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000607315 245__ $$aTagging more quark jet flavours at FCC-ee at 91 GeV with a transformer-based neural network
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000607315 520__ $$aJet flavour tagging is crucial in experimental high-energy physics. A tagging algorithm, \texttt{DeepJetTransformer}, is presented, which exploits a transformer-based neural network that is substantially faster to train. The \texttt{DeepJetTransformer} network uses information from particle flow-style objects and secondary vertex reconstruction as is standard for $b$- and $c$-jet identification supplemented by additional information, such as reconstructed V$^0$s and $K^{\pm}/\pi^{\pm}$ discrimination, typically not included in tagging algorithms at the LHC. The model is trained as a multiclassifier to identify all quark flavours separately and performs excellently in identifying $b$- and $c$-jets. An $s$-tagging efficiency of $40\%$ can be achieved with a $10\%$$ud$-jet background efficiency. The impact of including V$^0$s and $K^{\pm}/\pi^{\pm}$ discrimination is presented. The network is applied on exclusive $Z \to q\bar{q}$ samples to examine the physics potential and is shown to isolate $Z \to s\bar{s}$ events. Assuming all other backgrounds can be efficiently rejected, a $5\sigma$ discovery significance for $Z \to s\bar{s}$ can be achieved with an integrated luminosity of $60~\text{nb}^{-1}$, corresponding to less than a second of the FCC-ee run plan at the $Z$ resonance.
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000607315 7001_ $$0P:(DE-HGF)0$$aMoor, De$$b1
000607315 7001_ $$0P:(DE-H253)PIP1104458$$aGautam, Kunal$$b2$$eCorresponding author
000607315 7001_ $$0P:(DE-H253)PIP1104457$$aPloerer, Eduardo$$b3
000607315 7001_ $$0P:(DE-H253)PIP1108470$$aIlg, Armin$$b4
000607315 7001_ $$0P:(DE-H253)PIP1025156$$aMacchiolo, Anna$$b5
000607315 7001_ $$0P:(DE-HGF)0$$aCanellli, Florencia$$b6
000607315 773__ $$0PERI:(DE-600)1459069-4$$a10.1140/epjc/s10052-025-13785-y$$gVol. 85, no. 2, p. 165$$n2$$p165$$tThe European physical journal / C$$v85$$x1434-6044$$y2024
000607315 7870_ $$0PUBDB-2024-07333$$aBlekman, Freya et.al.$$d2024$$iIsParent$$rarXiv:2406.08590 ; DESY-24-086$$tJet Flavour Tagging at FCC-ee with a Transformer-based Neural Network: DeepJetTransformer
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