Merge branch 'main' of https://github.com/quantumdynamics927-dotcom/QPyth

Author: quantumdynamics927-dotcom

quantumpytho/validation/__init__.py

@@ -51,4 +51,4 @@
     "validation_records_to_csv",
     "validation_records_to_json",
     "validation_records_to_markdown",
-]
+]

quantumpytho/validation/benchmarks.py

@@ -88,4 +88,4 @@ def reference_benchmarks() -> list[BenchmarkCase]:
         ghz_benchmark(),
         rotation_layer_benchmark(),
         parity_benchmark(),
-    ]
+    ]

quantumpytho/validation/integrations.py

@@ -68,4 +68,4 @@ def validation_config_from_archive_job(
             "result_schema": detail.result_schema,
             **(metadata or {}),
         },
-    )
+    )

quantumpytho/validation/metrics.py

@@ -45,7 +45,9 @@ def total_variation_distance(
     return 0.5 * sum(abs(dist_a.get(key, 0.0) - dist_b.get(key, 0.0)) for key in keys)
 
 
-def hellinger_distance(counts_a: Mapping[str, int], counts_b: Mapping[str, int]) -> float:
+def hellinger_distance(
+    counts_a: Mapping[str, int], counts_b: Mapping[str, int]
+) -> float:
     """Compute Hellinger distance between two count distributions."""
     dist_a, dist_b, keys = _union_probabilities(counts_a, counts_b)
     squared = sum(
@@ -60,7 +62,9 @@ def jensen_shannon_divergence(
 ) -> float:
     """Compute Jensen-Shannon divergence in bits between two distributions."""
     dist_a, dist_b, keys = _union_probabilities(counts_a, counts_b)
-    midpoint = {key: 0.5 * (dist_a.get(key, 0.0) + dist_b.get(key, 0.0)) for key in keys}
+    midpoint = {
+        key: 0.5 * (dist_a.get(key, 0.0) + dist_b.get(key, 0.0)) for key in keys
+    }
 
     def _kl_divergence(left: dict[str, float], right: dict[str, float]) -> float:
         divergence = 0.0
@@ -71,7 +75,9 @@ def _kl_divergence(left: dict[str, float], right: dict[str, float]) -> float:
                 divergence += left_value * math.log2(left_value / right_value)
         return divergence
 
-    return 0.5 * _kl_divergence(dist_a, midpoint) + 0.5 * _kl_divergence(dist_b, midpoint)
+    return 0.5 * _kl_divergence(dist_a, midpoint) + 0.5 * _kl_divergence(
+        dist_b, midpoint
+    )
 
 
 def expectation_value_z(counts: Mapping[str, int], qubit_index: int = 0) -> float:
@@ -126,7 +132,9 @@ def energy_error(simulated_energy: float, hardware_energy: float) -> float:
     return abs(simulated_energy - hardware_energy)
 
 
-def hardware_match_score(counts_a: Mapping[str, int], counts_b: Mapping[str, int]) -> float:
+def hardware_match_score(
+    counts_a: Mapping[str, int], counts_b: Mapping[str, int]
+) -> float:
     """Convert TVD into a simple customer-facing match score percentage."""
     score = (1.0 - total_variation_distance(counts_a, counts_b)) * 100.0
     return max(0.0, min(100.0, score))
@@ -141,4 +149,4 @@ def compute_counts_metrics(
         "hellinger": hellinger_distance(counts_a, counts_b),
         "js_divergence": jensen_shannon_divergence(counts_a, counts_b),
         "match_score": hardware_match_score(counts_a, counts_b),
-    }
+    }

quantumpytho/validation/provenance.py

@@ -64,4 +64,4 @@ def to_dict(self) -> dict[str, Any]:
 
 def utc_now_iso() -> str:
     """Return an ISO-8601 UTC timestamp for validation records."""
-    return datetime.now(timezone.utc).isoformat()
+    return datetime.now(timezone.utc).isoformat()

quantumpytho/validation/reporting.py

@@ -11,7 +11,9 @@
 
 def validation_records_to_json(records: list[ValidationRecord]) -> str:
     """Serialize validation records to JSON."""
-    return json.dumps([record.to_dict() for record in records], indent=2, sort_keys=True)
+    return json.dumps(
+        [record.to_dict() for record in records], indent=2, sort_keys=True
+    )
 
 
 def validation_records_to_csv(records: list[ValidationRecord]) -> str:
@@ -50,4 +52,4 @@ def validation_records_to_markdown(records: list[ValidationRecord]) -> str:
         lines.append(
             f"| {record.benchmark_id} | {record.backend_name} | {record.tvd_raw:.4f} | {match_score:.2f}% | {record.n_repeats} |"
         )
-    return "\n".join(lines)
+    return "\n".join(lines)

