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However, the code is rough and should be used at your own risk!
Event Samples
Prefilter Definition
Prefilters are defined in more detail here.
Pass 7 Events
To replicate compare with Bill's Pass7 results, I 've gathered collected the root files that he was using. I believe that the they correspond to the following data sets in the data catalog:
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The first step is to compare against the event selection that Bill does. The results seem very comparable. One possible difference is that IM truncates it's floating point precision.
BILL PASS7 | SIG | BKG |
---|---|---|
RibbonCut_p7 | 99.66% (99.66%) | 88.38% (88.38%) |
CornerCut_p7 | 98.25% (98.59%) | 83.70% (94.70%) |
BasicTileCut_p7 | 90.19% (91.79%) | 16.04% (19.16%) |
TotalTileEnergyCut_p7 | 85.42% (94.71%) | 6.269% (39.09%) |
VetoTileCut_p7 | 84.37% (98.77%) | 4.384% (69.94%) |
TileEdgeCut_p7 | 84.29% (99.91%) | 4.312% (98.35%) |
ALEX PASS7 | SIG | BKG |
---|---|---|
RibbonCut_p7 | 99.6% (99.6%) – 121159 | 89.25% (89.25%) – 159950 |
CornerCut_p7 | 98.29% (98.68%) – 119564 | 85.81% (96.15%) – 153790 |
BasicTileCut_p7 | 92.64% (94.25%) – 112691 | 13.95% (16.26%) – 25009 |
TotalTileEnergyCut_p7 | 86.39% (93.25%) – 105089 | 7.007% (50.21%) – 12558 |
VetoTileCut_p7 | 84.8% (98.16%) – 103159 | 4.951% (70.66%) – 8873 |
TileEdgeCut_p7 | 84.74% (99.93%) – 103084 | 4.884% (98.65%) – 8753 |
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and I will use these final Pass 7 cuts in subsequent comparisons with Pass 8 data.
Selection Efficiency as a Function of Energy
Name | Individual Selection | Selection with Respect to Complement |
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RibbonVeto |
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CornerVeto |
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BasicTileVeto |
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TotalTileEnergyVeto |
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TkrVTileVeto |
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TileEdgeVeto |
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Sequential Cuts (Sig) | Sequential Cuts (Bkg) |
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Pass 8 Events
Data Set
The Pass8 event samples I use come from the standard Pass8 MC data sets with overlays corresponding to GR-v19r4p1gr13.
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Correcting the gamma efficiency of TotalTileEnergy Cut and appending the Cal1ConeCut_p8 at the end. It can be seen that without the Cal1ConeCut, nearly twice as much background sneaks through. The power of the Cal1ConeCut is quite impressive.
CUT PASS7 ACD2 | SIG | BKG |
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RibbonCut2_p7 | 99.01% (99.01%) – 60482 | 89.9% (89.9%) – 50790 |
CornerCut2_p7 | 97.99% (98.96%) – 59856 | 86.69% (96.43%) – 48978 |
BasicTileCut2_p7 | 92.92% (94.83%) – 56760 | 22.73% (26.22%) – 12843 |
TotalTileEnergyCut2_p7 | 86.05% (92.61%) – 52566 | 13.42% (59.03%) – 7581 |
VetoTileCut2_p7 | 82.59% (95.98%) – 50452 | 9.709% (72.35%) – 5485 |
TileEdgeCut2_p7 | 82.54% (99.94%) – 50421 | 9.693% (99.84%) – 5476 |
Cal1ConeCut_p8 | 80.34% (97.33%) – 49073 | 4.461% (46.02%) – 2520 |
PASS8 | SIG | BKG | |
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RibbonVeto_p8 | 99.5% (99.5%) | VetoHit1Cut_p8 | 95.12% 89.9% (89.9%) |
CornerVeto_p8 | 98.6% (99.1%) | 86.9% (96.6%) | |
Tkr1SigmaVeto_p8 | 93.3% (94.7%) | 22.5% (25.9%) | |
TkrSigmaHitVeto_p8 | 88.7% (95%) | 16.6% (73.7%) | |
Tkr1ConeVeto_p8 | 83.7% (94.3%) | 10.5% (63.6%) | |
Cal1ConeVeto_p8 | 81.7% (97.6%) | 4.96% (47.1%) |
Wiki Markup |
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{htmlcomment:hidden} || OLD PASS8 || SIG || BKG || | VetoHit1Cut_p8 | 95.12% (95.12%) |
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-- 58105 | 26.2% (26.2%) |
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-- 14802 | | TotalTileEnergyCut_p8 |
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| 86.53% (90.96%) |
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-- 52855 | 12.83% (48.99%) |
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-- 7251 | | VetoGap1Cut_p8 |
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| 86.36% (99.8%) |
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-- 52750 | 12.65% (98.52%) |
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-- 7144 | | VetoHitCut_p8 |
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| 85.53% (99.05%) |
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-- 52247 | 12.06% (95.34%) |
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-- 6811 | | Cal1ConeCut_p8 |
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| 82.85% (96.86%) |
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-- 50609 | 5.245% (43.5%) -- 2963 | {htmlcomment} |
The power of the Cal1ConeCut comes from the fact that the majority of the residual background is sneaking through the bottom of the TKR. The direction of these events is poorly reconstructed since, especially at high energy, the longest straightest track will often come from back-splash. On the other hand, the CAL axis will point along the direction of the incident particle causing the ACD to query the proper tiles.
P7 Residual BKG | P8 Residual BKG (P7 CUTS) | P8 Residual BKG w/CAL (P7 CUTS) | P8 CAL CUT |
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Selection Efficiency as a Function of Energy
Name | Individual Selection | Selection with Respect to Complement |
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RibbonVeto |
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CornerVeto |
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Tkr1SigmaVeto |
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TkrSigmaHitVeto |
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Tkr1ConeVeto |
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Cal1ConeVeto |
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Sequential Selections (Sig) | Sequential Selections (Bkg) |
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| – 2963 |