OmniFold: A Method to Simultaneously Unfold All Observables
Name
PhysRevLett.124.182001.pdf
Description
Published version
Size
886.26 KB
Format
Adobe PDF
Checksum (MD5)
ef881e65b1d087503c18b7b7799ccc5c
Author(s)
Andreassen, Anders
Komiske, Patrick T
Metodiev, Eric M
Nachman, Benjamin
Thaler, Jesse
Date Issued
2020
Journal
Physical Review Letters
Publisher
American Physical Society (APS)
Version
Final published version
Abstract
© 2020 authors. Published by the American Physical Society. Collider data must be corrected for detector effects ("unfolded") to be compared with many theoretical calculations and measurements from other experiments. Unfolding is traditionally done for individual, binned observables without including all information relevant for characterizing the detector response. We introduce OmniFold, an unfolding method that iteratively reweights a simulated dataset, using machine learning to capitalize on all available information. Our approach is unbinned, works for arbitrarily high-dimensional data, and naturally incorporates information from the full phase space. We illustrate this technique on a realistic jet substructure example from the Large Hadron Collider and compare it to standard binned unfolding methods. This new paradigm enables the simultaneous measurement of all observables, including those not yet invented at the time of the analysis.
MIT Department
Massachusetts Institute of Technology. Center for Theoretical Physics
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1103/PHYSREVLETT.124.182001
