Composite Higgs at high transverse momentum

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 field means that single-Higgs production via gluon fusion is insensitive to the mass spectrum of the top-partners. However in associated production this is not the case, and new physics scales may be probed. In the course of the work we consider scenarios with both one and two light top-partner multiplets in the spectrum of composite states. In compliance with perturbativity and experimental constraints, we study corrections to the Higgs couplings and the effects that the light top-partner multiplets have on the transverse momentum spectrum of the Higgs. Interestingly, we find that the corrections to the Standard Model expectation depend strongly on the representation of the top-partners in the global symmetry

Non-Custodial Warped Extra Dimensions at the LHC?

With the prospect of improved Higgs measurements at the LHC and at proposed future colliders such as ILC, CLIC and TLEP we study the non-custodial Randall-Sundrum model with bulk SM fields and compare brane and bulk Higgs scenarios. The latter bear resemblance to the well studied type III two-Higgs-doublet models. We compute the electroweak precision observables and argue that incalculable contributions to these, in the form of higher dimensional operators, could have an impact on the T-parameter. This could potentially reduce the bound on the lowest Kaluza-Klein gauge boson masses to the 5 TeV range, making them detectable at the LHC. In a second part, we compute the misalignment between fermion masses and Yukawa couplings caused by vector-like Kaluza-Klein fermions in this setup. The misalignment of the top Yukawa can easily reach 10%, making it observable at the high-luminosity LHC. Corrections to the bottom and tau Yukawa couplings can be at the percent level and detectable at ILC, CLIC or TLEP.Comment: 24 pages, 4 figures; v2: Typo in eq.48 fixed, references adde

Kaluza-Klein gravitons at LHC2

In this work we study constraints from new searches for heavy particles at the LHC on the allowed masses and couplings of a KK Graviton in a holographic composite Higgs model. Keeping new electroweak states heavy such that electroweak precision tests are satisfied, we control the mass of the lightest KK graviton using a brane kinetic term. With this we study KK graviton masses from 0.5-3 TeV. In our analysis we also employ Little Randall-Sundrum (RS) Models, characterised by a lower UV scale in the 5D model which in turn implies modified couplings to massless bulk fields. Viewing this scenario as a strongly coupled 4D theory with a composite Higgs boson, the KK graviton is interpreted as a composite spin-2 state and the varying UV scale corresponds to a varying intermediate scale between the cutoff of the low energy effective theory and the Planck scale. We find that KK gravitons with masses in the range 0.5-3 TeV are compatible with current collider constraints, where the most promising channels for detecting these states are the di-photon and ZZ channels. A detection is more likely in the little RS models, in which the dual gauge theory has a larger number of colours than in traditional RS models

Bump Hunting in Latent Space

Unsupervised anomaly detection could be crucial in future analyses searching for rare phenomena in large datasets, as for example collected at the LHC. To this end, we introduce a physics inspired variational autoencoder (VAE) architecture which performs competitively and robustly on the LHC Olympics Machine Learning Challenge datasets. We demonstrate how embedding some physical observables directly into the VAE latent space, while at the same time keeping the classifier manifestly agnostic to them, can help to identify and characterise features in measured spectra as caused by the presence of anomalies in a dataset.Comment: 5 pages, 4 figure

A Normalized Autoencoder for LHC Triggers

Autoencoders are an effective analysis tool for the LHC, as they represent one of its main goal of finding physics beyond the Standard Model. The key challenge is that out-of-distribution anomaly searches based on the compressibility of features do not apply to the LHC, while existing density-based searches lack performance. We present the first autoencoder which identifies anomalous jets symmetrically in the directions of higher and lower complexity. The normalized autoencoder combines a standard bottleneck architecture with a well-defined probabilistic description. It works better than all available autoencoders for top vs QCD jets and reliably identifies different dark-jet signals.Comment: 26 pages, 11 figures; update based on referees repor

Bayesian Probabilistic Modelling for Four-Tops at the LHC

Monte Carlo (MC) generators are crucial for analyzing data at hadron colliders, however, even a small mismatch between the MC simulations and the experimental data can undermine the interpretation of LHC searches in the SM and beyond. The jet multiplicity distributions used in four-top searches, one of the ultimate rare processes in the SM currently being explored at the LHC, makes $pp\to t\bar tt \bar t$ an ideal testing ground to explore for new ways to reduce the impact of MC mismodelling on such observables. In this Letter, we propose a novel weakly-supervised method capable of disentangling the $t\bar t t\bar t$ signal from the dominant background, while partially correcting for possible MC imperfections. A mixture of multinomial distributions is used to model the light-jet and $b$-jet multiplicities under the assumption that these are conditionally independent given a categorical latent variable. The signal and background distributions generated from a deliberately untuned MC simulator are used as model priors. The posterior distributions, as well as the signal fraction, are then learned from the data using Bayesian inference. We demonstrate that our method can mitigate the effects of large MC mismodellings using a realistic $t\bar tt\bar t$ search in the same-sign dilepton channel, leading to corrected posterior distributions that better approximate the underlying truth-level spectra.Comment: 5 pages, 3 figures, with supplementary material at https://github.com/ManuelSzewc/bayes-4top