feat: Allow Core CKF to skip the start surface (#3535)

Allows the user to skip the first surface during track finding with the CKF. This is necessary if the surface was already processed with a different pass, i.e. forward and backward, to avoid feeding the same measurement twice.
acts-project · Aug 30, 2024 · c231382 · c231382
1 parent 2493b0e
commit c231382
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Showing 13 changed files with 21 additions and 9 deletions.
diff --git a/CI/physmon/reference/trackfinding_1muon/orthogonal/performance_ckf.root b/CI/physmon/reference/trackfinding_1muon/orthogonal/performance_ckf.root
diff --git a/CI/physmon/reference/trackfinding_1muon/orthogonal/tracksummary_ckf_hist.root b/CI/physmon/reference/trackfinding_1muon/orthogonal/tracksummary_ckf_hist.root
diff --git a/CI/physmon/reference/trackfinding_1muon/seeded/performance_ckf.root b/CI/physmon/reference/trackfinding_1muon/seeded/performance_ckf.root
diff --git a/CI/physmon/reference/trackfinding_1muon/seeded/tracksummary_ckf_hist.root b/CI/physmon/reference/trackfinding_1muon/seeded/tracksummary_ckf_hist.root
diff --git a/...reference/trackfinding_4muon_50vertices/performance_vertexing_amvf_gauss_notime_hist.root b/...reference/trackfinding_4muon_50vertices/performance_vertexing_amvf_gauss_notime_hist.root
diff --git a/...on/reference/trackfinding_4muon_50vertices/performance_vertexing_amvf_grid_time_hist.root b/...on/reference/trackfinding_4muon_50vertices/performance_vertexing_amvf_grid_time_hist.root
diff --git a/...hysmon/reference/trackfinding_4muon_50vertices/performance_vertexing_ivf_notime_hist.root b/...hysmon/reference/trackfinding_4muon_50vertices/performance_vertexing_ivf_notime_hist.root
diff --git a/...smon/reference/trackfinding_ttbar_pu200/performance_vertexing_amvf_gauss_notime_hist.root b/...smon/reference/trackfinding_ttbar_pu200/performance_vertexing_amvf_gauss_notime_hist.root
diff --git a/CI/physmon/reference/trackfinding_ttbar_pu200/performance_vertexing_amvf_grid_time_hist.root b/CI/physmon/reference/trackfinding_ttbar_pu200/performance_vertexing_amvf_grid_time_hist.root
diff --git a/CI/physmon/reference/trackfinding_ttbar_pu200/tracksummary_ckf_hist.root b/CI/physmon/reference/trackfinding_ttbar_pu200/tracksummary_ckf_hist.root
diff --git a/Core/include/Acts/TrackFinding/CombinatorialKalmanFilter.hpp b/Core/include/Acts/TrackFinding/CombinatorialKalmanFilter.hpp
@@ -234,6 +234,10 @@ struct CombinatorialKalmanFilterOptions {
 
   /// Whether to consider energy loss.
   bool energyLoss = true;
+
+  /// Skip the pre propagation call. This effectively skips the first surface
+  /// @note This is useful if the first surface should not be considered in a second reverse pass
+  bool skipPrePropagationUpdate = false;
 };
 
 template <typename track_container_t>
@@ -524,6 +528,9 @@ class CombinatorialKalmanFilter {
     /// Whether to consider energy loss.
     bool energyLoss = true;
 
+    /// Skip the pre propagation call. This effectively skips the first surface
+    bool skipPrePropagationUpdate = false;
+
     /// Calibration context for the finding run
     const CalibrationContext* calibrationContextPtr{nullptr};
 
@@ -547,6 +554,12 @@ class CombinatorialKalmanFilter {
         return;
       }
 
+      if (state.stage == PropagatorStage::prePropagation &&
+          skipPrePropagationUpdate) {
+        ACTS_VERBOSE("Skip pre-propagation update (first surface)");
+        return;
+      }
+
       ACTS_VERBOSE("CombinatorialKalmanFilter step");
 
       assert(!result.activeBranches.empty() && "No active branches");
@@ -1263,6 +1276,8 @@ class CombinatorialKalmanFilter {
     combKalmanActor.targetReached.surface = tfOptions.targetSurface;
     combKalmanActor.multipleScattering = tfOptions.multipleScattering;
     combKalmanActor.energyLoss = tfOptions.energyLoss;
+    combKalmanActor.skipPrePropagationUpdate =
+        tfOptions.skipPrePropagationUpdate;
     combKalmanActor.actorLogger = m_actorLogger.get();
     combKalmanActor.updaterLogger = m_updaterLogger.get();
     combKalmanActor.calibrationContextPtr = &tfOptions.calibrationContext.get();

diff --git a/Examples/Algorithms/TrackFinding/src/TrackFindingAlgorithm.cpp b/Examples/Algorithms/TrackFinding/src/TrackFindingAlgorithm.cpp
@@ -368,6 +368,7 @@ ProcessCode TrackFindingAlgorithm::execute(const AlgorithmContext& ctx) const {
                                    ctx.calibContext, slAccessorDelegate,
                                    extensions, secondPropOptions);
   secondOptions.targetSurface = m_cfg.reverseSearch ? nullptr : pSurface.get();
+  secondOptions.skipPrePropagationUpdate = true;
 
   using Extrapolator = Acts::Propagator<Acts::SympyStepper, Acts::Navigator>;
   using ExtrapolatorOptions =
@@ -542,9 +543,6 @@ ProcessCode TrackFindingAlgorithm::execute(const AlgorithmContext& ctx) const {
                 ACTS_WARNING("Second track has no reference surface.");
                 continue;
               }
-              if (secondTrack.nMeasurements() <= 1) {
-                continue;
-              }
 
