Track finding at Belle II

Bertacchi, V.; Bilka, T.; Braun, N.; Casarosa, G.; Corona, L.; Cunliffe, S.; Dattola, F.; Marino, G. de; Nuccio, M. De; Pietro, G. De; Dong, T. V.; Dujany, G.; Ecker, P.; Eliachevitch, M.; Fillinger, T.; Frost, O.; Frühwirth, R.; Gebauer, U.; Glazov, Sasha; Gosling, Nicolas; Guo, A. Q.; Hauth, T.; Heck, M.; Kaleta, M.; Kandra, J.; Kleinwort, C.; Kuhr, T.; Kurz, S.; Kvasnička, P.; Lettenbichler, Jakob; Lueck, T.; Martini, A.; Metzner, F.; Neverov, D.; Niebuhr, C.; Paoloni, E.; Patra, S.; Piilonen, L. E.; Praz, C.; Prim, M. T.; Pulvermacher, C.; Racs, Sebastian; Rad, N.; Rados, P.; Ritter, M.; Rizzo, G.; Rostomyan, A.; Scavino, B.; Schlüter, T.; Schwenker, B.; Spataro, S.; Spruck, B.; Svidras, H.; Tenchini, F.; Uematsu, Y.; Webb, J.; Wessel, C.; Zani, L.

doi:10.1016/j.cpc.2020.107610

Cited by 40 publications

(18 citation statements)

References 24 publications

(31 reference statements)

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“…In identifying tracks, we demand charged particles to be within the geometric acceptance and to have transverse momentum p T > 100 MeV; we also assign a detection efficiency per track of 0.9. While track-finding efficiencies are strongly dependent on p T , impact parameter, and decay position, the 0.9 value we use is a simple way of incorporating tracking inefficiencies that gives, on average, results consistent with expectations from the Belle II detector [93]. Same-sign tracks with angular separation θ < 0.05 are merged and counted as one, although we find this has little effect on our results.…”

Section: Simulation and Analysismentioning

confidence: 51%

Multi-track displaced vertices at B-factories

Acevedo

Blackburn

Blinov

et al. 2021

J. High Energ. Phys.

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We propose a program at B-factories of inclusive, multi-track displaced vertex searches, which are expected to be low background and give excellent sensitivity to non-minimal hidden sectors. Multi-particle hidden sectors often include long-lived particles (LLPs) which result from approximate symmetries, and we classify the possible decays of GeV-scale LLPs in an effective field theory framework. Considering several LLP production modes, including dark photons and dark Higgs bosons, we study the sensitivity of LLP searches with different number of displaced vertices per event and track requirements per displaced vertex, showing that inclusive searches can have sensitivity to a large range of hidden sector models that are otherwise unconstrained by current or planned searches.

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Section: Simulation and Analysismentioning

confidence: 51%

Multi-track displaced vertices at B-factories

Acevedo

Blackburn

Blinov

et al. 2021

J. High Energ. Phys.

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“…While this section has focused on the LHC, modern machine learning tools are also being applied at Belle II (e.g. for tracking [188]), and older machine learning algorithms have a long history at previous colliders and will be essential for the physics program of future colliders.…”

Section: A Energy Frontiermentioning

confidence: 99%

Machine Learning in the Search for New Fundamental Physics

Karagiorgi¹,

Kasieczka²,

Kravitz³

et al. 2021

Preprint

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Machine learning plays a crucial role in enhancing and accelerating the search for new fundamental physics. We review the state of machine learning methods and applications for new physics searches in the context of terrestrial high energy physics experiments, including the Large Hadron Collider, rare event searches, and neutrino experiments. While machine learning has a long history in these fields, the deep learning revolution (early 2010s) has yielded a qualitative shift in terms of the scope and ambition of research. These modern machine learning developments are the focus of the present review.

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“…The HLT runs the Belle II software framework basf2 [3,4] to perform a full reconstruction of the recorded events. Utilizing the offline reconstruction software, additional systematics which could be introduced by a simplified reconstruction are avoided.…”

Section: Hlt Processingmentioning

confidence: 99%

Design and Performance of the Belle II High Level Trigger

Prim¹,

Braun²,

Guan³

et al. 2021

Proceedings of 40th International Conference on High Energy Physics — PoS(ICHEP2020)

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The data acquisition system of the Belle II detector is designed for a sustained first-level trigger rate of up to 30 kHz at the design luminosity of the SuperKEKB collider. The raw data read out from the subdetector frontends is delivered in realtime into an online High Level Trigger (HLT) farm, consisting of up to 20 computing nodes housing around 5000 processing cores, where it is reconstructed by the full Belle II reconstruction software in realtime. Based on this online reconstruction, events are filtered before being stored to disk for later offline processing and analysis. In this manuscript we will present the newly developed data flow throughout the HLT system utilizing the open-source library ZeroMQ, which was first used in the beam run period in fall 2019. Further, we show the performance of the HLT reconstruction and how the current setup scales with the anticipated future data rates when SuperKEKB increases its luminosity to the design value.

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Track finding at Belle II

Cited by 40 publications

References 24 publications

Multi-track displaced vertices at B-factories

Multi-track displaced vertices at B-factories

Machine Learning in the Search for New Fundamental Physics

Design and Performance of the Belle II High Level Trigger

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