170 citations · 1.2k across the 88 of their papers we have counts for
10 papers · 1 filter
Bin-to-bin correlations in the extraction of proton's transverse structure
Laurent Favart, Francesco Hautmann, Aleksandra Lelek +1
We investigate the determination of non-perturbative QCD contributions, associated with proton's transverse structure, from high-precision experimental data for electroweak boson p…
Anomaly detection for multijet scenarios
Gregor Kasieczka, Sung Hak Lim, Louis Moureaux +3
Signals of physics beyond the Standard Model continue to resist discovery at the LHC. Recent years have seen the proliferation of new anomaly detection techniques, promising discov…
Kitchen Sink Anomaly Detection
Ranit Das, Marie Hein, Gregor Kasieczka +6
An enormous amount of R&D effort has resulted in many new resonant anomaly detection methods being proposed in recent years. However, the vast majority of previous R&D studies have…
Intrinsic and soft gluons in Monte Carlo event generators
Louis Moureaux, Aleksandra Lelek, Francesco Hautmann +1
Experimental measurements of the transverse momentum of Drell-Yan lepton pairs are sensitive to non-perturbative physics associated with the intrinsic parton transverse momentum $k…
How to pick the best anomaly detector?
Marie Hein, Gregor Kasieczka, Michael Krämer +3
Anomaly detection has the potential to discover new physics in unexplored regions of the data. However, choosing the best anomaly detector for a given data set in a model-agnostic…
Quirk SUEP
David Curtin, Sascha Dreyer, Max Fusté Costa +6
We propose searching for physics beyond the Standard Model in the low-transverse-momentum tracks accompanying hard-scatter events at the LHC. TeV-scale resonances connected to a da…
Weakly supervised anomaly detection with event-level variables
Liam Brennan, Tamas Almos Vami, Oz Amram +7
We introduce a new topology for weakly supervised anomaly detection searches, di-object plus~X. In this topology, one looks for a resonance decaying to two standard model particles…
Universal New Physics Latent Space
Anna Hallin, Gregor Kasieczka, Sabine Kraml +4
We develop a machine learning method for mapping data originating from both Standard Model processes and various theories beyond the Standard Model into a unified representation (l…
Accelerating Resonance Searches via Signature-Oriented Pre-training
Congqiao Li, Antonios Agapitos, Jovin Drews +9
The search for heavy resonances beyond the Standard Model (BSM) is a key objective at the LHC. While the recent use of advanced deep neural networks for boosted-jet tagging signifi…
The small kt-region in Drell-Yan production at next-to-leading order with the Parton Branching Method
I. Bubanja, A. Bermudez Martinez, L. Favart +10
The Parton Branching (PB) method describes the evolution of transverse momentum dependent (TMD) parton distributions, covering all kinematic regions from small to large transverse…