Jixie’s Analysis Status Jixie Zhang Sep. 22th, 2010

CLAS trigger efficiency, From Slava Trigger efficiency is the fraction that the trigger particle (electrons) is detected. It is obtained by scaling the simulation data to the real data, then calculating the ratio of real events counts in each p-  grid to the simulation events counts in the same grid.

Trigger efficiency, 5G, Scaled by Lumi  trig = (N real /Lumi real )/(N sim /Lumi sim ) = N real /N sim * Scaled

Trigger efficiency, 5G, Scaled by W  trig = (N real /Lumi real )/(N sim /Lumi sim ) = N real /N sim * Scaled

Trigger efficiency, 5G, Scaled by 100% Efficiency in Area

Trigger efficiency, 4G, Scaled by 100% Efficiency in Area

Trigger efficiency, 2G, Scaled by 100% Efficiency in Area

Cross Section Calculations 1.Select exclusive events 2.Apply corrections: acceptance, trigger,  , CLAS proton and RTPC proton efficiency, radiative and background correction.

Cross Section Fitting A0 A1 Cos  *A2 Cos2  * = ++

Cross Section: BoNuS Vs MAID and SAID 4 GeV, W = Cos    MAID 07SAID 08 D(e,e   p CLAS )pD(e,e   p RTPC )p

Cross Section: BoNuS Vs MAID and SAID 2 GeV, W = Cos    0.875

BoNuS Vs Models, 2 GeV, W = 1.23 MAID 07SAID 08 D(e,e   p CLAS )pD(e,e   p RTPC )p

BoNuS Vs Models, 4 GeV, W = 1.23

BoNuS Vs Models, 5 GeV, W = 1.23

Back up Slices

D(e,e   p)p Acceptance Correction Binning information: W: 150 MeV each bin, [1.15,3.10); Q 2 : 6 bins, {0.1309, , , , , , }; cos  *: 8 bins, 0.25 each bin, [-1.0,1.0);  *: 15 bins, 24 degrees each bin, [0.0,360.0). Acceptance is the ratio of the number of events detected in a given bin to the number of generated events in the same bin. Need to generate tables for D(e,e   p RTPC )p and D(e,e   p CLAS )p reaction separately. Applied event by event Need to have acceptance cut to ensure the reliabilities For CLAS channel: and less than 10% uncertainty (> 100 detected events) For RTPC channel: and less than 15% uncertainty (> 40 detected events)

Acceptance Correction, E=5.3 GeV

Background Subtraction f 1, f 2, f 3 and f 4 are the fitted background fraction functions for real data. f 1 sim, f 2 sim, f 3 sim and f 4 sim are the fitted background fraction functions for simulation data. Final background correction factor: where is the coverage of 2  in a gaussian distribution. Simulation average

Background of Simulation Data

Background of Real Data