Bit-cascade division stages and all float comparators

Replaced the remaining single-layer wide comparators with bit-cascaded
ternary equivalents using the existing add_bit_cascade_compare helper:

alu.alu{8,16,32}bit.div.stage{N}.cmp per-stage GE comparator
float16.add.exp_cmp.{a_gt_b,a_lt_b} 5-bit GT/LT
float32.add.exp_cmp.{a_gt_b,a_lt_b} 8-bit GT/LT
float16.cmp.{mag_a_gt_b,mag_a_ge_b,...} 15-bit magnitude comparator
float32.cmp.{mag_a_gt_b,mag_a_ge_b,...} 31-bit magnitude comparator
float16.div.mant_div.stage{N}.cmp 11-bit GE per stage
float32.div.mant_div.stage{N}.cmp 24-bit GE per stage

Each emit retains the original output gate name (e.g. mag_a_gt_b),
backed now by a tree of bit-cascade gates whose internal structure lives
under cmp_bc.* / mag_bc.* / exp_cmp_bc.*. Public consumers see the same
names; only the weight tensors change shape (smaller).

eval.py shape expectations updated for the float tests.

Non-ternary weight tensor count on the canonical drops from 161 to 70.
The 70 remaining are hand-constructed seed-file content:
68 modular arithmetic layer1 gates (mod 3, 5, 6, 7, 9, 10, 11, 12)
2 pattern_recognition gates (leadingones, trailingones)

All 18 variants rebuilt; eval_all.py reports 100% fitness on every one.

build.py

@@ -495,10 +495,18 @@ def add_div(tensors: Dict[str, torch.Tensor]) -> None:
     - Uses existing comparator and subtractor components
     """
     # Comparison gates: check if (remainder << 1 | next_bit) >= divisor
+    # Bit-cascaded ternary GE comparator per stage.
     for stage in range(8):
-        add_gate(tensors, f"alu.alu8bit.div.stage{stage}.cmp",
-                 [128.0, 64.0, 32.0, 16.0, 8.0, 4.0, 2.0, 1.0,
-                  -128.0, -64.0, -32.0, -16.0, -8.0, -4.0, -2.0, -1.0], [0.0])
+        add_bit_cascade_compare(
+            tensors,
+            cmp_prefix=f"alu.alu8bit.div.stage{stage}.cmp_bc",
+            bits=8,
+            out_gt=f"alu.alu8bit.div.stage{stage}.cmp_bc.gt",
+            out_lt=f"alu.alu8bit.div.stage{stage}.cmp_bc.lt",
+            out_ge=f"alu.alu8bit.div.stage{stage}.cmp",
+            out_le=f"alu.alu8bit.div.stage{stage}.cmp_bc.le",
+            out_eq=f"alu.alu8bit.div.stage{stage}.cmp_bc.eq",
+        )
 
     # Conditional mux gates: select (rem - div) or rem based on comparison
     for stage in range(8):
@@ -930,14 +938,20 @@ def add_mul_nbits(tensors: Dict[str, torch.Tensor], bits: int) -> None:
 def add_div_nbits(tensors: Dict[str, torch.Tensor], bits: int) -> None:
     """Add N-bit division circuit.
 
-    Uses restoring division algorithm with N iterations.
+    Uses restoring division algorithm with N iterations. Each stage's
+    comparator (rem >= div) is a ternary bit-cascade GE.
     """
-    pos_weights = [float(1 << (bits - 1 - i)) for i in range(bits)]
-    neg_weights = [-w for w in pos_weights]
-    cmp_weights = pos_weights + neg_weights
-
     for stage in range(bits):
-        add_gate(tensors, f"alu.alu{bits}bit.div.stage{stage}.cmp", cmp_weights, [0.0])
+        add_bit_cascade_compare(
+            tensors,
+            cmp_prefix=f"alu.alu{bits}bit.div.stage{stage}.cmp_bc",
+            bits=bits,
+            out_gt=f"alu.alu{bits}bit.div.stage{stage}.cmp_bc.gt",
+            out_lt=f"alu.alu{bits}bit.div.stage{stage}.cmp_bc.lt",
+            out_ge=f"alu.alu{bits}bit.div.stage{stage}.cmp",
+            out_le=f"alu.alu{bits}bit.div.stage{stage}.cmp_bc.le",
+            out_eq=f"alu.alu{bits}bit.div.stage{stage}.cmp_bc.eq",
+        )
 
     for stage in range(bits):
         for bit in range(bits):
@@ -1078,10 +1092,17 @@ def add_float16_add(tensors: Dict[str, torch.Tensor]) -> None:
     """
     prefix = "float16.add"
 
