Abstract
Direct searches for new particles at colliders have traditionally been factorized into model proposals by theorists and model testing by experimentalists. With the recent advent of machine learning methods that allow for the simultaneous unfolding of all observables in a given phase space region, there is a new opportunity to blur these traditional boundaries by performing searches on unfolded data. This could facilitate a research program where data are explored in their natural high dimensionality with as little model bias as possible. We study how the information about physics beyond the Standard Model is preserved by full phase space unfolding using an important physics target at the Large Hadron Collider (LHC): exotic Higgs boson decays involving hadronic final states. We find that if the signal cross section is high enough, information about the new physics is visible in the unfolded data. We will show that in some cases, quantifiably all of the information about the new physics is encoded in the unfolded data. Finally, we show that there are still many cases when the unfolding does not work fully or precisely, such as when the signal cross section is small. This study will serve as an important benchmark for enhancing unfolding methods for the LHC and beyond.
Highlights
Analyses at the Large Hadron Collider (LHC) are generally classified as measurements or searches if their goal is to search for indirect or direct signs of physics beyond the Standard Model (SM), respectively
If MULTIFOLD preserves the complete phase space—the event-by-event distribution of all variables in the data sample including beyond the Standard Model (BSM) physics, any threshold cut on this classifier should have the same efficiency with the unfolded data as it does with the Truth
The OMNIFOLD and MULTIFOLD methods can be used for unbinned, all-variable unfolding in the presence of BSM physics, but there are inherent limitations on its applicability for truth-level searches for new physics
Summary
Analyses at the Large Hadron Collider (LHC) are generally classified as measurements or searches if their goal is to search for indirect or direct signs of physics beyond the Standard Model (SM), respectively. The detector response may depend on additional unmeasured features and may vary strongly within a given bin If these properties are significantly different for new particles, an unfolding derived with SM simulations is likely to be inaccurate. This feature of current unfolding methods has been studied in [8] and limits the applicability of recasting tools such as CONTUR [9]. We investigate the ability of OMNIFOLD to preserve information about new particles present in the data.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
