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Ascomycota, the most speciose phylum of fungi, is a complex entity, comprising three diversesubphyla: Pezizomycotina, Saccharomycotina, and Taphrinomycotina. The largest and most diversesubphylum, Pezizomycotina, is a rich tapestry of 16 classes and 171 orders. Saccharomycotina, thesecond largest subphylum, is a diverse collection of seven classes and 12 orders, whileTaphrinomycotina, the smallest, is a unique assembly of six classes and six orders. Over the pastdecade, numerous taxonomic studies have focused on the generic, family, and class classifications ofAscomycota. These efforts, well-documented across various databases, are crucial for acomprehensive understanding of the classification. However, the study of taxonomy at the ordinallevel, a crucial tier in the taxonomic hierarchy, has been largely overlooked. In a global collaborationwith mycologists and lichenologists, this study presents the first comprehensive information on theorders within Pezizomycotina and Taphrinomycotina. The recent taxonomic classification ofSaccharomycotina has led to the exclusion of this subphylum from the present study, as an immediaterevision is not necessary. Each order is thoroughly discussed, highlighting its historical significance,current status, key identification characteristics, evolutionary relationships, ecological and economicroles, future recommendations, and updated family-level classification. Teaching diagrams for thelife cycles of several orders, viz. Asterinales, Helotiales, Hypocreales, Laboulbeniales, Meliolales,Mycosphaerellales, Ophiostomatales, Pezizales, Pleosporales, Phyllachorales, Rhytismatales,Sordariales, Venturiales, Xylariales (Pezizomycotina) and Pneumocystidales,Schizosaccharomycetales and Taphrinales (Taphrinomycotina) are provided. Each diagram is explained with a representative genus/genera of their sexual and asexual cycles of each order. WithinPezizomycotina, Dothideomycetes contains the highest number of orders, with 57, followed bySordariomycetes (52 orders), Lecanoromycetes (21 orders), Eurotiomycetes and Leotiomycetes (12orders each), Laboulbeniomycetes (3 orders), and Arthoniomycetes and Xylonomycetes (2 orderseach). Candelariomycetes, Coniocybomycetes, Geoglossomycetes, Lichinomycetes, Orbiliomycetes,Pezizomycetes, Sareomycetes, and Xylobotryomycetes each contain a single order, whileThelocarpales and Vezdaeales are treated as incertae sedis within Pezizomycotina. Notably, theclasses Candelariomycetes, Coniocybomycetes, Geoglossomycetes, Sareomycetes, andXylonomycetes, all recently grouped under Lichinomycetes, are treated as separate classes based onphylogenetic analysis and current literature. Within Lecanoromycetes, the synonymization ofSporastatiales with Rhizocarpales and Sarrameanales with Schaereriales is not supported in thephylogenetic analysis. These orders are retained separately, and the justifications are provided undereach section as well as in the discussion. Within Leotiomycetes, the order Medeolariales, which wasonce considered part of Helotiales, is treated as a distinct order based on phylogenetic evidence. Theclassification of Medeolariales may change as more data becomes available from different generegions. Lahmiales (Leotiomycetes) is not included in the phylogenetic analysis due to a lack ofmolecular data. Sareomycetes and Xylonomycetes are treated as separate classes. Spathulosporamixed with Lulworthiales and the inclusion of Spathulosporales within Lulworthiomycetidae issupported and extant molecular sampling is important to resolve the phylogenetic boundaries ofmembers of this subclass. The majority of the classes of Pezizomycotina and Taphrinomycotinaformed monophyletic clades in the phylogenetic analysis conducted based on SSU, LSU, 5.8S, TEFand RPB2 sequence data. However, Arthoniomycetes nested with the basal lineage ofDothideomycetes and formed a monophyletic clade also known as the superclass, Dothideomyceta.In Taphrinomycotina, a single order is accepted within each class. 

