test: verify large-grid edges affect CLLN outputs

2 files changed, 41 insertions, 1 deletions

diff --git a/experiments/coupled_ladder_audit.py b/experiments/coupled_ladder_audit.py
index 13692b9..fa8c599 100644
--- a/experiments/coupled_ladder_audit.py
+++ b/experiments/coupled_ladder_audit.py
@@ -26,6 +26,7 @@ from sdil.physical_grid import (  # noqa: E402
     GridSquareLawImperfection,
     RingClassificationDataset,
     edge_voltage_drops,
+    output_difference,
 )
 
 
@@ -82,6 +83,29 @@ def main() -> None:
     )
     kcl_residual = maximum_unknown_kcl_residual(
         side32, gates32, state32)
+    sensitivity_indices = np.unique(np.linspace(
+        0, side32.edge_count - 1, 128, dtype=int))
+    sensitivity_step_v = 1e-5
+    sampled_sensitivities = []
+    sources32 = side32.source_values(*dataset.inputs_v[0])
+    for edge in sensitivity_indices:
+        gates_plus = gates32.copy()
+        gates_minus = gates32.copy()
+        gates_plus[edge] += sensitivity_step_v
+        gates_minus[edge] -= sensitivity_step_v
+        output_plus = output_difference(
+            side32,
+            solve_linear_grid_state(side32, gates_plus, sources32),
+        )
+        output_minus = output_difference(
+            side32,
+            solve_linear_grid_state(side32, gates_minus, sources32),
+        )
+        sampled_sensitivities.append(
+            (output_plus - output_minus) / (2.0 * sensitivity_step_v))
+    absolute_sensitivities = np.abs(np.asarray(sampled_sensitivities))
+    sampled_influence_fraction = float(np.mean(
+        absolute_sensitivities > 1e-9))
 
     edge_count = side4.edge_count
     rng = np.random.default_rng(20260829)
@@ -158,6 +182,8 @@ def main() -> None:
         "released_side4_layout_exact": layout_exact,
         "released_side4_gate_vector_exact": tiling_exact,
         "side32_kcl_residual_below_1e_12": kcl_residual < 1e-12,
+        "side32_sampled_edges_influence_output": (
+            sampled_influence_fraction == 1.0),
         "common_mode_cancellation_below_1e_12": (
             common_mode_cancellation_error < 1e-12),
         "default_imperfection_is_state_dependent": (
@@ -176,6 +202,15 @@ def main() -> None:
         "checks": checks,
         "measurements": {
             "side32_maximum_unknown_kcl_residual_a": kcl_residual,
+            "side32_sampled_edge_count": len(sensitivity_indices),
+            "side32_sampled_output_sensitivity_min_abs": float(
+                np.min(absolute_sensitivities)),
+            "side32_sampled_output_sensitivity_median_abs": float(
+                np.median(absolute_sensitivities)),
+            "side32_sampled_output_sensitivity_max_abs": float(
+                np.max(absolute_sensitivities)),
+            "side32_sampled_influence_fraction_above_1e_9": (
+                sampled_influence_fraction),
             "common_mode_cancellation_max_abs_v_per_s": (
                 common_mode_cancellation_error),
             "state_dependent_neutral_bias_difference_rms_v_per_s": (
@@ -201,4 +236,3 @@ def main() -> None:
 
 if __name__ == "__main__":
     main()
-
diff --git a/results/coupled_ladder/x0_locality_audit.json b/results/coupled_ladder/x0_locality_audit.json
index a21f9c0..cd41471 100644
--- a/results/coupled_ladder/x0_locality_audit.json
+++ b/results/coupled_ladder/x0_locality_audit.json
@@ -6,6 +6,7 @@
     "released_side4_layout_exact": true,
     "released_side4_gate_vector_exact": true,
     "side32_kcl_residual_below_1e_12": true,
+    "side32_sampled_edges_influence_output": true,
     "common_mode_cancellation_below_1e_12": true,
     "default_imperfection_is_state_dependent": true,
     "ideal_paths_have_identical_gates": true,
@@ -15,6 +16,11 @@
   },
   "measurements": {
     "side32_maximum_unknown_kcl_residual_a": 8.646088809098271e-19,
+    "side32_sampled_edge_count": 128,
+    "side32_sampled_output_sensitivity_min_abs": 5.488387522234461e-08,
+    "side32_sampled_output_sensitivity_median_abs": 9.380685117577059e-06,
+    "side32_sampled_output_sensitivity_max_abs": 0.00011643896263846541,
+    "side32_sampled_influence_fraction_above_1e_9": 1.0,
     "common_mode_cancellation_max_abs_v_per_s": 3.552713678800501e-15,
     "state_dependent_neutral_bias_difference_rms_v_per_s": 1.0419674628075035,
     "ideal_path_max_gate_difference_v": 0.0,