STAR Protected
Update 09.18.2018 -- Run 9 pp: Default Unfolding vs. Efficiency +- 5% (R = 0.2 Charged Jets)
Following up from yesterday:
Update 09.17.2018 -- Run 9 pp: Default Unfolding vs. Efficiency +- 5% (R = 0.2 Charged Jets)
Earlier today, I presented the systematic uncertainties for the unfolded pi0- and gamma-triggered R = 0.2 charged jet distributions.
iTPC software
1-189, at 15:00 (GMT), duration : 01:00
Phone Dial-in
+1.408.740.7256 (United States)
+1.888.240.2560 (US Toll Free)
+1.408.317.9253 (Alternate
| Time | Talk | Presenter |
|---|---|---|
| 11:00 | number of hits in sectors depending on voltage ( 00:20 ) 3 files | Maria Stefaniak |
| 11:00 | number of hits in sectors depending on voltage ( 00:20 ) 3 files | Maria Stefaniak |
Update 09.17.2018 -- Run 9 pp: Unfolding Systematics, Gamma (R = 0.2, 9 - 11 and 11 - 15 GeV)
Following up on earlier today:
Update 09.17.2018 -- Run 9 pp: Unfolding Systematics, Pi0 (R = 0.2, 9 - 11 and 11 - 15 GeV)
The plots below show the systematic uncertainties on two of the unfolded pi0 spectra, R = 0.2 charged jets for 'eTtrg = 9 - 11' GeV and 'eTtrg = 11 - 15 GeV'. The legends indicate the different
Update 09.14.2018 -- SVD Unfolding: Singular Values and Kreg (With No pTjet = 23 - 30 GeV/c Bin)
Following up on earlier today (see link below), it was suggested in a local meeting today to try unfolding with SVD without the last bin of data (pTjet = 23 - 30 GeV/c).
Update 09.14.2018 -- SVD Unfolding: Singular Values and Kreg (With No pTjet = 23 - 30 GeV/c Bin)
Following up on earlier today (see link below), it was suggested in a local meeting today to try unfolding with SVD without the last bin of data (pTjet = 23 - 30 GeV/c).
JetCorr Follow-Up [09.11.2018] -- SVD Unfolding: Singular Values and Kreg
In response to slide 13 of the presentation below, it was suggested that I take a look into the so-called "d" vector and singular values of the SVD unfolding when it comes to selecting a sol
Update 09.13.2018 -- Run 9 pp: Unfolding Errors
A question that's been dogging us for a while is how to disentangle the errors due to the unfolding from the propagated statistical errors. Unsurprisingly, RooUnfold has methods built in to keep
Update 09.11.2018 -- Pythia: Adjusting Efficiency, and Fit Test
In order to assess systematics, I implemented the ability to adjust the efficiency by a specified percentage (a relative percentage that is). The 2 plots below show that the code is wor
iTPC software
1-189 physics BNL, at 15:00 (GMT), duration : 01:00
Phone Dial-in
+1.408.740.7256 (United States)
+1.888.240.2560 (US Toll Free)
+1.408.317.9253 (Alternate
JetCorr Update -- September 11th, 2018
Slides for the JetCorr weekly meeting on September 18th, 2018.
Update 09.07.2018 -- Pythia: particle vs. detector level check (R = 0.2, 0.5)
Previously I checked how the particle and detector level recoil jet spectra compare to each other in embedding in order to get an idea of how large of corrections we should be expecting:
Update 09.06.2018 -- Run 9 embedding: particle vs. detector level check (R = 0.2, 0.5)
One of the surprising about the unfolding results for R = 0.2 and 0.5 is how small the corrections are at high pTjet. The corrections appear to be consistent with unity for pTjet > 5 GeV/c or
Update 09.05.2018 -- Run 9 pp: unfolding results, pi0 and gamma triggers (R = 0.5)
Recently, I unfolded the pi0 and gamma-rich triggered data for R = 0.5 charged jets. The shown solutions were selected in the usual manner: first, the pi0 solution is defined to be the one with
Update 09.02.2018 -- Run 9 pp: tracking efficiency, systematic error (R = 0.2 jets)
Below are the systematic errors due to the tracking efficiency for R = 0.2 charged jets (for each bin of 'eTtrg'). The tracking efficiency was implemented as discussed in these posts: