Related papers: ATLAS flavour-tagging algorithms for the LHC Run 2…
Results are presented of searches and measurements in the top quark sector by the ATLAS and CMS experiments. These analyses use data from proton-proton collisions at a centre-of-mass energy of 13 TeV, recorded during Run 2 at the Large…
This paper describes a study of techniques for identifying Higgs bosons at high transverse momenta decaying into bottom-quark pairs, $H \rightarrow b\bar{b}$, for proton-proton collision data collected by the ATLAS detector at the Large…
Heavy-flavor hadron production, in particular bottom hadron production, is difficult to study in deep-inelastic scattering (DIS) experiments due to small production rates and branching fractions. To overcome these limitations, a method for…
A measurement of the $B_s \rightarrow J/\psi \phi$ decay parameters, updated to include flavour tagging is reported using $4.9 fb^{-1}$ of integrated luminosity collected by the ATLAS detector from $\sqrt{s}= 7$TeV $pp$ collisions recorded…
This contribution summarises the results on heavy-flavour correlations and jets measured with ALICE detector. Studies of D$^{0}$-tagged jets are presented in various collision systems and energies. The measurement of the fraction of jet…
The search for first top-quark pair candidate events and the related background studies using data-driven techniques are reported for about 300 inverse nb of 7 TeV proton-proton collision data delivered by the Large Hadron Collider (LHC)…
The ATLAS experiment has successfully recorded over 300 nb^-1 of pp collisions at 7 TeV provided by the Large Hadron Collider, with an efficiency of 94%. We describe the data acquisition, trigger, reconstruction, calibration, monitoring,…
The application of machine learning (ML) in high energy physics (HEP), specifically in heavy-flavor jet tagging at Large Hadron Collider (LHC) experiments, has experienced remarkable growth and innovation in the past decade. This review…
Two machine learning techniques for jet measurements at the LHCb experiment are presented: a regression-based method for jet-energy calibration and a deep neural network algorithm for jet flavour tagging, distinguishing between $b$-quark,…
The identification of jets originating from beauty quarks in heavy-ion collisions is important to study the properties of the hot and dense matter produced in such collisions. A variety of algorithms for b-jet tagging was elaborated at the…
The ATLAS experiment relies on real-time hadronic jet reconstruction and $b$-tagging to record fully hadronic events containing $b$-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm…
Heavy flavour jet tagging is widely used in the determination of cross sections including the production of heavy flavoured quarks. This requires the knowledge of heavy and light flavour jet tagging efficiencies and their uncertainties. A…
This article reports on a search for dijet resonances using $132$ fb$^{-1}$ of $pp$ collision data recorded at $\sqrt{s} = 13$ TeV by the ATLAS detector at the Large Hadron Collider. The search is performed solely on jets reconstructed…
Identifying the flavour of neutral $B$ mesons production is one of the most important components needed in the study of time-dependent $CP$ violation. The harsh environment of the Large Hadron Collider makes it particularly hard to succeed…
A search for new heavy scalars with flavour-violating decays in final states with multiple leptons and $b$-tagged jets is presented. The results are interpreted in terms of a general two-Higgs-doublet model involving an additional scalar…
Jet flavor tagging is of utmost importance for unlocking the full physics potential of any future collider experiment. The performance of any jet flavor identification algorithm depends both on its underlying architecture and on the…
A search is presented for particles that decay producing a large jet multiplicity and invisible particles. The event selection applies a veto on the presence of isolated electrons or muons and additional requirements on the number of…
A new algorithm based on a deep neural network, DeepSets, for tagging the production flavour of neutral $B^0$ and $B^0_s$ mesons in proton-proton collisions is presented. Exploiting a comprehensive set of tracks associated with the…
Results of a search for the pair production of photon-jets$-$collimated groupings of photons$-$in the ATLAS detector at the Large Hadron Collider are reported. Highly collimated photon-jets can arise from the decay of new, highly boosted…
Jet flavour tagging is crucial in experimental high-energy physics. A tagging algorithm, DeepJetTransformer, is presented, which exploits a transformer-based neural network that is substantially faster to train than state-of-the-art graph…