RS energy deficit.


1. The RS energy calibration

Select Km22 monitor sample and measure the average ADC counts in each layer. To convert the ADC counts to the actual energy deposit in  each layer, one needs to have an estimate energy deposit in each layer for Km22 sample. From the Monte Carlo simulation, one can generate the Km22 sample with a proper beam profile. Assuming the Km22 trigger is well simulated, one can then derive the so-called RS calibration constants from

                                               rd_cal = <ADC>/E_mean(UMC)
and
                                               E_layer = ADC_layer /rd_cal

Where E_mean(UMC) is the mean energy in each RS layer. In addition to the trigger, the beam profile and the dip angle can affect this value since velocity of particle penetrating each RS layer and effective energy deposit in each RS layer may vary.  The average of ADC counts <ADC> can also be affected by accidental hits, especially in the environment of high rate. In PNN1 data analysis, this contamination can be either prevented by  switching to TD energy (if the timing of accidental hit differs from the track time) or removed by applying a so-called RS dE/dx cut (if the timing of accidental hit is very close to the track time).

2. The observed energy deficit

1) In total Kp21 energy

Year 2002 1998 UMC Expected
Peak (MeV) 102.6 105.1 105.9 108.5

2) before entering RS and after entering RS

Year E_exp-E_meas for Tg+IC (MeV) E_exp-Emeas for RS (MeV)
2002 2.33±0.05 3.98±0.03
1998 2.58±0.01  0.80±0.02
UMC 2.31±0.04 0.40±0.04
Expected 0.0 0.0

Apparently, the energy deficit in the target and IC keeps unchanged and is well simulated by Monte Calro. However, one does see a significant deficit in RS, completely accounting for the total Kp21 energy deficit.

3. The energy deficit in each RS layer

1) in piscat monitor sample (plot). The selection criteria are
      if(ptot.lt.100.or.ptot.gt.300)return
      if(nhz.lt.5)return
      if(abs(cos3d).gt.0.5)return
      if(pr_rf.lt.0.02)return
      if(ntr_d.ne.1)return
      if(ext(2))return
      if(ext(4))return
      if(abs(deltarp/sig_p).gt.3)return
      if(ipiflg.ne.0)return
      if(b4abm.gt.1.2)return
      if(tpi-tk.gt.2)return
      if(.not.l12)return
      if(.not.lhex)return
      if(itgqualt.gt.1)return


2) in Km21 monitor sample (plot).
      if(ptot.lt.100.or.ptot.gt.300)return
      if(nhz.lt.5)return
      if(abs(cos3d).gt.0.5)return
      if(ntr_d.ne.1)return
      if(b4abm.lt.1.2)return
      if(itgqualt.gt.1)return
      if(pr_rf.lt.0.02)return 
      if(tpi-tk.lt.2)return
      if(layv4.ne.18)return
      if(abs(ptot-235.5).gt.12)return    

Both piscat and km21 samples show a consistent energy deficit in the RS inner layers. But the energy deposits in the outer layers have a trend to increase. By checking the dip angle and the stopping z position, one can find a clear difference between piscat and Km21 sample. Requiring 0.3<|cos3d|<0.5, layv4=18 and |zf|>30 cm for the piscat sample, one gets a very similar plot as that shown for the km21 monitor sample.

4. Empirical correction and consistency check

Applying the correction factors given by the piscat monitor analysis to the Kp21 monitor, the peak energy becomes 105.2+/-0.1 MeV, close to what we have for the 1998 data. Using UTC measurement to give the predicted RS energy, namely

                       Ers(UTC) = sqrt((pdc-1.3)**2+139.57**2)-139.57
and
                     Deltar_Ers = Ers(UTC) - Ers

one has Deltar_Ers = 1.1 +/- 0.1 MeV (see the plots for this correction). There is still a disagreement between
the UTC prediction and the RS measurement.