Search

A search for heavy right-handed Majorana neutrinos is performed with the ATLAS detector at the CERN Large Hadron Collider, using the 140  fb−1 of proton–proton collision data at s=13  TeV collected during Run 2. This search targets tt¯ production, in which both top quarks decay into a bottom quark and a W boson, where one of the W bosons decays hadronically and the other decays into an electron or muon and a heavy neutral lepton. The heavy neutral lepton is identified through a decay into an electron or muon and another W boson, resulting in a pair of same-charge same-flavor leptons in the final state. This paper presents the first search for heavy neutral leptons in the mass range of 15–75 GeV using tt¯ events. No significant excess is observed over the background expectation, and upper limits are placed on the signal cross sections. Assuming a benchmark scenario of the phenomenological type-I seesaw model, these cross section limits are then translated into upper limits on the mixing parameters of the heavy Majorana neutrino with Standard Model neutrinos. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

IntroductionIdentifying low-cost, minimally-invasive screening instruments for Alzheimer's disease (AD) trial enrichment will improve the efficiency of AD trials.MethodsA total of 685 cognitively normal (CN) individuals and individuals with mild cognitive impairment (MCI) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were grouped according to cutoffs of genetic risk factor (G) polygenic hazard score (PHS) and tau pathology (T) plasma phosphorylated tau-181 (p-tau181) into four groups: G+T+, G-T-, G+T-, and G-T+. We assessed the associations between group level and longitudinal cognitive decline and AD conversion. Power analyses compared the estimated sample size required to detect differences in cognitive decline.ResultsThe G+T+ group was associated with faster cognitive decline and higher AD risk. Clinical trials enrolling G+T+ participants would benefit from significantly reduced sample sizes compared with similar trials using only single makers as an inclusion criterion.DiscussionThe combination of two low-cost, minimally-invasive measures-genetics and plasma biomarkers-would be a promising screening procedure for clinical trial enrollment.HighlightsParticipants with unimpaired or mildly impaired cognition were grouped based on cutoffs on genetic risk factors (G: polygenic hazardous score [PHS]) and Alzheimer's pathology (T: baseline plasma phosphorylated tau-181 [p-tau181]). Participants with high PHSs and plasma p-tau181 levels (G+T+) were at risk of faster cognitive decline and AD progression. The combination of PHS and plasma p-tau181 could enhance clinical trial enrichment more effectively than using single biomarkers.

Throughout adulthood and ageing our brains undergo structural loss in an average pattern resembling faster atrophy in Alzheimer's disease (AD). Using a longitudinal adult lifespan sample (aged 30-89; 2-7 timepoints) and four polygenic scores for AD, we show that change in AD-sensitive brain features correlates with genetic AD-risk and memory decline in healthy adults. We first show genetic risk links with more brain loss than expected for age in early Braak regions, and find this extends beyond APOE genotype. Next, we run machine learning on AD-control data from the Alzheimer's Disease Neuroimaging Initiative using brain change trajectories conditioned on age, to identify AD-sensitive features and model their change in healthy adults. Genetic AD-risk linked with multivariate change across many AD-sensitive features, and we show most individuals over age ~50 are on an accelerated trajectory of brain loss in AD-sensitive regions. Finally, high genetic risk adults with elevated brain change showed more memory decline through adulthood, compared to high genetic risk adults with less brain change. Our findings suggest quantitative AD risk factors are detectable in healthy individuals, via a shared pattern of ageing- and AD-related neurodegeneration that occurs along a continuum and tracks memory decline through adulthood.

AimsAnxiety disorders are prevalent and anxiety symptoms (ANX) co-occur with many psychiatric disorders. We aimed to identify genomic loci associated with ANX, characterize its genetic architecture, and genetic overlap with psychiatric disorders.MethodsWe included a genome-wide association study of ANX (meta-analysis of UK Biobank and Million Veterans Program, n = 301,732), schizophrenia (SCZ), bipolar disorder (BIP), major depression (MD), attention-deficit/hyperactivity disorder (ADHD), and autism spectrum disorder (ASD), and validated the findings in the Norwegian Mother, Father, and Child Cohort (n = 95,841). We employed the bivariate causal mixture model and local analysis of covariant association to characterize the genetic architecture including overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of loci associated with anxiety and shared with psychiatric disorders.ResultsAnxiety was polygenic with 12.9k genetic variants and overlapped extensively with psychiatric disorders (4.1k-11.4k variants) with predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 119 novel loci for anxiety by conditioning on the psychiatric disorders, and loci shared between anxiety and MD n=47 , BIP n=33 , SCZ n=71 , ADHD n=20 , and ASD n=5 . Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways including cell adhesion and neurofibrillary tangle compared with genes annotated to the shared loci.ConclusionsAnxiety is highly polygenic phenotype with extensive genetic overlap with psychiatric disorders, and we identified novel loci for anxiety implicating new molecular pathways. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified molecular underpinnings may lead to potential drug targets.

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pile-up) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two.

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques.

Our understanding of brain iron regulation and its disruption in disease is limited. Excess iron affects motor circuitry, contributing to Parkinson's disease (PD) risk. The molecular mechanisms regulating central iron levels, beyond a few well-known genes controlling peripheral iron, remain unclear. We generated scores based on the archetypal brain iron accumulation observed in magnetic resonance imaging scans of individuals with excessive dietary iron absorption and hemochromatosis risk. Genome-wide analysis revealed that this score is highly heritable, identifying loci associated with iron homeostasis, and driven by peripheral iron levels. Our score predicted gait abnormalities and showed a U-shaped relationship with PD risk, identifying individuals with threefold increased risk. These results establish a hormetic relationship between brain iron and PD risk, where central iron levels are strongly determined by genetics via peripheral iron. This framework combining forward and reverse genetics is a powerful study design to understand genomic drivers underlying high dimensional phenotypes.

