276 citations · 882 across the 11 of their papers we have counts for
12 papers
TopFitter: Fitting top-quark Wilson Coefficients to Run II data
Stephen Brown, Andy Buckley, Christoph Englert +7
We describe the latest TopFitter analysis, which uses top quark observables to fit the Wilson Coefficients of the SM augmented with dimension-6 operators. In particular, we discuss…
Effective Field Theory in the top sector: do multijets help?
Christoph Englert, Michael Russell, Chris D. White
Many studies of possible new physics employ effective field theory (EFT), whereby corrections to the Standard Model take the form of higher-dimensional operators, suppressed by a l…
Dark Matter in Anomaly-Free Gauge Extensions
Martin Bauer, Sascha Diefenbacher, Tilman Plehn +2
A consistent model for vector mediators to dark matter needs to be anomaly-free and include a scalar mode from mass generation. For the leading U(1) extensions we review the struct…
Interpreting top-quark LHC measurements in the standard-model effective field theory
J. A. Aguilar Saavedra, C. Degrande, G. Durieux +32
This note proposes common standards and prescriptions for the effective-field-theory interpretation of top-quark measurements at the LHC.
Top quark physics in the Large Hadron Collider era
Michael Russell
We explore various aspects of top quark phenomenology at the Large Hadron Collider and proposed future machines. After summarising the role of the top quark in the Standard Model (…
Deep-learned Top Tagging with a Lorentz Layer
Anja Butter, Gregor Kasieczka, Tilman Plehn +1
We introduce a new and highly efficient tagger for hadronically decaying top quarks, based on a deep neural network working with Lorentz vectors and the Minkowski metric. With its…
Top quark electroweak couplings at future lepton colliders
Christoph Englert, Michael Russell
We perform a comparative study of the reach of future collider options for the scale of non-resonant new physics effects in the top quark sector, phrased in the language o…
Deep-learning Top Taggers or The End of QCD?
Gregor Kasieczka, Tilman Plehn, Michael Russell +1
Machine learning based on convolutional neural networks can be used to study jet images from the LHC. Top tagging in fat jets offers a well-defined framework to establish our DeepT…
Results from TopFitter
Andy Buckley, Christoph Englert, James Ferrando +5
We discuss a global fit of top quark BSM couplings, phrased in the model-independent language of higher-dimensional effective operators, to the currently available data from the LH…
Giving top quark effective operators a boost
Christoph Englert, Karl Nordstrom, Liam Moore +1
We investigate the prospects to systematically improve generic effective field theory-based searches for new physics in the top sector during LHC run 2 as well as the high luminosi…
Constraining top quark effective theory in the LHC Run II era
Andy Buckley, Christoph Englert, James Ferrando +4
We perform an up-to-date global fit of top quark effective theory to experimental data from the Tevatron, and from LHC Runs I and II. Experimental data includes total cross-section…
A global fit of top quark effective theory to data
Andy Buckley, Christoph Englert, James Ferrando +4
In this paper we present a global fit of beyond the Standard Model (BSM) dimension six operators relevant to the top quark sector to currently available data. Experimental measurem…