Calefice, L., Hennequin, A., Henry, L., Jashal, B. K., Mendoza, D., Oyanguren, A., et al. (2022). Effect of the high-level trigger for detecting long-lived particles at LHCb. Front. Big Data, 5, 1008737–13pp.
Abstract: Long-lived particles (LLPs) show up in many extensions of the Standard Model, but they are challenging to search for with current detectors, due to their very displaced vertices. This study evaluated the ability of the trigger algorithms used in the Large Hadron Collider beauty (LHCb) experiment to detect long-lived particles and attempted to adapt them to enhance the sensitivity of this experiment to undiscovered long-lived particles. A model with a Higgs portal to a dark sector is tested, and the sensitivity reach is discussed. In the LHCb tracking system, the farthest tracking station from the collision point is the scintillating fiber tracker, the SciFi detector. One of the challenges in the track reconstruction is to deal with the large amount of and combinatorics of hits in the LHCb detector. A dedicated algorithm has been developed to cope with the large data output. When fully implemented, this algorithm would greatly increase the available statistics for any long-lived particle search in the forward region and would additionally improve the sensitivity of analyses dealing with Standard Model particles of large lifetime, such as KS0 or Lambda (0) hadrons.
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ATLAS Collaboration(Aad, G. et al), Akiot, A., Amos, K. R., Aparisi Pozo, J. A., Bailey, A. J., Bouchhar, N., et al. (2023). Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3. J. Instrum., 18(11), P11006–38pp.
Abstract: The ATLAS experiment relies on real-time hadronic jet reconstruction and b-tagging to record fully hadronic events containing b-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm the high-level-trigger farm, even at the reduced event rate that passes the ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAS has mitigated these computational demands by introducing a fast neural-network-based b-tagger, which acts as a low-precision filter using input from hadronic jets and tracks. It runs after a hardware trigger and before the remaining high-level-trigger reconstruction. This design relies on the negligible cost of neural-network inference as compared to track reconstruction, and the cost reduction from limiting tracking to specific regions of the detector. In the case of Standard Model HH -> b (b) over barb (b) over bar, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaining high-level trigger by a factor of five at the small cost of reducing the overall signal efficiency by roughly 2%.
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Esteve, R., Toledo, J., Monrabal, F., Lorca, D., Serra, L., Mari, A., et al. (2012). The trigger system in the NEXT-DEMO detector. J. Instrum., 7, C12001–9pp.
Abstract: NEXT-DEMO is a prototype of NEXT (Neutrino Experiment with Xenon TPC), an experiment to search for neutrino-less double beta decay using a 100 kg radio-pure, 90 % enriched (136Xe isotope) high-pressure gaseous xenon TPC with electroluminescence readout. The detector is based on a PMT plane for energy measurements and a SiPM tracking plane for topological event filtering. The experiment will be located in the Canfranc Underground Laboratory in Spain. Front-end electronics, trigger and data-acquisition systems (DAQ) have been built. The DAQ is an implementation of the Scalable Readout System (RD51 collaboration) based on FPGA. Our approach for trigger is to have a distributed and reconfigurable system in the DAQ itself. Moreover, the trigger allows on-line triggering based on the detection of primary or secondary scintillation light, or a combination of both, that arrives to the PMT plane.
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