Using holistic event information in the trigger Article Swipe

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Dylan Bourgeois , S. Stahl , C. Fitzpatrick · YOU? · · 2018 · Open Access · · DOI: https://doi.org/10.48550/arxiv.1808.00711

In order to achieve the data rates proposed for the future Run 3 upgrade of the LHCb detector, new processing models must be developed to deal with the increased throughput. For this reason, we aim to investigate the feasibility of purely data-driven holistic methods, with the constraint of introducing minimal computational overhead, hence using only raw detector information. These filters should be unbiased - having a neutral effect with respect to the studied physics channels. In particular, the use of machine learning based methods seems particularly suitable, potentially providing a natural formulation for heuristic-free, unbiased filters whose objective would be to optimize between throughput and bandwidth.

Type

preprint

Language

en

Landing Page

http://arxiv.org/abs/1808.00711

PDF

https://arxiv.org/pdf/1808.00711

OA Status

green

References

35

Related Works

20

OpenAlex ID

https://openalex.org/W2886685416

Raw OpenAlex JSON