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At least 163 records · Page 9

Measurements of WH and ZH production with Higgs boson decays into bottom quarks and direct constraints on the charm Yukawa coupling in 13 TeV pp collisions with the ATLAS detector

A study of the Higgs boson decaying into bottom quarks (H → $b\bar{b}$) and charm quarks (H → $c\bar{c}$) is performed, in the associated production channel of the Higgs boson with a W or Z boson, using 140 fb −1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the ATLAS detector. The individual production of WH and ZH with H → $b\bar{b}$ is established with observed (expected) significances of 5.3 (5.5) and 4.9 (5.6) standard deviations, respectively. Differential cross-section measurements of the gauge boson transverse momentum within the simplified template cross-section framework are performed in a total of 13 kinematical fiducial regions.

Hadron-Hadron Scattering↗

Measurement of the Higgs boson production in association with top quarks in multilepton final states in pp collisions at s=13 TeV with the ATLAS detector

A measurement of the associated production of a top-quark pair with the Higgs boson (tt¯H$$ t\overline{t}H $$) in multilepton final states is presented. The analysis is based on a data sample of proton-proton collisions at s=13$$ \sqrt{s}=13 $$ TeV recorded with the ATLAS detector at the CERN Large Hadron Collider and corresponding to an integrated luminosity of 140 fb−1. Six final states defined by the number and flavour of reconstructed charged leptons are combined in a simultaneous likelihood fit to extract the tt¯H$$ t\overline{t}H $$ signal and constrain the most relevant backgrounds. The measured tt¯H$$ t\overline{t}H $$ cross-section normalised to Standard Model (SM) prediction is σtt¯H/σSM=0.63−0.19+0.20$$ {\sigma}_{t\overline{t}H}/{\sigma}^{\mathrm{SM}}=0.{63}_{-0.19}^{+0.20} $$. This result corresponds to an observed (expected) significance of 3.3σ (5.3σ). Additionally, two other fits are used to measure the tt¯H$$ t\overline{t}H $$ cross-section differentially in bins of the Higgs boson transverse momentum in the simplified template cross-section framework, and to extract the associated production cross-section of a single top-quark with the Higgs boson (tH) together with the tt¯H$$ t\overline{t}H $$ one. The CP structure of the top quark-Higgs boson Yukawa coupling is probed through an analysis of tt¯H$$ t\overline{t}H $$ and tH events. The results are compatible with the SM hypothesis, and values of the mixing angle between CP-even and CP-odd top-Higgs Yukawa couplings of |α| > 62° are excluded at 68% confidence level.

Aad, G↗

Observation of flow vector fluctuations in p–Pb collisions at \(\sqrt{{s}_{NN}}=5.02\) TeV

Measurements of transverse momentum (pT) and pseudorapidity (η) dependent flow vector fluctuations in p–Pb collisions at $$\sqrt{{s}_{NN}}=5.02$$ TeV at the CERN Large Hadron Collider are presented. By studying long-range two-particle correlations with a template fit method, potential biases from non-flow effects such as jets and resonance decays are effectively suppressed. Significant pT- and η-dependent fluctuations of the second-harmonic flow vector are observed with more than 5σ confidence in p–Pb collisions, similar to the observations in Pb–Pb collisions. The influence of residual non-flow effects has been evaluated and cannot account for the observed fluctuations, thereby confirming the observation of flow vector fluctuations in small collision systems at the LHC. Comparisons to model calculations from 3DGlauber+MUSIC+UrQMD and the parton transport model from AMPT are also presented. The measurements provide constraints on the theoretical modelling of the three-dimensional initial geometry and its event-by-event fluctuations, offering critical insights into the origin of collective flow in small collision systems at the LHC.