Non-coding mutations in the TERT promoter (TERTp), typically at one of two bases -124 and -146 bp upstream of the start codon, are among the most prevalent driver mutations in human cancer. Several additional recurrent TERTp mutations have been reported but their functions and origins remain largely unexplained. Here, we show that atypical TERTp mutations arise secondary to canonical TERTp mutations in a two-step process. Canonical TERTp mutations create de novo binding sites for ETS family transcription factors that induce favourable conditions for DNA damage formation by UV light, thus creating a hotspot effect but only after a first mutational hit. In agreement, atypical TERTp mutations co-occur with canonical driver mutations in large cancer cohorts and arise subclonally specifically on the TERTp driver mutant chromosome homolog of melanoma cells treated with UV light in vitro. Our study gives an in-depth view of TERTp mutations in cancer and provides a mechanistic explanation for atypical TERTp mutations.

PurposeCognitive impairment is prevalent among individuals with epilepsy, and increasing evidence indicates that genetic factors can underlie this relationship. However, the extent to which epilepsy subtypes differ in their genetic relationship with cognitive function, and information about the specific genetic variants involved remain largely unknown.MethodsWe investigated the genetic relationship between epilepsies and general cognitive ability (COG) using complementary statistical tools, including linkage disequilibrium score (LDSC) regression, MiXeR and conjunctional false discovery rate (conjFDR). We analyzed genome-wide association study data on COG (n = 269,867) and common epilepsies (n = 27,559 cases, 42,436 controls), including the broad phenotypes 'all epilepsy', focal epilepsies and genetic generalized epilepsies (GGE), as well as specific subtypes. We functionally annotated the identified loci using several biological resources and validated the results in independent samples.ResultsUsing MiXeR, COG (11.2k variants) was estimated to be almost four times more polygenic than 'all epilepsy', GGE, juvenile myoclonic epilepsy (JME), and childhood absence epilepsy (CAE) (2.5k - 2.9k variants). The other epilepsy phenotypes were insufficiently powered for MiXeR analysis. We quantified extensive genetic overlap between COG and epilepsy types, but with varying negative genetic correlations (-0.23 to -0.04). COG was estimated to share 2.9k variants with both GGE and 'all epilepsy', and 2.3k variants with both JME and CAE. Using conjFDR, we identified 66 distinct loci shared between COG and epilepsies, including novel associations for GGE (27), 'all epilepsy' (5), JME (5) and CAE (5). The implicated genes were significantly expressed in multiple brain regions. The results were validated in independent samples (COG: p = 3.62 × 10-7; 'all epilepsy': p = 2.58 × 10-3).ConclusionOur study further dissects the substantial genetic basis shared between epilepsies and COG and identifies novel shared loci. An improved understanding of the genetic relationship between epilepsies and COG may lead to the development of novel comorbidity-targeted epilepsy treatments.

PurposeThe purpose of the present study is to develop a calibration method to account for differences in echo times (TE) and facilitate the use of restriction spectrum imaging restriction score (RSIrs) as a quantitative biomarker for the detection of clinically significant prostate cancer (csPCa).MethodsThis study included 197 consecutive patients who underwent MRI and biopsy examination; 97 were diagnosed with csPCa (grade group ≥ 2). RSI data were acquired three times during the same session: twice at minimum TE ~75 ms and once at TE = 90 ms (TEmin1, TEmin2, and TE90, respectively). A linear regression model was determined to match the C-maps of TE90 to the reference C-maps of TEmin1 within the interval ranging from 95th to 99th percentile of signal intensity within the prostate. RSIrs comparisons were made at the 98th percentile within each patient's prostate. We compared RSIrs from calibrated TE90 (RSIrsTE90corr) and uncorrected TE90 (RSIrsTE90) to RSIrs from reference TEmin1 (RSIrsTEmin1) and repeated TEmin2 (RSIrsTEmin2). Calibration performance was evaluated with sensitivity, specificity and area under the ROC curve (AUC).ResultsScaling factors for C1, C2, C3, and C4 were estimated as 1.68, 1.33, 1.02, and 1.13, respectively. In non-csPCa cases, the 98th percentile of RSIrsTEmin2 and RSIrsTEmin1 differed by 0.27 ± 0.86SI (mean ± standard deviation), whereas RSIrsTE90 differed from RSIrsTEmin1 by 1.82 ± 1.20SI. After calibration, this bias was reduced to -0.51 ± 1.21SI, representing a 72% reduction in absolute error. For patients with csPCa, the difference was 0.54 ± 1.98SI between RSIrsTEmin2 and RSIrsTEmin1 and 2.28 ± 2.06SI between RSIrsTE90 and RSIrsTEmin1. After calibration, the mean difference decreased to -1.03SI, a 55% reduction in absolute error. At the Youden index for patient-level classification of csPCa (8.94SI), RSIrsTEmin1 has a sensitivity of 66% and a specificity of 72%.ConclusionsThe proposed linear calibration method produces similar quantitative biomarker values for acquisitions with different TE, reducing TE-induced error by 72% and 55% for non-csPCa and csPCa, respectively.

