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Artificial Intelligence is poised to transform the design of complex, large-scale detectors like ePIC at the future Electron Ion Collider. Featuring a central detector with additional detecting systems in the far forward and far backward regions, the ePIC experiment incorporates numerous design parameters and objectives, including performance, physics reach, and cost, constrained by mechanical and geometric limits.This project aims to develop a scalable, distributed AI-assisted detector design for the EIC (AID(2)E), employing state-of-the-art multiobjective optimization to tackle complex designs. Supported by the ePIC software stack and usingGeant4simulations, our approach benefits from transparent parameterization and advanced AI features.The workflow leverages the PanDA and iDDS systems, used in major experiments such as ATLAS at CERN LHC, the Rubin Observatory, and sPHENIX at RHIC, to manage the compute intensive demands of ePIC detector simulations. Tailored enhancements to the PanDA system focus on usability, scalability, automation, and monitoring.Ultimately, this project aims to establish a robust design capability, apply a distributed AI-assisted workflow to the ePIC detector, and extend its applications to the design of the second detector (Detector-2) in the EIC, as well as to calibration and alignment tasks. Additionally, we are developing advanced data science tools to efficiently navigate the complex, multidimensional trade-offs identified through this optimization process.

 

Abstract. Processing Earth observation data modelled in a time-series of raster format is critical to solving some of the most complex problems in geospatial science ranging from climate change to public health. Researchers are increasingly working with these large raster datasets that are often terabytes in size. At this scale, traditional GIS methods may fail to handle the processing, and new approaches are needed to analyse these datasets. The objective of this work is to develop methods to interactively analyse big raster datasets with the goal of most efficiently extracting vector data over specific time periods from any set of raster data. In this paper, we describe RINX (Raster INformation eXtraction) which is an end-to-end solution for automatic extraction of information from large raster datasets. RINX heavily utilises open source geospatial techniques for information extraction. It also complements traditional approaches with state-of-the- art high-performance computing techniques. This paper discusses details of achieving big temporal data extraction with RINX, implemented on the use case of air quality and climate data extraction for long term health studies, which includes methods used, code developed, processing time statistics, project conclusions, and next steps. 

A search for leptoquark pair production decaying into$$te^- \bar{t}e^+$$$t{e}^{-}\overline{t}{e}^{+}$or$$t\mu ^- \bar{t}\mu ^+$$$t{\mu }^{-}\overline{t}{\mu }^{+}$in final states with multiple leptons is presented. The search is based on a dataset ofppcollisions at$$\sqrt{s}=13~\text {TeV} $$$\sqrt{s}=13\text{TeV}$recorded with the ATLAS detector during Run 2 of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb$$^{-1}$$$_{}^{-1}$. Four signal regions, with the requirement of at least three light leptons (electron or muon) and at least two jets out of which at least one jet is identified as coming from ab-hadron, are considered based on the number of leptons of a given flavour. The main background processes are estimated using dedicated control regions in a simultaneous fit with the signal regions to data. No excess above the Standard Model background prediction is observed and 95% confidence level limits on the production cross section times branching ratio are derived as a function of the leptoquark mass. Under the assumption of exclusive decays into$$te^{-}$$$t{e}^{-}$($$t\mu ^{-}$$$t{\mu }^{-}$), the corresponding lower limit on the scalar mixed-generation leptoquark mass$$m_{\textrm{LQ}_{\textrm{mix}}^{\textrm{d}}}$$$m_{{\text{LQ}}_{\text{mix}}^{\text{d}}}$is at 1.58 (1.59) TeV and on the vector leptoquark mass$$m_{{\tilde{U}}_1}$$$m_{{\tilde{U}}_1}$at 1.67 (1.67) TeV in the minimal coupling scenario and at 1.95 (1.95) TeV in the Yang–Mills scenario.

 

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).

 

A search for high-mass resonances decaying into a$\tau$-lepton and a neutrino using proton-proton collisions at a center-of-mass energy of$\sqrt{s}=13\mathrm{TeV}$is presented. The full run 2 data sample corresponding to an integrated luminosity of$139{\mathrm{fb}}^{-1}$recorded by the ATLAS experiment in the years 2015–2018 is analyzed. The$\tau$-lepton is reconstructed in its hadronic decay modes and the total transverse momentum carried out by neutrinos is inferred from the reconstructed missing transverse momentum. The search for new physics is performed on the transverse mass between the$\tau$-lepton and the missing transverse momentum. No excess of events above the Standard Model expectation is observed and upper exclusion limits are set on the$W^{\prime }\to \tau \nu$production cross section. Heavy$W^{\prime }$vector bosons with masses up to 5.0 TeV are excluded at 95% confidence level, assuming that they have the same couplings as the Standard Model$W$boson. For nonuniversal couplings,$W^{\prime }$bosons are excluded for masses less than 3.5–5.0 TeV, depending on the model parameters. In addition, model-independent limits on the visible cross section times branching ratio are determined as a function of the lower threshold on the transverse mass of the$\tau$-lepton and missing transverse momentum.

A summary of the constraints from searches performed by the ATLAS collaboration for the electroweak production of charginos and neutralinos is presented. Results from eight separate ATLAS searches are considered, each using 140 fb⁻¹of proton-proton data at a centre-of-mass energy of$$ \sqrt{s} $$$\sqrt{s}$= 13 TeV collected at the Large Hadron Collider during its second data-taking run. The results are interpreted in the context of the 19-parameter phenomenological minimal supersymmetric standard model, whereR-parity conservation is assumed and the lightest supersymmetric particle is assumed to be the lightest neutralino. Constraints from previous electroweak, flavour and dark matter related measurements are also considered. The results are presented in terms of constraints on supersymmetric particle masses and are compared with limits from simplified models. Also shown is the impact of ATLAS searches on parameters such as the dark matter relic density and the spin-dependent and spin-independent scattering cross-sections targeted by direct dark matter detection experiments. The Higgs boson andZboson ‘funnel regions’, where a low-mass neutralino would not oversaturate the dark matter relic abundance, are almost completely excluded by the considered constraints. Example spectra for non-excluded supersymmetric models with light charginos and neutralinos are also presented.

 

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.