Abdallah, D A H↗

Measurements of the production cross-sections of a Higgs boson in association with a vector boson and decaying into WW * with the ATLAS detector at $\sqrt{s}$ = 13 TeV

Measurements of the total and differential Higgs boson production cross-sections, via WH and ZH associated production using H → WW* → ℓνℓν and H → WW* → ℓνjj decays, are presented. The analysis uses proton-proton events delivered by the Large Hadron Collider at a centre-of-mass energy of 13 TeV and recorded by the ATLAS detector between 2015 and 2018. The data correspond to an integrated luminosity of 140 fb −1 . The sum of the WH and ZH cross-sections times the H → WW* branching fraction is measured to be ${0.44}_{-0.09}^{+0.10}$ (stat.)$_{-0.05}^{+0.06}$ (syst.) pb, in agreement with the Standard Model prediction. Higgs boson production is further characterised through measurements of the differential cross-section as a function of the transverse momentum of the vector boson and in the framework of Simplified Template Cross-Sections.

hadron-hadron scattering↗

Interpretations of the ATLAS measurements of Higgs boson production and decay rates and differential cross-sections in pp collisions at $\sqrt{s}$ = 13 TeV

Measurements of the Higgs boson production times decay rates and differential cross-sections have recently been performed by the ATLAS experiment in several decay channels using up to 139 fb -1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV recorded at the Large Hadron Collider. This paper presents multiple interpretations of these Higgs boson measurements. Measurements of production-mode cross-sections, simplified template cross-sections and fiducial differential cross-sections in different decay channels are reparameterised in terms of the impact of Standard Model effective field theory operators, and constraints are reported on the corresponding Wilson coefficients. Production and decay rate measurements are interpreted in UV-complete extensions of the Standard Model, namely the two-Higgs-doublet model (2HDM) near the alignment limit and the Minimal Supersymmetric Standard Model (MSSM) for various MSSM benchmark scenarios. The constraints on the 2HDM parameters (cos(β - α), tanβ) and the MSSM parameters (m A , tanβ) are complementary to those obtained from direct searches for additional Higgs bosons.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Measurement of boosted Higgs bosons produced via vector boson fusion or gluon fusion in the H →$ \textrm{b}\overline{\textrm{b}} $ decay mode using LHC proton-proton collision data at $ \sqrt{s} $ = 13 TeV

A measurement is performed of Higgs bosons produced with high transverse momentum (p$_{T}$) via vector boson or gluon fusion in proton-proton collisions. The result is based on a data set with a center-of-mass energy of 13 TeV collected in 2016–2018 with the CMS detector at the LHC and corresponds to an integrated luminosity of 138 fb$^{−1}$. The decay of a high-p$_{T}$ Higgs boson to a boosted bottom quark-antiquark pair is selected using large-radius jets and employing jet substructure and heavy-flavor taggers based on machine learning techniques. Independent regions targeting the vector boson and gluon fusion mechanisms are defined based on the topology of two quark-initiated jets with large pseudorapidity separation. The signal strengths for both processes are extracted simultaneously by performing a maximum likelihood fit to data in the large-radius jet mass distribution. The observed signal strengths relative to the standard model expectation are $ {4.9}_{-1.6}^{+1.9} $ and $ {1.6}_{-1.5}^{+1.7} $ for the vector boson and gluon fusion mechanisms, respectively. A differential cross section measurement is also reported in the simplified template cross section framework.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Search for $t$-channel scalar and vector leptoquark exchange in the high-mass dimuon and dielectron spectra in proton-proton collisions at $\sqrt{s}=13$ TeV

A search for t-channel exchange of leptoquarks (LQs) is performed in dimuon and dielectron spectra using proton-proton collision data collected at $\sqrt{s}=13$ TeV with the CMS detector at the CERN LHC. The data correspond to an integrated luminosity of 138 fb −1 . Eight scenarios are considered, in which up or down quarks couple to muons or electrons via a scalar or vector LQ exchange, for dilepton invariant masses above 500 GeV. The LQ masses are probed up to 5 TeV, beyond a regime probed by previous pair-production and single-production searches. The differential distributions of dilepton events are fit to templates that model the nonresonant LQ exchange and various standard model background processes. Limits are set on LQ-fermion coupling strengths for scalar and vector LQ masses in the 1–5 TeV range at 95% confidence level, establishing stringent limits on first- and second-generation LQs.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High throughput automated characterization of enamel microstructure using synchrotron tomography and optical flow imaging

