Update hard_scatter/ttbar/v1 dataset card

README.md

@@ -3,151 +3,281 @@ license: cc-by-4.0
 task_categories:
 - other
 tags:
+
 - physics
+
 - high-energy-physics
+
 - particle-physics
+
 - tracking
+
 - calorimetry
+
 - machine-learning
+
 - simulation
+
 pretty_name: ColliderML Top-Quark Pair Production (No Pileup)
 size_categories:
 - 10K<n<100K
 configs:
+
 - config_name: particles
   data_files:
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events1000-1999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events10000-10999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events11000-11999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events15000-15999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events2000-2999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events24000-24999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events25000-25999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events28000-28999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events33000-33999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events34000-34999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events42000-42999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events47000-47999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events51000-51999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events55000-55999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events57000-57999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events60000-60999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events61000-61999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events65000-65999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events66000-66999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events68000-68999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events75000-75999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events76000-76999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events78000-78999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events83000-83999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events88000-88999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events9000-9999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events92000-92999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/truth/particles/hard_scatter.ttbar.v1.truth.particles.events97000-97999.parquet"
+
+
 - config_name: tracker_hits
   data_files:
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events1000-1999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events10000-10999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events11000-11999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events15000-15999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events2000-2999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events24000-24999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events25000-25999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events28000-28999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events33000-33999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events34000-34999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events42000-42999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events47000-47999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events51000-51999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events55000-55999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events57000-57999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events60000-60999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events61000-61999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events65000-65999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events66000-66999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events68000-68999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events75000-75999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events76000-76999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events78000-78999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events83000-83999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events88000-88999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events9000-9999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events92000-92999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracker_hits/hard_scatter.ttbar.v1.reco.tracker_hits.events97000-97999.parquet"
+
+
 - config_name: calo_hits
   data_files:
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events1000-1999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events10000-10999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events11000-11999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events15000-15999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events2000-2999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events24000-24999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events25000-25999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events28000-28999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events33000-33999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events34000-34999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events42000-42999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events47000-47999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events51000-51999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events55000-55999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events57000-57999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events60000-60999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events61000-61999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events65000-65999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events66000-66999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events68000-68999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events75000-75999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events76000-76999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events78000-78999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events83000-83999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events88000-88999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events9000-9999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events92000-92999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/calo_hits/hard_scatter.ttbar.v1.reco.calo_hits.events97000-97999.parquet"
+
+
 - config_name: tracks
   data_files:
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events1000-1999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events10000-10999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events11000-11999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events15000-15999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events2000-2999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events24000-24999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events25000-25999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events28000-28999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events33000-33999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events34000-34999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events42000-42999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events47000-47999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events51000-51999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events55000-55999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events57000-57999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events60000-60999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events61000-61999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events65000-65999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events66000-66999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events68000-68999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events75000-75999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events76000-76999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events78000-78999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events83000-83999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events88000-88999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events9000-9999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events92000-92999.parquet"
+
   - "https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet/reco/tracks/hard_scatter.ttbar.v1.reco.tracks.events97000-97999.parquet"
+
+
 ---
 
 # ColliderML: ColliderML Top-Quark Pair Production (No Pileup)
 
 ## Dataset Description
 
-This dataset contains simulated high-energy physics collision events generated using the **Open Data Detector (ODD)** geometry within the **ACTS (A Common Tracking Software)** framework.
+This dataset contains simulated high-energy physics collision events for top-quark pair (ttbar) production with no pileup (single interaction per event) generated using the **Open Data Detector (ODD)** geometry within the **ACTS (A Common Tracking Software)** framework, representing a generic collider detector similar to those at the LHC.
 
 ### Dataset Summary
 
 - **Campaign**: `hard_scatter`
 - **Process**: Top-quark pair (ttbar) production
 - **Version**: `v1`
-- **Pileup**: 0
+- **Number of Events**: ~28000 events
+- **Pileup**: 0 (no additional interactions)
 - **Detector**: Open Data Detector (ODD)
 - **Format**: Apache Parquet with list columns for variable-length data
 - **License**: cc-by-4.0
@@ -158,99 +288,447 @@ This dataset is designed for machine learning tasks in high-energy physics, incl
 
 - **Particle tracking**: Reconstruct charged particle trajectories from detector hits
 - **Track-to-particle matching**: Associate reconstructed tracks with truth particles
-- **Jet tagging**: Identify jets originating from different particle types
+- **Jet tagging**: Identify jets originating from top quarks, b-quarks, or light quarks
 - **Energy reconstruction**: Predict particle energies from calorimeter deposits
-- **Physics analysis**: Event classification and signal/background discrimination
+- **Physics analysis**: Event classification (signal vs. background discrimination)
 - **Representation learning**: Study hierarchical information at different detector levels
 
