Unfolding without Iterations, Adversaries, or Surrogates
Fuente:
arXiv
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| Autori principali: | , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866917299981647872 |
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| author | Ore, Ayodele Plehn, Tilman |
| author_facet | Ore, Ayodele Plehn, Tilman |
| contents | Correcting measurements for detector effects and constructing appropriate public data representations is a pressing problem in LHC physics. Current methods solve this inverse problem by relying on iterations, minimax optimization, or a surrogate forward mapping. We introduce Adversary-free Unfolding SanS Iteration or Emulation (AUSSIE), which dispenses with these mechanisms while remaining asymptotically correct. AUSSIE replaces the second OmniFold step with a new loss function that directly yields solutions with minimal dependence on the reference simulation. We showcase AUSSIE on various unfolding tasks, including full-phase-space jet substructure. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_24282 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Unfolding without Iterations, Adversaries, or Surrogates Ore, Ayodele Plehn, Tilman High Energy Physics - Phenomenology High Energy Physics - Experiment Data Analysis, Statistics and Probability Correcting measurements for detector effects and constructing appropriate public data representations is a pressing problem in LHC physics. Current methods solve this inverse problem by relying on iterations, minimax optimization, or a surrogate forward mapping. We introduce Adversary-free Unfolding SanS Iteration or Emulation (AUSSIE), which dispenses with these mechanisms while remaining asymptotically correct. AUSSIE replaces the second OmniFold step with a new loss function that directly yields solutions with minimal dependence on the reference simulation. We showcase AUSSIE on various unfolding tasks, including full-phase-space jet substructure. |
| title | Unfolding without Iterations, Adversaries, or Surrogates |
| topic | High Energy Physics - Phenomenology High Energy Physics - Experiment Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2602.24282 |