The remarkable damage-tolerance of enamel has been attributed to its hierarchical microstructure and the organized bands of decussated rods. A thorough characterization of the microscale rod evolution within the enamel is needed to elucidate this complex structure. While prior efforts in this area have made use of single particle tracking to track a single rod evolution to various degrees of success, such a process can be both computationally and labor intensive, limited to the evolution path of a single rod, and is therefore prone to error from potentially tracking outliers. Particle image velocimetry (PIV) is a well-established algorithm to derive field information from image sequences for processes that are time-dependent, such as fluid flows and structural deformation. In this work, we demonstrate the use of PIV in extracting the full-field microstructural distribution of rods within the enamel. Further, enamel samples from a wild African lion were analyzed using high-energy synchrotron X-ray micro-tomography. Results from the PIV analysis provide sufficient full-field information to reconstruct the growth of individual rods that can potentially enable rapid analysis of complex microstructures from high resolution synchrotron datasets. Such information can serve as a template for designing damage-tolerant bioinspired structures for advanced manufacturing.

36 MATERIALS SCIENCE↗

Spectral distortions to momentum and scalar exchanges by non-turbulent motion and patchy landscape variability

Modifications to the spectra of turbulent velocity and scalars and co-spectra of vertical fluxes of momentum and scalars due to patchy landscape heterogeneity and non-stationarity are explored for a Mediterranean ecosystem. About 9 months of high frequency measurements of the three velocity components, water vapor concentration, carbon dioxide concentration, and air temperature were analyzed for different seasons (spring/summer) and prevalent wind directions (southeast/northwest). The two wind directions sampled a contrast of clumped and patchy landscape comprised of olive trees (southeast) and wall bounded flow disturbed by the presence of few upwind trees (northwest). The measured spectra and co-spectra were also compared to theoretical scaling forms from stationary, planar homogeneous flow, in the absence of subsidence as derived from the Kansas experiment. To assess the role of low frequency non-turbulent motion on the spectral and co-spectral content, a 5-min Fourier cutoff was introduced and the analysis was limited to near-neutral conditions where the boundary layer depth is shallow compared to its unstable counterpart. It was shown that the velocity statistics were not appreciably impacted by the low-frequency motion causing non-stationarity. Moreover, the turbulent scalar fluxes were also shown not to be significantly impacted by such low frequency motion. The scalar variances were impacted, especially the water vapor variance and its concomitant spectral shape. When the non-turbulent motion was filtered, the scalar spectra at low wavenumbers followed expectations from the so-called attached eddy hypothesis (i.e. exhibited a $k^{-1}_x$ scaling with $k_x$ defining the longitudinal wavenumber) applicable for near-neutral conditions. For momentum co-spectra, the canonical shapes from the Kansas experiment appear to describe well the measurements here and in both dominant directions and seasons with some adjustment to the integral time scales based on wind direction. For the scalar co-spectra, deviations from the Kansas experiment were prevalent. The most noticeable and surprising deviations were their slow decay with increased sampling frequency at inertial subrange scales. This slow decay was shown not to contribute appreciably to the overall scalar fluxes. At those fine scales, predictions from local isotropy were expected to hold. The scalar co-spectral deviations from local isotropy were then discussed using a simplified co-spectral budget model where scalar–scalar co-spectra naturally emerged and the interplay between landscape heterogeneity and a scale-dependent pressure-scalar de-correlation time was postulated. It is also envisaged that the findings here offer a preliminary template for analyzing eddy-covariance data in situations that deviate from ideal conditions, especially regarding low-frequency modulations of scalar spectra and vertical scalar flux co-spectra.