+### Languages
+
+N/A (Physics data)
+
 ## Dataset Structure
 
-### Data Configurations
+### Data Instances
+
+Each row in the Parquet files represents a single collision event. Variable-length quantities (e.g., lists of particles, hits, tracks) are stored as Parquet list columns.
+
+Example event structure:
 
-The dataset contains 4 data types:
+```python
+{
+    'event_id': 42,
+    'particle_id': [0, 1, 2, 3, ...],  # List of particle IDs
+    'pdg_id': [11, -11, 211, ...],     # Particle type codes
+    'px': [1.2, -0.5, 3.4, ...],       # Momentum components (GeV)
+    'py': [0.8, 1.1, -0.3, ...],
+    'pz': [5.2, -2.1, 10.5, ...],
+    'energy': [5.5, 2.3, 11.2, ...],
+    # ... additional fields
+}
+```
 
+### Data Fields
 
-#### particles
+The dataset contains 4 data types organized by detector hierarchy:
 
-- **Number of files**: 28
-- **Fields**: event_id, particle_id, pdg_id, mass, energy, charge, vx, vy, vz, time, px, py, pz, vertex_primary, parent_id
 
-#### tracker_hits
+#### 1. `particles` (Truth-level)
 
-- **Number of files**: 28
-- **Fields**: event_id, x, y, z, true_x, true_y, true_z, time, particle_id, cell_id, detector, volume_id, layer_id, surface_id
+Truth information about generated particles before detector simulation.
 
-#### calo_hits
+| Field | Type | Description |
+|-------|------|-------------|
+| `event_id` | int64 | Unique event identifier |
+| `particle_id` | list<int64> | Unique particle ID within event |
+| `pdg_id` | list<int64> | PDG particle code (e.g., 11=electron, 13=muon, 211=pion) |
+| `mass` | list<float64> | Particle rest mass (GeV/c²) |
+| `energy` | list<float64> | Particle total energy (GeV) |
+| `charge` | list<float64> | Electric charge (in units of e) |
+| `px`, `py`, `pz` | list<float64> | Momentum components (GeV/c) |
+| `vx`, `vy`, `vz` | list<float64> | Vertex position (mm) |
+| `time` | list<float64> | Production time (ns) |
+| `num_tracker_hits` | list<int64> | Number of hits in tracker |
+| `num_calo_hits` | list<int64> | Number of hits in calorimeter |
+| `vertex_primary` | list<int64> | Primary vertex flag (1=primary, 0=secondary) |
+| `parent_id` | list<float64> | ID of parent particle |
 
-- **Number of files**: 28
-- **Fields**: event_id, detector, total_energy, x, y, z, contrib_particle_ids, contrib_energies, contrib_times
+**Typical event**: ~200-500 particles per event
 
-#### tracks
 
-- **Number of files**: 28
-- **Fields**: event_id, d0, z0, phi, theta, qop, majority_particle_id, hit_ids, track_id
 