               // TODO a copy of the track should not be necessary but is the
               //      safest way with the current EDM
@@ -559,8 +557,7 @@ ProcessCode TrackFindingAlgorithm::execute(const AlgorithmContext& ctx) const {
               secondTrackCopy.reverseTrackStates(true);
 
               firstState.previous() =
-                  (*std::next(secondTrackCopy.trackStatesReversed().begin()))
-                      .index();
+                  secondTrackCopy.outermostTrackState().index();
 
               // finalize the track candidate
 

diff --git a/Examples/Python/tests/root_file_hashes.txt b/Examples/Python/tests/root_file_hashes.txt
@@ -33,16 +33,16 @@ test_digitization_example_input[smeared]__particles.root: 5fe7dda2933ee6b9615b06
 test_digitization_example_input[smeared]__measurements.root: 243c2f69b7b0db9dbeaa7494d4ea0f3dd1691dc90f16e10df6c0491ff4dc7d62
 test_digitization_example_input[geometric]__particles.root: 5fe7dda2933ee6b9615b064d192322fe07831133cd998e5ed99a3b992b713a10
 test_digitization_example_input[geometric]__measurements.root: 63ec81635979058fb8976f94455bf490cf92b7b142c4a05cc39de6225f5de2fb
-test_ckf_tracks_example[generic-full_seeding]__trackstates_ckf.root: c4eb6e58fe2351f41dce134878e523f8b78b875ffd5c87bb094ebb3aa0e8e432
-test_ckf_tracks_example[generic-full_seeding]__tracksummary_ckf.root: 4fa859b395e172c613d466a2ea25cdd56ed1ab3cfd857d230f21bc184310d668
+test_ckf_tracks_example[generic-full_seeding]__trackstates_ckf.root: b61fa5d207d3d87742a8bae454eb4c97b2ef6613fe38f388f147da104ec7ff84
+test_ckf_tracks_example[generic-full_seeding]__tracksummary_ckf.root: 18580d384e3ceb126be9c5d8857e176cff6c7d549155012d87939c91dba87015
 test_ckf_tracks_example[generic-full_seeding]__performance_seeding_trees.root: 0e0676ffafdb27112fbda50d1cf627859fa745760f98073261dcf6db3f2f991e
 test_ckf_tracks_example[generic-truth_estimated]__trackstates_ckf.root: afc9984f5b1f0b9d42156a1c3917df68144f1c486dd2b9b9a199309aa958cddc
 test_ckf_tracks_example[generic-truth_estimated]__tracksummary_ckf.root: e5db2791d9d09d88705c0dbeba666b4df441ecc920b9e400510df2913766e112
 test_ckf_tracks_example[generic-truth_estimated]__performance_seeding.root: 1facb05c066221f6361b61f015cdf0918e94d9f3fce2269ec7b6a4dffeb2bc7e
 test_ckf_tracks_example[generic-truth_smeared]__trackstates_ckf.root: 47c5e18de310363fdebe79d6c82c3cf5407200f2f06879f79217924d28a67a6e
 test_ckf_tracks_example[generic-truth_smeared]__tracksummary_ckf.root: 961aa19995a8a1c64a365c6d72a90eee9809efaaee652b674db287acacfb810c
-test_ckf_tracks_example[odd-full_seeding]__trackstates_ckf.root: a7d3aba70ea614964e62a9acde1c7aeb280c68d2d57bd733ecb34ced938dd716
-test_ckf_tracks_example[odd-full_seeding]__tracksummary_ckf.root: 3b27644bf25c20e5ed0d25f2273b68a470c63b07677a806cb176d4c91abd153e
+test_ckf_tracks_example[odd-full_seeding]__trackstates_ckf.root: 65e17d3747dbf415bcaf31101e23bb48e61d8bc5da817e0fd33a4d03d77d4601
+test_ckf_tracks_example[odd-full_seeding]__tracksummary_ckf.root: 2a905c02e3fd3b9f0626ee204294c223d9a05e7774a4234c51114e4e380954b9
 test_ckf_tracks_example[odd-full_seeding]__performance_seeding_trees.root: 43c58577aafe07645e5660c4f43904efadf91d8cda45c5c04c248bbe0f59814f
 test_ckf_tracks_example[odd-truth_estimated]__trackstates_ckf.root: a1103e9429076d3e5d0b9e3007710d26460ca9c4824c586522adedb19ce9e442
 test_ckf_tracks_example[odd-truth_estimated]__tracksummary_ckf.root: a5eecfb6907406286c56db4df19937539cb43e454307bc53bd1eda535526736c