Canopy turbulence↗

Engineering a photoenzyme to use red light

Photoenzymatic reactions involving flavin-dependent “ene”-reductases (EREDs) rely on protein-templated charge transfer (CT) complexes between the cofactor and substrate for radical initiation. These complexes typically absorb in the blue region of the electromagnetic spectrum. Here, we engineered an ERED to form CT complexes that absorb red light. Mechanistic studies indicate that red-light activity is due to the growth of a red-absorbing shoulder off the previously identified cyan absorption feature. Molecular dynamics simulations, docking, and excited-state calculations suggest that the cyan feature involves a π→π* transition on flavin, whereas the red-light absorption is a π→π* transition between flavin and the substrate. Furthermore, differences in the electronic transition are due to changes in the substrate-binding conformation and allosteric tuning of the electronic structure of the cofactor-substrate complex. Microenvironment tuning of the CT complex for red-light activity is observed with other engineered photoenzymatic reactions, highlighting this effect’s generality.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A multiscale design method using interpretable machine learning for phononic materials with closely interacting scales

Manipulating the dispersive characteristics of vibrational waves is beneficial for many applications, e.g., high-precision instruments. architected hierarchical phononic materials have sparked promise tunability of elastodynamic waves and vibrations over multiple frequency ranges. In this article, hierarchical unit-cells are obtained, where features at each length scale result in a band gap within a targeted frequency range. Our novel approach, the ‘‘hierarchical unit-cell template method,’’ is an interpretable machine-learning approach that uncovers global unit-cell shape/topology patterns corresponding to predefined band-gap objectives. A scale-separation effect is observed where the coarse-scale band-gap objective is mostly unaffected by the fine-scale features despite the closeness of their length scales, thus enabling an efficient hierarchical algorithm. Moreover, the hierarchical patterns revealed are not predefined or self-similar hierarchies as common in current hierarchical phononic materials. Furthermore, our approach offers a flexible and efficient method for the exploration of new regions in the hierarchical design space, extracting minimal effective patterns for inverse design in applications targeting multiple frequency ranges.

Architected materials↗

Molecularly engineered ZnO–carbon nanosheets from fumaric acid precursors for efficient photocatalytic water purification

The photocatalytic breakdown of organic contaminants is crucial for the development of water purification technology. Zinc oxide (ZnO) is an extensively researched photocatalyst; however, its efficacy is hindered by rapid charge recombination and limited utilization of UV irradiation. Resolving these issues necessitates integrating ZnO with conductive carbon phases via scalable, low-temperature synthesis. We provide a molecularly designed sol–gel method that converts zinc–fumarate coordination networks into two-dimensional ZnO–carbon nanosheets utilizing solely aqueous precursors and mild annealing temperatures (400–600 °C). This method utilizes fumaric acid as a dicarboxylate linker and polyvinylpyrrolidone (PVP) as a structural carbon source to produce ultrathin wurtzite ZnO nanosheets embedded inside an amorphous carbon matrix. The resultant ZnO-C hybrid achieves nearly complete methylene blue degradation within 10 min under UV-A illumination, demonstrating first-order kinetics and outstanding recyclability. Compared with commercial ZnO, the ZnO–C nanosheets exhibit comparable rapid photocatalytic degradation, enhanced adsorption behavior, a porous nanosheet morphology, and an integrated ZnO–carbon interfacial structure. These findings provide a viable molecular-templating approach to fabricating various metal oxide–carbon photocatalysts and underscore substantial enhancements in semiconductor efficacy in eco-friendly water treatment systems.

Ozcan, Muca [ORNL] (ORCID:0000000320020474)↗

Supersonic hot jet ablative testing and analysis of boron nitride nanotube hybrid composites

Boron nitride nanotubes (BNNTs) are high-strength, high-modulus nanotubes with high thermal and oxidative stabilities. Two hybrid composites were prepared with satin weave carbon fiber (CF) and resole-type phenolic resin: one with surface layers of BNNTs and one with alternating interlayers of BNNTs. The samples were subjected to hot jet tests that simulate realistic high-pressure-temperature conditions to understand the behavior of BNNTs under high-pressure erosion. Adding BNNTs to CF/phenolic laminates enhanced the ablation resistance by reinforcing the char material and mitigated localized thermal damage. Hybrid laminates exhibited up to 14% lower weight loss, 55% increase in flexural modulus, higher thermal diffusivity, and improved char yield and microstructure compared to CF/phenolic samples. The surface layer hybrid had many surviving nanotubes reinforcing the char and crystalline oxide structures that could mitigate further oxygen diffusion. Further, various characterization methods were used to deduce possible mechanisms and their products, indicating that BNNTs could serve as growth templates for direct crystalline boron oxide formation. Overall, hybrid BNNT/CF/phenolic laminates displayed better ablation resistance and favorable microstructure evolution under high-pressure conditions.

