14-16 November 2018
Fermilab
America/Chicago timezone

Disentangling Jet Categories at Colliders (20'+5')

16 Nov 2018, 10:35
25m
One West (WH1W) (Fermilab)

One West (WH1W)

Fermilab

Speaker

Eric Metodiev (Massachusetts Institute of Technology)

Description

The “jet topics” framework identifies (or defines) underlying classes of jets directly from data with little to no input from simulation or theory. Due to a mathematical connection between mixed samples of jets and emergent themes in documents, methods from topic modeling and blind source separation can be used to extract jet topics from data. Any machine-learned jet tagger, treated as a likelihood-ratio approximator, can be directly applied as a jet topic extractor. I apply the jet topics method to extract quark and gluon distributions and fractions from simulated Z+jet and dijet samples, and I discuss the potential for fully data-driven training and calibration of jet taggers.

Primary author

Eric Metodiev (Massachusetts Institute of Technology)

Co-authors

Jesse Thaler (MIT) Patrick Komiske (Massachusetts Institute of Technology)

Presentation Materials

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