High-momentum top quarks are a natural physical system in collider experiments for testing models of new physics, and jet substructure methods are key both to exploiting their largest decay mode and to assuaging resolution difficulties as the boosted system becomes increasingly collimated in the detector. To be used in new-physics interpretation studies, it is crucial that related methods get implemented in analysis frameworks allowing for the reinterpretation of the results of the LHC such as MadAnalysis 5 and Rivet. We describe the implementation of the HEPTopTagger algorithm in these two frameworks, and we exemplify the usage of the resulting functionalities to explore the sensitivity of boosted top reconstruction performance to new physics contributions from the Standard Model Effective Field Theory. The results of this study lead to important conclusions about the implicit assumption of Standard-Model-like top quark decays in associated collider analyses, and for the prospects to constrain the Standard Model Effective Field Theory via kinematic observables built from boosted semi-leptonic  $$t\bar{t}$$  <math> <mrow> <mi>t</mi> <mover> <mrow> <mi>t</mi> </mrow> <mrow> <mo>¯</mo> </mrow> </mover> </mrow> </math>   events selected using HEPTopTagger.

United Kingdom

Jack Araz

Andy Buckley

France

Benjamin Fuks

Searches for new physics with boosted top quarks in the MadAnalysis 5 and Rivet frameworks

3D (3 dimensional) Young diagrams are a generalization of 2D Young diagrams. In this paper, We consider 3D Bosons and 3-Jack polynomials. We associate three parameters h 1, h 2, h 3 to y, x, z-axis respectively. 3-Jack polynomials are polynomials of P  n,j , n ≥ j with coefficients in ℂ(h 1, h 2, h 3), which are the generalization of Schur functions and Jack polynomials to 3D case. Similar to Schur functions, 3-Jack polynomials can also be determined by the vertex operators and the Pieri formulas.

China

Na Wang

Ke Wu

3D bosons, 3-Jack polynomials and affine Yangian of   <math> <mi>gl</mi> <mfenced> <mn>1</mn> </mfenced> </math>  $$ \mathfrak{gl}(1) $$

In this paper, we define one kind of new Jack polynomials denoted by <math><mi>J</mi><msub><mrow><mi>k</mi></mrow><mrow><mi>λ</mi></mrow></msub></math>, which equal the standard Jack polynomials <math><msubsup><mrow><mi>P</mi></mrow><mrow><mi>λ</mi></mrow><mrow><mi>α</mi></mrow></msubsup></math> multiplied by a coefficient. We show that the structure constant <math><msubsup><mrow><mi>C</mi></mrow><mrow><mi>λ</mi><mi>μ</mi></mrow><mrow><mi>ν</mi></mrow></msubsup></math> in <math><mi>J</mi><msub><mrow><mi>k</mi></mrow><mrow><mi>λ</mi></mrow></msub><mo>⋅</mo><mi>J</mi><msub><mrow><mi>k</mi></mrow><mrow><mi>μ</mi></mrow></msub><mo>=</mo><msub><mrow><mo>∑</mo></mrow><mrow><mi>ν</mi></mrow></msub><msubsup><mrow><mi>C</mi></mrow><mrow><mi>λ</mi><mi>μ</mi></mrow><mrow><mi>ν</mi></mrow></msubsup><mi>J</mi><msub><mrow><mi>k</mi></mrow><mrow><mi>ν</mi></mrow></msub></math> can be given from affine Yangian of <math><mrow><mi>gl</mi></mrow><mo>(</mo><mn>1</mn><mo>)</mo></math>. Then we give the Boson-Fermion correspondence for Jack polynomials <math><mi>J</mi><msub><mrow><mi>k</mi></mrow><mrow><mi>λ</mi></mrow></msub></math> and show that 3-Schur functions <math><msub><mrow><mi>S</mi></mrow><mrow><mi>π</mi></mrow></msub></math> equal Jack polynomials <math><mi>J</mi><msub><mrow><mi>k</mi></mrow><mrow><mi>λ</mi></mrow></msub></math> in the special case of <math><msub><mrow><mi>h</mi></mrow><mrow><mn>1</mn></mrow></msub><mo>=</mo><mi>h</mi></math>, <math><msub><mrow><mi>h</mi></mrow><mrow><mn>2</mn></mrow></msub><mo>=</mo><mo>−</mo><msup><mrow><mi>h</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></math>, <math><msub><mrow><mi>h</mi></mrow><mrow><mn>3</mn></mrow></msub><mo>=</mo><mo>−</mo><mi>h</mi><mo>+</mo><msup><mrow><mi>h</mi></mrow><mrow><mo>−</mo><mn>1</mn></mrow></msup></math>.

Zhennan Cui

Yang Bai

Jack polynomials and affine Yangian

We present an extension of the simplified fast detector simulator of MadAnalysis 5 – the SFS framework – with methods making it suitable for the treatment of long-lived particles of any kind. This allows users to make use of intuitive Python commands and straightforward C++ methods to introduce detector effects relevant for long-lived particles, and to implement selection cuts and plots related to their properties. In particular, the impact of the magnetic field inside a typical high-energy physics detector on the trajectories of any charged object can now be easily simulated. As an illustration of the capabilities of this new development, we implement three existing LHC analyses dedicated to long-lived objects, namely a CMS run 2 search for displaced leptons in the  $$e\mu $$  <math> <mrow> <mi>e</mi> <mi>μ</mi> </mrow> </math>   channel (CMS-EXO-16-022), the full run 2 CMS search for disappearing track signatures (CMS-EXO-19-010), and the partial run 2 ATLAS search for displaced vertices featuring a pair of oppositely charged leptons (ATLAS-SUSY-2017-04). We document the careful validation of all MadAnalysis 5 SFS implementations of these analyses, which are publicly available as entries in the MadAnalysis 5 Public Analysis Database and its associated dataverse.