A search is presented for direct pair production of the stop, the supersymmetric partner of the top quark, in a decay through an R-parity violating coupling to a charged lepton and a b-quark. The dataset corresponds to an integrated luminosity of 140  fb−1 of proton-proton collisions at a center-of-mass energy of s=13  TeV collected between 2015 and 2018 by the ATLAS detector at the LHC. The final state has two charged leptons (electrons or muons) and two b-jets. The results of the search are interpreted in the context of a Minimal Supersymmetric Standard Model with an additional B−L gauge symmetry that is spontaneously broken. No significant excess is observed over the Standard Model background, and exclusion limits on stop pair production are set at 95% confidence level. The corresponding lower limits on the stop mass for 100% branching ratios to a b-quark and an electron, muon, or tau-lepton are 1.9 TeV, 1.8 TeV and 800 GeV, respectively, extending the reach of previous LHC searches. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

A search for long-lived particles (LLPs) using 140  fb^{-1} of pp collision data with sqrt[s]=13  TeV recorded by the ATLAS experiment at the LHC is presented. The search targets LLPs with masses between 5 and 55 GeV that decay hadronically in the ATLAS inner detector. Benchmark models with LLP pair production from exotic decays of the Higgs boson and models featuring long-lived axionlike particles (ALPs) are considered. No significant excess above the expected background is observed. Upper limits are placed on the branching ratio of the Higgs boson to pairs of LLPs, the cross section for ALPs produced in association with a vector boson, and, for the first time, on the branching ratio of the top quark to an ALP and a u/c quark.

A search for the exclusive hadronic decays W^{±}→π^{±}γ, W^{±}→K^{±}γ, and W^{±}→ρ^{±}γ is performed using up to 140  fb^{-1} of proton-proton collisions recorded with the ATLAS detector at a center-of-mass energy of sqrt[s]=13  TeV. If observed, these rare processes would provide a unique test bench for the quantum chromodynamics factorization formalism used to calculate cross sections at colliders. Additionally, at future colliders, these decays could offer a new way to measure the W boson mass through fully reconstructed decay products. The search results in the most stringent upper limits to date on the branching fractions B(W^{±}→π^{±}γ)

Non-invasive prenatal testing (NIPT) employs ultra-low-pass sequencing of maternal plasma cell-free DNA to detect fetal trisomy. Its global adoption has established NIPT as a large human genetic resource for exploring genetic variations and their associations with phenotypes. Here, we present methods for analyzing large-scale, low-depth NIPT data, including customized algorithms and software for genetic variant detection, genotype imputation, family relatedness, population structure inference, and genome-wide association analysis of maternal genomes. Our results demonstrate accurate allele frequency estimation and high genotype imputation accuracy (R2>0.84) for NIPT sequencing depths from 0.1× to 0.3×. We also achieve effective classification of duplicates and first-degree relatives, along with robust principal-component analysis. Additionally, we obtain an R2>0.81 for estimating genetic effect sizes across genotyping and sequencing platforms with adequate sample sizes. These methods offer a robust theoretical and practical foundation for utilizing NIPT data in medical genetic research.

The associated production of Higgs and W bosons via vector-boson fusion is highly sensitive to the relative sign of the Higgs boson couplings to W and Z bosons. In this Letter, two searches for this process are presented, using 140  fb−1 of proton-proton collision data at s=13  TeV recorded by the ATLAS detector at the LHC. The first search targets scenarios with opposite-sign couplings of the W and Z bosons to the Higgs boson, while the second targets standard model-like scenarios with same-sign couplings. Both analyses consider Higgs boson decays into a pair of b quarks and W boson decays with an electron or muon. The data exclude the opposite-sign coupling hypothesis with a significance beyond 5σ, and the observed (expected) upper limit set on the cross section for vector-boson fusion WH production is 9.0 (8.7) times the standard model value at 95% confidence level. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

The basal ganglia are subcortical brain structures involved in motor control, cognition, and emotion regulation. We conducted univariate and multivariate genome-wide association analyses (GWAS) to explore the genetic architecture of basal ganglia volumes using brain scans obtained from 34,794 Europeans with replication in 4,808 white and generalization in 5,220 non-white Europeans. Our multivariate GWAS identified 72 genetic loci associated with basal ganglia volumes with a replication rate of 55.6% at P

This Letter presents a differential cross-section measurement of Lund subjet multiplicities, suitable for testing current and future parton shower Monte Carlo algorithms. This measurement is made in dijet events in 140 fb−1 of s=13 TeV proton–proton collision data collected with the ATLAS detector at CERN's Large Hadron Collider. The data are unfolded to account for acceptance and detector-related effects, and are then compared with several Monte Carlo models and to recent resummed analytical calculations. The experimental precision achieved in the measurement allows tests of higher-order effects in QCD predictions. Most predictions fail to accurately describe the measured data, particularly at large values of jet transverse momentum accessible at the Large Hadron Collider, indicating the measurement's utility as an input to future parton shower developments and other studies probing fundamental properties of QCD and the production of hadronic final states up to the TeV-scale.

Measurements of jet cross-section ratios between inclusive bins of jet multiplicity are performed in 140  fb−1 of proton-proton collisions with s=13  TeV center-of-mass energy, recorded with the ATLAS detector at CERN’s Large Hadron Collider. These ratios are constructed from double-differential cross-section measurements that are made in bins of jet multiplicity and other observables that are sensitive the energy scale and angular distribution of radiation due to the strong interaction in the final state. Additionally, the scalar sum of the two leading jets’ transverse momenta is measured triple differentially, in bins of the third jet’s transverse momentum and of jet multiplicity. These measurements are unfolded to account for acceptance and detector-related effects. The measured distributions are used to construct ratios of the inclusive jet-multiplicity bins, which have been shown to be sensitive to the strong coupling αS while being less sensitive than other observables to systematic uncertainties and parton distribution functions. The measured distributions are compared with state-of-the-art QCD calculations, including next-to-next-to-leading-order predictions for two- and three-jet events. These predictions are generally found to model the data well and perform best in bins with a modest requirement on the third jet’s transverse momentum. Significant differences between data and Monte Carlo predictions are observed in events with large rapidity gaps and invariant masses of the leading jet pair. Studies leading to reduced jet energy scale uncertainties significantly improve the precision of this work and are documented herein. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

This paper describes measurements of the transverse momentum spectra of W and Z bosons produced in proton–proton collisions at centre-of-mass energies of s=5.02 TeV and s=13 TeV with the ATLAS experiment at the Large Hadron Collider. Measurements are performed in the electron and muon channels, W→ℓν and Z→ℓℓ (ℓ=e or μ), and for W events further separated by charge. The data were collected in 2017 and 2018, in dedicated runs with reduced instantaneous luminosity, and correspond to 255 and 338 pb-1 at s=5.02 TeV and 13 TeV, respectively. These conditions optimise the reconstruction of the W-boson transverse momentum. The distributions observed in the electron and muon channels are unfolded, combined, and compared to QCD calculations based on parton shower Monte Carlo event generators and analytical resummation. The description of the transverse momentum distributions by Monte Carlo event generators is imperfect and shows significant differences largely common to W-, W+ and Z production. The agreement is better at s=5.02 TeV, especially for predictions that were tuned to Z production data at s=7 TeV. Higher-order, resummed predictions based on DYTurbo generally match the data best across the spectra. Distribution ratios are also presented and test the understanding of differences between the production processes.

The inclusive cross section for the production of a single top quark in association with a W boson is measured using 140  fb−1 of proton-proton collision data collected with the ATLAS detector at s=13  TeV. Events containing two charged leptons and at least one jet identified as originating from a b-quark are selected. A multivariate discriminant is constructed to separate the tW signal from the tt¯ background. The cross section is extracted using a profile likelihood fit to the signal and control regions and it is measured to be σtW=75−14+15  pb, in good agreement with the Standard Model prediction. The measured cross section is used to extract a value for the left-handed form factor at the Wtb vertex times the Cabibbo-Kobayashi-Maskawa matrix element |fLVVtb| of 0.97±0.10. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

This report reviews the published results of searches for possible additional scalar particles and exotic decays of the Higgs boson performed by the ATLAS Collaboration using up to 140 fb−1 of 13 TeV proton–proton collision data collected during Run 2 of the Large Hadron Collider. Key results are examined, and observed excesses, while never statistically compelling, are noted. Constraints are placed on parameters of several models which extend the Standard Model, for example by adding one or more singlet or doublet fields, or offering exotic Higgs boson decay channels. Summaries of new searches as well as extensions of previous searches are discussed. These new results have a wider reach or attain stronger exclusion limits. New experimental techniques that were developed for these searches are highlighted. Search channels which have not yet been examined are also listed, as these provide insight into possible future areas of exploration.

This paper reports a summary of searches for a fermionic dark matter candidate in the context of theoretical models characterised by a mediator particle exchange in the s-channel. The data sample considered consists of pp collisions delivered by the Large Hadron Collider during its Run 2 at a centre-of-mass energy of s=13TeV and recorded by the ATLAS detector, corresponding to up to 140 fb-1. The interpretations of the results are based on simplified models where the new mediator particles can be spin-0, with scalar or pseudo-scalar couplings to fermions, or spin-1, with vector or axial-vector couplings to fermions. Exclusion limits are obtained from various searches characterised by final states with resonant production of Standard Model particles, or production of Standard Model particles in association with large missing transverse momentum.

Abstract: The ratio of branching ratios of the W boson to muons and electrons, $$R^{\,\mu /e}_W={{\mathcal {B}}(W\rightarrow \mu u )}$$ R W μ / e = B ( W → μ ν ) /$${{\mathcal {B}}(W\rightarrow eu )}$$ B ( W → e ν ) , has been measured using $$140\,\text{ fb}^{-1}\,$$ 140 fb - 1 of pp collision data at $$\sqrt{s}=13$$ s = 13  $$\text {T}\text {e}\hspace{-1.00006pt}\text {V}$$ Te V collected with the ATLAS detector at the LHC, probing the universality of lepton couplings. The ratio is obtained from measurements of the $$t\bar{t}$$ t t ¯ production cross-section in the ee, $$e\mu $$ e μ and $$\mu \mu $$ μ μ dilepton final states. To reduce systematic uncertainties, it is normalised by the square root of the corresponding ratio $$R^{\,\mu \mu /ee}_Z$$ R Z μ μ / e e for the Z boson measured in inclusive $$Z\rightarrow ee$$ Z → e e and $$Z\rightarrow \mu \mu $$ Z → μ μ events. By using the precise value of $$R^{\,\mu \mu /ee}_Z$$ R Z μ μ / e e determined from $$e^+e^-$$ e + e - colliders, the ratio $$R^{\,\mu /e}_W$$ R W μ / e is determined to be $$\begin{aligned} R^{\,\mu /e}_W&= 0.9995\pm 0.0022\,\mathrm {(stat)}\,\pm 0.0036\,\mathrm {(syst)}\\ &\quad \pm 0.0014\,\mathrm {(ext)} . \end{aligned}$$ R W μ / e = 0.9995 ± 0.0022 ( stat ) ± 0.0036 ( syst ) ± 0.0014 ( ext ) . The three uncertainties correspond to data statistics, experimental systematics and the external measurement of $$R^{\,\mu \mu /ee}_Z$$ R Z μ μ / e e , giving a total uncertainty of 0.0045, and confirming the Standard Model assumption of lepton flavour universality in W-boson decays at the 0.5% level.