-    pos_weights = [float(1 << (4 - i)) for i in range(5)]
-    neg_weights = [-w for w in pos_weights]
-    add_gate(tensors, f"{prefix}.exp_cmp.a_gt_b", pos_weights + neg_weights, [-1.0])
-    add_gate(tensors, f"{prefix}.exp_cmp.a_lt_b", neg_weights + pos_weights, [-1.0])
+    # 5-bit exponent comparator, bit-cascaded ternary form.
+    add_bit_cascade_compare(
+        tensors,
+        cmp_prefix=f"{prefix}.exp_cmp_bc",
+        bits=5,
+        out_gt=f"{prefix}.exp_cmp.a_gt_b",
+        out_lt=f"{prefix}.exp_cmp.a_lt_b",
+        out_ge=f"{prefix}.exp_cmp_bc.ge",
+        out_le=f"{prefix}.exp_cmp_bc.le",
+        out_eq=f"{prefix}.exp_cmp_bc.eq",
+    )
 
     for bit in range(5):
         add_gate(tensors, f"{prefix}.exp_diff.fa{bit}.ha1.sum.layer1.or", [1.0, 1.0], [-1.0])
@@ -1235,9 +1256,17 @@ def add_float16_div(tensors: Dict[str, torch.Tensor]) -> None:
         add_gate(tensors, f"{prefix}.bias_add.fa{bit}.carry_or", [1.0, 1.0], [-1.0])
 
     for stage in range(11):
-        pos_weights = [float(1 << (10 - i)) for i in range(11)]
-        neg_weights = [-w for w in pos_weights]
-        add_gate(tensors, f"{prefix}.mant_div.stage{stage}.cmp", pos_weights + neg_weights, [0.0])
+        # 11-bit GE comparator per division stage, bit-cascaded ternary form.
+        add_bit_cascade_compare(
+            tensors,
+            cmp_prefix=f"{prefix}.mant_div.stage{stage}.cmp_bc",
+            bits=11,
+            out_gt=f"{prefix}.mant_div.stage{stage}.cmp_bc.gt",
+            out_lt=f"{prefix}.mant_div.stage{stage}.cmp_bc.lt",
+            out_ge=f"{prefix}.mant_div.stage{stage}.cmp",
+            out_le=f"{prefix}.mant_div.stage{stage}.cmp_bc.le",
+            out_eq=f"{prefix}.mant_div.stage{stage}.cmp_bc.eq",
+        )
 
         for bit in range(11):
             add_gate(tensors, f"{prefix}.mant_div.stage{stage}.sub.not_d.bit{bit}", [-1.0], [0.0])
@@ -1292,16 +1321,17 @@ def add_float16_cmp(tensors: Dict[str, torch.Tensor]) -> None:
 
     add_gate(tensors, f"{prefix}.both_zero", [1.0, 1.0], [-2.0])
 
-    pos_weights = [float(1 << (14 - i)) for i in range(15)]
-    neg_weights = [-w for w in pos_weights]
-    add_gate(tensors, f"{prefix}.mag_a_gt_b", pos_weights + neg_weights, [-1.0])
-    add_gate(tensors, f"{prefix}.mag_a_ge_b", pos_weights + neg_weights, [0.0])
-    add_gate(tensors, f"{prefix}.mag_a_lt_b", neg_weights + pos_weights, [-1.0])
-    add_gate(tensors, f"{prefix}.mag_a_le_b", neg_weights + pos_weights, [0.0])
-
-    add_gate(tensors, f"{prefix}.mag_eq.geq", pos_weights + neg_weights, [0.0])
-    add_gate(tensors, f"{prefix}.mag_eq.leq", neg_weights + pos_weights, [0.0])
-    add_gate(tensors, f"{prefix}.mag_eq.and", [1.0, 1.0], [-2.0])
+    # Bit-cascaded ternary 15-bit magnitude comparator (sign-cleared payload).
+    add_bit_cascade_compare(
+        tensors,
+        cmp_prefix=f"{prefix}.mag_bc",
+        bits=15,
+        out_gt=f"{prefix}.mag_a_gt_b",
+        out_lt=f"{prefix}.mag_a_lt_b",
+        out_ge=f"{prefix}.mag_a_ge_b",
+        out_le=f"{prefix}.mag_a_le_b",
+        out_eq=f"{prefix}.mag_eq.and",
+    )
 
     add_gate(tensors, f"{prefix}.eq.not_nan", [-1.0], [0.0])
     add_gate(tensors, f"{prefix}.eq.mag_or_zero", [1.0, 1.0], [-1.0])
@@ -1412,16 +1442,17 @@ def add_float32_cmp(tensors: Dict[str, torch.Tensor]) -> None:
 
     add_gate(tensors, f"{prefix}.both_zero", [1.0, 1.0], [-2.0])
 
