| Issue |
EPJ Web Conf.
Volume 337, 2025
27th International Conference on Computing in High Energy and Nuclear Physics (CHEP 2024)
|
|
|---|---|---|
| Article Number | 01312 | |
| Number of page(s) | 8 | |
| DOI | https://doi.org/10.1051/epjconf/202533701312 | |
| Published online | 07 October 2025 | |
https://doi.org/10.1051/epjconf/202533701312
Real-time monitoring of LHCb interaction region with a fast trackless methodology
1 Scuola Normale Superiore, Pisa, Italy
2 Università di Pisa, Italy
3 INFN Sezione di Pisa, Italy
4 École Polytechnique Fédérale, Lausanne, Switzerland
* e-mail: giulio.cordova@cern.ch
Published online: 7 October 2025
The increasing computing power and bandwidth of FPGAs opens new possibilities in the field of real-time processing of high-energy physics data. The LHCb experiment has implemented a cluster-finder FPGA architecture aimed at reconstructing hits in its innermost silicon-pixel detector onthe-fly during readout. In addition to accelerating the event reconstruction procedure by providing it with higher-level primitives, this system enables further opportunities. LHCb triggerless readout architecture makes these reconstructed hit positions available for every collision, amounting to a flow of 1011 hits per second, that can be used for further analysis. In this work, we have implemented a set of programmable counters, counting the hit rate at many locations in the detector volume simultaneously. We use these data to continuously track the motion of the beams overlap region and the relative position of the detector elements, with precisions of µm and time granularity of (ms). We show that this can be achieved by simple linear combination of data, that can be executed in real time with minimal computational effort. This novel approach allows a fast and precise determination of the beamline position without the need to reconstruct more complex quantities like tracks and vertices. We report results obtained with pp collision data collected in 2024 at LHCb.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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