Abstract: Pixel sensors in 3D technology equip the outer ends of the staves of the Insertable B Layer (IBL), the innermost layer of the ATLAS Pixel Detector, which was installed before the start of LHC Run 2 in 2015. 3D pixel sensors are expected to exhibit more tolerance to radiation damage and are the technology of choice for the innermost layer in the ATLAS tracker upgrade for the HL-LHC programme. While the LHC has delivered an integrated luminosity of  ≃ 235 fb-1 since the start of Run 2, the 3D sensors have received a non-ionising energy deposition corresponding to a fluence of ≃ 8.5 × 1014 1 MeV neutron-equivalent cm-2 averaged over the sensor area. This paper presents results of measurements of the 3D pixel sensors' response during Run 2 and the first two years of Run 3, with predictions of its evolution until the end of Run 3 in 2025. Data are compared with radiation damage simulations, based on detailed maps of the electric field in the Si substrate, at various fluence levels and bias voltage values. These results illustrate the potential of 3D technology for pixel applications in high-radiation environments.

Results from a wide range of searches targeting different experimental signatures with and without missing transverse momentum (ETmiss) are used to constrain a Two-Higgs-Doublet Model (2HDM) with an additional pseudo-scalar mediating the interaction between ordinary and dark matter (2HDM+a). The analyses use up to 139 fb-1 of proton-proton collision data at a centre-of-mass energy s=13 TeV recorded with the ATLAS detector at the Large Hadron Collider during 2015-2018. The results from three of the most sensitive searches are combined statistically. These searches target signatures with large ETmiss and a leptonically decaying Z boson; large ETmiss and a Higgs boson decaying to bottom quarks; and production of charged Higgs bosons in final states with top and bottom quarks, respectively. Constraints are derived for several common and new benchmark scenarios in the 2HDM+a.

This paper presents a search for exotic decays of the Higgs boson into a pair of new pseudoscalar particles, H→aa, where one pseudoscalar decays into a b-quark pair and the other decays into a τ-lepton pair, in the mass range 12≤ma≤60  GeV. The analysis uses pp collision data at s=13  TeV collected with the ATLAS detector at the LHC, corresponding to an integrated luminosity of 140  fb−1. No significant excess above the Standard Model (SM) prediction is observed. Assuming the SM Higgs boson production cross section, the search sets upper limits at 95% confidence level on the branching ratio of Higgs bosons decaying into bb¯τ+τ−, B(H→aa→bb¯τ+τ−), between 2.2% and 3.9% depending on the pseudoscalar mass. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Abstract: This paper presents a measurement of the production cross-section of a Z boson in association with b- or c-jets, in proton–proton collisions at $$\sqrt{s} = 13$$ s = 13 TeV with the ATLAS experiment at the Large Hadron Collider using data corresponding to an integrated luminosity of 140 $$\hbox {fb}^{-1}$$ fb - 1 . Inclusive and differential cross-sections are measured for events containing a Z boson decaying into electrons or muons and produced in association with at least one b-jet, at least one c-jet, or at least two b-jets with transverse momentum $$p_\text {T} > 20$$ p T > 20 GeV and rapidity $$|y| < 2.5$$ | y | < 2.5 . Predictions from several Monte Carlo generators based on next-to-leading-order matrix elements interfaced with a parton-shower simulation, with different choices of flavour schemes for initial-state partons, are compared with the measured cross-sections. The results are also compared with novel predictions, based on infrared and collinear safe jet flavour dressing algorithms. Selected $$Z + \ge 1~c$$ Z + ≥ 1 c -jet observables, optimized for sensitivity to intrinsic-charm, are compared with benchmark models with different intrinsic-charm fractions.

The HEALthy Brain and Child Development (HBCD) Study, a multi-site prospective longitudinal cohort study, will examine human brain, cognitive, behavioral, social, and emotional development beginning prenatally and planned through early childhood. The acquisition of multimodal magnetic resonance-based brain development data is central to the studys core protocol. However, application of Magnetic Resonance Imaging (MRI) methods in this population is complicated by technical challenges and difficulties of imaging in early life. Overcoming these challenges requires an innovative and harmonized approach, combining age-appropriate acquisition protocols together with specialized pediatric neuroimaging strategies. The HBCD MRI Working Group aimed to establish a core acquisition protocol for all 27 HBCD Study recruitment sites to measure brain structure, function, microstructure, and metabolites. Acquisition parameters of individual modalities have been matched across MRI scanner platforms for harmonized acquisitions and state-of-the-art technologies are employed to enable faster and motion-robust imaging. Here, we provide an overview of the HBCD MRI protocol, including decisions of individual modalities and preliminary data. The result will be an unparalleled resource for examining early neurodevelopment which enables the larger scientific community to assess normative trajectories from birth through childhood and to examine the genetic, biological, and environmental factors that help shape the developing brain.

Wildlife tagging provides critical insights into animal movement ecology, physiology, and behavior amid global ecosystem changes. However, the stress induced by capture, handling, and tagging can impact post-release locomotion and activity and, consequently, the interpretation of study results. Here, we analyze post-tagging effects on 1585 individuals of 42 terrestrial mammal species using collar-collected GPS and accelerometer data. Species-specific displacements and overall dynamic body acceleration, as a proxy for activity, were assessed over 20 days post-release to quantify disturbance intensity, recovery duration, and speed. Differences were evaluated, considering species-specific traits and the human footprint of the study region. Over 70% of the analyzed species exhibited significant behavioral changes following collaring events. Herbivores traveled farther with variable activity reactions, while omnivores and carnivores were initially less active and mobile. Recovery duration proved brief, with alterations diminishing within 4-7 tracking days for most species. Herbivores, particularly males, showed quicker displacement recovery (4 days) but slower activity recovery (7 days). Individuals in high human footprint areas displayed faster recovery, indicating adaptation to human disturbance. Our findings emphasize the necessity of extending tracking periods beyond 1 week and particular caution in remote study areas or herbivore-focused research, specifically in smaller mammals.

This Letter presents results from a combination of searches for Higgs boson pair production using 126-140  fb^{-1} of proton-proton collision data at sqrt[s]=13  TeV recorded with the ATLAS detector. At 95% confidence level (CL), the upper limit on the production rate is 2.9 times the standard model (SM) prediction, with an expected limit of 2.4 assuming no Higgs boson pair production. Constraints on the Higgs boson self-coupling modifier κ_{λ}=λ_{HHH}/λ_{HHH}^{SM}, and the quartic HHVV coupling modifier κ_{2V}=g_{HHVV}/g_{HHVV}^{SM}, are derived individually, fixing the other parameter to its SM value. The observed 95% CL intervals are -1.2

This Letter presents the first study of the energy dependence of diboson polarization fractions in WZ→ℓνℓ′ℓ′(ℓ,ℓ′=e,μ) production. The dataset used corresponds to an integrated luminosity of 140  fb−1 of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector. Two fiducial regions with an enhanced presence of events featuring two longitudinally polarized bosons are defined. A nonzero fraction of events with two longitudinally polarized bosons is measured with an observed significance of 5.3 standard deviations in the region with 100200  GeV, where pTZ is the transverse momentum of the Z boson. This Letter also reports the first study of the radiation-amplitude-zero effect. Events with two transversely polarized bosons are analyzed for the ΔY(ℓWZ) and ΔY(WZ) distributions defined respectively as the rapidity difference between the lepton from the W boson decay and the Z boson and the rapidity difference between the W boson and the Z boson. Significant suppression of events near zero is observed in both distributions. Unfolded ΔY(ℓWZ) and ΔY(WZ) distributions are also measured and compared to theoretical predictions. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Purpose To develop and validate a deep learning (DL) method to detect and segment enhancing and nonenhancing cellular tumor on pre- and posttreatment MRI scans in patients with glioblastoma and to predict overall survival (OS) and progression-free survival (PFS). Materials and Methods This retrospective study included 1397 MRI scans in 1297 patients with glioblastoma, including an internal set of 243 MRI scans (January 2010 to June 2022) for model training and cross-validation and four external test cohorts. Cellular tumor maps were segmented by two radiologists on the basis of imaging, clinical history, and pathologic findings. Multimodal MRI data with perfusion and multishell diffusion imaging were inputted into a nnU-Net DL model to segment cellular tumor. Segmentation performance (Dice score) and performance in distinguishing recurrent tumor from posttreatment changes (area under the receiver operating characteristic curve [AUC]) were quantified. Model performance in predicting OS and PFS was assessed using Cox multivariable analysis. Results A cohort of 178 patients (mean age, 56 years ± 13 [SD]; 116 male, 62 female) with 243 MRI timepoints, as well as four external datasets with 55, 70, 610, and 419 MRI timepoints, respectively, were evaluated. The median Dice score was 0.79 (IQR, 0.53-0.89), and the AUC for detecting residual or recurrent tumor was 0.84 (95% CI: 0.79, 0.89). In the internal test set, estimated cellular tumor volume was significantly associated with OS (hazard ratio [HR] = 1.04 per milliliter; P < .001) and PFS (HR = 1.04 per milliliter; P < .001) after adjustment for age, sex, and gross total resection (GTR) status. In the external test sets, estimated cellular tumor volume was significantly associated with OS (HR = 1.01 per milliliter; P < .001) after adjustment for age, sex, and GTR status. Conclusion A DL model incorporating advanced imaging could accurately segment enhancing and nonenhancing cellular tumor, distinguish recurrent or residual tumor from posttreatment changes, and predict OS and PFS in patients with glioblastoma. Keywords: Segmentation, Glioblastoma, Multishell Diffusion MRI Supplemental material is available for this article. © RSNA, 2024.

The fundamental trade-off between current and future reproduction has long been considered to result in a tendency for species that can grow large to begin reproduction at a larger size. Due to the prolonged time required to reach maturity, estimates of tree maturation size remain very rare and we lack a global view on the generality and the shape of this trade-off. Using seed production from five continents, we estimate tree maturation sizes for 486 tree species spanning tropical to boreal climates. Results show that a species' maturation size increases with maximum size, but in a non-proportional way: the largest species begin reproduction at smaller sizes than would be expected if maturation were simply proportional to maximum size. Furthermore, the decrease in relative maturation size is steepest in cold climates. These findings on maturation size drivers are key to accurately represent forests' responses to disturbance and climate change.

A search is presented for the pair production of heavy vectorlike quarks (VLQs) that each decay into a W boson and a light quark. This study focuses on events where one W boson decays into leptons and the other into hadrons. The search analyzed 140  fb−1 of pp collision data with s=13  TeV, recorded by the ATLAS detector from 2015 to 2018 during run 2 of the Large Hadron Collider. The final state is characterized by a high-transverse-momentum isolated electron or muon, large missing transverse momentum, multiple small-radius jets, and a single large-radius jet identified as originating from the hadronic decay of a boosted W boson. With higher center-of-mass energy and integrated luminosity than in the run 1 search, and improved analysis tools, this analysis excludes VLQs (Q) with masses below 1530 GeV at 95% confidence level for the branching ratio B(Q→Wq)=1, an improvement of 840 GeV on the previous ATLAS limit. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Ever since they have been studied, gas discharges have been classified by their visual appearance as well as by their current and voltage levels. Glow and arc discharges are the most prominent and well-known modes of discharges involving electrodes. In a first approximation, they are distinguished by their current and voltage levels, and current–voltage characteristics are a common way to display their relations. In this review, glow discharges are defined by their individual electron emission mechanism such as secondary electron emission by photons and primary ions, and arcs by their respective collective mechanism such as thermionic or explosive electron emission. Emitted electrons are accelerated in the cathode sheath and play an important role in sustaining the discharge plasma. In some cases, however, electron emission is not important for sustaining the plasma, and consequently we have neither a glow nor an arc discharge but a third type of discharge, the ohmic discharge. In part 1 of this review, these relationships are explained for quasi-stationary discharges, culminating with updated graphical presentations of I–V characteristics (Figs. 15 and 16). In part 2, further examples are reviewed to include time-dependent discharges, discharges with electron trapping (hollow cathode, E×B discharges) and active anode effects.

A search for heavy Majorana neutrinos in scattering of same-sign W boson pairs in proton–proton collisions at s=13 TeV at the LHC is reported. The dataset used corresponds to an integrated luminosity of 140 fb−1, collected with the ATLAS detector during 2015–2018. The search is performed in final states including a same-sign ee or eμ pair and at least two jets with large invariant mass and a large rapidity difference. No significant excess of events with respect to the Standard Model background predictions is observed. The results are interpreted in a benchmark scenario of the Phenomenological Type-I Seesaw model. New constraints are set on the values of the |VeN|2 and |VeNVμN⁎| parameters for heavy Majorana neutrino masses between 50 GeV and 20 TeV, where VℓN is the matrix element describing the mixing of the heavy Majorana neutrino mass eigenstate with the Standard Model neutrino of flavour ℓ=e,μ. The sensitivity to the Weinberg operator is investigated and constraints on the effective ee and eμ Majorana neutrino masses are reported. The statistical combination of the ee and eμ channels with the previously published μμ channel is performed.

Several processes studied by the ATLAS experiment at the Large Hadron Collider produce low-momentum b-flavored hadrons in the final state. This paper describes the calibration of a dedicated tagging algorithm that identifies b-flavored hadrons outside of hadronic jets by reconstructing the soft secondary vertices originating from their decays. The calibration is based on a proton-proton collision dataset at a center-of-mass energy of 13 TeV corresponding to an integrated luminosity of 140  fb−1. Scale factors used to correct the algorithm’s performance in simulated events are extracted for the b-tagging efficiency and the mistag rate of the algorithm using a data sample enriched in tt¯ events. Several orthogonal measurement regions are defined, binned as a function of the multiplicities of soft secondary vertices and jets containing a b-flavored hadron in the event. The mistag rate scale factors are estimated separately for events with low and high average numbers of interactions per bunch crossing. The results, which are derived from events with low missing transverse momentum, are successfully validated in a phase space characterized by high missing transverse momentum and therefore are applicable to new physics searches carried out in either phase space regime. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma. For the alveolar subtype (ARMS), the presence of the PAX3::FOXO1 fusion gene and/or metastases are strong predictors of poor outcome. Metastatic PAX3::FOXO1+ ARMS often responds to chemotherapies initially, only to subsequently relapse and become resistant with most patients failing to survive beyond 8 years post-diagnosis. No curative intent phase II or phase III clinical trial has been available for patients in the past 10 years (ARST0921). Thus, metastatic ARMS represents a significantly unmet clinical need. Chemotherapy resistance in ARMS has previously been attributed to PAX3::FOXO1-mediated cell cycle checkpoint adaptation, which is mediated by an HDAC3-SMARCA4-miR-27a-PAX3::FOXO1 circuit that can be disrupted by HDAC3 inhibition. In this study, we investigated the therapeutic efficacy of combining the epigenetic regulator entinostat, a Class I Histone Deacetylase (HDAC1-3) inhibitor, with RMS-specific chemotherapies in patient derived xenograft (PDX) models of RMS. We identified single agent, additive or synergistic relationships between relapse-specific chemotherapies and clinically relevant drug exposures of entinostat in three PAX3::FOXO1+ ARMS mouse models. This preclinical data provides further rationale for clinical investigation of entinostat, already known to be well tolerated in a pediatric phase I clinical trial (ADVL1513).

A search for the nonresonant production of Higgs boson pairs in the HH→bb¯τ+τ− channel is performed using 140  fb−1 of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. The analysis strategy is optimized to probe anomalous values of the Higgs boson self-coupling modifier κλ and of the quartic HHVV (V=W,Z) coupling modifier κ2V. No significant excess above the expected background from Standard Model processes is observed. An observed (expected) upper limit μHH

Genome-wide association studies (GWAS) implicate broad genomic loci containing clusters of highly correlated genetic variants. Finemapping techniques can select and prioritize variants within each GWAS locus which are more likely to have a functional influence on the trait. Here, we present a novel method, Finemap-MiXeR, for finemapping causal variants from GWAS summary statistics, controlling for correlation among variants due to linkage disequilibrium. Our method is based on a variational Bayesian approach and direct optimization of the Evidence Lower Bound (ELBO) of the likelihood function derived from the MiXeR model. After obtaining the analytical expression for ELBOs gradient, we apply Adaptive Moment Estimation (ADAM) algorithm for optimization, allowing us to obtain the posterior causal probability of each variant. Using these posterior causal probabilities, we validated Finemap-MiXeR across a wide range of scenarios using both synthetic data, and real data on height from the UK Biobank. Comparison of Finemap-MiXeR with two existing methods, FINEMAP and SuSiE RSS, demonstrated similar or improved accuracy. Furthermore, our method is computationally efficient in several aspects. For example, unlike many other methods in the literature, its computational complexity does not increase with the number of true causal variants in a locus and it does not require any matrix inversion operation. The mathematical framework of Finemap-MiXeR is flexible and may also be applied to other problems including cross-trait and cross-ancestry finemapping.