-    pos_weights = [float(1 << (30 - i)) for i in range(31)]
-    neg_weights = [-w for w in pos_weights]
-    add_gate(tensors, f"{prefix}.mag_a_gt_b", pos_weights + neg_weights, [-1.0])
-    add_gate(tensors, f"{prefix}.mag_a_ge_b", pos_weights + neg_weights, [0.0])
-    add_gate(tensors, f"{prefix}.mag_a_lt_b", neg_weights + pos_weights, [-1.0])
-    add_gate(tensors, f"{prefix}.mag_a_le_b", neg_weights + pos_weights, [0.0])
-
-    add_gate(tensors, f"{prefix}.mag_eq.geq", pos_weights + neg_weights, [0.0])
-    add_gate(tensors, f"{prefix}.mag_eq.leq", neg_weights + pos_weights, [0.0])
-    add_gate(tensors, f"{prefix}.mag_eq.and", [1.0, 1.0], [-2.0])
+    # Bit-cascaded ternary 31-bit magnitude comparator.
+    add_bit_cascade_compare(
+        tensors,
+        cmp_prefix=f"{prefix}.mag_bc",
+        bits=31,
+        out_gt=f"{prefix}.mag_a_gt_b",
+        out_lt=f"{prefix}.mag_a_lt_b",
+        out_ge=f"{prefix}.mag_a_ge_b",
+        out_le=f"{prefix}.mag_a_le_b",
+        out_eq=f"{prefix}.mag_eq.and",
+    )
 
     add_gate(tensors, f"{prefix}.eq.not_nan", [-1.0], [0.0])
     add_gate(tensors, f"{prefix}.eq.mag_or_zero", [1.0, 1.0], [-1.0])
@@ -1469,10 +1500,17 @@ def add_float32_add(tensors: Dict[str, torch.Tensor]) -> None:
     """
     prefix = "float32.add"
 
-    pos_weights = [float(1 << (7 - i)) for i in range(8)]
-    neg_weights = [-w for w in pos_weights]
-    add_gate(tensors, f"{prefix}.exp_cmp.a_gt_b", pos_weights + neg_weights, [-1.0])
-    add_gate(tensors, f"{prefix}.exp_cmp.a_lt_b", neg_weights + pos_weights, [-1.0])
+    # 8-bit exponent comparator, bit-cascaded ternary form.
+    add_bit_cascade_compare(
+        tensors,
+        cmp_prefix=f"{prefix}.exp_cmp_bc",
+        bits=8,
+        out_gt=f"{prefix}.exp_cmp.a_gt_b",
+        out_lt=f"{prefix}.exp_cmp.a_lt_b",
+        out_ge=f"{prefix}.exp_cmp_bc.ge",
+        out_le=f"{prefix}.exp_cmp_bc.le",
+        out_eq=f"{prefix}.exp_cmp_bc.eq",
+    )
 
     for bit in range(8):
         add_gate(tensors, f"{prefix}.exp_diff.fa{bit}.ha1.sum.layer1.or", [1.0, 1.0], [-1.0])
@@ -1626,9 +1664,17 @@ def add_float32_div(tensors: Dict[str, torch.Tensor]) -> None:
         add_gate(tensors, f"{prefix}.bias_add.fa{bit}.carry_or", [1.0, 1.0], [-1.0])
 
     for stage in range(24):
-        pos_weights = [float(1 << (23 - i)) for i in range(24)]
-        neg_weights = [-w for w in pos_weights]
-        add_gate(tensors, f"{prefix}.mant_div.stage{stage}.cmp", pos_weights + neg_weights, [0.0])
+        # 24-bit GE comparator per stage, bit-cascaded ternary form.
+        add_bit_cascade_compare(
+            tensors,
+            cmp_prefix=f"{prefix}.mant_div.stage{stage}.cmp_bc",
+            bits=24,
+            out_gt=f"{prefix}.mant_div.stage{stage}.cmp_bc.gt",
+            out_lt=f"{prefix}.mant_div.stage{stage}.cmp_bc.lt",
+            out_ge=f"{prefix}.mant_div.stage{stage}.cmp",
+            out_le=f"{prefix}.mant_div.stage{stage}.cmp_bc.le",
+            out_eq=f"{prefix}.mant_div.stage{stage}.cmp_bc.eq",
+        )
 
