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This algorithm performs clustering in the ECAL and HCAL calorimeters using a 2x2 window and applies region-based energy thresholds to accept clusters. It can be used for classification of e/gamma, tau, and jet fragments.
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MB SLHC Calorimeter Trigger Algorithms
The Algorithm Calorimeter Clustering in 2x2 overlapping clusters Cluster Overlap cleanup,Classification (e/gamma,tau, jet fragment) Jet construction from fragments MET calculation from clusters Sort and select
Step 1 : clustering Virtual clustering card Window size(Calotowers) : can be 6x6,8x8,etc. Optimal to be decided Need a mapping from calotowers(iEta,iPhi) -> input point in lattice A for loop is not enough since there are cracks,endcap is different etc. Solution: XML XERCES_C XML Parser integrated by default in CMSSW Virtual “Card” Info read by XML file
Clustering “card” setup <CLUSTERING_CARD> <GEOMETRY eta0 = “1” phi0 = “1” dimension = “9” /> <ACTIVITY_CUTS ecal_tower = “1” hcal_tower = “1” ecal_cluster =”1” hcal_cluster = “1” /> <WIRE no = “0” eta = “1” phi = “1” /> <WIRE etc...> </CLUSTERING_CARD> 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80
2x2 clustering algorithm Loop on the lattice Take towers over a minumum threshold ECAL ET > Thr1 OR HCAL Et > Thr2 Slide a 2x2 window One calotower step Put a threshold on the total ECAL,HCAL Et of the cluster to accept it Notation Active CaloTower 2x2 cluster Cluster origin
Example 1:Adjacent towers Thresholds are down to emulate occupancy.. This could be a tau 6 clusters
Example 2:Isolated single towers This could look like two e/gamma 4 clusters each
Example 3:High occupancy This could be a jet (~14 clusters)
Example 4: Adjacent towers innoisy environment This could look like a tau(6 clusters) with a jet fragment/pile up deposit near it
Code status Last week:Code was written to Read Calo TPG digis Perform Clustering When CVS module is approved it will be uploaded to L1Trigger/SLHCCaloTrigger The next implementations are for cluster overlap filtering and cluster classification Not sure what is better to do first As shown from the examples above isolated regions can be (maybe) identified by cluster patterns (yellow circles..) too.