qrao31 import Pauli, color_group_to_qrac_encode, create_pauli_term
-from quri_parts.core.operator import pauli_label, PAULI_IDENTITY, Operator
 
 
 def qrac21_encode_ising(
@@ -33,7 +36,9 @@ def qrac21_encode_ising(
 
         color, pauli_kind = encoded_ope[idx]
         pauli_str = create_pauli_term([pauli_kind], [color], n_qubit)
-        pauli_terms.append(Operator({pauli_label(pauli_str): np.sqrt(2) * coeff}))
+        pauli_terms.append(
+            Operator({pauli_label(pauli_str): np.sqrt(2) * coeff})
+        )
 
     for (i, j), coeff in ising.quad.items():
         if coeff == 0.0:

jijmodeling_transpiler_quantum/quri_parts/qrao/qrao31.py

@@ -1,8 +1,11 @@
 from __future__ import annotations
+
 import enum
+
 import numpy as np
+from quri_parts.core.operator import PAULI_IDENTITY, Operator, pauli_label
+
 from jijmodeling_transpiler_quantum.core.ising_qubo import IsingModel
-from quri_parts.core.operator import pauli_label, PAULI_IDENTITY, Operator
 
 
 class Pauli(enum.Enum):
@@ -36,7 +39,9 @@ def color_group_to_qrac_encode(
     return qrac31
 
 
-def create_pauli_term(operators: list[Pauli], indices: list[int], n_qubit: int) -> str:
+def create_pauli_term(
+    operators: list[Pauli], indices: list[int], n_qubit: int
+) -> str:
     """Create a Pauli term string given a list of operators and indices.
 
     Args:
@@ -85,7 +90,9 @@ def qrac31_encode_ising(
         color, pauli_kind = encoded_ope[idx]
         pauli_operator = create_pauli_term([pauli_kind], [color], n_qubit)
 
-        pauli_terms.append(Operator({pauli_label(pauli_operator): np.sqrt(3) * coeff}))
+        pauli_terms.append(
+            Operator({pauli_label(pauli_operator): np.sqrt(3) * coeff})
+        )
 
     for (i, j), coeff in ising.quad.items():
         if coeff == 0.0: