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At least 991 records · Page 55

Dysregulation of lung epithelial cell homeostasis and immunity contributes to Middle East respiratory syndrome coronavirus disease severity

Coronaviruses (CoV) emerge suddenly from animal reservoirs to cause novel diseases in new hosts. Discovered in 2012, the Middle East respiratory syndrome coronavirus (MERS-CoV) is endemic in camels in the Middle East and is continually causing local outbreaks and epidemics. While all three newly emerging human CoVs from the past 20 years (SARS-CoV, SARS-CoV-2, and MERS-CoV) cause respiratory disease, each CoV has unique host interactions that drive differential pathogeneses. To better understand the virus and host interactions driving lethal MERS-CoV infection, we performed a longitudinal multi-omics analysis of sublethal and lethal MERS-CoV infection in mice. Significant differences were observed in body weight loss, virus titers, and acute lung injury among lethal and sub-lethal virus doses. Virus-induced apoptosis of type I and II alveolar epithelial cells suggests that loss or dysregulation of these key cell populations was a major driver of severe disease. Omics analysis suggested differential pathogenesis was multi-factorial with clear differences among innate and adaptive immune pathways as well as those that regulate lung epithelial homeostasis. Infection of mice lacking functional T and B cells showed that adaptive immunity was important in controlling viral replication but also increased pathogenesis. In summary, we provide a high-resolution host response atlas for MERS-CoV infection and disease severity. Multi-omics studies of viral pathogenesis offer a unique opportunity to not only better understand the molecular mechanisms of disease but also to identify genes and pathways that can be exploited for therapeutic intervention all of which is important for our future pandemic preparedness.

MERS-CoV↗

Measurements of the Higgs boson inclusive and differential fiducial cross sections in the 4$\ell$ decay channel at $\sqrt{s}$ = 13 TeV

Inclusive and differential fiducial cross sections of the Higgs boson are measured in the H → Z Z * → 4 ℓ ( ℓ = e , μ ) decay channel. The results are based on proton-proton collision data produced at the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector from 2015 to 2018, equivalent to an integrated luminosity of 139 $\hbox {fb}^{-1}$ fb - 1 . The inclusive fiducial cross section for the H → Z Z * → 4 ℓ process is measured to be σ fid = 3.28 ± 0.32 fb, in agreement with the Standard Model prediction of σ fid , SM = 3.41 ± 0.18 fb. Differential fiducial cross sections are measured for a variety of observables which are sensitive to the production and decay of the Higgs boson. All measurements are in agreement with the Standard Model predictions. The results are used to constrain anomalous Higgs boson interactions with Standard Model particles.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Calorimetry with deep learning: particle simulation and reconstruction for collider physics

Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of single isolated particles produced in high-energy physics collisions. We train neural networks on single-particle shower data at the calorimeter-cell level, and show significant improvements for simulation and reconstruction when using these networks compared to methods which rely on currently-used state-of-the-art algorithms. We define two models: an end-to-end reconstruction network which performs simultaneous particle identification and energy regression of particles when given calorimeter shower data, and a generative network which can provide reasonable modeling of calorimeter showers for different particle types at specified angles and energies. We investigate the optimization of our models with hyperparameter scans. Furthermore, we demonstrate the applicability of the reconstruction model to shower inputs from other detector geometries, specifically ATLAS-like and CMS-like geometries. These networks can serve as fast and computationally light methods for particle shower simulation and reconstruction for current and future experiments at particle colliders.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance of a geometric deep learning pipeline for HL-LHC particle tracking

The Exa.TrkX project has applied geometric learning concepts such as metric learning and graph neural networks to HEP particle tracking. Exa.TrkX’s tracking pipeline groups detector measurements to form track candidates and filters them. The pipeline, originally developed using the TrackML dataset (a simulation of an LHC-inspired tracking detector), has been demonstrated on other detectors, including DUNE Liquid Argon TPC and CMS High-Granularity Calorimeter. This paper documents new developments needed to study the physics and computing performance of the Exa.TrkX pipeline on the full TrackML dataset, a first step towards validating the pipeline using ATLAS and CMS data. The pipeline achieves tracking efficiency and purity similar to production tracking algorithms. Crucially for future HEP applications, the pipeline benefits significantly from GPU acceleration, and its computational requirements scale close to linearly with the number of particles in the event.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

