STAR HardProbes PWG

["Ma, Rongrong" <marr AT bnl.gov>]

Hello Nihar

Thanks for looking further into this. 

In Sec. 3.14, it is stated "whereas for p + p as an ansatz, the uniform distribution is considered as it has only upper bound with all possible positive values below that limit". I have a few questions about this procedure. 

- In Sec. 2.8 where the upper limits in the pp measurement are estimated, a Poisson distribution is assumed. Why do you change to assume a uniform distribution?

- By "with all possible positive values below that limit", do you not take into account values above that limit which has a 5% probability? 

In order to understand Sec. 3.14, I also read through Sec. 2.8 and have a couple additional questions. 

- In Eq. (2), you have \Lambda/n, where n is the number of trigger events. Why do you need to divide \Lambda by n given that \Lambda is already number of recoil jets per trigger?

- Here it is stated that Z = 1.96 for 95% confidence interval, which is different from 95% upper bound. Why do you convert CI to upper bound?

A related question: when calculating I_AA, the p+p reference values are interpolated based on a fit to the p+p distribution with an exponential function. How do you deal with the 95% upper limit in this interpolation procedure?

Best

Rongrong

On Jul 13, 2024, at 1:35 PM, Nihar Sahoo <nihar AT rcf.rhic.bnl.gov> wrote:

After thinking on your comments, I realized my lower limit is not correct for R=0.2 case.
And I agree with you. I recalculated and included a section 3.14 and a Fig.29 in AN to show the lower limit of IAA calculation.

With this, I updated also Fig.3 and 6 in the paper draft.
Please find the version 3 paper draft: https://drupal.star.bnl.gov/STAR/system/files/AcoplanarityPaper_v3.pdf

And analysis note version-3 with Sec 3.14 and Fig.29:
https://drupal.star.bnl.gov/STAR/system/files/AcoplanarityAanalysisNote_V3.pdf

Please have a look.