Add ProcessRouter for physics-process-based expert gating

Routes on the physics process (Compton, phot, brems, ...) that ends a
step, supervised by a small classifier since process is a post-step
outcome unobservable at gate time. Threads a process label end-to-end
through the data pipeline (loader, build_features, dataset batches,
training loss/checkpointing) alongside the existing EnergyRouter.

tests/test_transforms.py

@@ -235,7 +235,48 @@ def test_build_features_clamps_n_sec_label_to_k_max():
     pdg_map = {11: 0}
     mat_map = {"PbWO4": 0}
 
-    _, _, _, n_sec, _, _, _, _ = build_features(data, pdg_map, mat_map)
+    _, _, _, n_sec, _, _, _, _, _ = build_features(data, pdg_map, mat_map)
 
     assert n_sec.max() <= K_MAX
     np.testing.assert_array_equal(n_sec, [0, 5, K_MAX])
+
+
+def _minimal_step_data(N: int, process: np.ndarray | None = None) -> dict:
+    rng = np.random.default_rng(0)
+    data = {
+        "pdg": np.full(N, 11, dtype=np.int32),
+        "material": np.full(N, "PbWO4", dtype=object),
+        "pre_pos": rng.standard_normal((N, 3)).astype(np.float32),
+        "pre_E": np.full(N, 10.0, dtype=np.float32),
+        "pre_dir": np.tile(np.array([0, 0, 1], dtype=np.float32), (N, 1)),
+        "layer_id": np.zeros(N, dtype=np.int32),
+        "n_sec": np.zeros(N, dtype=np.int32),
+        "e_sec": np.full(N, 1.0, dtype=np.float32),
+        "step_length": np.full(N, 1.0, dtype=np.float32),
+        "post_E": np.full(N, 9.0, dtype=np.float32),
+        "edep": np.full(N, 1.0, dtype=np.float32),
+        "post_dir": np.tile(np.array([0, 0, 1], dtype=np.float32), (N, 1)),
+        "post_pos": rng.standard_normal((N, 3)).astype(np.float32),
+    }
+    if process is not None:
+        data["process"] = process
+    return data
+
+
+def test_build_features_proc_idx_zero_without_proc_map():
+    data = _minimal_step_data(3, process=np.array(["compt", "phot", "eIoni"], dtype=object))
+    pdg_map, mat_map = {11: 0}, {"PbWO4": 0}
+
+    *_, proc_idx, _, _ = build_features(data, pdg_map, mat_map)
+
+    np.testing.assert_array_equal(proc_idx, [0, 0, 0])
+
+
+def test_build_features_proc_idx_looks_up_proc_map():
+    data = _minimal_step_data(3, process=np.array(["compt", "phot", "eIoni"], dtype=object))
+    pdg_map, mat_map = {11: 0}, {"PbWO4": 0}
+    proc_map = {"compt": 0, "phot": 1, "eIoni": 2}
+
+    *_, proc_idx, _, _ = build_features(data, pdg_map, mat_map, proc_map=proc_map)
+
+    np.testing.assert_array_equal(proc_idx, [0, 1, 2])