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ParticleNet: Jet Tagging via Particle Clouds
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How to represent a jet is at the core of machine learning on jet physics. Inspired by the notion of point clouds, we propose a new approach that considers a jet as an unordered set of its constituent particles, effectively a "particle cloud". Such a particle cloud representation of jets is efficient in incorporating raw information of jets and also explicitly respects the permutation symmetry. Based on the particle cloud representation, we propose ParticleNet, a customized neural network architecture using Dynamic Graph Convolutional Neural Network for jet tagging problems. The ParticleNet architecture achieves state-of-the-art performance on two representative jet tagging benchmarks and is improved significantly over existing methods.
Forward citations
Cited by 22 Pith papers
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Predict before you train: Scaling Laws for particle physics foundation models
A Chinchilla-style law fit on ParticleViT runs below 10^19 FLOPs predicts held-out pretraining loss within ~1% at >100× compute and tracks downstream jet-tagging rejection.
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Benchmarking Machine Learning Architectures for ttH Multilepton Signal Sensitivity
A controlled benchmark of six ML classifiers on a new simulated ttH multilepton dataset finds symmetry-constrained graph models (Particle Transformer, LorentzNet) and azimuthal RoPE encoding outperform tabular baselines.
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ParticleTransformer is all you need for reconstructing hadronic tau leptons
Transformer models trained on FCC-ee CLD simulation reconstruct hadronic taus with per-mille mis-ID, F1 up to 0.95, sub-per-mille charge errors, and percent-level transverse momentum resolution.
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Measurement of the jet mass in hadronic decays of boosted W bosons at 13 TeV and extraction of the W boson mass
Unfolded double-differential W+jets cross section versus jet p_T and soft-drop mass yields m_W = 80.83 ± 0.55 GeV, the most precise all-jets extraction at a hadron collider.
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Search for single production of a vector-like T quark decaying to a top quark and a neutral scalar boson in the lepton+jets final state in proton-proton collisions at $\sqrt{s}$ = 13 TeV
No evidence of a single vector-like T quark decaying to a top quark plus a neutral scalar is found; new 95% CL exclusion limits are set, first for the new-scalar channel.
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Search for dark matter in a signature with a four-prong large-radius jet in proton-proton collisions at $\sqrt{s}$ = 13 TeV
No significant excess is observed in the four-prong large-radius jet + MET signature; 95% CL upper limits are set on the signal strength versus mediator mass or χ₂χ₁Y₀ coupling.
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Search for nonresonant triple Higgs boson production in the final state with six bottom quarks in proton-proton collisions at $\sqrt{s}$ = 13 TeV
No excess is observed; the 95% CL upper limit on nonresonant HHH→6b is 44 fb (588×SM), with κ3 constrained to −7.4 < κ3 < 12.4 (κ4=1) and κ4 to −177 < κ4 < 185 (κ3=1).
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Exclusive Quark and Gluon Dijet Production as Probes of GPDs at Collider Energies
Exclusive quark and gluon dijet electroproduction is analyzed in collinear factorization as a GPD probe, extending prior work with helicity GPDs and an electromagnetic channel, with HERA comparisons and EIC projections.
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Search for Higgs boson production at high transverse momentum in the WW decay channel in proton-proton collisions at $\sqrt{s}$ = 13 TeV
A first dedicated search for highly Lorentz-boosted H->WW decays at the LHC finds mu = -0.19 +0.48/-0.46, consistent with no signal above background.
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Search for pair production of heavy resonances in final states with a photon and large-radius jets in proton-proton collisions at $\sqrt{s}$ = 13 TeV
Using 138 fb^-1 of CMS data, the first tt-gamma-g channel search finds no excess and excludes spin-1/2 (spin-3/2) excited top quarks below 930 (1330) GeV.
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Search for heavy resonances decaying into two Higgs bosons in the $\mathrm{b\bar{b}}\tau^+\tau^-$ final state in proton-proton collisions at $\sqrt{s}$ = 13 TeV
No excess is observed in resonant Higgs pair production in the bb tau tau final state; 95% CL limits are set on spin-0 and spin-2 resonance cross sections from 1 to 4.5 TeV.
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Combination of searches for heavy vector boson resonances in proton-proton collisions at $\sqrt{s}$ = 13 TeV
A CMS combination of searches finds no heavy vector boson resonance and excludes HVT W′/Z′ bosons below 5.5 TeV (weak coupling), 4.8 TeV (strong coupling), and 2.0 TeV for VBF production at 95% CL.
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Search for the pair production of long-lived supersymmetric partners of the tau lepton in proton-proton collisions at $\sqrt{s}$ = 13 TeV
No long-lived staus are observed; CMS excludes stau masses up to 425 GeV at 50 mm lifetime (mass-degenerate) and decay lengths 21-94 mm / 6-333 mm at 200 GeV.
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Search for dark matter produced in association with a Higgs boson decaying to bottom quarks in proton-proton collisions at $\sqrt{s}$ = 13 TeV
A CMS search with 138 fb^-1 of 13 TeV data finds no dark matter produced with a Higgs boson decaying to bottom quarks, and sets 95% CL exclusions on Z' and 2HDM+a model parameters.
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Search for a boosted Higgs boson decaying to bottom quark pairs in association with a W or Z boson in proton-proton collisions at $\sqrt{s}$ = 13 TeV
In 138 fb^-1 of 13 TeV proton collisions, CMS measures the boosted VH, H->bb signal strength as mu=0.72^{+0.75}_{-0.71}, consistent with the Standard Model.
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Probing new physics in the Boosted $HH \to b\bar{b}\gamma\gamma$ channel at the LHC
A dedicated boosted-jet category in HH→bbγγ is projected to narrow the κ2V constraint to [-0.4, 2.6] at 95% CL and improve heavy-resonance limits by 1–2x at 308 fb⁻¹.
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KIGNet: Physics-Motivated Multi-Graph Representation Learning for Explainable Jet Tagging
E-PCN reaches 94.67% macro-accuracy on 10-class jet tagging by weighting graphs with angular separation, transverse momentum, momentum fraction, and invariant mass, with Grad-CAM showing the first two account for 76% ...
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The PYTHIA Facility
PYTHIA is presented as a 'big science facility' in software form: since 2018 its manuals drew ~9,600 citing works and ~47,000 unique authors across LHC, heavy-ion, flavor, astroparticle, and ML-for-physics communities.
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HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency
HEPTAPOD uses LLM agents to drive FeynRules, MadGraph, Pythia, and analysis tools through schema-validated tool calls and run-card templates, demonstrated on a leptoquark signal scan.
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SuperSONIC: Cloud-Native Infrastructure for ML Inferencing
SuperSONIC is a cloud-native inference-as-a-service framework for scientific experiments, and its automatic GPU scaling improves average latency and GPU utilization over static allocations in a synthetic test.
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The ILD Detector: A Versatile Detector for an Electron-Positron Collider at Energies up to 1 TeV
The ILD concept paper presents a particle-flow-optimized detector design, its performance requirements, technology options, and readiness for both linear and circular electron-positron colliders up to 1 TeV.
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Recent results on searches with boosted Higgs bosons at CMS
A conference proceedings that reviews recent CMS boosted Higgs searches and machine-learning jet taggers without adding a new measurement.
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