feat: add normalized min-sum to density evolution engine

Thread cn_mode and alpha parameters through the entire DE pipeline:
de_cn_update_vectorized(), density_evolution_step(), run_de(),
compute_threshold(), and compute_threshold_for_profile().

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

model/test_density_evolution.py

@@ -249,3 +249,35 @@ class TestNormalizedMinSum:
         assert result_default == result_explicit, (
             f"Default and explicit offset should match: {result_default} vs {result_explicit}"
         )
+
+
+class TestNormalizedMinSumDE:
+    """Tests for normalized min-sum in the density evolution engine."""
+
+    def test_de_normalized_converges(self):
+        """DE at lam_s=10 with normalized mode should converge."""
+        from density_evolution import run_de, ORIGINAL_STAIRCASE_PROFILE
+        np.random.seed(42)
+        converged, error_frac = run_de(
+            ORIGINAL_STAIRCASE_PROFILE, lam_s=10.0, lam_b=0.1,
+            z_pop=10000, max_iter=50,
+            cn_mode='normalized', alpha=0.75
+        )
+        assert converged, f"DE normalized should converge at lam_s=10, error_frac={error_frac}"
+
+    def test_de_normalized_threshold_different(self):
+        """Normalized and offset modes should produce different thresholds."""
+        from density_evolution import compute_threshold, ORIGINAL_STAIRCASE_PROFILE
+        np.random.seed(42)
+        thresh_offset = compute_threshold(
+            ORIGINAL_STAIRCASE_PROFILE, lam_b=0.1, z_pop=10000, tol=0.5,
+            cn_mode='offset'
+        )
+        np.random.seed(42)
+        thresh_norm = compute_threshold(
+            ORIGINAL_STAIRCASE_PROFILE, lam_b=0.1, z_pop=10000, tol=0.5,
+            cn_mode='normalized', alpha=0.75
+        )
+        assert thresh_norm != thresh_offset, (
+            f"Thresholds should differ: offset={thresh_offset}, normalized={thresh_norm}"
+        )