+#### 2. `tracker_hits` (Detector-level)
+
+Digitized spatial measurements from the tracking detector (silicon sensors).
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `event_id` | int64 | Unique event identifier |
+| `x`, `y`, `z` | list<float64> | Measured hit position (mm) |
+| `true_x`, `true_y`, `true_z` | list<float64> | True (simulated) hit position before digitization (mm) |
+| `time` | list<float64> | Hit time (ns) |
+| `particle_id` | list<int64> | Truth particle that created this hit |
+| `volume_id` | list<int64> | Detector volume identifier |
+| `layer_id` | list<int64> | Detector layer number |
+| `surface_id` | list<int64> | Sensor surface identifier |
+| `cell_id` | list<int64> | Cell/pixel identifier |
+| `detector` | list<int64> | Detector subsystem code |
+
+**Typical event**: ~2,000-5,000 hits per event
+
+
+
+#### 3. `calo_hits` (Calorimeter-level)
+
+Energy deposits in the calorimeter system (electromagnetic + hadronic).
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `event_id` | int64 | Unique event identifier |
+| `detector` | list<string> | Calorimeter subsystem name |
+| `cell_id` | list<string> | Calorimeter cell identifier |
+| `total_energy` | list<float64> | Total energy deposited in cell (GeV) |
+| `x`, `y`, `z` | list<float64> | Cell center position (mm) |
+| `contrib_particle_ids` | list<list<int64>> | IDs of particles contributing to this cell |
+| `contrib_energies` | list<list<float64>> | Energy contribution from each particle (GeV) |
+| `contrib_times` | list<list<float64>> | Time of each contribution (ns) |
+
+**Note**: Nested lists for contributions (one cell can have multiple particle deposits).
+
+**Typical event**: ~500-1,000 calorimeter cells with deposits
+
+
+
+#### 4. `tracks` (Reconstruction-level)
+
+Reconstructed particle tracks from pattern recognition and track fitting algorithms.
+
+| Field | Type | Description |
+|-------|------|-------------|
+| `event_id` | int64 | Unique event identifier |
+| `track_id` | list<int64> | Unique track identifier within event |
+| `majority_particle_id` | list<int64> | Truth particle with most hits on this track |
+| `d0` | list<float64> | Transverse impact parameter (mm) |
+| `z0` | list<float64> | Longitudinal impact parameter (mm) |
+| `phi` | list<float64> | Azimuthal angle (radians) |
+| `theta` | list<float64> | Polar angle (radians) |
+| `qop` | list<float64> | Charge divided by momentum (e/GeV) |
+| `hit_ids` | list<list<int32>> | List of tracker hit IDs assigned to this track |
+
+**Track parameters**: Standard ACTS track representation (perigee parameters at origin).
+
+**Derived quantities**:
+- Transverse momentum: `pt = abs(1/qop) * sin(theta)`
+- Pseudorapidity: `eta = -ln(tan(theta/2))`
+- Total momentum: `p = abs(1/qop)`
+
+**Typical event**: ~50-150 reconstructed tracks per event
+
+
+### Data Splits
+
+Currently, the dataset does not have predefined train/validation/test splits. Users should implement their own splitting strategy based on their use case. Recommended approach:
+
+```python
+from sklearn.model_selection import train_test_split
+
+# Example: 70% train, 15% validation, 15% test
+all_events = list(range(28000))
+train_val, test = train_test_split(all_events, test_size=0.15, random_state=42)
+train, val = train_test_split(train_val, test_size=0.176, random_state=42)  # 0.176 * 0.85 ≈ 0.15
+```
+
+## Dataset Creation
+
+### Curation Rationale
+
+This dataset was created to support machine learning research in high-energy physics, specifically for:
+
+1. **Benchmarking tracking algorithms**: Compare traditional and ML-based track reconstruction methods
+2. **Hierarchical representation learning**: Study information flow from detector hits → tracks → particles
+3. **Physics analysis**: Develop ML models for event classification and particle identification
+4. **Open science**: Provide publicly accessible, realistic detector simulation data
+
+This dataset contains simulated ttbar events with no pileup,
+useful for developing and testing machine learning algorithms
+for particle tracking and physics analysis.
 
