iTPC offline QA

 

EPD 2019 Correlation Files

Career opportunities in HEP/science

 

Speaker : Lijuan Ruan


Talk time : 13:35, Duration : 00:30

RHIC20yearsslides

 

HF minutes 2019/02/21

FST weekly meeting

 

FST weekly meeting

 

SDU paper review

 Charge-dependent pair correlations relative to a third particle in p+Au and d+Au collisions at RHIC

FMS+RP Analysis Miscellaneous Clean-Up Tasks

GridLeak Wall currents (first look)

(click on images on this page for higher resolution)

Embedding status and priority

Speaker : Xianglei Zhu


Talk time : 09:30, Duration : 00:20

 

PWGC Meeting

2019-02-22 09:30
2019-02-22 11:30
America/New York
Friday, 22 February 2019
https://bluejeans.com/883580682/9067, at 14:30 (GMT), duration : 02:00
TimeTalkPresenter
09:30Embedding status and priority ( 00:20 ) 1 fileXianglei Zhu

Presentation to bulkcorr - 20 Feb 2019 - HBT in FXT 4.5 GeV

presentation to bulkcorr on HBT in FXT for bulkcorr-only paper.

Slides for David Stewart

Reference


Talk time : 17:00, Duration : 00:13

Not sure how to just attach slides for the meeting, so I have put these in under a "talk". I

Run15 pp200 Transverse -- Jet Meeting 2019-02-20

 

Update 02.19.2019 -- Run 9 pp: track efficiency vs eTtrg

The next episode in my investigation of the run 9 tracking efficiency: how does it vary with trigger eT?  The previous installments can be found here:

Update 02.05.2019 -- Run 9 pp: (detector-level) Pythia8 rebin and ratio to Embedding

[Recorded on 02.19.2019] This is a follow-up from the previous post.

Update 02.04.2019 -- Run 9 pp: comparing tracks, Pythia8 vs. Embedding

[Recorded on 02.19.2019] This post continues the line of inquiry laid out in these posts:

Update 01.21.2019 -- Run 9 pp: adjusting response for Pythia8

[Recorded on 02.19.2019] The post below shows that our approximation of the run 9 response is wrong.

Update 01.07.2019 -- Run 9 pp: (detector-level) Pythia vs. Embedding Vs. Data Jet Spectra

[Recorded on 02.19.2019] Before, we had noticed that the largest uncertainty in our unfolding was whether we were using a response trained using Pythia6 (via STAR's embedding process)