OmniFold: A Method to Simultaneously Unfold All Observables
Journal Article
·
· Physical Review Letters
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.
- Research Organization:
- Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States); Massachusetts Institute of Technology (MIT), Cambridge, MA (United States)
- Sponsoring Organization:
- National Science Foundation (NSF); USDOE Office of Science (SC), High Energy Physics (HEP) (SC-25); USDOE Office of Science (SC), Nuclear Physics (NP) (SC-26)
- Grant/Contract Number:
- AC02-05CH11231; SC0011090; SC0012567; SC0019128
- OSTI ID:
- 1617705
- Alternate ID(s):
- OSTI ID: 1630646
OSTI ID: 1760242
- Journal Information:
- Physical Review Letters, Journal Name: Physical Review Letters Journal Issue: 18 Vol. 124; ISSN 0031-9007; ISSN PRLTAO
- Publisher:
- American Physical Society (APS)Copyright Statement
- Country of Publication:
- United States
- Language:
- English