- pagebs's home page
- Posts
- 2017
- June (1)
- 2016
- 2015
- 2014
- December (2)
- November (1)
- October (2)
- September (4)
- August (1)
- July (2)
- June (2)
- May (3)
- April (2)
- March (2)
- February (2)
- January (1)
- 2013
- November (1)
- October (3)
- September (2)
- August (3)
- July (4)
- June (4)
- May (2)
- April (2)
- March (2)
- February (4)
- January (2)
- 2012
- December (2)
- November (3)
- October (2)
- September (1)
- August (3)
- July (3)
- June (6)
- May (2)
- April (3)
- March (3)
- February (2)
- January (2)
- 2011
- December (2)
- November (1)
- October (7)
- September (3)
- August (2)
- July (5)
- June (2)
- May (2)
- April (4)
- March (2)
- January (1)
- 2010
- December (2)
- October (4)
- September (1)
- August (4)
- July (1)
- June (2)
- May (2)
- March (4)
- February (2)
- January (2)
- 2009
- December (1)
- November (2)
- October (1)
- September (2)
- August (1)
- July (2)
- June (1)
- May (2)
- April (2)
- March (1)
- February (1)
- January (6)
- 2008
- My blog
- Post new blog entry
- All blogs
Run 9 200GeV Dijet Cross Section Time Variation Investigation
Here I look into the dependance of the dijet cross section on the time into the run ...
Figure 1: In this figure, the dijet yield is broken into 10 day periods and normalized by the integrated luminosity for that period. The upper left plot shows the spectra and the upper right plot shows the ratio (10 Day Period / Full Run) for each 10 day period. The bottom panels show the same things except the runs have been grouped differently.
Figure 2: This figure shows the ratio (10 day period / Full run) but now the samples are normalized in different ways. The upper left panel is normalized using the integrated luminosity (same as in figure 1), the upper right panel is normalized using the number of BBCMB-Cat2 triggers as reported in the run log, the bottom left panel is normalized using the number of ZDCMB triggers as reported in the run log, and the bottom right panel is normalized using the number of VPDMB triggers as reported in the run log.
Figure 3: This figure shows the averages of several quantities as a function of run index for all events/jets which are used in the dijet cross section.
Figure 4: This figure shows the ratios of various scalar quantities as a function of run. Note: due to the way my code is set up, it was much easier to make these plots with index running from 1-773.
L2/BBC | L2/ZDC | L2/VPD | BBC/ZDC | BBC/VPD | ZDC/VPD | Dijets/BBC | |
12 | 14.11 | 22.107 | 0.0221 | 1.567 | 0.00156 | 0.000998 | 1.1899 |
13 | 13.798 | 22.0459 | 0.0219 | 1.598 | 0.00159 | 0.000993 | 1.2247 |
14 | 12.748 | 21.341 | 0.0212 | 1.674 | 0.00166 | 0.000994 | 1.1252 |
15 | 12.360 | 21.0260 | 0.0214 | 1.701 | 0.00173 | 0.00102 | 1.0339 |
16 | 11.649 | 19.669 | 0.0200 | 1.688 | 0.00171 | 0.00102 | 1.0028 |
17 | 11.529 | 18.766 | 0.0206 | 1.628 | 0.00178 | 0.00110 | 0.9673 |
18 | 11.686 | 19.407 | 0.0207 | 1.661 | 0.00177 | 0.00106 | 0.9645 |
RFF Fit: p0 Val; p0 Err; Chi2/NDF | FF Before Rot: p0 Val; p0 Err; Chi2/NDF | FF After Rot: p0 Val; p0 Err; Chi2/NDF | |
Dijet Mass | 24.2808; 0.0049; 741/363 | 24.4848; 0.0047; 563/332 | 24.4533; 0.0099; 118/73 |
Jet Pt | 11.6379; 0.0020; 1053/363 | 11.7361; 0.0019; 782/332 | 11.7207; 0.0041; 163/73 |
# Tracks | 4.1487; 0.0010; 682/363 | 4.1346; 0.0010; 725/332 | 4.1057; 0.0021; 100/73 |
# Towers | 9.1582; 0.0017; 802/363 | 9.1550; 0.0017; 599/332 | 9.1663; 0.0035; 133/73 |
Sum Track Pt | 6.3893; 0.0019; 987/363 | 6.4271; 0.0018; 852/332 | 6.3770; 0.0039; 274/73 |
Sum Tower Pt | 5.4073; 0.0015; 467/363 | 5.4666; 0.0015; 431/332 | 5.5003; 0.0031; 90/73 |
Track Pt | 1.5399; 0.0004; 2306/363 | 1.5544; 0.0004; 1206/332 | 1.5533; 0.0008; 333/73 |
Tower E | 0.6484; 0.0002; 737/363 | 0.6566; 0.0002; 519/332 | 0.6601; 0.0003; 114/73 |
Tower ADC | 79.7662; 0.0102; 1105/363 | 79.5555; 0.0100; 594/332 | 79.6377; 0.0208; 116/73 |
Figure 10: This figure shows the average number of tracks in the jets of a dijet for the data (Top) and the embedding sample (Bottom) with the same three fits used in figure 7. Note that the spread in points is much greater in simulation than in the data. Also the errors in the simulation are much smaller (I don't think I took into account the weights properly in the error). Similar plots for all other quantities shown in figure 7 can be found in this PDF.
Although the spread in points in the simulation is large, there do not seem to be any systematic shifts in the averages over the course of the run as there appears to be in the data.
In a message to list, Jamie D. suggested that I look at dead areas in the TPC to see if they correlate with shifts in the various detector quantities. These dead areas should appear in certain sectors only as specific RDO boards die, so I have broken up the average number of tracks and average track pt plots by sector.
According to Gene's blog, there were two sectors which had RDO boards die during the period of my analysis: sector 2 and sector 18 (there were also a couple of boards which died on day 180). The board in sector 2 died durring run 10162027 which corresponds roughly to index 721. Looking at the average number of tracks plots, there is no obvious feature in sector 2 at index 721, but there is a broad dip between index 500 and 700 which I don't have an explanation for. Sector 18 had two boards die, one on run 10158014 (index 650) and one on run 10174044 (index 912). There is a definite decrease around index 912 and a decrease a short while after index 650.
Figure 11: This figure shows the systematic associated with the time variation of the cross section. The size of the systematic was taken as the magnitude of the difference between the RFF and FF cross sections as calculated and shown in figure 9. The first panel shows the sys/cross sec ratio, the middle panel shows the old cross sec ratio, and the bottom panel shows the cross sec ratio with the new systematic.
- pagebs's blog
- Login or register to post comments