DOE OSTI · 3025137
A practical guide to unbinned unfolding
Abstract
Unfolding, in the context of high-energy particle physics, refers to the process of removing detector distortions in experimental data. The resulting unfolded measurements are straightforward to use for direct comparisons between experiments and a wide variety of theoretical predictions. For decades, popular unfolding strategies were designed to operate on data formatted as one or more binned histograms. In recent years, new strategies have emerged that use machine learning to unfold datasets in an unbinned manner, allowing for higher-dimensional analyses and more flexibility for current and future users of the unfolded data. This guide comprises recommendations and practical considerations from researchers across a number of major particle physics experiments who have recently put these techniques into practice on real data.
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Canelli, Florencia [Univ. of Zurich (Switzerland)] (ORCID:0000000163612117), Cormier, Kyle [Univ. of Zurich (Switzerland)] (ORCID:0000000178733579), Cudd, Andrew [Univ. of Colorado, Boulder, CO (United States)] (ORCID:0000000234897528), Gillberg, Dag [Carleton Univ., Ottawa, ON (Canada)] (ORCID:0000000303410171), Huang, Roger G. [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)] (ORCID:0000000198321192), Jin, Weijie [Univ. of Zurich (Switzerland)] (ORCID:0009000989767702), Lee, Sookhyun [Univ. of Tennessee, Knoxville, TN (United States)] (ORCID:0000000335239479), Mikuni, Vinicius [Nagoya Univ. (Japan)] (ORCID:0000000215792421), Miller, Laura [TRIUMF, Vancouver, BC (Canada)] (ORCID:0000000155393233), Nachman, Benjamin [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Stanford Univ., CA (United States); SLAC National Accelerator Laboratory (SLAC), Menlo Park, CA (United States)] (ORCID:0000000310240932), Pan, Jingjing [Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Yale Univ., New Haven, CT (United States)] (ORCID:0000000206649199), Pani, Tanmay [Rutgers Univ., New Brunswick, NJ (United States)] (ORCID:0000000233025883), Pettee, Mariel [Univ. of Wisconsin, Madison, WI (United States)] (ORCID:0000000192083218), Song, Youqi [Yale Univ., New Haven, CT (United States)] (ORCID:0000000261499197), Acosta, Fernando Torales [Google, New York, NY (United States)] (ORCID:0000000225863481). 2026-02-02. A practical guide to unbinned unfolding. https://doi.org/10.1140/epjc%2Fs10052-025-15265-9
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