# PREX2AcceptanceTodoList

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Counting and Optics portal Optics Meetings

- Collimator Definition (Ryan)

- Verify collimator image in G4HRS reconstruction
- Check collimator image in data reconstruction
- Verify collimator image in HAMC

- Optics Data (Siyu)

- Demonstrate residuals in PREX reconstruction data base
- Pointing - precision
- Verify pointing over sieve holes

- Acceptance function (Ryan)

- Calculate, histogram polar scattering angle from data (Th_data)
- Calculate, histogram polar scattering angle from G4HRS (Th_MC) (post target, assuming beam axis and beam energy)
- Calculate, histogram polar scattering angle from G4HRS (Th_V)
- from each Th_data, Th_MC, and Th_V, calculate <Th>, <Q2>, <A>, d<A>/dR

- G4HRS compare to focal plane data (Hanjie)
- G4HRS check apertures (Cip to get this started?)
- HAMC updates and studies (Devi, Bob)
- Fix collimator in hamc. It appears to be rotated and maybe shifted.
- Collimator should agree with engineering drawing. (X,Y) shadow of accepted events versus engineering drawing.
- Prove that the collimator alone, and not other apertures, defines the acceptance in hamc. It is a check of the HRS model in hamc. (Need same for g4mc). We already assume this is proven to be true for the data. Bob will provide instructions.
- Comparisons of data to hamc to certify hamc (need same for g4mc). Compare momentum, Qsq, scattering angle, azimuthal angle, tg_th, tg_ph, focal plane variables X, Y, tantheta, tanphi. Of course, there is redundancy in these, as they are not independent. Bob will provide example macros.
- Comparisons of acceptance function for g4mc versus hamc. They should agree exactly ! Even a toy MC should get this right because the acceptance is defined by the angle bite (collimator) and the momentum bite (quartz detector).
- Sensitivity studies to evaluate the systematic error caused by imperfections in the acceptance function.

- Warm up exercise (Devi, Bob)
- Use the acceptance function to compute Qsq and scattering angle, and compare these to the data. Bob will provide example macros.
- The next step uses the asymmetry values tabulated by Horowitz.
- Look at the asymmetry integrated over the acceptance function and see how it shifts (dA/A) with changes in the MC assumptions, e.g. target thickness or detector cut. Ideally dA/A << 1%. If the shifts are small, we are done. This study will require running hamc several times with changes in the parameters. Each run will produce a new acceptance function, and then we run a macro that integrates the asymmetries. Bob will provide an example macro.