Optimisation of the vertex detector and measurement of Higgs decays to second-generation quarks at the CEPC

TL;DR

This work investigates measuring Higgs decays to second-generation quarks at CEPC by optimizing the vertex detector geometry, focusing on the inner radius and spatial resolution. It leverages the Jet Origin Identification (JOI) AI framework to propagate detector-geometry changes from track-level impact parameters to jet-flavour tagging and Higgs-boson measurements in the ννH channel. The key finding is that the innermost vertex radius is the dominant parameter for flavour tagging and Higgs sensitivity: halving the inner radius and spatial resolution yields roughly a factor of two improvement in impact-parameter resolution, translating to about a 4% gain in H→cc precision and an 8% gain in H→ss significance, with spatial resolution playing a comparatively smaller role. The results provide detector-design guidance for future Higgs factories, are validated against Geant4 with agreement at the ~5% level, and acknowledge limitations due to optimistic backgrounds and the need to extend studies to additional production channels and more realistic background modeling.

Abstract

The vertex detector is crucial for precision measurements of the Higgs boson at the electron-positron Higgs factory. Benchmarked with $H \to c\bar{c}$ and $H \to s\bar{s}$ measurements in the $ν\barνH$ channel, we perform an optimisation study on the inner radius and spatial resolution of the vertex detector using the Jet Origin Identification (JOI) framework, which determines the parton flavor of jets using advanced Artificial Intelligence (AI) algorithm. We observe that, compared to the reference detector configuration, halving the inner radius and spatial resolution improves the transverse and longitudinal impact parameter resolution approximately by a factor of two, while increasing the accuracy and significance of the $H \to c\bar{c}/s\bar{s}$ measurement by 4\% and 8\%, respectively. Conversely, doubling these parameters results in comparable degradation, with variations in the inner radius being the dominant factor. Our results provide guidance for detector design and highlight promising prospects for identifying the $H \to s\bar{s}$ decay mode at future Higgs factories.

Figures (10)

• Figure 1: Schematic view of pixel detector. Two layers of silicon pixel sensors are mounted on both sides of each of the three ladders to provide six space points. Only the silicon sensor sensitive region (in orange) is depicted. The vertex detector surrounds the beam pipe (red).
• Figure 2: Left: RMS of $\Delta d_0$ (top) and $\Delta z_0$ (bottom) versus geometry scale $\log_2 (\text{new} / \text{baseline})$. Right: normalised $\Delta d_0$ (top) and $\Delta z_0$ (bottom) distributions for $R_{\rm rad}=0.5$, baseline, and $R_{\rm rad}=2$, respectively. The simulated samples are $H\!\to b\bar{b}$.
• Figure 3: Left: The migration matrix of 11-dimensional jet identification of JOI under the CEPC CDR configuration. The matrix is normalized to unity for each truth label (row). Right: The comparison of JOI and XGboost of the $b$-jet tagging efficiency. refTDR_report
• Figure 4: The migration matrix of $M_{11}$ with $R_{rad.}$ =0.5 (left) and $R_{rad.}$ =2 (right). The matrix is normalized to unity for each truth label.
• Figure 5: Left: Key misidentification rates and tagging efficiencies versus $\log_2(\text{new}/\text{baseline})$ for different inner radius configurations. Right: Trace of the JOI migration matrix versus $\log_{2}(\text{new}/\text{baseline})$ for different inner radius and resolution configurations. Orange points indicate scans of the inner radius, while blue points indicate scans of the spatial resolution. Dashed lines represent linear fits to the configurations, respectively.