-### Data Location
 
-The Parquet files are hosted on NERSC public portal:
+### Source Data
 
-Base URL: `https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet`
+#### Initial Data Collection and Normalization
+
+The data is generated through the following simulation chain:
+
+1. **Event Generation**: Events generated using a Monte Carlo event generator
+2. **Detector Simulation**: Particle propagation through the Open Data Detector using ACTS
+3. **Digitization**: Conversion of energy deposits to realistic detector signals
+4. **Reconstruction**: Track finding and fitting using ACTS tracking algorithms
+5. **Format Conversion**: EDM4HEP → Parquet using the ColliderML data pipeline
+
+#### Who are the source data producers?
+
+The data is produced by the **ColliderML collaboration** as part of the **ATLAS ITk ML Reconstruction** project at NERSC (National Energy Research Scientific Computing Center).
+
+### Annotations
+
+#### Annotation process
+
+The dataset includes truth-level annotations automatically generated during the simulation:
+
+- **Particle-level truth**: Generator-level particle information
+- **Hit-to-particle associations**: Which particle created each detector hit
+- **Track-to-particle matching**: `majority_particle_id` links reconstructed tracks to truth particles
+
+These annotations enable supervised learning for tasks like:
+- Track efficiency (did we reconstruct this particle?)
+- Track purity (how many hits belong to the correct particle?)
+- Fake rate (how many tracks are not matched to real particles?)
+
+#### Who are the annotators?
+
+N/A (Annotations are from simulation ground truth)
+
+### Personal and Sensitive Information
+
+This dataset contains only simulated physics data. No personal or sensitive information is included.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+This dataset supports fundamental physics research and ML algorithm development. It has no direct social impact but contributes to:
+
+- Open science and reproducible research
+- Education in HEP and ML
+- Development of algorithms that may have broader applications (e.g., pattern recognition, tracking in medical imaging)
+
+### Discussion of Biases
+
+As a simulated dataset, biases may arise from:
+
+1. **Generator-level biases**: The event generator's modeling of the physics process
+2. **Detector simulation biases**: Approximations in material interactions, detector response
+3. **Reconstruction biases**: Algorithm choices in track finding and fitting
+4. **Pileup modeling**: This dataset has no pileup; real LHC data has 20-60 simultaneous collisions
+
+Users should be aware that models trained on this data may not generalize to:
+- Real detector data (requires calibration and alignment)
+- Different detector geometries
+- Different pileup conditions
+
+### Other Known Limitations
+
+- **Limited statistics**: ~28000 events (consider data augmentation for large models)
+- **Single physics process**: Only Top-quark pair (ttbar) production; does not include background processes
+- **Idealized detector**: ODD is a generic detector, not an exact replica of ATLAS/CMS
+- **Simplified simulation**: Some detector effects may be simplified
+
+## Additional Information
+
+### Dataset Curators
+
+This dataset is maintained by the ColliderML team:
+
+- Primary contact: daniel.thomas.murnane@cern.ch
+- Collaboration: ATLAS ITk ML Reconstruction working group
+- Infrastructure: NERSC (National Energy Research Scientific Computing Center)
+
+### Licensing Information
+
+This dataset is released under the **Creative Commons Attribution 4.0 International (CC BY 4.0)** license.
+
+You are free to:
+- **Share**: Copy and redistribute the material
+- **Adapt**: Remix, transform, and build upon the material
+
+Under the following terms:
+- **Attribution**: You must give appropriate credit and indicate if changes were made
+
+### Citation Information
+
+If you use this dataset in your research, please cite:
+
+```bibtex
+@dataset{colliderml_ttbar_v1_2025,
+  title={ {ColliderML: ColliderML Top-Quark Pair Production (No Pileup)} },
+  author={ {ColliderML Collaboration} },
+  year={ 2025 },
+  publisher={NERSC},
+  howpublished={\url{ https://huggingface.co/datasets/OpenDataDetector/ColliderML_ttbar_pu0 }},
+  note={Simulation performed using ACTS and the Open Data Detector}
+}
+```
+
+### Contributions
+
+This dataset was produced using:
+
+- **ACTS (A Common Tracking Software)**: https://acts.readthedocs.io/
+- **Open Data Detector**: https://acts.readthedocs.io/en/latest/examples/open_data_detector.html
+- **EDM4HEP**: https://edm4hep.web.cern.ch/
+- **ColliderML Pipeline**: https://github.com/ATLAS-ITk-ML/colliderml
 
 ## How to Use This Dataset
 
 ### Loading the Dataset
 
+The dataset is hosted on the NERSC public portal and can be streamed directly without downloading:
+
 ```python
 from datasets import load_dataset
 
-# Load a specific configuration
-ds = load_dataset(
+
+# Load particles
+particles_ds = load_dataset(
+    "OpenDataDetector/ColliderML_ttbar_pu0",
+    "particles",
+    split="train"
+)
+
+# Load tracker_hits
+tracker_hits_ds = load_dataset(
     "OpenDataDetector/ColliderML_ttbar_pu0",
-    "particles",  # Choose: particles, tracker_hits, calo_hits, tracks
+    "tracker_hits",
     split="train"
 )
 
-# Iterate over events
-for event in ds:
+# Load calo_hits
+calo_hits_ds = load_dataset(
+    "OpenDataDetector/ColliderML_ttbar_pu0",
+    "calo_hits",
+    split="train"
+)
+
+# Load tracks
+tracks_ds = load_dataset(
+    "OpenDataDetector/ColliderML_ttbar_pu0",
+    "tracks",
+    split="train"
+)
+
+```
+
+### Example: Iterating Over Events
+
+```python
+import numpy as np
+
+# Iterate over first 10 events
+for i, event in enumerate(particles_ds.take(10)):
     event_id = event['event_id']
-    print(f"Event {event_id}")
+    n_particles = len(event['particle_id'])
+
+    print(f"Event {event_id}: {n_particles} particles")
+
+    # Access list columns as numpy arrays
+    px = np.array(event['px'])
+    py = np.array(event['py'])
+    pz = np.array(event['pz'])
+
+    # Compute transverse momentum
+    pt = np.sqrt(px**2 + py**2)
+    print(f"  Mean pt: {pt.mean():.2f} GeV")
 ```
 
