Unfolding without Iterations, Adversaries, or Surrogates

TL;DR

AUSSIE is a novel unfolding method in LHC physics that eliminates the need for iterations, adversaries, or surrogates, providing asymptotically correct solutions with less dependence on reference simulations.

Contribution

It introduces AUSSIE, a new unfolding approach that simplifies existing methods by removing iterative and adversarial components while maintaining accuracy.

Findings

Successfully applied to jet substructure unfolding tasks.

Achieves minimal dependence on reference simulations.

Remains asymptotically correct without iterative procedures.

Abstract

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.