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20182025
most citedAnomaly detection with spiking neural networks for LHC physics

1 citations · 1 across the 1 of their papers we have counts for

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hep-ph2019

Dilaton portal in strongly interacting twin Higgs models

Aqeel Ahmed, Barry M. Dillon, Saereh Najjari

We consider a strongly interacting twin Higgs (SITH) model where an ultraviolet completion of twin Higgs mechanism is realized by a strongly coupled approximately scale invariant t…

hep-ph2019

Higgs boson potential at colliders: status and perspectives

B. Di Micco, M. Gouzevitch, J. Mazzitelli +104

This document summarises the current theoretical and experimental status of the di-Higgs boson production searches, and of the direct and indirect constraints on the Higgs boson se…

hep-ph2019

Axion-like-particle decay in strong electromagnetic backgrounds

B. King, B. M. Dillon, K. A. Beyer +1

The decay of a massive pseudoscalar, scalar and U(1) boson into an electron-positron pair in the presence of strong electromagnetic backgrounds is calculated. Of particular interes…

hep-ph2019

Composite Higgs at high transverse momentum

Andrea Banfi, Barry M. Dillon, Wissarut Ketaiam +1

In this paper we explore composite Higgs scenarios through the effects of light top-partners in Higgs+Jet production at the LHC. The pseudo-Goldstone boson nature of the Higgs fiel…

hep-ph2019

Uncovering latent jet substructure

Barry M. Dillon, Darius A. Faroughy, Jernej F. Kamenik

We apply techniques from Bayesian generative statistical modeling to uncover hidden features in jet substructure observables that discriminate between different a priori unknown un…

hep-ph2019

The Machine Learning Landscape of Top Taggers

G. Kasieczka, T. Plehn, A. Butter +24

Based on the established task of identifying boosted, hadronically decaying top quarks, we compare a wide range of modern machine learning approaches. Unlike most established metho…