feat: add Z=128 support for matrix construction and validation

Make validate_matrix() and run_full_pipeline() accept z parameter
instead of using hardcoded Z=32. Thread cn_mode/alpha to validation.
Add --z/--cn-mode/--alpha CLI options to full pipeline.

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

model/density_evolution.py

@@ -757,7 +757,8 @@ def verify_matrix(H_base, z=32):
 # FER Validation
 # =============================================================================
 
-def validate_matrix(H_base, lam_s_points, n_frames=200, lam_b=0.1, max_iter=30):
+def validate_matrix(H_base, lam_s_points, n_frames=200, lam_b=0.1, max_iter=30,
+                    z=32, cn_mode='offset', alpha=0.75):
     """
     Run full Monte Carlo FER simulation for a base matrix.
 
@@ -765,7 +766,6 @@ def validate_matrix(H_base, lam_s_points, n_frames=200, lam_b=0.1, max_iter=30):
     """
     from ldpc_analysis import generic_decode, peg_encode
 
-    z = Z
     k = z
     H_full = _build_full_h_from_base(H_base, z)
 
@@ -790,7 +790,8 @@ def validate_matrix(H_base, lam_s_points, n_frames=200, lam_b=0.1, max_iter=30):
             llr_q = quantize_llr(llr_float)
 
             decoded, converged, iters, sw = generic_decode(
-                llr_q, H_base, z=z, max_iter=max_iter, q_bits=Q_BITS
+                llr_q, H_base, z=z, max_iter=max_iter, q_bits=Q_BITS,
+                cn_mode=cn_mode, alpha=alpha
             )
             total_iter += iters
 
@@ -813,7 +814,7 @@ def validate_matrix(H_base, lam_s_points, n_frames=200, lam_b=0.1, max_iter=30):
     return results
 
 
-def run_full_pipeline(lam_b=0.1, seed=42):
+def run_full_pipeline(lam_b=0.1, seed=42, z=32, cn_mode='offset', alpha=0.75):
     """
     Full pipeline: optimize -> construct -> validate.
     """
@@ -854,8 +855,8 @@ def run_full_pipeline(lam_b=0.1, seed=42):
 
     # Step 3: Construct matrix
     print("\n--- Step 3: Matrix construction ---")
-    H_opt, girth = construct_base_matrix(best_degrees, z=32, n_trials=2000)
+    H_opt, girth = construct_base_matrix(best_degrees, z=z, n_trials=2000)
-    checks = verify_matrix(H_opt, z=32)
+    checks = verify_matrix(H_opt, z=z)
     print(f"  Constructed matrix: girth={girth}, rank={checks['actual_rank']}/{checks['expected_rank']}")
     print(f"  Encodable: {checks['encodable']}, Full rank: {checks['full_rank']}")
     print(f"  Base matrix:\n{H_opt}")
@@ -867,10 +868,13 @@ def run_full_pipeline(lam_b=0.1, seed=42):
     print(f"\n{'lam_s':>8s} {'Optimized':>12s} {'Original':>12s} {'PEG ring':>12s}")
     print("-" * 50)
 
-    fer_opt = validate_matrix(H_opt, lam_s_points, n_frames=200, lam_b=lam_b)
+    fer_opt = validate_matrix(H_opt, lam_s_points, n_frames=200, lam_b=lam_b,
-    fer_orig = validate_matrix(H_BASE, lam_s_points, n_frames=200, lam_b=lam_b)
+                              z=z, cn_mode=cn_mode, alpha=alpha)
+    fer_orig = validate_matrix(H_BASE, lam_s_points, n_frames=200, lam_b=lam_b,
+                               z=z, cn_mode=cn_mode, alpha=alpha)
     fer_peg = validate_matrix(ref_matrices['PEG ring [7,3,3,3,2,2,2,2]'],
-                               lam_s_points, n_frames=200, lam_b=lam_b)
+                               lam_s_points, n_frames=200, lam_b=lam_b,
+                               z=z, cn_mode=cn_mode, alpha=alpha)
 
     for lam_s in lam_s_points:
         f_opt = fer_opt[lam_s]['fer']
@@ -1016,7 +1020,7 @@ def main():
             print(f"  lam_s={lam_s:.1f}: FER={r['fer']:.3f}, BER={r['ber']:.6f}")
 
     elif args.command == 'full':
-        run_full_pipeline(seed=args.seed)
+        run_full_pipeline(seed=args.seed, z=args.z, cn_mode=args.cn_mode, alpha=args.alpha)
 
     else:
         parser.print_help()

model/test_density_evolution.py

@@ -283,6 +283,31 @@ class TestNormalizedMinSumDE:
         )
 
 
+class TestZ128Support:
+    """Tests for Z=128 matrix construction and optimization."""
+
+    def test_construct_z128_valid(self):
+        """Construct matrix for [7,4,4,4,4,3,3,3] with z=128. Verify full rank, girth >= 6, encodable."""
+        from density_evolution import construct_base_matrix, verify_matrix
+        np.random.seed(42)
+        target = [7, 4, 4, 4, 4, 3, 3, 3]
+        H_base, girth = construct_base_matrix(target, z=128, n_trials=500)
+        checks = verify_matrix(H_base, z=128)
+        assert checks['full_rank'], f"Full rank failed: {checks['actual_rank']}/{checks['expected_rank']}"
+        assert girth >= 6, f"Girth {girth} should be >= 6"
+        assert checks['encodable'], "Should be encodable"
+
+    def test_validate_z128_runs(self):
+        """Run validate_matrix with z=128, n_frames=5 at lam_s=5. Verify returns dict with FER."""
+        from density_evolution import construct_base_matrix, validate_matrix
+        np.random.seed(42)
+        target = [7, 4, 4, 4, 4, 3, 3, 3]
+        H_base, girth = construct_base_matrix(target, z=128, n_trials=200)
+        results = validate_matrix(H_base, lam_s_points=[5.0], n_frames=5, lam_b=0.1, z=128)
+        assert 5.0 in results, f"Expected key 5.0, got {list(results.keys())}"
+        assert 'fer' in results[5.0]
+
+
 class TestAlphaOptimization:
     """Tests for alpha sweep optimization."""