Iterative HOMER with uncertainties

Butter, Anja [Heidelberg Univ. (Germany); Sorbonne Univ., Paris (France); Univ. of Paris (France); Centre National de la Recherche Scientifique (CNRS), Paris (France). Inst. National de Physique Nucleaire et de Physique des Particules (IN2P3), Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE)]; Ore, Ayodele [Heidelberg Univ. (Germany)] (ORCID:0000000169253565); Palacios Schweitzer, Sofia [Heidelberg Univ. (Germany)] (ORCID:0009000402967204); Plehn, Tilman [Heidelberg Univ. (Germany)] (ORCID:0000000156607790); Assi, Benoît [Univ. of Cincinnati, OH (United States)]; Bierlich, Christian [Lund Univ. (Sweden)] (ORCID:0000000239786085); Ilten, Philip [Univ. of Cincinnati, OH (United States)] (ORCID:0000000155341732); Menzo, Tony [Univ. of Cincinnati, OH (United States)] (ORCID:0000000220134570); Mrenna, Stephen [Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Univ. of Cincinnati, OH (United States)]; Szewc, Manuel [Univ. of Cincinnati, OH (United States); National Univ. of General San Martín (UNSAM), Buenos Aires (Argentina)] (ORCID:0000000230145388); Wilkinson, Michael K. [Univ. of Cincinnati, OH (United States)] (ORCID:0000000165612145); Youssef, Ahmed [Univ. of Cincinnati, OH (United States)] (ORCID:0000000315854757); Zupan, Jure [Univ. of Cincinnati, OH (United States)] (ORCID:000000019445537X)

doi:10.21468/scipostphys.20.2.042

DOE OSTI · 3018283

Iterative HOMER with uncertainties

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Abstract

We present iHOMER, an iterative version of the HOMER method to extract Lund fragmentation functions from experimental data. Through iterations, we address the information gap between latent and observable phase spaces and systematically remove bias. To quantify uncertainties on the inferred weights, we use a combination of Bayesian neural networks and uncertainty-aware regression. We find that the combination of iterations and uncertainty quantification produces well-calibrated weights that accurately reproduce the data distribution. A parametric closure test shows that the iteratively learned fragmentation function is compatible with the true fragmentation function.

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Butter, Anja [Heidelberg Univ. (Germany); Sorbonne Univ., Paris (France); Univ. of Paris (France); Centre National de la Recherche Scientifique (CNRS), Paris (France). Inst. National de Physique Nucleaire et de Physique des Particules (IN2P3), Laboratoire de Physique Nucléaire et de Hautes Énergies (LPNHE)], Ore, Ayodele [Heidelberg Univ. (Germany)] (ORCID:0000000169253565), Palacios Schweitzer, Sofia [Heidelberg Univ. (Germany)] (ORCID:0009000402967204), Plehn, Tilman [Heidelberg Univ. (Germany)] (ORCID:0000000156607790), Assi, Benoît [Univ. of Cincinnati, OH (United States)], Bierlich, Christian [Lund Univ. (Sweden)] (ORCID:0000000239786085), Ilten, Philip [Univ. of Cincinnati, OH (United States)] (ORCID:0000000155341732), Menzo, Tony [Univ. of Cincinnati, OH (United States)] (ORCID:0000000220134570), Mrenna, Stephen [Fermi National Accelerator Laboratory (FNAL), Batavia, IL (United States); Univ. of Cincinnati, OH (United States)], Szewc, Manuel [Univ. of Cincinnati, OH (United States); National Univ. of General San Martín (UNSAM), Buenos Aires (Argentina)] (ORCID:0000000230145388), Wilkinson, Michael K. [Univ. of Cincinnati, OH (United States)] (ORCID:0000000165612145), Youssef, Ahmed [Univ. of Cincinnati, OH (United States)] (ORCID:0000000315854757), Zupan, Jure [Univ. of Cincinnati, OH (United States)] (ORCID:000000019445537X). 2026-02-12. Iterative HOMER with uncertainties. https://doi.org/10.21468/scipostphys.20.2.042

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