100MeV learning.

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Presentation transcript:

100MeV learning

MC To learn track with different pt from ( 50~120MeV) Now learn pt=100MeV for example Simulate fixpt single track pt =100MeV Pion- Disable decay Disable delta e

Different event evtStyle: record different event evtStyle == 0 : other hits in MdcDigi hit collection but not in Mc imformation evtStyle == 999 : multi-curved event evtStyle ==1 : one curved event evtStyle ==-999 maxlayer <12 ( |cos| too large) -999 1 999 total 3 232 3629 1115 4979

Define hits style by MC information Hits on the first half of track Hits on the second half of track Hits on the second curved track of a multi-turn event Multi-Curved event: 1115/4779=23% in fixpt=100MeV pion- number of multi-curved event vs costa Proportion of multi-curved event vs costa Inside |cos|<0.4 when|cos| get smaller ,more multi-curved tracks

Layer max : the outer layer track can hit In all one-curved events , Layer 35 : stereo hit Layer 36 : axial hit Tend to collect more axial hits

Number of first half-circle Hit vs |cos| nHit In all one-curved events , Number of first half-circle Hit vs |cos| Hit number vs |cos| Below 20 : most are from layer ( 8~12) 0.7>|cos|>0.4: track hit layer 36 ,more axial hit

Peak learning Peak + PeakWidth : represent track on Hough space take evtStyle == 1 ( one-curve event ) into consideration Define the first half circle hits as useful hits Test the peak if it matches the track in MC information Cut Hough space into (400*400) bins (bin width very small ) Rho(houghmap) – rhoTruth Rho(houghmap) – rhoTruth 3606/3919 = 99.5% Other event : large pt (seem not 100MeV add noise No noise Get the right peak from hough map 3606/3919 = 98.6%

Track learning Peak + PeakWidth : represent track on Hough space Track hit selection : first half circle hits selected by Hough Peak width : from (0bins,1bins)..(1bins,1bins) to (8bins,8bins) Select eff: Not end ….. (0,0)->(7,8)