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CERN Accelerating science

LHCb Figures

新增:
2022-06-24
12:08
Van der Meer scans in Run 2 /LHCb Collaboration
We show the preliminary results from the first Van der Meer scan of Run 2..
LHCB-FIGURE-2022-013.- Geneva : CERN, 2022 - m. pages.

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2022-06-24
12:06
Preliminary analysis of Run 3 Van der Meer scans with PLUME /LHCb Collaboration
We present preliminary results from the first Van der Meer scan for the absolute luminosity calibration performed at $\sqrt{s}=0.9$ TeV using the PLUME detector. We use the data from the LHCb online luminosity monitor and the beam parameters provided by LHC..
LHCB-FIGURE-2022-012.- Geneva : CERN, 2022 - m. pages.

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2022-06-15
16:56
Long-lived particle reconstruction and selection downstream of the LHCb magnet /LHCb collaboration
The LHCb detector reconstructs charged tracks in different categories, depending on the subdetectors used for the reconstruction. These track categories are used differently in the LHCb trigger and in analysis. [...]
LHCB-FIGURE-2022-011.- Geneva : CERN, 20 - 4. Fulltext: lhcb-figure-2022-00X - ZIP; lhcb_figure_2022_00X (8) - PDF;

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2022-06-02
08:57
Standalone track reconstruction and matching algorithms for the GPU-based High Level Trigger at LHCb /LHCb collaboration
We present the performance of an alternative track reconstruction for LHCb’s first level High Level Trigger (Allen). A version of this reconstruction starts with two monolithic tracking algorithms, the VELO-pixel tracking and the HybridSeeding on Scintillating-Fiber tracker, which reconstructs track segments in standalone subdetectors. [...]
LHCB-FIGURE-2022-010.- Geneva : CERN, 24 - 15. Fulltext: lhcb-figure-2022-010 - ZIP; LHCb-FIGURE-2022-010 - PDF;

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2022-05-31
14:43
Long-lived particle reconstruction and selection downstream of the LHCb magnet /LHCb collaboration
A series of figures demonstrating the feasibility and performance of long-lived particle reconstruction and selection downstream of the LHCb magnet is shown, using Run 2 simulation and data..
LHCB-FIGURE-2022-009.- Geneva : CERN, 24 - 7. Fulltext: PDF;

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2022-05-31
14:34
Very preliminary $p$/$\pi$ separation for $T$ tracks /LHCb collaboration
Very preliminary $p$/$π$ separation performance from RICH 2 in Run 3 for $T$ tracks is illustrated..
LHCB-FIGURE-2022-008.- Geneva : CERN, 2022 - 3. Fulltext: PDF;

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2022-05-30
16:27
HLT1 forward tracking performance /LHCb collaboration
We present the forward tracking performances at LHCb’s first High Level Trigger (HLT1). The document shows comparison plots of the HLT1 Forward algorithm using Velo or VeloUT input tracks to perform the full long track reconstruction [...]
LHCB-FIGURE-2022-007.- Geneva : CERN, 31 - 4. Fulltext: LHCb_FIGURE_2022_007_zip - PDF.ZIP; LHCb_FIGURE_2022_007 - PDF;

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2022-05-30
14:11
VELO and SciFi alignment accuracy studies for Run 3 /LHCb collaboration
The expected alignment accuracy is studied for the Run 3 VELO and SciFi detectors using simulated samples with randomly generated input misalignments..
LHCB-FIGURE-2022-006.- Geneva : CERN, 2022 - 4. Fulltext: LHCb-FIGURE-2022-006 - ZIP; LHCb_FIGURE_2022_006 - PDF;

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2022-05-23
15:06
HLT2 reconstruction throughput and Forward Tracking performance for Run 3 of LHCb /LHCb collaboration
The track reconstruction performance of the Forward Tracking as used in HLT2 of Run 3 is shown including track reconstruction efficiencies, fake track fraction and momentum resolution. Event throughput and timing fractions of algorithms run in the HLT2 reconstruction sequence are shown, including the fraction taken by the Forward Tracking. [...]
LHCB-FIGURE-2022-005.- Geneva : CERN, 2022-05-25 Fulltext: LHCB_FIGURE_2022_005zip - ZIP; LHCB_FIGURE_2022_005 - PDF;

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2022-04-14
16:57
Machine-Learnt parametrizations for the Ultra-Fast Simulation of the LHCb detector /LHCb collaboration
High-quality parametrizations of the response of the LHCb experiment to traversing charged particles are being developed using Machine Learning algorithms including Gradient Boosting Decision Trees and Deep Neural Networks trained in adversarial configuration. The trained models are intended to replace parts of the detector simulation to reduce the CPU hours requested to produce large simulated samples. [...]
LHCB-FIGURE-2022-004.- Geneva : CERN, 2022 Fulltext: LHCB-FIGURE-2022-004 - PDF; figs - ZIP;

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