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| Main Authors: | , |
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| Format: | Preprint |
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2026
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| Online Access: | https://arxiv.org/abs/2605.14783 |
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| _version_ | 1866911685680300032 |
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| author | Lin, Jiahui Liu, Yandong |
| author_facet | Lin, Jiahui Liu, Yandong |
| contents | Optimal observables provide statistically powerful probes of small deformations from a reference theory, but in realistic collider measurements they are rarely available in compact analytic form. We show that interpretable event-level observables can be discovered by AI-driven symbolic evolution using score information from matrix-element reweighting as the statistical target. Focusing on the CP-sensitive interaction $HZ_{μν}\tilde Z^{μν}$, we study two complementary realizations of the same coupling structure: associated production $e^+e^-\to Z(\to μ^-μ^+)H$ and the decay channel $pp\to H\to ZZ^*\to e^-e^+μ^-μ^+$. The learned observables retain substantially more local Fisher information than standard angular baselines while remaining compact analytic functions. In both cases, the discovered expressions recover characteristic helicity-interference harmonics. In associated production these harmonics are supplemented by laboratory-frame asymmetry mappings, while in four-lepton decay the robust component is the angular kernel, with the mass-ratio factor serving as a bounded representative prefactor. These results recast optimal-observable design as a symbolic discovery problem and provide a transparent route to information-efficient, interpretable probes of collider interference. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2605_14783 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | AI-Driven Discovery of Information-Efficient Collider Observables for Interference Measurements Lin, Jiahui Liu, Yandong High Energy Physics - Phenomenology Optimal observables provide statistically powerful probes of small deformations from a reference theory, but in realistic collider measurements they are rarely available in compact analytic form. We show that interpretable event-level observables can be discovered by AI-driven symbolic evolution using score information from matrix-element reweighting as the statistical target. Focusing on the CP-sensitive interaction $HZ_{μν}\tilde Z^{μν}$, we study two complementary realizations of the same coupling structure: associated production $e^+e^-\to Z(\to μ^-μ^+)H$ and the decay channel $pp\to H\to ZZ^*\to e^-e^+μ^-μ^+$. The learned observables retain substantially more local Fisher information than standard angular baselines while remaining compact analytic functions. In both cases, the discovered expressions recover characteristic helicity-interference harmonics. In associated production these harmonics are supplemented by laboratory-frame asymmetry mappings, while in four-lepton decay the robust component is the angular kernel, with the mass-ratio factor serving as a bounded representative prefactor. These results recast optimal-observable design as a symbolic discovery problem and provide a transparent route to information-efficient, interpretable probes of collider interference. |
| title | AI-Driven Discovery of Information-Efficient Collider Observables for Interference Measurements |
| topic | High Energy Physics - Phenomenology |
| url | https://arxiv.org/abs/2605.14783 |