-### Loading Multiple Configurations
+### Example: Computing Track Features
 
 ```python
-from datasets import load_dataset
+import numpy as np
 
-# Load all configurations
+for event in tracks_ds.take(5):
+    # Get track parameters
+    qop = np.array(event['qop'])
+    theta = np.array(event['theta'])
+    phi = np.array(event['phi'])
+
+    # Compute derived quantities
+    pt = np.abs(1.0 / qop) * np.sin(theta)
+    eta = -np.log(np.tan(theta / 2.0))
+
+    print(f"Event {event['event_id']}: {len(qop)} tracks")
+    print(f"  pt range: [{pt.min():.2f}, {pt.max():.2f}] GeV")
+    print(f"  eta range: [{eta.min():.2f}, {eta.max():.2f}]")
+```
+
+### Example: Matching Tracks to Particles
+
+```python
+# Load both datasets
 particles = load_dataset("OpenDataDetector/ColliderML_ttbar_pu0", "particles", split="train")
-tracker_hits = load_dataset("OpenDataDetector/ColliderML_ttbar_pu0", "tracker_hits", split="train")
-calo_hits = load_dataset("OpenDataDetector/ColliderML_ttbar_pu0", "calo_hits", split="train")
 tracks = load_dataset("OpenDataDetector/ColliderML_ttbar_pu0", "tracks", split="train")
+
+# Process event-by-event
+for particle_event, track_event in zip(particles, tracks):
+    assert particle_event['event_id'] == track_event['event_id']
+
+    # Get particle information
+    particle_ids = np.array(particle_event['particle_id'])
+    particle_px = np.array(particle_event['px'])
+    particle_py = np.array(particle_event['py'])
+
+    # Get track information
+    track_particle_ids = np.array(track_event['majority_particle_id'])
+
+    # Compute truth pt for particles
+    particle_pt = np.sqrt(particle_px**2 + particle_py**2)
+
+    # Find matched tracks
+    for i, pid in enumerate(track_particle_ids):
+        if pid in particle_ids:
+            idx = np.where(particle_ids == pid)[0][0]
+            truth_pt = particle_pt[idx]
+            print(f"Track {i}: matched to particle {pid}, pt={truth_pt:.2f} GeV")
 ```
 
-## Citation
+### Data Location
 
-If you use this dataset in your research, please cite:
+The Parquet files are hosted at:
 
-```bibtex
-@dataset{colliderml_ttbar_v1,
-  title={ColliderML: ColliderML Top-Quark Pair Production (No Pileup)},
-  author={ColliderML Collaboration},
-  year={2025},
-  publisher={NERSC},
-  howpublished={\url{https://huggingface.co/datasets/OpenDataDetector/ColliderML_ttbar_pu0}},
-  note={Simulation performed using ACTS and the Open Data Detector}
-}
 ```
+https://portal.nersc.gov/cfs/m4958/ColliderML/hard_scatter/ttbar/v1/parquet
+
+├── truth/
+│   └── particles/
+│       └── *.parquet (28 files)
+
+├── reco/
+│   └── tracker_hits/
+│       └── *.parquet (28 files)
+
+├── reco/
+│   └── calo_hits/
+│       └── *.parquet (28 files)
+
+├── reco/
+│   └── tracks/
+│       └── *.parquet (28 files)
+
+```
+
+### File Naming Convention
+
+Files follow the pattern:
+```
+<campaign>.<dataset>.<version>.<category>.<object>.<event_range>.parquet
+```
+
+Example: `hard_scatter.ttbar.v1.truth.particles.events1000-1999.parquet`
+- Campaign: `hard_scatter`
+- Dataset: `ttbar`
+- Version: `v1`
+- Category: `truth`
+- Object: one of particles, tracker_hits, calo_hits, tracks
+- Event range: `eventsXXXX-YYYY` (inclusive)
+
+### Performance Tips
+
+1. **Streaming**: Use the dataset API for efficient memory usage
+2. **Batch processing**: Process events in chunks for better performance
+3. **Selective loading**: Only load the data types you need
+4. **Caching**: Use dataset caching for repeated experiments
+
+### Related Datasets
+
+
 
-## Contact
+### Support
 
-- **Primary contact**: daniel.thomas.murnane@cern.ch
-- **Collaboration**: ATLAS ITk ML Reconstruction working group
-- **Infrastructure**: NERSC (National Energy Research Scientific Computing Center)
+For questions, issues, or feature requests:
+- Email: daniel.thomas.murnane@cern.ch
+- GitHub: https://github.com/ATLAS-ITk-ML/colliderml/issues
 
-## Acknowledgments
+### Acknowledgments
 
 This work was supported by:
 - ATLAS ITk ML Reconstruction project
@@ -260,4 +738,4 @@ This work was supported by:
 ---
 
 **Last updated**: October 2025
-**Dataset version**: v1
+**Dataset version**: v1