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<p>A new algorithm has been developed at LHCb which is able to reconstruct and select very displaced vertices in real time at the first level of the trigger (HLT1). It makes use of the Upstream Tracker (UT) and the Scintillator Fiber detector (SciFi) of LHCb and it is executed on GPUs inside the Allen framework. In addition to an optimized strategy, it utilizes a Neural Network (NN) implementation to increase the track efficiency and reduce the ghost rates, with very high throughput and limited time budget. Besides serving to reconstruct <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41781_2025_141_Article_IEq1.gif" Format="GIF" Height="21" Rendition="HTML" Resolution="72" Type="Linedraw" Width="21" /> </InlineMediaObject> <EquationSource Format="TEX">\({\text{K}} ^0_{\text{S}}\)</EquationSource> <EquationSource Format="MATHML"><math> <msubsup> <mrow> <mtext>K</mtext> </mrow> <mtext>S</mtext> <mn>0</mn> </msubsup> </math></EquationSource> </InlineEquation> and <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41781_2025_141_Article_IEq2.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="16" /> </InlineMediaObject> <EquationSource Format="TEX">\(\varLambda\)</EquationSource> <EquationSource Format="MATHML"><math> <mi>Λ</mi> </math></EquationSource> </InlineEquation> particles from the Standard Model, the <Emphasis FontCategory="NonProportional">Downstream</Emphasis> algorithm and the associated two-track vertexing could largely increase the LHCb physics potential for detecting long-lived particles during the Run 3.</p>

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A Downstream and Vertexing Algorithm for Long Lived Particles (LLP) Selection at the First High Level Trigger (HLT1) of LHCb

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月1日

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  • V. Kholoimov,
  • B. Kishor Jashal,
  • A. Oyanguren,
  • V. Svintozelskyi,
  • J. Zhuo

摘要

A new algorithm has been developed at LHCb which is able to reconstruct and select very displaced vertices in real time at the first level of the trigger (HLT1). It makes use of the Upstream Tracker (UT) and the Scintillator Fiber detector (SciFi) of LHCb and it is executed on GPUs inside the Allen framework. In addition to an optimized strategy, it utilizes a Neural Network (NN) implementation to increase the track efficiency and reduce the ghost rates, with very high throughput and limited time budget. Besides serving to reconstruct \({\text{K}} ^0_{\text{S}}\) K S 0 and \(\varLambda\) Λ particles from the Standard Model, the Downstream algorithm and the associated two-track vertexing could largely increase the LHCb physics potential for detecting long-lived particles during the Run 3.