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Update 08.15.2018 -- Run 9 pp: purity as a function of zTtrk (in bins of eTtrg)
Previously, I reported on the Run9 gamma-rich purity as a function of both zTtrk and eTtrg:
Update 08.14.2018 - Run 9 embedding: varying tracking efficiency, jet matching efficiency (TEST)
Following up on yesterday's test of adjusting the tracking efficiency:
Update 08.13.2018 -- Run 9 embedding: Updated Jet Matching Efficiency and Jet Energy Resolution (R = 0.2, 0.3, 0.4, and 0.5)
The last time I calculated the JER for R = 0.4, I noticed the matching efficiency was abnormally low. In the post below, I checked if it was due to my matching algorithm. It wasn't.
Update 08.13.2018 -- Run 9 embedding: varying tracking efficiency (TEST)
As part of the systematics for the analysis, we would like to vary the tracking efficiency by 5% or so. Since I'm working with the Run 9 dijet embedding, the tracking efficiency is set by the Ge
Update 08.10.2018 -- Run 9 embedding: Jet Matching Efficiency (R = 0.2, 0.3, 0.4, and 0.5)
Previously, I took a look at the JER for a variety of R's:
Update 08.07.2018 -- Run 9 embedding: Jet Energy Resolution (R = 0.2, 0.3, 0.4, and 0.5)
The previous couple of times I showed the JER, it was for eTtrg = 9 - 15 GeV (the first 2 links below). However, when it comes time to unfold the various eTtrg bins of data, I'll probably use th
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Update 08.06.2018 -- Run 9 pp: Purity Systematics, NS Bounds
Following up on the systematic study of Run9 purity vs. zTtrk yesterday (link below), here's how the purity varies with the definition of the NS peak.
Update 08.05.2018 -- Run 9 pp: Purity as a function of eTtrg and zTtrk
The last time I calculated the purity as a function of 'eTtrg' I used tracks with 'zTtrk = (0.2, 0.3)'. Those plots can be found in the links below.
Update 08.03.2018 -- Run 9 pp: Systematic Errors, Unfolding Algorithm and Regularization (R = 0.2, 0.5)
Now that I figured out what was going on with the SVD algorithm (see link below), I went about estimating the systematic errors due to the choice of unfolding algorithm (Bayesian vs.
Update 08.02.2018 -- Run 9 pp: Follow-Up On Weird SVD Behavior
Previously, I noted some "weird" behavior when I tried unfolding my distributions with the SVD algorithm:
Update 07.31.2018 -- Run 9 pp: Systematic Errors, Prior (R = 0.5)
After unfolding the charged R = 0.5 jets using a different binning (see link below), I checked the systematic error due the choice of prior.