Abstract: The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider.Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied.This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV.The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study.The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance.To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.

Continuous advancements in scientific and engineering understanding of earthquake phenomena, combined with the associated development of representative physics-based models, is providing a foundation for high-performance, fault-to-structure earthquake simulations. However, regional-scale applications of high-performance models have been challenged by the computational requirements at the resolutions required for engineering risk assessments. The EarthQuake SIMulation (EQSIM) framework, a software application development under the US Department of Energy (DOE) Exascale Computing Project, is focused on overcoming the existing computational barriers and enabling routine regional-scale simulations at resolutions relevant to a breadth of engineered systems. This multidisciplinary software development—drawing upon expertise in geophysics, engineering, applied math and computer science—is preparing the advanced computational workflow necessary to fully exploit the DOE’s exaflop computer platforms coming online in the 2023 to 2024 timeframe. Achievement of the computational performance required for high-resolution regional models containing upward of hundreds of billions to trillions of model grid points requires numerical efficiency in every phase of a regional simulation. This includes run time start-up and regional model generation, effective distribution of the computational workload across thousands of computer nodes, efficient coupling of regional geophysics and local engineering models, and application-tailored highly efficient transfer, storage, and interrogation of very large volumes of simulation data. This article summarizes the most recent advancements and refinements incorporated in the workflow design for the EQSIM integrated fault-to-structure framework, which are based on extensive numerical testing across multiple graphics processing unit (GPU)-accelerated platforms, and demonstrates the computational performance achieved on the world’s first exaflop computer platform through representative regional-scale earthquake simulations for the San Francisco Bay Area in California, USA.

A search is performed for localized excesses in the low-mass dijet invariant mass distribution, targeting a hypothetical new particle decaying into two jets and produced in association with either a high transverse momentum photon or a jet. The search uses the full Run 2 data sample from LHC proton-proton collisions collected by the ATLAS experiment at a center-of-mass energy of 13 TeV during 2015–2018. Two variants of the search are presented for each type of initial-state radiation: one that makes no jet flavor requirements and one that requires both of the jets to have been identified as containing b-hadrons. No excess is observed relative to the Standard Model prediction, and the data are used to set upper limits on the production cross section for a benchmark Z′ model and, separately, for generic, beyond the Standard Model scenarios which might produce a Gaussian-shaped contribution to dijet invariant mass distributions. The results extend the current constraints on dijet resonances to the mass range between 200 and 650 GeV. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

A measurement of the Standard Model Higgs boson produced in association with a W or Z boson and decaying into a pair of τ-leptons is presented. This search is based on proton-proton collision data collected at s=13 TeV by the ATLAS experiment at the LHC corresponding to an integrated luminosity of 140 fb−1. For the Higgs boson candidate, only final states with at least one τ-lepton decaying hadronically (τ→hadrons+ντ) are considered. For the vector bosons, only leptonic decay channels are considered: Z→ℓℓ and W→ℓνℓ, with ℓ=e,μ. An excess of events over the expected background is found with an observed (expected) significance of 4.2 (3.6) standard deviations, providing evidence of the Higgs boson produced in association with a vector boson and decaying into a pair of τ-leptons. The ratio of the measured cross-section to the Standard Model prediction is μVHττ=1.28−0.29+0.30(stat.)−0.21+0.25(syst.). This result represents the most accurate measurement of the VH(ττ) process achieved to date.

This paper reports cross-section measurements of ZZ production in pp collisions at s=13.6TeV at the Large Hadron Collider. The data were collected by the ATLAS detector in 2022, and correspond to an integrated luminosity of 29 fb−1. Events in the ZZ→4ℓ (ℓ=e, μ) final states are selected and used to measure the inclusive and differential cross-sections in a fiducial region defined close to the analysis selections. The inclusive cross-section is further extrapolated to the total phase space with a requirement of 66

Searches for exclusive decays of the Higgs boson into D⁎γ and of the Z boson into D0γ and Ks0γ can probe flavour-violating Higgs boson and Z boson couplings to light quarks. Searches for these decays are performed with a pp collision data sample corresponding to an integrated luminosity of 136.3 fb−1 collected at s=13TeV between 2016–2018 with the ATLAS detector at the CERN Large Hadron Collider. In the D⁎γ and D0γ channels, the observed (expected) 95% confidence-level upper limits on the respective branching fractions are B(H→D⁎γ)

Post-traumatic stress disorder (PTSD) genetics are characterized by lower discoverability than most other psychiatric disorders. The contribution to biological understanding from previous genetic studies has thus been limited. We performed a multi-ancestry meta-analysis of genome-wide association studies across 1,222,882 individuals of European ancestry (137,136 cases) and 58,051 admixed individuals with African and Native American ancestry (13,624 cases). We identified 95 genome-wide significant loci (80 new). Convergent multi-omic approaches identified 43 potential causal genes, broadly classified as neurotransmitter and ion channel synaptic modulators (for example, GRIA1, GRM8 and CACNA1E), developmental, axon guidance and transcription factors (for example, FOXP2, EFNA5 and DCC), synaptic structure and function genes (for example, PCLO, NCAM1 and PDE4B) and endocrine or immune regulators (for example, ESR1, TRAF3 and TANK). Additional top genes influence stress, immune, fear and threat-related processes, previously hypothesized to underlie PTSD neurobiology. These findings strengthen our understanding of neurobiological systems relevant to PTSD pathophysiology, while also opening new areas for investigation.