Lorentz-Equivariant Geometric Algebra Transformers for Top-Quark Event Reconstruction

Results are presented for Lorentz-equivariant geometric algebra transformers (LGaTr) in three event reconstruction tasks involving top quarks.

By Abasov, Dudko, Markina +4Oct 21, 2026

Score████░░░░░░4.4

Caveats

Preprint; not yet peer reviewed.

VerdictWorth a reader's time today.

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Abstract

Results are presented for Lorentz-equivariant geometric algebra transformers (LGaTr) in three event reconstruction tasks involving top quarks. Geometric algebra provides a common Lorentz-covariant representation of four-momenta and typed physical objects. Performance of LGaTr is evaluated on three different physics tasks - tt/tWb separation, FCNC detection in single top-quark production and universal event reconstruction. LGaTr is outperforming the baseline networks in tW/tt separation and full event reconstruction and is showing comparable or better performance to standard transformer-based networks. The implementation is provided in a companion repository https://github.com/emil2001/top-quark-universal-nets.

E. Abasov, L. Dudko, A. Markina, M. Perfilov, P. Volkov, G. Vorotnikov, A. Zaborenko

The editor's rubric

Heuristic review

Leverage4 / 5: A general-purpose tool used across several fields (Adam, ResNet, LoRA, next-generation sequencing).; 18% of this desk’s rubric
Magnitude3 / 5: Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.; 20% of this desk’s rubric
Evidence3 / 5: Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.; 22% of this desk’s rubric
Novelty2 / 5: A new combination of known ideas.; 22% of this desk’s rubric
Trajectory3 / 5: A clear path to scale.; 10% of this desk’s rubric
Stakes2 / 5: Benefits a professional community (practitioners, clinicians, engineers).; 8% of this desk’s rubric

Dimension	Level	Weight	What that level means
Leverage	████░ 4	18%	A general-purpose tool used across several fields (Adam, ResNet, LoRA, next-generation sequencing).
Magnitude	███░░ 3	20%	Large gain: roughly 2x, or a clear new state of the art on a hard, unsaturated problem.
Evidence	███░░ 3	22%	Solid: multiple benchmarks or cohorts, ablations, fair baselines, released code or data.
Novelty	██░░░ 2	22%	A new combination of known ideas.
Trajectory	███░░ 3	10%	A clear path to scale.
Stakes	██░░░ 2	8%	Benefits a professional community (practitioners, clinicians, engineers).

Editor’s rationale

Heuristic triage from title and abstract text only, not a reading of the paper. Cues found: breadth (general-purpose, many tasks); gains (outperforms); verification (multiple benchmarks, code released).

How the score was computed

rank-2026-10-18

Score████░░░░░░4.4

Score = 10 × (75% × adjusted merit / 10 + 15% × attention + 10% × freshness)

Desks place stronger verdicts first, then use this score to order work within the same verdict.

Merit: 5.8 / 10; Weighted rubric, evidence-gated.
Adjusted merit: 4.7 / 10; Shrunk toward the desk prior by editor confidence (38%).
Attention: 0%; Citations, upvotes, points, mentions.
Freshness: 93%; Half-life decay since publication.

No attention signals recorded yet.

The record

Reviewed by heuristic-v7 on Oct 22, 2026, 07:29 UTC. Paper type: empirical.
Categories: hep-ph
TOP, No.2 in the Physics edition of October 22, 2026.