The diphoton $$q_T$$ spectrum at N$$^3$$LL$$^\prime $$ + NNLO

Abstract We present a $$q_T$$ q T -resummed calculation of diphoton production at order N $$^3$$ 3 LL $$^\prime $$ ′ + NNLO. To reach the primed level of accuracy we have implemented the recently published three-loop $${\mathcal {O}}(\alpha _s^3)$$ O ( α s 3 ) virtual corrections in the $$q\bar{q}$$ q q ¯ channel and the three-loop transverse momentum dependent beam functions and combined them with the existing infrastructure of , a code performing resummation at order N $${}^3$$ 3 LL. While the primed predictions are parametrically not more accurate, one typically observes from lower orders and other processes that they are the dominant effect of the next order. We include in both the $$q\bar{q}$$ q q ¯ and loop-induced gg channel the hard contributions consistently together at order $$\alpha _s^3$$ α s 3 and find that the resummed $$q\bar{q}$$ q q ¯ channel without matching stabilizes indeed. Due to large matching corrections and large contributions and uncertainties from the gg channel, the overall improvements are small though. We furthermore study the effect of hybrid-cone photon isolation and hard-scale choice on our fully matched results to describe the ATLAS $$\text {8}$$ 8 TeV data and find that the hybrid-cone isolation worsens agreement at small $$q_T$$ q T compared to smooth-cone isolation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

New physics in rare B decays after Moriond 2021

Abstract The anomalies in rare B decays endure. We present results of an updated global analysis that takes into account the latest experimental input – in particular the recent results on $$R_K$$ R K and BR $$(B_s \rightarrow \mu ^+\mu ^-)$$ ( B s → μ + μ - ) – and that qualitatively improves the treatment of theory uncertainties. Fit results are presented for the Wilson coefficients of four-fermion contact interactions. We find that muon specific Wilson coefficients $$C_9 \simeq -0.73$$ C 9 ≃ - 0.73 or $$C_9 = -C_{10} \simeq -0.39$$ C 9 = - C 10 ≃ - 0.39 continue to give an excellent description of the data. If only theoretically clean observables are considered, muon specific $$C_{10} \simeq 0.60$$ C 10 ≃ 0.60 or $$C_9=-C_{10} \simeq -0.35$$ C 9 = - C 10 ≃ - 0.35 improve over the Standard Model by $$\sqrt{\Delta \chi ^2} \simeq 4.7\sigma $$ Δ χ 2 ≃ 4.7 σ and $$\sqrt{\Delta \chi ^2} \simeq 4.6\sigma $$ Δ χ 2 ≃ 4.6 σ , respectively. In various new physics scenarios we provide predictions for lepton flavor universality observables and CP asymmetries that can be tested with more data. We update our previous combination of ATLAS, CMS, and LHCb data on BR $$(B_s \rightarrow \mu ^+\mu ^-)$$ ( B s → μ + μ - ) and BR $$(B^0\rightarrow \mu ^+\mu ^-)$$ ( B 0 → μ + μ - ) taking into account the full two-dimensional non-Gaussian experimental likelihoods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Accelerating $\mathrm{LHC}$ event generation with simplified pilot runs and fast $\mathrm{PDF}$s

Poor computing efficiency of precision event generators for LHC physics has become a bottleneck for Monte-Carlo event simulation campaigns. We provide solutions to this problem by focusing on two major components of general-purpose event generators: The PDF evaluator and the matrix-element generator. For a typical production setup in the ATLAS experiment, we show that the two can consume about 80% of the total runtime. Using NLO simulations of pp→ℓ + ℓ - +jets and pp→$t\bar{t}$+jets as an example, we demonstrate that the computing footprint of LHAPDF and SHERPA can be reduced by factors of order 10, while maintaining the formal accuracy of the event sample. The improved codes are made publicly available.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurements of $W^{+}W^{-}$ production in decay topologies inspired by searches for electroweak supersymmetry

This paper presents a measurement of fiducial and differential cross-sections for $W$ + $W$ - production in proton–proton collisions at $\sqrt{s}$ = $13$ TeV with the ATLAS experiment at the Large Hadron Collider using a dataset corresponding to an integrated luminosity of 139 fb -1 . Events with exactly one electron, one muon and no hadronic jets are studied. The fiducial region in which the measurements are performed is inspired by searches for the electroweak production of supersymmetric charginos decaying to two-lepton final states. The selected events have moderate values of missing transverse momentum and the ‘stransverse mass’ variable $m$ T2 , which is widely used in searches for supersymmetry at the LHC. The ranges of these variables are chosen so that the acceptance is enhanced for direct $W$ + $W$ - production and suppressed for production via top quarks, which is treated as a background. The fiducial cross-section and particle-level differential cross-sections for six variables are measured and compared with two theoretical SM predictions from perturbative QCD calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for Majorana neutrinos in same-sign WW scattering events from pp collisions at $\sqrt{s}=13$ TeV

A search for Majorana neutrinos in same-sign WW scattering events is presented. The analysis uses $\sqrt{s}=13$ TeV proton–proton collision data with an integrated luminosity of 140 fb -1 recorded during 2015–2018 by the ATLAS detector at the Large Hadron Collider. The analysis targets final states including exactly two same-sign muons and at least two hadronic jets well separated in rapidity. The modelling of the main backgrounds, from Standard Model same-sign WW scattering and WZ production, is constrained with data in dedicated signal-depleted control regions. The distribution of the transverse momentum of the second-hardest muon is used to search for signals originating from a heavy Majorana neutrino with a mass between 50 GeV and 20 TeV. No significant excess is observed over the background expectation. The results are interpreted in a benchmark scenario of the Phenomenological Type-I Seesaw model. In addition, the sensitivity to the Weinberg operator is investigated. Upper limits at the 95% confidence level are placed on the squared muon-neutrino–heavy-neutrino mass-mixing matrix element |V μN | 2 as a function of the heavy Majorana neutrino’s mass m N , and on the effective μμ Majorana neutrino mass |m μμ |.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of the inclusive isolated-photon production cross section in pp and Pb–Pb collisions at $\mathbf {\sqrt{\textit{s}_{NN }} = 5.02}$ TeV

The ALICE Collaboration at the CERN LHC has measured the inclusive production cross section of isolated photons at midrapidity as a function of the photon transverse momentum (p$^{γ}_{T}$), in Pb–Pb collisions in different centrality intervals, and in pp collisions, at centre-of-momentum energy per nucleon pair of $\sqrt{s_{NN}}$ = 5.02 TeV. The photon transverse momentum range is between 10–14 and 40–140 GeV/c, depending on the collision system and on the Pb–Pb centrality class. The result extends to lower p$^{γ}_{T}$ than previously published results by the ATLAS and CMS experiments at the same collision energy. The covered pseudorapidity range is |η γ | < 0.67. The isolation selection is based on a charged particle isolation momentum threshold p$^{iso, ch}_{T}$ GeV/c within a cone of radii R = 0.2 and 0.4. The nuclear modification factor is calculated and found to be consistent with unity in all centrality classes, and also consistent with the HG-PYTHIA model, which describes the event selection and geometry biases that affect the centrality determination in peripheral Pb–Pb collisions. The measurement is compared to next-to-leading order perturbative QCD calculations and to the measurements of isolated photons and Z 0 bosons from the CMS experiment, which are all found to be in agreement.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Status of weak scale supersymmetry after LHC Run 2 and ton-scale noble liquid WIMP searches

After completion of LHC Run 2, the ATLAS and CMS experiments had collected of order 139 fb –1 of data at √s = 13 TeV. While discovering a very Standard Model-like Higgs boson of mass m h ≃ 125 GeV, no solid signal for physics beyond the Standard Model has emerged so far at LHC. In addition, no WIMP signals have emerged so far at ton-scale noble liquid WIMP search experiments. For the case of weak scale supersymmetry (SUSY), which is touted as a simple and elegant solution to the gauge hierarchy problem and likely low energy limit of compactified string theory, LHC has found rather generally that gluinos are beyond about 2.2 TeV whilst top squark must lie beyond 1.1 TeV. These limits contradict older simplistic notions of naturalness that emerged in the 1980s–1990s, leading to the rather pessimistic view that SUSY is now excluded except for perhaps some remaining narrow corners of parameter space. Yet, this picture ignores several important developments in SUSY/string theory that emerged in the 21st century: 1. the emergence of the string theory landscape and its solution to the cosmological constant problem, 2. a more nuanced view of naturalness including the notion of “stringy naturalness”, 3. the emergence of anomaly-free discrete R-symmetries and their connection to R-parity, Peccei-Quinn symmetry, the SUSY μ problem and proton decay and 4. the importance of including a solution to the strong CP problem. Rather general considerations from the string theory landscape favor large values of soft terms, subject to the vacuum selection criteria that electroweak symmetry is properly broken (no charge and/or color breaking (CCB) minima) and the resulting magnitude of the weak scale is not too far from our measured value. Then stringy naturalness predicts a Higgs mass m h ~ 125 GeV whilst sparticle masses are typically lifted beyond present LHC bounds. Lastly, in light of these refinements in theory perspective confronted by LHC and dark matter search results, we review the most likely LHC, ILC and dark matter signatures that are expected to arise from weak scale SUSY as we understand it today.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Heavy-ion physics at the LHC

Heavy-ion collisions have been part of the programme of the LHC since its conception. The main nucleus–nucleus system is 208 82 + Pb + 208 82 + Pb . During the Runs 1 and 2, the LHC provided Pb+Pb collisions with centre-of-mass energy per nucleon pair √ s NN = 2.76 and 5.02 TeV, Xe+Xe with √ s NN = 5.44 TeV, and p+Pb with √ s NN = 5.02 and 8.16 TeV. The LHC performance with heavy-ion beams is described in Ref. 1. The ALICE detector was conceived to be dedicated to the study of heavy-ion collisions. The ATLAS and CMS experiments participated in the programme since the very beginning, and the LHCb experiment participated since the end of Run 1. Figure 1 shows event displays of Pb+Pb collisions from the four experiments.

Audurier, Benjamin↗

Scaling Resolution of Gigapixel Whole Slide Images Using Spatial Decomposition on Convolutional Neural Networks

Gigapixel images are prevalent in scientific domains ranging from remote sensing, and satellite imagery to microscopy, etc. However, training a deep learning model at the natural resolution of those images has been a challenge in terms of both, overcoming the resource limit (e.g. HBM memory constraints), as well as scaling up to a large number of GPUs. In this paper, we trained Residual neural Networks (ResNet) on 22,528 x 22,528-pixel size images using a distributed spatial decomposition method on 2,304 GPUs on the Summit Supercomputer. We applied our method on a Whole Slide Imaging (WSI) dataset from The Cancer Genome Atlas (TCGA) database. WSI images can be in the size of 100,000 x 100,000 pixels or even larger, and in this work we studied the effect of image resolution on a classification task, while achieving state-of-the-art AUC scores. Moreover, our approach doesn't need pixel-level labels, since we're avoiding patching from the WSI images completely, while adding the capability of training arbitrary large-size images. This is achieved through a distributed spatial decomposition method, by leveraging the non-block fat-tree interconnect network of the Summit architecture, which enabled GPU-to-GPU direct communication. Finally, detailed performance analysis results are shown, as well as a comparison with a data-parallel approach when possible.

Tsaris, Aristeidis (aris)↗

CGSim: A Simulation Framework for Large Scale Distributed Computing Environment

Large-scale distributed computing infrastructures such as the Worldwide LHC Computing Grid (WLCG) require comprehensive simulation tools for evaluating performance, testing new algorithms, and optimizing resource allocation strategies. However, existing simulators suffer from limited scalability, hardwired algorithms, lack of real-time monitoring, and inability to generate datasets suitable for modern machine learning approaches. We present CGSim, a simulation framework for large-scale distributed computing environments that addresses these limitations. Built upon the validated SimGrid simulation framework, CGSim provides high-level abstractions for modeling heterogeneous grid environments while maintaining accuracy and scalability. Key features include a modular plugin mechanism for testing custom workflow scheduling and data movement policies, interactive real-time visualization dashboards, and automatic generation of event-level datasets suitable for AI-assisted performance modeling. We demonstrate CGSim’s capabilities through a comprehensive evaluation using production ATLAS PanDA workloads, showing significant calibration accuracy improvements across WLCG computing sites. Scalability experiments show near-linear scaling for multi-site simulations, with distributed workloads achieving 6 × better performance compared to single-site execution. The framework enables researchers to simulate WLCG-scale infrastructures with hundreds of sites and thousands of concurrent jobs within practical time budget constraints on commodity hardware.

Vatsavai, Sairam Sri [Brookhaven National Laborato↗

Rare and Experimentally Challenging Supersymmetry Signatures

Supersymmetry has long played a central role in the search for physics beyond the Standard Model at colliders, providing a comprehensive and internally consistent framework for generating well-motivated experimental signatures. For more than 15 years of Large Hadron Collider (LHC) operation, the CMS and ATLAS Collaborations have achieved remarkable sensitivity to a wide range of supersymmetric signatures. Despite this unprecedented reach, no conclusive evidence for supersymmetry has emerged. If supersymmetry is nature's solution to outstanding questions in particle physics, it is necessarily challenging to find. In this article, we review supersymmetric signatures that are particularly rare or otherwise challenging, with a focus on searches at the LHC. We highlight experimental challenges related to detector constraints and analysis difficulties, in addition to model challenges in the interpretation and optimization of searches. Here, we also identify regions of signature space that remain comparatively unconstrained and therefore represent promising targets for future exploration.

Large Hadron Collider↗

Boson–Boson Interactions at the LHC

Vector boson scattering is a key production process to probe the electroweak symmetry breaking of the Standard Model and is one of the most important topics of the physics program for the HL-LHC since it involves both self-couplings of vector bosons and their coupling with the Higgs boson. If the Higgs mechanism is not the sole source of electroweak symmetry breaking, the scattering amplitude deviates from the Standard Model prediction at high scattering energy. Moreover, deviations may be detectable even if a New Physics scale is higher than the reach of direct searches. In this review, the most recent experimental measurements of the production cross sections of vector boson pairs in association with two jets in proton–proton collisions at $\sqrt{s}$ = 13 TeV at the LHC are reported, using data sets recorded by the ATLAS and CMS detectors. Applications to searches for New Physics, as well as prospects for measuring the electroweak vector boson scattering processes with larger data samples, are also summarized.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Automated CT registration, segmentation, and quantification (AutoCT) v1.0

Processing and analyzing brain imaging is crucial in both scientific development and clinical field. In this software package, we build a pipeline that integrates automatic registration, segmentation, and quantitative analysis for subjects' CT scans. Leveraging diffeomorphic transformations, we enable optimized forward and inverse mappings between an image and the reference. Furthermore, we extract localized features from deformation field based on an online template process, which advances statistical learning downstream. The created templates, atlas as well as our methods provide the brain imaging community tools for AI implementations.

Essiari, Abdelilah↗