scholarly journals Measurement of $ {\text{B}}\overline {\text{B}} $ angular correlations based on secondary vertex reconstruction at $ \sqrt {s} = 7\,{\text{TeV}} $

2011 ◽  
Vol 2011 (3) ◽  
Author(s):  
V. Khachatryan ◽  
◽  
A. M. Sirunyan ◽  
A. Tumasyan ◽  
W. Adam ◽  
...  
Keyword(s):  
Secondary Vertex ◽  
Angular Correlations ◽  
Vertex Reconstruction

scholarly journals A track finding algorithm for the inner tracking system of MPD/NICA

2019 ◽  
Vol 204 ◽  
pp. 07006 ◽  
Author(s):  
Dmitry Zinchenko ◽  
Eduard Nikonov ◽  
Alexander Zinchenko
Keyword(s):  
Tracking System ◽  
Simulated Data ◽  
Secondary Vertex ◽  
Track Reconstruction ◽  
Interaction Point ◽  
Inner Tracking System ◽  
Pixel Sensors ◽  
First Results ◽  
Vertex Reconstruction

An inner tracking system (ITS) based on silicon pixel sensors is currently considered as one of the possible MPD upgrade steps. The main purpose of the new detector is to provide a better precision of the primary and secondary vertex reconstruction and improve track reconstruction in MPD in the region close to the interaction point. To study the ITS performance a new track finding algorithm was developed, which better takes into account the new system’s advantages. In this paper the new algorithm is described and first results obtained on simulated data are presented.

scholarly journals Secondary vertex finding in jets with neural networks

2021 ◽  
Vol 81 (6) ◽  
Author(s):  
Jonathan Shlomi ◽  
Sanmay Ganguly ◽  
Eilam Gross ◽  
Kyle Cranmer ◽  
Yaron Lipman ◽  
...  
Keyword(s):  
Performance Metrics ◽  
Graph Model ◽  
New Physics ◽  
Classification Performance ◽  
Common Vertex ◽  
Intermediate Step ◽  
Secondary Vertex ◽  
Vertex Reconstruction ◽  
Flavor Tagging ◽  
Traditional Approaches

AbstractJet classification is an important ingredient in measurements and searches for new physics at particle colliders, and secondary vertex reconstruction is a key intermediate step in building powerful jet classifiers. We use a neural network to perform vertex finding inside jets in order to improve the classification performance, with a focus on separation of bottom vs. charm flavor tagging. We implement a novel, universal set-to-graph model, which takes into account information from all tracks in a jet to determine if pairs of tracks originated from a common vertex. We explore different performance metrics and find our method to outperform traditional approaches in accurate secondary vertex reconstruction. We also find that improved vertex finding leads to a significant improvement in jet classification performance.

scholarly journals Secondary Vertex Reconstruction

2020 ◽  
pp. 159-165
Author(s):  
Rudolf Frühwirth ◽  
Are Strandlie
Keyword(s):  
Secondary Vertex ◽  
Hadronic Interactions ◽  
Vertex Reconstruction ◽  
Detector Material

AbstractThe chapter reviews methods for the search for secondary vertices. Four types of secondary vertices are discussed in detail: decays of short-lived particles, decays of long-lived particles, photon conversions, and hadronic interactions in the detector material.

Quantitative Light-Scattering Angular Correlations of Conglomerate Particles

1997 ◽  
Author(s):  
Paul Pellegrino ◽  
Gorden Videen ◽  
Ronald G. Pinnick
Keyword(s):  
Light Scattering ◽  
Angular Correlations

The evidence from angular correlations on the spin of the λ‡

1956 ◽  
Vol 3 (5) ◽  
pp. 1069-1092 ◽  
Author(s):  
G. Morpurgo
Keyword(s):  
Angular Correlations

Spectral and angular correlations in disordered wave guides

1992 ◽  
Vol 162 (6) ◽  
pp. 493-496
Author(s):  
Eugene Kogan ◽  
Moshe Kaveh
Keyword(s):  
Angular Correlations ◽  
Wave Guides

Energy-Angular Correlations and Sequential Decay in theH2(p, 2p)nandH1(d, 2p)nReactions

1965 ◽  
Vol 37 (3) ◽  
pp. 523-528 ◽  
Author(s):  
W. D. SIMPSON ◽  
J. D. BRONSON ◽  
W. R. JACKSON ◽  
G. C. PHILLIPS
Keyword(s):  
Sequential Decay ◽  
Angular Correlations
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