We study ???? violation (CPV) in the sneutrino sector within the B-L extension of the minimal supersymmetric Standard Model, wherein an inverse seesaw mechanism has been implemented. CPV arises from the new superpotential couplings in the (s)neutrino sector, which can be complex and the mixing of ???? eigenstates induced by those couplings. CPV leads to asymmetries in so-called T-odd observables, but we argue that such asymmetries also lead to a wider distribution of those observables. We look at a final state where a sneutrino decays to a lepton, two jets, and missing transverse momentum at the Future Circular Collider operating in hadron-hadron mode at 100 TeV and with a luminosity of 3??ab-1. In order to exclude the ???? conserving scenario we need to improve traditional analysis by introducing boosted decision trees using both standard kinematic variables and T-odd observables and we need ??' boson not too much above current bounds as a portal to produce sneutrinos efficiently.

We study the generation of baryon asymmetry as well as dark matter (DM) in an extended reheating period after the end of slow-roll inflation. Within the regime of perturbative reheating, we consider different monomial potential of the inflaton field during reheating era. The inflaton condensate reheats the Universe by decaying into the Standard Model (SM) bath either via fermionic or bosonic decay modes. Assuming the leptogenesis route to baryogenesis in a canonical seesaw framework with three right handed neutrinos (RHN), we consider both the radiation bath and perturbative inflaton decay to produce such RHNs during the period of reheating when the maximum temperature of the SM bath is well above the reheating temperature. The DM, assumed to be a SM gauge singlet field, also gets produced from the bath during the reheating period via UV freeze-in. In addition to obtaining different parameter space for such nonthermal leptogenesis and DM for both bosonic and fermionic reheating modes and the type of monomial potential, we discuss the possibility of probing such scenarios via spectral shape of primordial gravitational waves. Published by the American Physical Society 2025

We define the notion of Tate–Shafarevich group and Selmer group of the Chow group of zero cycles of degree zero of an abelian variety defined over a global function field and prove that the Selmer group is finite

Interest in deep learning in collider physics has been growing in recent years, specifically in applying these methods in jet classification, anomaly detection, particle identification etc. Among those, jet classification using neural networks is one of the well-established areas. In this review, we discuss different tagging frameworks available to tag boosted objects, especially boosted Higgs boson and top quark, at the Large Hadron Collider (LHC). Our aim is to study the interplay of traditional jet substructure-based methods with the state-of-the-art machine learning ones. In this methodology, we would gain some interpretability of those machine learning methods, and which in turn helps to propose hybrid taggers relevant for tagging of those boosted objects belonging to both Standard Model (SM) and physics beyond the SM. © The Author(s), under exclusive licence to EDP Sciences, Springer-Verlag GmbH Germany, part of Springer Nature 2024.

Top tagging has emerged as a fast-evolving subject due to the top quark’s significant role in probing physics beyond the standard model. For the reconstruction of top jets, machine learning models have shown a substantial improvement in the classification performance compared to the previous methods. In this work, we build top taggers using N-Subjettiness ratios and several energy correlation observables as input features to train the eXtreme Gradient BOOSTed decision tree (XGBOOST). The study finds that tighter parton-level matching leads to more accurate tagging. However, in real experimental data, where the parton-level data are unknown, this matching cannot be done. We train the XGBOOST models without performing this matching and show that this difference impacts the taggers’ effectiveness. Additionally, we test the tagger under different simulation conditions, including changes in centre-of-mass energy, parton distribution functions (PDFs), and pileup effects, demonstrating its robustness with performance deviations of less than 1%. Furthermore, we use the SHapley Additive exPlanation (SHAP) framework to calculate the importance of the features of the trained models. It helps us to estimate how much each feature of the data contributed to the model’s prediction and what regions are of more importance for each input variable. Finally, we combine all the tagger variables to form a hybrid tagger and interpret the results using the Shapley values

We compare different jet-clustering algorithms in establishing fully hadronic final states stemming from the chain decay of a heavy Higgs state into a pair of the 125 GeV Higgs boson that decays into bottom-antibottom quark pairs. Such 4b events typically give rise to boosted topologies, wherein bb¯ pairs emerging from each 125 GeV Higgs boson tend to merge into a single, fat b-jet. Assuming large hadron collider (LHC) settings, we illustrate how both the efficiency of selecting the multi-jet final state and the ability to reconstruct from it the masses of all Higgs bosons depend on the choice of jet-clustering algorithm and its parameter settings. We indicate the optimal choice of clustering method for the purpose of establishing such a ubiquitous beyond the SM (BSM) signal, illustrated via a Type-II 2-Higgs Doublet Model (2HDM).

