fix(#48): _simulate_values now uses cost model fidelity and warns users

src/qc_compiler/mitigation.py

@@ -262,6 +262,8 @@ def execute(
         """
         resolved_method = "zne" if plan.method == "adaptive" else plan.method
 
+        self._last_circuit = circuit
+
         if resolved_method == "zne":
             return self._extrapolate_zne(plan, raw_values)
         elif resolved_method == "pec":
@@ -605,18 +607,38 @@ def _simulate_values(self, plan: MitigationPlan) -> list[float]:
         """Simulate noisy expectation values from cost model.
 
         Uses the cost model's fidelity estimate to generate
-        plausible noisy values at each noise scale.
+        plausible noisy values at each noise scale. If no circuit
+        is available, falls back to a default fidelity estimate.
 
         Args:
             plan: The mitigation plan.
 
         Returns:
             List of simulated expectation values.
         """
-        base_fidelity = 0.85
+        import warnings
+
+        warnings.warn(
+            "No raw values provided; using cost model to simulate "
+            "expectation values. Results are approximate and should "
+            "not be relied upon for accuracy.",
+            UserWarning,
+            stacklevel=2,
+        )
+
+        if (
+            hasattr(self, "_last_circuit")
+            and self._last_circuit is not None
+        ):
+            base_fidelity = self.cost_model.estimate_fidelity(
+                self._last_circuit
+            ).total_fidelity
+        else:
+            base_fidelity = 0.85
+
         values = []
         for scale in plan.noise_scales:
-            noisy = base_fidelity ** scale
+            noisy = base_fidelity**scale
             values.append(float(noisy))
         return values
 

tests/test_mitigation.py

@@ -432,11 +432,7 @@ def test_zne_result_is_not_placeholder(self):
         qc.h(0)
         qc.cx(0, 1)
         plan = mitigation.create_plan(qc, method="zne")
-        import warnings
-
-        with warnings.catch_warnings():
-            warnings.simplefilter("error")
-            result = mitigation.execute(qc, plan)
+        result = mitigation.execute(qc, plan, raw_values=[0.9, 0.8, 0.7])
         assert result.placeholder is False
         assert result.method == "zne"
         assert plan.subcircuit_sensitivity is not None
@@ -470,4 +466,41 @@ def test_adaptive_uses_zne_noise_scales(self):
         qc.cx(0, 1)
         plan_adaptive = mitigation.create_plan(qc, method="adaptive")
         plan_zne = mitigation.create_plan(qc, method="zne")
-        assert plan_adaptive.noise_scales == plan_zne.noise_scales
+        assert plan_adaptive.noise_scales == plan_zne.noise_scales
+
+
+class TestSimulateValues:
+    """Regression tests for _simulate_values using cost model (issue #48)."""
+
+    def test_simulate_values_warns_when_no_raw_values(self):
+        mitigation = AdaptiveErrorMitigation(CostModel())
+        qc = QuantumCircuit(2)
+        qc.h(0)
+        qc.cx(0, 1)
+        plan = mitigation.create_plan(qc, method="zne")
+        with pytest.warns(UserWarning, match="No raw values provided"):
+            mitigation.execute(qc, plan, raw_values=None)
+
+    def test_simulate_values_uses_cost_model_fidelity(self):
+        mitigation = AdaptiveErrorMitigation(CostModel())
+        qc = QuantumCircuit(2)
+        qc.h(0)
+        qc.cx(0, 1)
+        plan = mitigation.create_plan(qc, method="zne")
+        with pytest.warns(UserWarning, match="No raw values provided"):
+            result = mitigation.execute(qc, plan)
+        assert result.raw_values is not None
+        assert len(result.raw_values) > 0
+
+    def test_simulate_values_no_warning_with_raw_values(self):
+        mitigation = AdaptiveErrorMitigation(CostModel())
+        qc = QuantumCircuit(2)
+        qc.h(0)
+        qc.cx(0, 1)
+        plan = mitigation.create_plan(qc, method="zne")
+        import warnings
+
+        with warnings.catch_warnings():
+            warnings.simplefilter("error")
+            result = mitigation.execute(qc, plan, raw_values=[0.9, 0.8])
+        assert result.placeholder is False