42 ENGINEERING↗

Consistent performance of large language models in rare disease diagnosis across ten languages and 4917 cases

Background Large language models (LLMs) are increasingly used medicine for diverse applications including differential diagnostic support. The training data used to create LLMs such as the Generative Pretrained Transformer (GPT) predominantly consist of English-language texts, but LLMs could be used across the globe to support diagnostics if language barriers could be overcome. Initial pilot studies on the utility of LLMs for differential diagnosis in languages other than English have shown promise, but a large-scale assessment on the relative performance of these models in a variety of European and non-European languages on a comprehensive corpus of challenging rare-disease cases is lacking. Methods We created 4917 clinical vignettes using structured data captured with Human Phenotype Ontology (HPO) terms with the Global Alliance for Genomics and Health (GA4GH) Phenopacket Schema. These clinical vignettes span a total of 360 distinct genetic diseases with 2525 associated phenotypic features. We used translations of the Human Phenotype Ontology together with language-specific templates to generate prompts in English, Chinese, Czech, Dutch, French, German, Italian, Japanese, Spanish, and Turkish. We applied GPT-4o, version gpt-4o-2024-08-06, and the medically fine-tuned Meditron3-70B to the task of delivering a ranked differential diagnosis using a zero-shot prompt. An ontology-based approach with the Mondo disease ontology was used to map synonyms and to map disease subtypes to clinical diagnoses in order to automate evaluation of LLM responses. Findings For English, GPT-4o placed the correct diagnosis at the first rank 19.9% and within the top-3 ranks 27.0% of the time. In comparison, for the nine non-English languages tested here the correct diagnosis was placed at rank 1 between 16.9% and 20.6%, within top-3 between 25.4% and 28.6% of cases. The Meditron3 model placed the correct diagnosis within the first 3 ranks for 20.9% of cases in English and between 19.9% and 24.0% for the other nine languages. Interpretation The differential diagnostic performance of LLMs across a comprehensive corpus of rare-disease cases was largely consistent across the ten languages tested. This suggests that the utility of LLMs in clinical settings may extend to non-English clinical settings.

Artificial intelligence↗

Design, synthesis, evaluation and X-ray structural studies of potent HIV-1 protease inhibitors containing substituted oxaspirocyclic carbamates as the P2 ligands

Here, we report here the design, synthesis and evaluation of a series of HIV-1 protease inhibitors that incorporate substituted oxaspirocyclic carbamate derivatives to serve as the P2 ligands. Various substituted ligand derivatives were synthesized in a racemic manner, using a tandem Prins/pinacol reaction as the key reaction. This reaction sets the relative stereochemistry of the oxaspirocyclic template in a highly diastereoselective manner. Reaction of the resulting ketone with enantiopure (S)-tert-butyl sulfinamide provided a convenient pathway to resolve the oxaspirocyclic ketone derivatives. The absolute stereochemical identity was determined by X-ray crystallography. The structure-activity studies demonstrate the effect of the stereochemistry of the oxaspirocyclic ring systems as well as the substitution effect on the aromatic ring. Several inhibitors exhibited potent HIV-1 protease inhibitory activity. One of these inhibitors displayed subnanomolar HIV-1 protease affinity and also exhibited potent antiviral activity. A high-resolution X-ray crystal structure of this inhibitor-bound HIV-1 protease show that the oxaspirocyclic P2 ligand forms an unconventional C–H⋯O bond with the backbone carboxyl group of Gly48’ and an interesting N–H … π interaction with the aromatic ring in the S2 subsite of HIV-1 protease active site.