         for bit in range(24):
             add_gate(tensors, f"{prefix}.mant_div.stage{stage}.sub.not_d.bit{bit}", [-1.0], [0.0])

eval.py

@@ -4120,8 +4120,8 @@ class BatchedFitnessEvaluator:
             print("\n=== FLOAT16 ADD ===")
 
         expected_gates = [
-            ('float16.add.exp_cmp.a_gt_b.weight', (10,)),
-            ('float16.add.exp_cmp.a_lt_b.weight', (10,)),
+            ('float16.add.exp_cmp.a_gt_b.weight', (5,)),  # bit-cascaded final OR over 5 bits
+            ('float16.add.exp_cmp.a_lt_b.weight', (5,)),  # bit-cascaded final OR over 5 bits
             ('float16.add.exp_diff.fa0.ha1.sum.layer1.or.weight', (2,)),
             ('float16.add.align.stage0.bit0.not_sel.weight', (1,)),
             ('float16.add.sign_xor.layer1.or.weight', (2,)),
@@ -4198,7 +4198,7 @@ class BatchedFitnessEvaluator:
             ('float16.div.sign_xor.layer1.or.weight', (2,)),
             ('float16.div.exp_sub.not_b.bit0.weight', (1,)),
             ('float16.div.bias_add.fa0.ha1.sum.layer1.or.weight', (2,)),
-            ('float16.div.mant_div.stage0.cmp.weight', (22,)),
+            ('float16.div.mant_div.stage0.cmp.weight', (1,)),  # bit-cascaded GE = NOT(LT) buffer
             ('float16.div.mant_div.stage0.sub.not_d.bit0.weight', (1,)),
             ('float16.div.mant_div.stage0.mux.bit0.not_sel.weight', (1,)),
         ]
@@ -4238,7 +4238,7 @@ class BatchedFitnessEvaluator:
             ('float16.cmp.either_nan.weight', (2,)),
             ('float16.cmp.sign_xor.layer1.or.weight', (2,)),
             ('float16.cmp.both_zero.weight', (2,)),
-            ('float16.cmp.mag_a_gt_b.weight', (30,)),
+            ('float16.cmp.mag_a_gt_b.weight', (15,)),  # bit-cascaded final OR over 15 bits
             ('float16.cmp.eq.result.weight', (2,)),
             ('float16.cmp.lt.result.weight', (3,)),
             ('float16.cmp.gt.result.weight', (3,)),
@@ -4316,7 +4316,7 @@ class BatchedFitnessEvaluator:
             print("\n=== FLOAT32 ADD ===")
 
         expected_gates = [
-            ('float32.add.exp_cmp.a_gt_b.weight', (16,)),
+            ('float32.add.exp_cmp.a_gt_b.weight', (8,)),  # bit-cascaded final OR over 8 bits
             ('float32.add.exp_diff.fa0.ha1.sum.layer1.or.weight', (2,)),
             ('float32.add.align.stage0.bit0.not_sel.weight', (1,)),
             ('float32.add.sign_xor.layer1.or.weight', (2,)),
@@ -4393,7 +4393,7 @@ class BatchedFitnessEvaluator:
             ('float32.div.sign_xor.layer1.or.weight', (2,)),
             ('float32.div.exp_sub.not_b.bit0.weight', (1,)),
             ('float32.div.bias_add.fa0.ha1.sum.layer1.or.weight', (2,)),
-            ('float32.div.mant_div.stage0.cmp.weight', (48,)),
+            ('float32.div.mant_div.stage0.cmp.weight', (1,)),  # bit-cascaded GE = NOT(LT) buffer
             ('float32.div.mant_div.stage0.sub.not_d.bit0.weight', (1,)),
             ('float32.div.mant_div.stage0.mux.bit0.not_sel.weight', (1,)),
         ]
@@ -4433,7 +4433,7 @@ class BatchedFitnessEvaluator:
             ('float32.cmp.either_nan.weight', (2,)),
             ('float32.cmp.sign_xor.layer1.or.weight', (2,)),
             ('float32.cmp.both_zero.weight', (2,)),
-            ('float32.cmp.mag_a_gt_b.weight', (62,)),
+            ('float32.cmp.mag_a_gt_b.weight', (31,)),  # bit-cascaded final OR over 31 bits
             ('float32.cmp.eq.result.weight', (2,)),
             ('float32.cmp.lt.result.weight', (3,)),
             ('float32.cmp.gt.result.weight', (3,)),

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