quantumpytho/validation/runner.py

@@ -72,7 +72,9 @@ def _coerce_counts(result: Any) -> dict[str, int]:
         counts = result.counts
         if isinstance(counts, dict):
             return {str(key): int(value) for key, value in counts.items()}
-    raise TypeError("Executor result must be a counts dict or expose a 'counts' attribute")
+    raise TypeError(
+        "Executor result must be a counts dict or expose a 'counts' attribute"
+    )
 
 
 def _transpile_shared(
@@ -104,7 +106,9 @@ def run_benchmark_case(
 ) -> ValidationRecord:
     """Run one benchmark through a shared transpilation pipeline and score agreement."""
     logical_hash = _hash_circuit(benchmark.circuit)
-    transpiled_circuit = _transpile_shared(benchmark.circuit, config, backend, transpiler)
+    transpiled_circuit = _transpile_shared(
+        benchmark.circuit, config, backend, transpiler
+    )
     transpiled_hash = _hash_circuit(transpiled_circuit)
 
     sim_counts = _coerce_counts(simulation_executor(transpiled_circuit, config.shots))
@@ -129,7 +133,9 @@ def run_benchmark_case(
 
     metric_mean = mean(raw_metrics)
     metric_std = pstdev(raw_metrics) if len(raw_metrics) > 1 else 0.0
-    ci95_half_width = 1.96 * metric_std / math.sqrt(len(raw_metrics)) if raw_metrics else 0.0
+    ci95_half_width = (
+        1.96 * metric_std / math.sqrt(len(raw_metrics)) if raw_metrics else 0.0
+    )
 
     settings = config.to_transpilation_settings()
     return ValidationRecord(
@@ -190,4 +196,4 @@ def run_benchmark_suite(
             now_fn=now_fn,
         )
         for benchmark in benchmarks
-    ]
+    ]

tests/test_validation_integrations.py

@@ -55,7 +55,9 @@ def test_build_noisy_simulation_executor_delegates_to_noisy_simulator_engine():
     """Noisy simulation adapter should forward circuit and shot count correctly."""
     circuit = QuantumCircuit(1, 1)
 
-    with patch("quantumpytho.validation.integrations.NoisySimulatorEngine") as mock_engine_cls:
+    with patch(
+        "quantumpytho.validation.integrations.NoisySimulatorEngine"
+    ) as mock_engine_cls:
         mock_engine = mock_engine_cls.return_value
         mock_engine.run.return_value.counts = {"0": 7, "1": 3}
 
@@ -109,4 +111,4 @@ def test_validation_config_from_archive_job_uses_archive_metadata(tmp_path):
     assert config.optimization_level == 3
     assert config.resilience_level == 2
     assert config.metadata["archive_job_id"] == "d6vconfig0000000001"
-    assert config.metadata["workload"] == "bell"
+    assert config.metadata["workload"] == "bell"

tests/test_validation_metrics.py

@@ -78,4 +78,4 @@ def test_mean_absolute_expectation_error_returns_zero_for_empty_inputs_and_indic
 
 
 def test_energy_error_is_absolute_difference():
-    assert energy_error(-1.25, -1.0) == pytest.approx(0.25)
+    assert energy_error(-1.25, -1.0) == pytest.approx(0.25)

tests/test_validation_runner.py

@@ -30,10 +30,12 @@ def simulation_executor(circuit: QuantumCircuit, shots: int) -> dict[str, int]:
         seen_circuit_ids.append(("sim", id(circuit), shots, circuit.name))
         return {"00": 60, "11": 40}
 
-    hardware_runs = iter([
-        {"00": 58, "11": 42},
-        {"00": 57, "11": 43},
-    ])
+    hardware_runs = iter(
+        [
+            {"00": 58, "11": 42},
+            {"00": 57, "11": 43},
+        ]
+    )
 
     def hardware_executor(circuit: QuantumCircuit, shots: int) -> dict[str, int]:
         seen_circuit_ids.append(("hw", id(circuit), shots, circuit.name))
@@ -45,7 +47,10 @@ def hardware_executor(circuit: QuantumCircuit, shots: int) -> dict[str, int]:
         optimization_level=3,
         basis_gates=["rz", "sx", "x", "cz"],
         n_repeats=2,
-        corrected_counts_resolver=lambda counts: {"00": counts["00"] + 1, "11": counts["11"] - 1},
+        corrected_counts_resolver=lambda counts: {
+            "00": counts["00"] + 1,
+            "11": counts["11"] - 1,
+        },
     )
 
     record = run_benchmark_case(
@@ -172,4 +177,4 @@ def test_run_benchmark_case_clamps_repeat_count_to_one():
     assert record.n_repeats == 1
     assert record.std_metric == 0.0
     assert record.ci95_low == pytest.approx(0.0)
-    assert record.ci95_high == pytest.approx(0.0)
+    assert record.ci95_high == pytest.approx(0.0)