arXiv subjects
Publications and source records attributed to Michael Russell.
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 the inclusion of new LHC Run II data and the implementation of particle-level observables.
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 large energy scale. Fits of such a theory to data typically use parton level observables, which limits the datasets one can use. In order to theoretically model search channels involving many additional jets, it is important to include tree-level matrix elements matched to a parton shower algorithm, and a suitable matching procedure to remove the double counting of additional radiation. There are then two potential problems: (i) EFT corrections are absent in the shower, leading to an extra source of discontinuities in the matching procedure; (ii) the uncertainty in the matching procedure may be such that no additional constraints are obtained from observables sensitive to radiation. In this paper, we review why the first of these is not a problem in practice, and perform a detailed study of the second. In particular, we quantify the additional constraints on EFT expected from top pair plus multijet events, relative to inclusive top pair production alone.
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 structure and constraints, including kinetic mixing at loop level. The thermal relic density suggests that the vector and scalar masses are similar. For the LHC we combine a $Z'$ shape analysis with mono-jets. For the latter, we find that a shape analysis offers significant improvement over existing cut-and-count approaches. Direct detection limits strongly constrain the kinetic mixing angle and we propose a $\ell^+\ell^- E_T$ search strategy based on the scalar mediator.
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 (and some of its well-known extensions), we discuss the formulation of the Standard Model as a low energy effective theory. We isolate the sector of this effective theory that pertains to the top quark and that can be probed with top observables at hadron colliders, and present a global fit of this sector to currently available data from the LHC and Tevatron. Various directions for future improvement are sketched, including analysing the potential of boosted observables and future colliders, and we highlight the importance of using complementary information from different colliders. Interpretational issues related to the validity of the effective field theory formulation are elucidated throughout. Finally, we present an application of artificial neural network algorithms to identifying highly-boosted top quark events at the LHC, and comment on further refinements of our analysis that can be made.
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 novel machine learning setup and architecture it allows us to identify boosted top quarks not only from calorimeter towers, but also including tracking information. We show how the performance of our tagger compares with QCD-inspired and image-recognition approaches and find that it significantly increases the performance for strongly boosted top quarks.
We perform a comparative study of the reach of future $e^+e^-$ collider options for the scale of non-resonant new physics effects in the top quark sector, phrased in the language of higher-dimensional operators. Our focus is on the electroweak top quark pair production process $e^+e^- \to Z^*/\gamma \to t\bar t $, and we study benchmark scenarios at the ILC and CLIC. We find that both are able to constrain mass scales up to the few TeV range in the most sensitive cases, improving by orders of magnitude on the forecasted capabilities of the LHC. We discuss the role played by observables such as forward-backward asymmetries, and making use of different beam polarisation settings, and highlight the possibility of lifting a degeneracy in the allowed parameter space by combining top observables with precision $Z$-pole measurements from LEP1.
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 DeepTop approach and compare its performance to QCD-based top taggers. We first optimize a network architecture to identify top quarks in Monte Carlo simulations of the Standard Model production channel. Using standard fat jets we then compare its performance to a multivariate QCD-based top tagger. We find that both approaches lead to comparable performance, establishing convolutional networks as a promising new approach for multivariate hypothesis-based top tagging.
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 LHC and Tevatron. We examine the interplay between inclusive and differential measurements, and the complementarity of LHC and Tevatron results. We conclude with a discussion of projections for improvement over LHC Run II.
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 luminosity phase. In particular, we assess the benefits of high momentum transfer final states on top EFT-fit as a function of systematic uncertainties in comparison with sensitivity expected from fully-resolved analyses focusing on $t\bar t$ production. We find that constraints are typically driven by fully-resolved selections, while boosted top quarks can serve to break degeneracies in the global fit. This demystifies and clarifies the importance of high momentum transfer final states for global fits to new interactions in the top sector from direct measurements.
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-sections up to 13 TeV, as well as differential distributions, for both single top and pair production. We also include the top quark width, charge asymmetries, and polarisation information from top decay products. We present bounds on the coefficients of dimension six operators, and examine the interplay between inclusive and differential measurements, and Tevatron / LHC data. All results are currently in good agreement with the Standard Model.
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 measurements include parton-level top-pair and single top production from the LHC and the Tevatron. Higher order QCD corrections are modelled using differential and global K-factors, and we use novel fast-fitting techniques developed in the context of Monte Carlo event generator tuning to perform the fit. This allows us to provide new, fully correlated and model-independent bounds on new physics effects in the top sector from the most current direct hadron-collider measurements in light of the involved theoretical and experimental systematics. As a by-product, our analysis constitutes a proof-of-principle that fast fitting of theory to data is possible in the top quark sector, and paves the way for a more detailed analysis including top quark decays, detector corrections and precision observables.
A subject's heart beat can be nearly invisible in a spectrum, when that spectrum is generated using conventional methods of Fourier analysis. The phenomenon has been observed in records of both electrocardiography type and seismocardiography type. The mechanisms of nonlinear physics responsible for these complexities involve the phenomenon of amplitude modulation. Fortunately, there is a simple remedy to prevent loss of valuable frequency domain information. Instead of operating on the raw signal, one simply rectifies that signal before performing the fast Fourier transform (FFT) calculation. Alternatively, nearly equivalent spectra can be obtained by operating on the signal with the Teager-Kaiser operator before doing the FFT.