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LHCb Figures

Darreres entrades:
Preliminary performance of NN based electron ID at Hlt1 /LHCb Collaboration
The figure shows the discrimination power in HLT1 of the (black) NN-based electron ID and the (blue) ratio of the energy deposited in the ECAL with respect to the momentum of the track, which is the baseline as of spring 2024. The performance was evaluated on 2024 simulation, using electrons from a 100 \mev hypothesis Dark Photon decaying to a $e^+e^-$ pair as signal proxy and combinatorial $\pi^\pm$ and $K^\pm$ as background proxies..
LHCB-FIGURE-2024-003.- Geneva : CERN, 2024 - 3. Fulltext: PDF;

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Dataflow diagrams for LHCb user analysis in Run 3 /LHCb Collaboration
This document presents a simplified overview of user analysis at LHCb in Run 3. This overview provides a generalised analysis workflow divided into three stages: selection of candidates, fitting of models, and further required processes [...]
LHCB-FIGURE-2024-002.- Geneva : CERN, 2024 - 7. Fulltext: LHCb-FIGURE-2024-002 - ZIP; main-2 - PDF;

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Ghost charge measurement with beam-gas imaging for fills 8997 and 8999 /LHCb Collaboration
We present figures comparing ghost charge fraction measurements in the LHC during June 2023 van der Meer calibration fills 8997 and 8999 from LHCb, using beam-gas imaging, and from the LHC’s Beam Synchrotron Radiation Telescope (BSRL). The LHCb measurements are found to be compatible with the bunched method used in the BSRL analysis within the accuracy required for the calibrations [...]
LHCB-FIGURE-2024-001.- Geneva : CERN, 2024 - 9. Fulltext: LHCb-FIGURE-2024-001 - ZIP; main-1 - PDF;

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First invariant mass spectra and performance figures of the 2023 ion run /LHCb Collaboration
This document presents a collection of performance figures produced with the early processing of a small fraction of the data collected in the ion run that took place at the end of 2023 operations. Data corresponds to lead-lead (PbPb) and lead-argon (PbAr) collisions at $ \sqrt {s_{NN}}=5.36 \ TeV$ and $\sqrt {s_{NN}}=70.9 \ GeV$, respectively [...]
LHCB-FIGURE-2023-030.- Geneva : CERN, 2023 - 11. Fulltext: PDF;

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Performance of new jet techniques based on machine learning for $H \to b \bar{b}$ and $H \to c \bar{c}$ searches /LHCb Collaboration
n this document, the performance of two different machine learning techniques for jet physics at LHCb are presented: a new regression method for improving the jet energy correction, and a new jet identification method based on a Deep Neural Network for distinguish $b$, $c$ and light jets. These new algorithms will be used to perform the inclusive search for $H\to b\bar{b}$ and $H \to c \bar{c}$ decays [...]
LHCB-FIGURE-2023-029.- Geneva : CERN, 2023 - 11. Fulltext: LHCb-FIGURE-2023-029(1) - ZIP; main - PDF;

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Downstream track reconstructio in HLT1 /LHCb Collaboration
Long-lived particles (LLPs) are present in the SM and in many new physics scenarios beyond it but they are very challenging to reconstruct at LHC due to their very displaced vertices. A new algorithm, called "Downstream", has been developed at LHCb which is able to reconstruct and select LLPs in real time at the first level of the trigger (HLT1). [...]
LHCB-FIGURE-2023-028.- Geneva : CERN, 2023 - 10. Fulltext: LHCb-FIGURE-2023-028 - ZIP; main - PDF;

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Performance of RETINA reconstruction of T-track primitives /LHCb Collaboration
A real-time tracking device (RETINA) is proposed based on distributed system of FPGAs, dedicated to the reconstruction of particles trajectories in the forward Scintillating Fibre tracker detector, with the aim to preserve the full physics potential of the experiment in Run 4, and in view of Run 5 and 6 (Upgrade II) at higher instantaneous luminosity. This system would enhance the DAQ system of the experiment, and would run in real time during physics data taking, reconstructing track primitives on-the-fly at the LHC collision rate, before the complete event is built. [...]
LHCB-FIGURE-2023-027.- Geneva : CERN, 2023 - 8. Fulltext: main - PDF; LHCb-FIGURE-2023-027 - ZIP;

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HLT2 reconstruction performance for T-track selections /LHCb Collaboration
This document describes the performance of secondary vertex fitting and MVA-based track filtering for selections with T tracks in the second level of the trigger (HLT2) in LHCb, and shows how these perform for Beyond the Standard Model long-lived particle searches. The reconstruction of particle decays using only tracks in the SciFi detector have specific considerations compared to long and downstream tracks. [...]
LHCB-FIGURE-2023-026.- Geneva : CERN, 2023 - 6. Fulltext: main - PDF; LHCb-FIGURE-2023-026 - ZIP;

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Track reconstruction by the RETINA Testbed demonstrator /LHCb Collaboration
he RETINA demonstrator is a prototype device for a 30 MHz real-time track reconstruction in the LHCb VELO detector, implemented in PCIe-hosted FPGA cards interconnected by fast optical links. The system is capable of processing live LHCb data opportunistically during physics data taking, thanks to a dedicated testbed facility fed by the experiment monitoring system. [...]
LHCB-FIGURE-2023-025.- Geneva : CERN, 2023 - 5. Fulltext: main - PDF; LHCb-FIGURE-2023-025 - ZIP;

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Performance of a GNN-Based Pipeline for Track Finding in the Velo, using simulated p-p collisions samples in the Upgrade. /LHCb collaboration
Over the next decade, increases in instantaneous luminosity and detector granularity will increase the amount of data that has to be analyzed by high-energy physics experiments, whether in real time or offline, by an order of magnitude. The reconstruction of charged particles, which has always been a crucial element of offline data processing pipelines, must increasingly be deployed from the very first stages of the real time processing to enable experiments to achieve their physics goals. [...]
LHCB-FIGURE-2023-024.- Geneva : CERN, 10 - 36. Fulltext: main - PDF; LHCb-FIGURE-2023-024 - ZIP;

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