A combination of searches for singly and doubly charged Higgs bosons, 𝐻± and 𝐻±±, produced via vector-boson fusion is performed using 140 fb−1 of proton–proton collisions at a centre-of-mass energy of 13 TeV, collected with the ATLAS detector during Run 2 of the Large Hadron Collider. Searches targeting decays to massive vector bosons in leptonic final states (electrons or muons) are considered. New constraints are reported on the production cross section times branching fraction for charged Higgs boson masses between 200 GeV and 3000 GeV. The results are interpreted in the context of the Georgi-Machacek model for which the most stringent constraints to date are set for the masses considered in the combination. 

Abstract The ATLAS trigger system is a crucial component of the ATLAS experiment at the LHC. It is responsible for selecting events in line with the ATLAS physics programme. This paper presents an overview of the changes to the trigger and data acquisition system during the second long shutdown of the LHC, and shows the performance of the trigger system and its components in the proton-proton collisions during the 2022 commissioning period as well as its expected performance in proton-proton and heavy-ion collisions for the remainder of the third LHC data-taking period (2022–2025). 

Abstract The ATLAS detector is installed in its experimental cavern at Point 1 of the CERN Large Hadron Collider. During Run 2 of the LHC, a luminosity of  ℒ = 2 × 10³⁴cm^-2s^-1was routinely achieved at the start of fills, twice the design luminosity. For Run 3, accelerator improvements, notably luminosity levelling, allow sustained running at an instantaneous luminosity of  ℒ = 2 × 10³⁴cm^-2s^-1, with an average of up to 60 interactions per bunch crossing. The ATLAS detector has been upgraded to recover Run 1 single-lepton trigger thresholds while operating comfortably under Run 3 sustained pileup conditions. A fourth pixel layer 3.3 cm from the beam axis was added before Run 2 to improve vertex reconstruction and b-tagging performance. New Liquid Argon Calorimeter digital trigger electronics, with corresponding upgrades to the Trigger and Data Acquisition system, take advantage of a factor of 10 finer granularity to improve triggering on electrons, photons, taus, and hadronic signatures through increased pileup rejection. The inner muon endcap wheels were replaced by New Small Wheels with Micromegas and small-strip Thin Gap Chamber detectors, providing both precision tracking and Level-1 Muon trigger functionality. Trigger coverage of the inner barrel muon layer near one endcap region was augmented with modules integrating new thin-gap resistive plate chambers and smaller-diameter drift-tube chambers. Tile Calorimeter scintillation counters were added to improve electron energy resolution and background rejection. Upgrades to Minimum Bias Trigger Scintillators and Forward Detectors improve luminosity monitoring and enable total proton-proton cross section, diffractive physics, and heavy ion measurements. These upgrades are all compatible with operation in the much harsher environment anticipated after the High-Luminosity upgrade of the LHC and are the first steps towards preparing ATLAS for the High-Luminosity upgrade of the LHC. This paper describes the Run 3 configuration of the ATLAS detector. 

Abstract The identification of jets originating from quarks and gluons, often referred to as quark/gluon tagging, plays an important role in various analyses performed at the Large Hadron Collider, as Standard Model measurements and searches for new particles decaying to quarks often rely on suppressing a large gluon-induced background. This paper describes the measurement of the efficiencies of quark/gluon taggers developed within the ATLAS Collaboration, usingTeV proton–proton collision data with an integrated luminosity of 140 fbcollected by the ATLAS experiment. Two taggers with high performances in rejecting jets from gluon over jets from quarks are studied: one tagger is based on requirements on the number of inner-detector tracks associated with the jet, and the other combines several jet substructure observables using a boosted decision tree. A method is established to determine the quark/gluon fraction in data, by using quark/gluon-enriched subsamples defined by the jet pseudorapidity. Differences in tagging efficiency between data and simulation are provided for jets with transverse momentum between 500 GeV and 2 TeV and for multiple tagger working points.