From 75422a917bffa308d3f6d84e705d1f7a35d74992 Mon Sep 17 00:00:00 2001
From: YurenHao0426 <Blackhao0426@gmail.com>
Date: Sat, 29 Aug 2026 12:51:32 -0500
Subject: feat: compose SDIL with physical overclamping

---
 experiments/physical_bias_p1_smoke.py | 54 +++++++++++++++++++++++++++++++++++
 1 file changed, 54 insertions(+)

(limited to 'experiments')

diff --git a/experiments/physical_bias_p1_smoke.py b/experiments/physical_bias_p1_smoke.py
index dc9b6f1..c23c9eb 100644
--- a/experiments/physical_bias_p1_smoke.py
+++ b/experiments/physical_bias_p1_smoke.py
@@ -20,6 +20,8 @@ from sdil.physical_coupled import (
     free_output,
     joint_solution,
     local_replay_update,
+    overclamped_clean_rate,
+    simulate_alternating_tasks,
     standard_clean_rate,
 )
 
@@ -73,12 +75,64 @@ def main() -> None:
     downstream[:] = np.random.default_rng(29).normal(size=downstream.shape)
     update_c = local_replay_update(affine, gates, teaching, eligibility, 0.03)
     assert np.array_equal(update_a, update_c)
+
+    _, output_free, output_clamped = overclamped_clean_rate(
+        circuit,
+        joint,
+        tasks[0],
+        nudging=0.25,
+        clamp_magnitude=circuit.high,
+        exact_target=True,
+    )
+    expected_clamped = output_free + 0.25 * (
+        circuit.high * np.sign(tasks[0].label_voltage - output_free)
+        - output_free
+    )
+    assert output_clamped == expected_clamped
+
+    exact_predictor = LocalPredictor.zeros(
+        field.reference_gate, scale, affine=True)
+    exact_predictor.coefficients[:, 0] = field.bias_at_reference
+    exact_predictor.coefficients[:, 1] = field.local_slopes * scale
+    shared = {
+        "period_seconds": 0.01,
+        "cycles": 8,
+        "initial_gates": np.asarray((4.0, 4.0)),
+        "overclamp_nudging": 0.25,
+        "overclamp_magnitude": circuit.high,
+        "overclamp_exact_target": True,
+    }
+    clean_overclamp = simulate_alternating_tasks(
+        circuit,
+        tasks,
+        field,
+        method="overclamp",
+        bias_strength=0.0,
+        **shared,
+    )
+    debiased_overclamp = simulate_alternating_tasks(
+        circuit,
+        tasks,
+        field,
+        method="overclamp_sdil",
+        bias_strength=1.0,
+        predictor=exact_predictor,
+        **shared,
+    )
+    assert np.allclose(
+        clean_overclamp["final_gates"],
+        debiased_overclamp["final_gates"],
+        atol=1e-12,
+        rtol=0.0,
+    )
+    assert debiased_overclamp["max_abs_clamp_displacement_v"] > 0.0
     print({
         "joint_solution": joint.tolist(),
         "affine_calibration_mae": float(affine_error),
         "constant_calibration_mae": float(constant_error),
         "neutral_observations_each": observations_affine,
         "local_replay_exact": True,
+        "sdil_overclamp_composition_exact": True,
         "autodiff_used": False,
     })
 
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