Modern jet flavour tagging in hadronic Z decays with archived ALEPH data

Abstract

We present a reanalysis of archived data from the ALEPH experiment at LEP in the $\mathrm{Z \to q\bar{q}}$ final state. We apply modern jet flavour tagging techniques to improve the separation between the different hadronic decay channels of the Z boson, achieving up to one order of magnitude improvement in misidentification rate for b- and c-quark jets compared to the legacy algorithms used for the most recent ALEPH results, for the same identification efficiency. We also present the first implementation of strange quark jet tagging with LEP data, which allows for the selection of a $\mathrm{Z \to s\bar{s}}$ enriched event sample. These improvements in the flavour tagging performance are achieved by leveraging the lifetime, particle identification, and secondary vertex information, as well as modern classifiers based on a deep learning approach. We also demonstrate the calibration of the tagger in data using a tag-and-probe method, obtaining good data to simulation agreement for all quark flavours. These results pave the way for improved measurements of electroweak precision observables with LEP archived data, and can serve as a guidance for the development of detectors and algorithms for future electron-positron colliders.

Figures (15)

• Figure 1: Basic properties of selected events in data and simulation: the invariant mass of the two jets in the event (left) and the energy of all selected jets (right). Data are shown as black markers, while the simulation is shown as filled histograms. The ${ \mathup{{{Z}}{} _{ {}} ^{ {}}} }\xspace \to { \mathup{{{q}}{} _{ {}} ^{ {}}} }\xspace{ \mathup{{ \overline{ {{ \mathup{{{q}}{} _{ {}} ^{ {}}} }\xspace}}}{} _{ {}} ^{ {}}} }\xspace$ simulation is split according to the quark flavour: $\mathup{{{b}}{} _{ {}} ^{ {}}}$ , $\mathup{{{c}}{} _{ {}} ^{ {}}}$ , $\mathup{{{s}}{} _{ {}} ^{ {}}}$ , and light ( $\mathup{{{u}}{} _{ {}} ^{ {}}}$ , $\mathup{{{d}}{} _{ {}} ^{ {}}}$ ). The lower panels show the ratio of data to simulation, with the grey band representing the statistical uncertainty in simulation.
• Figure 2: Primary vertex residuals in the $x$-coordinate (left) and $z$-coordinate (right). The residual is defined as the difference between reconstructed and true primary vertex position in simulation. The ${ \mathup{{{Z}}{} _{ {}} ^{ {}}} }\xspace \to { \mathup{{{q}}{} _{ {}} ^{ {}}} }\xspace{ \mathup{{ \overline{ {{ \mathup{{{q}}{} _{ {}} ^{ {}}} }\xspace}}}{} _{ {}} ^{ {}}} }\xspace$ simulation is split according to the quark flavour: $\mathup{{{b}}{} _{ {}} ^{ {}}}$ , $\mathup{{{c}}{} _{ {}} ^{ {}}}$ , $\mathup{{{s}}{} _{ {}} ^{ {}}}$ , and light ( $\mathup{{{u}}{} _{ {}} ^{ {}}}$ , $\mathup{{{d}}{} _{ {}} ^{ {}}}$ ). Each of these distributions is fitted with a student-t distributions, accounting for the wide tails. The resolution ($\sigma$) is defined as the fitted width of this distribution, and values in the order of 25 - 60 $\mu$m are achieved, depending on the direction and the quark flavour. The $y$-coordinate (not shown here) looks similar to the $x$-coordinate. All distributions have been normalized to unit surface area for easier shape comparison.
• Figure 3: Features of $\mathup{{{u}}{} _{ {}} ^{ {}}}$ / $\mathup{{{d}}{} _{ {}} ^{ {}}}$ , $\mathup{{{s}}{} _{ {}} ^{ {}}}$ , $\mathup{{{c}}{} _{ {}} ^{ {}}}$ , and $\mathup{{{b}}{} _{ {}} ^{ {}}}$ jets: number of reconstructed secondary vertices per jet (left) and reconstructed invariant mass of the secondary vertices (right). The secondary vertex mass is corrected for missing particles by comparing its observed flight direction to its momentum, as in Ref. Sirunyan_2018. All distributions have been normalized to unit surface area for easier shape comparison.
• Figure 4: Features of $\mathup{{{u}}{} _{ {}} ^{ {}}}$ / $\mathup{{{d}}{} _{ {}} ^{ {}}}$ , $\mathup{{{s}}{} _{ {}} ^{ {}}}$ , $\mathup{{{c}}{} _{ {}} ^{ {}}}$ , and $\mathup{{{b}}{} _{ {}} ^{ {}}}$ jets: reconstructed invariant mass of $V^{0}$ candidates (left) and number of reconstructed ${ \mathup{{{K}}{} _{ {}} ^{ {}}} }\xspace^{0}_{S}$ candidates (right). The resonance peaks in the mass distribution around 498$\,\text{Me\spaceV}$ and 1.116$\,\text{Ge\spaceV}$ correspond to the ${ \mathup{{{K}}{} _{ {}} ^{ {}}} }\xspace^{0}_{S}$ meson and the $\Lambda^{0}$ baryon respectively, as indicated in the figure. The number of ${ \mathup{{{K}}{} _{ {}} ^{ {}}} }\xspace^{0}_{S}$ candidates per jet is calculated after applying an extra invariant mass selection window of 450 - 550$\,\text{Me\spaceV}$. All distributions have been normalized to unit surface area for easier shape comparison.
• Figure 5: Left: wire $\mathrm{d}E/\mathrm{d}x$ as a function of track momentum for pions ($\pi$), kaons ( $\mathup{{{K}}{} _{ {}} ^{ {}}}$ ), protons ( $\mathup{{{p}}{} _{ {}} ^{ {}}}$ ), muons ($\mu$) and electrons ( $\mathup{{{e}}{} _{ {}} ^{ {}}}$ ) in simulation. The dashed lines show the expected mean $\mathrm{d}E/\mathrm{d}x$ for each species, using a fit procedure detailed in the text. Right: wire $\mathrm{d}E/\mathrm{d}x$ distribution for pions and kaons in the narrow momentum range $9 - 10\,\text{Ge\spaceV}\xspace$. The red dotted lines show fitted gaussian distributions, and the best-fit mean and standard deviation are displayed in the legend. A significant separation between pions and kaons is observed, even in this relatively high momentum range.