Boosted top quark tagging is one of the challenging, and at the same time exciting, tasks in high energy physics experiments, in particular in the exploration of new physics signals at the LHC. Several techniques have already been developed to tag a boosted top quark in its hadronic decay channel. Recently tagging the same in the semileptonic channel has begun to receive a lot of attention. In the current study, we develop a methodology to tag a boosted top quark (pT>200 GeV) in its semileptonic decay channel with a ?-lepton in the final state. In this analysis, the constituents of the top fatjet are reclustered using jet substructure technique to obtain the subjets, and then b- and ?- like subjets are identified by applying standard b- and ?-jet identification algorithms. We show that the dominant QCD background can be rejected effectively using several kinematic variables of these subjects, such as energy sharing among the jets, invariant mass, transverse mass, N-subjettiness etc., leading to high signal tagging efficiencies. We further assess possible improvements in the results by employing multivariate analysis techniques. We find that using this proposed top-tagger, a signal efficiency of ?77% against a background efficiency of ?3% can be achieved. We also extend the proposed top-tagger to the case of polarized top quarks by introducing a few additional observables calculated in the rest frame of the b-? system. We comment on how the same methodology will be useful for tagging a boosted heavy BSM particle with a b and ? in the final state.

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The detection of a single Higgs boson at the Large Hadron Collider (LHC) has allowed one to probe some properties of it, including the Yukawa and gauge couplings. However, in order to probe the Higgs potential, one has to rely on new production mechanisms, such as Higgs pair production. In this paper, we show that such a channel is also sensitive to the production and decay of a so-called 'flavon' field (HF), a new scalar state that arises in models that attempt to explain the hierarchy of the Standard Model (SM) fermion masses. Our analysis also focuses on the other decay channels involving the flavon particle, specifically the decay of the flavon to a pair of Z bosons (HF?ZZ) and the concurrent production of a top quark and charm quark via the ??tc decays (?=HF,AF), having one or more leptons in the final states. In particular, we show that, with 3000 fb-1 of accumulated data at 14 TeV (the Run 3 stage) of the LHC an heavy flavon HF with mass MHF?2mt can be explored with 3?-5? significance through these channels.

We assess the performance of different jet-clustering algorithms, in the presence of different resolution parameters and reconstruction procedures, in resolving fully hadronic final states emerging from the chain decay of the discovered Higgs boson into pairs of new identical Higgs states, the latter in turn decaying into bottom-antibottom quark pairs. We show that, at the large hadron collider (LHC), both the efficiency of selecting the multi-jet final state and the ability to reconstruct from it the masses of the Higgs bosons (potentially) present in an event sample depend strongly on the choice of acceptance cuts, jet-clustering algorithm as well as its settings. Hence, we indicate the optimal choice of the latter for the purpose of establishing such a benchmark Beyond the SM (BSM) signal. We then repeat the exercise for a heavy Higgs boson cascading into two SM-like Higgs states, obtaining similar results.

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We study displaced signatures of sneutrino pairs potentially emerging at the Large Hadron Collider (LHC) in a Next-to-Minimal Supersymmetric Standard Model supplemented with right-handed neutrinos triggering a Type-I seesaw mechanism. We show how such signatures can be established through a heavy Higgs portal, the sneutrinos then decaying to charged leptons and charginos giving rise to further leptons or hadrons. We finally illustrate how the Yukawa parameters of neutrinos can be extracted by measuring the lifetime of the sneutrino from the displaced vertices, thereby characterising the dynamics of the underlying mechanism of neutrino mass generation. We show our numerical results for the case of both the current and High-Luminosity LHC.