Mark Goodsell

Manuel Utsch

Recasting LHC searches for long-lived particles with MadAnalysis 5

For the purpose of cross-fertilising currently separate experimental approaches, we connect results of LHC analyses attempting to access the properties of additional W′ and Z′ bosons from Drell-Yan processes. Under theoretical assumptions linking the two new gauge bosons, we take into account that such possible states of nature are wide enough (in relation to the leptonic mass resolution) for the corresponding signals be significantly affected by interference effects with the background from the Standard Model. The shape of the differential cross section may then no longer be a standard Breit-Wigner distribution, and asymmetry observables would become useful for characterisation (and, possibly, discovery) purposes. Under such conditions we concentrate our analysis on specific widely-studied models: the Sequential Standard Model, a model with an additional SU(2) L  gauge symmetry, as well as standard and alternative realisations of the Left-Right Symmetric Model. We show how information gathered in Z′ boson searches in terms of cross section and/or asymmetry distributions can be used to improve W′ boson searches in terms of the LHC sensitivity, and vice versa.

Canada

Mariana Frank

Stefano Moretti

Özer Özdal

Cross-fertilising extra gauge boson searches at the LHC

Tensor Networks are non-trivial representations of high-dimensional tensors, originally designed to describe quantum many-body systems. We show that Tensor Networks are ideal vehicles to connect quantum mechanical concepts to machine learning techniques, thereby facilitating an improved interpretability of neural networks. This study presents the discrimination of top quark signal over QCD background processes using a Matrix Product State classifier. We show that entanglement entropy can be used to interpret what a network learns, which can be used to reduce the complexity of the network and feature space without loss of generality or performance. For the optimisation of the network, we compare the Density Matrix Renormalization Group (DMRG) algorithm to stochastic gradient descent (SGD) and propose a joined training algorithm to harness the explainability of DMRG with the efficiency of SGD.

Michael Spannowsky

Quantum-inspired event reconstruction with Tensor Networks: Matrix Product States

Ensemble learning is a technique where multiple component learners are combined through a protocol. We propose an Ensemble Neural Network (ENN) that uses the combined latent-feature space of multiple neural network classifiers to improve the representation of the network hypothesis. We apply this approach to construct an ENN from Convolutional and Recurrent Neural Networks to discriminate top-quark jets from QCD jets. Such ENN provides the flexibility to improve the classification beyond simple prediction combining methods by linking different sources of error correlations, hence improving the representation between data and hypothesis. In combination with Bayesian techniques, we show that it can reduce epistemic uncertainties and the entropy of the hypothesis by simultaneously exploiting various kinematic correlations of the system, which also makes the network less susceptible to a limitation in training sample size.

Combine and conquer: event reconstruction with Bayesian Ensemble Neural Networks

We introduce a new simplified fast detector simulator in the MadAnalysis 5 platform. The Python-like interpreter of the programme has been augmented by new commands allowing for a detector parametrisation through smearing and efficiency functions. On run time, an associated C++ code is automatically generated and executed to produce reconstructed-level events. In addition, we have extended the MadAnalysis 5 recasting infrastructure to support our detector emulator, and we provide predefined LHC detector configurations. We have compared predictions obtained with our approach to those resulting from the usage of the Delphes 3 software, both for Standard Model processes and a few new physics signals. Results generally agree to a level of about 10% or better, the largest differences in the predictions stemming from the different strategies that are followed to model specific detector effects. Equipped with these new functionalities, MadAnalysis 5 now offers a new user-friendly way to include detector effects when analysing collider events, the simulation of the detector and the analysis being both handled either through a set of intuitive Python commands or directly within the C++ core of the platform.

Georgios Polykratis

Simplified fast detector simulation in MadAnalysis 5

We study the production of Higgs bosons at high transverse momenta via vector-boson fusion (VBF) in the Standard Model Effective Field Theory (SMEFT). We find that contributions from four independent operator combinations dominate in this limit. These are the same ‘high energy primaries’ that control high energy diboson processes, including Higgs-strahlung. We perform detailed collider simulations for the diphoton decay mode of the Higgs boson as well as the three final states arising from the ditau channel. Using the quadratic growth of the SMEFT contributions relative to the Standard Model (SM) contribution, we project very stringent bounds on these operators that far surpass the corresponding bounds from the LEP experiment.

CERN

Shankha Banerjee

Rick Gupta

Precision SMEFT bounds from the VBF Higgs at high transverse momentum

The MadAnalysis 5 framework can be used to assess the potential of various LHC analyses for unraveling any specific new physics signal. We present an extension of the LHC reinterpretation capabilities of the programme allowing for the inclusion of theoretical and systematical uncertainties on the signal in the reinterpretation procedure. We have implemented extra methods dedicated to the extrapolation of the impact of a given analysis to higher luminosities, including various options for the treatment of the errors. As an application, we study three classes of new physics models. We first focus on a simplified model in which the Standard Model is supplemented by a gluino and a neutralino. We show that uncertainties could in particular degrade the bounds by several hundreds of GeV when considering 3000/fb of future LHC data. We next investigate another supersymmetry-inspired simplified model, in which the Standard Model is extended by a first generation squark species and a neutralino. We reach similar conclusions. Finally, we study a class of s-channel dark matter setups and compare the expectation for two types of scenarios differing in the details of the implementation of the mediation between the dark and Standard Model sectors.