jet-universe/sophon-ak4

Model Card: SophonAK4

The SophonAK4 model is a realistic small-radius (R = 0.4) anti-kT jet tagger developed for fast-simulation (Delphes) datasets under the JetClass-II configuration, designed to emulate the CMS detector conditions at the LHC.

Here, realistic indicates that the model achieves tagging performance comparable to state-of-the-art jet taggers used in the ATLAS and CMS experiments.

The model is constructed to cover a broad range of final states, including partons and leptons of various flavors and charges.

Model Details

SophonAK4 is trained using a multi-class classification approach based on di-X resonance processes, where the resonance X decays into multiple two-prong final states. Truth labelling is performed by associating reconstructed anti-kT jets with partons or leptons originating from these two-prong decays.

A total of 23 jet labels are defined:

• Single-prong labels: \(b\), \(\bar{b}\), \(c\), \(\bar{c}\), \(s\), \(\bar{s}\), \(d\), \(\bar{d}\), \(u\), \(\bar{u}\), \(g\), \(e^-\), \(e^+\), \(\mu^-\), \(\mu^+\), \(\tau_{\rm h}^-\), and \(\tau_{\rm h}^+\). These correspond to cases where a single truth particle (either a parton or a lepton) is matched to the jet within ΔR(jet, particle) T > 30 GeV and |η| Conclusion

• The b and c tagging performance of SophonAK4, evaluated on the Delphes simulation, is very compatible with that of the CMS taggers. Its performance falls between DeepJet and UParT, and is generally comparable to ParticleNet.

Click here to show the ROC curves with CMS results overlaid.

2. Performance across different pT and |η| regions is benchmarked below and can be compared with CMS benchmarks (Figs. 17, 19, 21, 23, 25, 27, 29, and 31).

Conclusion

• Tagging performance degrades in the low-pT and high-|η| regions but reaches the plateau beyond the turn-on point, indicating that the SophonAK4 tagger exhibits realistic flavor-tagging behavior across kinematic regimes.

Citation

If you find the SophonAK4 model useful in your research, please cite our [paper] that introduces the model:

@article{Zhao:2025rci,
    author = "Zhao, Yuzhe and Li, Congqiao and Agapitos, Antonios and Fu, Dawei and Gao, Leyun and Mao, Yajun and Li, Qiang",
    title = "{Novel $|V_{cb}|$ extraction method via boosted $bc$-tagging with in-situ calibration}",
    eprint = "2503.00118",
    archivePrefix = "arXiv",
    primaryClass = "hep-ph",
    month = "2",
    year = "2025"
}