<p>In future high-energy physics experiments, the electromagnetic calorimeter (ECAL) should operate with an exceptionally high luminosity. An ECAL featuring a layered readout in the longitudinal direction and precise time-stamped information offers a multidimensional view, thereby enriching our understanding of the showering process of electromagnetic particles in high-luminosity environments. This was used as the baseline design for several new experiments, including the planned upgrades of the current running experiments. Reconstructing and matching multidimensional information across different layers poses new challenges for the effective utilization of layered data. This study introduced a novel layered reconstruction framework for ECAL with a layered readout information structure and developed a corresponding layered clustering algorithm. This expands the concept of clusters from a plane to multiple layers. Additionally, this study presents the corresponding layered cluster correction methods, investigates the transverse shower profile utilized for overlapping cluster splitting, and develops a layered merged <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41365_2025_1740_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">$\pi ^0$</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>π</mi> <mn>0</mn> </msup> </math></EquationSource> </InlineEquation> reconstruction algorithm based on this framework. By incorporating energy and time information into 3-dimensions, this framework provides a suitable software platform for preliminary research on longitudinally segmented ECAL and new perspectives in physics analyses. Furthermore, using the PicoCal in LHCb Upgrade II as a concrete example, the performance of the framework was preliminarily evaluated using single photons and <InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41365_2025_1740_Article_IEq2.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">$\pi ^{0}$</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>π</mi> <mn>0</mn> </msup> </math></EquationSource> </InlineEquation> particles from the neutral <InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41365_2025_1740_Article_IEq3.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="21" /> </InlineMediaObject> <EquationSource Format="TEX">$B^0$</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>B</mi> <mn>0</mn> </msup> </math></EquationSource> </InlineEquation> meson decay <InlineEquation ID="IEq4"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41365_2025_1740_Article_IEq4.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="104" /> </InlineMediaObject> <EquationSource Format="TEX">$B^0\rightarrow \pi ^+\pi ^-\pi ^0$</EquationSource> <EquationSource Format="MATHML"><math> <mrow> <msup> <mi>B</mi> <mn>0</mn> </msup> <mo stretchy="false">→</mo> <msup> <mi>π</mi> <mo>+</mo> </msup> <msup> <mi>π</mi> <mo>-</mo> </msup> <msup> <mi>π</mi> <mn>0</mn> </msup> </mrow> </math></EquationSource> </InlineEquation> as benchmarks. The results demonstrate that, compared to the unlayered framework, utilizing this framework for longitudinally segmented ECAL significantly enhances the position resolution and the ability to split overlapping clusters, thereby improving the reconstruction resolution and efficiency for photons and <InlineEquation ID="IEq5"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="41365_2025_1740_Article_IEq1.gif" Format="GIF" Height="16" Rendition="HTML" Resolution="72" Type="Linedraw" Width="18" /> </InlineMediaObject> <EquationSource Format="TEX">$\pi ^0$</EquationSource> <EquationSource Format="MATHML"><math> <msup> <mi>π</mi> <mn>0</mn> </msup> </math></EquationSource> </InlineEquation>s.</p>

Layered reconstruction framework for longitudinal segmented electromagnetic calorimeter

期刊论文
发表日期：

2025年6月28日

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Jia-Le Fei,
Ao Yuan,
Ke Wei,
Liang Sun,
Ji-Ke Wang

摘要

In future high-energy physics experiments, the electromagnetic calorimeter (ECAL) should operate with an exceptionally high luminosity. An ECAL featuring a layered readout in the longitudinal direction and precise time-stamped information offers a multidimensional view, thereby enriching our understanding of the showering process of electromagnetic particles in high-luminosity environments. This was used as the baseline design for several new experiments, including the planned upgrades of the current running experiments. Reconstructing and matching multidimensional information across different layers poses new challenges for the effective utilization of layered data. This study introduced a novel layered reconstruction framework for ECAL with a layered readout information structure and developed a corresponding layered clustering algorithm. This expands the concept of clusters from a plane to multiple layers. Additionally, this study presents the corresponding layered cluster correction methods, investigates the transverse shower profile utilized for overlapping cluster splitting, and develops a layered merged $\pi ^0$ $π^{0}$ reconstruction algorithm based on this framework. By incorporating energy and time information into 3-dimensions, this framework provides a suitable software platform for preliminary research on longitudinally segmented ECAL and new perspectives in physics analyses. Furthermore, using the PicoCal in LHCb Upgrade II as a concrete example, the performance of the framework was preliminarily evaluated using single photons and $\pi ^{0}$ $π^{0}$ particles from the neutral $B^0$ $B^{0}$ meson decay $B^0\rightarrow \pi ^+\pi ^-\pi ^0$ $B^{0} \to π^{+} π^{-} π^{0}$ as benchmarks. The results demonstrate that, compared to the unlayered framework, utilizing this framework for longitudinally segmented ECAL significantly enhances the position resolution and the ability to split overlapping clusters, thereby improving the reconstruction resolution and efficiency for photons and $\pi ^0$ $π^{0}$ s.