2004
DOI: 10.2172/827318
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Study of Beam-Beam Effects at PEP-II

Abstract: Using a self-consistent three-dimensional simulation running on parallel supercomputers, we have modeled the beam-beam interaction at the PEP-II asymmetric £ ¥ ¤ ¦ £ § collider. To provide guidance for luminosity improvement, we scanned the tunes and currents in both rings and computed their impact on the luminosity and transverse beam sizes. We also studied the effects of colliding the beams with a small crossing angle. Where possible, the code was benchmarked against experimental measurements of luminosity a… Show more

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Cited by 33 publications
(45 citation statements)
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“…A more effective cosmic-background rejection was therefore designed, based on a bagged decision tree (BDT ) in the random forest approach [23][24][25], which combines nine input variables describing the position of the reconstructed annihilation vertices, the hit and track multiplicities, and topological variables characterizing the shape of the event and its orientation relative to the apparatus [1]. Observables that exhibit correlations with the reconstructed axial position z of the annihilation vertices or with the event time (used as a control variables) are excluded from the set of BDT input variables.…”
Section: Event Selection For Real-time Study Of Rf-induced Antihydrogmentioning
confidence: 99%
“…A more effective cosmic-background rejection was therefore designed, based on a bagged decision tree (BDT ) in the random forest approach [23][24][25], which combines nine input variables describing the position of the reconstructed annihilation vertices, the hit and track multiplicities, and topological variables characterizing the shape of the event and its orientation relative to the apparatus [1]. Observables that exhibit correlations with the reconstructed axial position z of the annihilation vertices or with the event time (used as a control variables) are excluded from the set of BDT input variables.…”
Section: Event Selection For Real-time Study Of Rf-induced Antihydrogmentioning
confidence: 99%
“…Multivariate discriminants are used to identify electrons, with a separate discriminant trained for the CC and EC regions. The discriminants are based on boosted decision trees [28][29][30][31][32] (BDTs) as implemented in the TMVA package [33] with input variables that are listed below. The BDTs are discussed in more detail in Sec.…”
Section: Identification Of Leptons Jets and 6 E Tmentioning
confidence: 99%
“…IX D). For the final multivariate analysis, we use a BDT in the one tight b-tag channel and all three two-b-tag channels, and we use a random forest decision tree (RF) [62] implemented in the STATPATTERNRECOGNITION package [28,63] for events in the zero and one loose b-tag channels.…”
Section: Multivariate Signal Discriminantsmentioning
confidence: 99%
“…We use multivariate analysis (MVA) based BumpHunter algorithm and Random forest algorithm included in StatPatternRecognition [79] to optimize pions related variables. The full m red range is used to optimize the pion related variables for both the datasets which are shown in Figure 3.11.…”
Section: Multivariate Analysismentioning
confidence: 99%