test(D1): exchange, Jet and fine-surface checks run on all-blocked storage

- test_exchange_window and test_raw_exchange_gpu fine(): dense root becomes
  a (12, 8) blocked root (fine(None) stays only for the dense reference test
  that D2 retires);
- jets: G1/G3 compare blocked layouts against the FINE_BLOCKS[0] reference
  (blocked root); the dense run is a separate leg D2 removes; G2 legacy
  actuation vs Jet on the blocked reference; CPU fixtures use a blocked root;
- test_refinement_blocked_fine.raw reads every level through its layout;
- test_fine_surface_gpu: new test_fine_surface_blocked_matches_uniform_four_hops
  (fine ROI after each of four hops vs the uniform 48^2 solver with the same
  tolerances, blowing/suction mass sign from raw exchange, zero actuation ==
  passive bit for bit); the cross-interface donor rejection passes tiles.
  The dense hook/ledger/audit probes in test_fine_surface_four_hops and the
  dense SoA fault tests stay until D2 retires them by name.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>

tests/validation/multigrid/test_refinement_blocked_fine.py

@@ -88,15 +88,13 @@ def seam_cells(layout, mapped):
 
 
 def raw(backend):
-    """Unmasked device arrays; blocked fine storage unpacked from owner cores."""
-    coarse, fine = backend._levels
-    out = [np.empty(coarse.shape, np.float32)]
-    out.append(np.empty(fine.shape if backend.fine_layout is None
-                        else backend.fine_layout.blocked_shape, np.float32))
-    cuda.memcpy_dtoh(out[0], coarse.current)
-    cuda.memcpy_dtoh(out[1], fine.current)
-    if backend.fine_layout is not None:
-        out[1] = backend.fine_layout.to_dense(out[1])
+    """Unmasked device arrays of every level; blocked storage unpacked from owner cores."""
+    out = []
+    for level in backend._levels:
+        array = np.empty(level.shape if level.layout is None else level.layout.blocked_shape,
+                         np.float32)
+        cuda.memcpy_dtoh(array, level.current)
+        out.append(array if level.layout is None else level.layout.to_dense(array))
     return out