Antiviral↗

Analyzing inference workloads for spatiotemporal modeling

Ensuring power grid resiliency, forecasting climate conditions, and optimization of transportation infrastructure are some of the many application areas where data is collected in both space and time. Spatiotemporal modeling is about modeling those patterns for forecasting future trends and carrying out critical decision-making by leveraging machine learning/deep learning. Once trained offline, field deployment of trained models for near real-time inference could be challenging because performance can vary significantly depending on the environment, available compute resources and tolerance to ambiguity in results. Users deploying spatiotemporal models for solving complex problems can benefit from analytical studies considering a plethora of system adaptations to understand the associated performance-quality trade-offs. To facilitate the co-design of next-generation hardware architectures for field deployment of trained models, it is critical to characterize the workloads of these deep learning (DL) applications during inference and assess their computational patterns at different levels of the execution stack. In this paper, we develop several variants of deep learning applications that use spatiotemporal data from dynamical systems. We study the associated computational patterns for inference workloads at different levels, considering relevant models (Long short-term Memory, Convolutional Neural Network and Spatio-Temporal Graph Convolution Network), DL frameworks (Tensorflow and PyTorch), precision (FP16, FP32, AMP, INT16 and INT8), inference runtime (ONNX and AI Template), post-training quantization (TensorRT) and platforms (Nvidia DGX A100 and Sambanova SN10 RDU). Overall, our findings indicate that although there is potential in mixed-precision models and post-training quantization for spatiotemporal modeling, extracting efficiency from contemporary GPU systems might be challenging. Instead, co-designing custom accelerators by leveraging optimized High Level Synthesis frameworks (such as SODA High-Level Synthesizer for customized FPGA/ASIC targets) can make workload-specific adjustments to enhance the efficiency.

97 MATHEMATICS AND COMPUTING↗

Machine learning guided search for energetically favorable metal borocarbide ternary compounds

In this work, we employ machine-learning (ML) combined with first principles calculations to efficiently search for the energetically favorable metal borocarbide (M-B-C) ternary compounds with M being the group 1–3 metal elements. Using a crystal graph convolutional neural network (CGCNN) ML approach followed by first-principles calculations, we predicted 47 energetically favorable stable and metastable ternary Na-B-C, Ca-B-C, and La-B-C ternary compounds with their decomposition energy (E d ) below or within 100 meV/atom from the currently known convex hulls. Phonon spectra and electronic structures of the 14 energetically favorable stable structures are also investigated by first-principles calculations. By substituting the metal atoms in the 29 energetically favorable non-equivalent template structures of Na (Ca, La)-B-C with other group 1–3 elements in the periodic table, we further obtain 22 stable structures and 52 metastable structures (E d ≤100 meV/atom with respect to the known convex hulls) for Li-B-C, K-B-C, Rb-B-C, Mg-B-C, Sr-B-C, Ba-B-C, Sc-B-C and Y-B-C ternary compounds. New convex hulls including our newly predicted stable ternary structures and the known stable structures are constructed for the M-B-C systems. The results obtained by our ML guided first-principles calculations enrich our knowledge in the structure and energy landscape of metal borocarbide ternary compounds and provide useful guidance for further experimental synthesis and discovery.

36 MATERIALS SCIENCE↗

Lattice-scale variations in viscosity are correlated with solution structure at mineral-water interfaces

At solid-liquid interfaces, the viscosity increases markedly from the bulk due to the collective interactions of ions and water molecules, influencing phenomena relevant to nanofluidics, colloidal dynamics, and electrochemistry. Here, in this study, we investigated dissipative forces at the boehmite-water interface using 3D atomic force microscopy. We observed an increase in interfacial solution viscosity, η, by 10-100-fold as the nanoprobe approached the surface in normal direction, with up to four oscillatory features showing average peaks of η/η bulk = 44-71. Moreover, the viscosity showed sub-nanometer variations within 0.5 nm from the interface, templated by the underlying crystal lattice and correlated with the interfacial solution structure. Beyond a near-wall region of approximately 1.2 nm, the dissipative response was comparable to that in bulk solution. Molecular dynamics simulations, along with statistical mechanical analyses, provided details on hydrodynamic structures near the interface. Specifically, the lattice-dependent dissipative responses are correlated with extensive hydrogen bonding by interfacial water molecules, which increased friction, particularly along the [001] direction. These results demonstrate how solution viscosity at mineral-water interfaces is anisotropic and correlated with the local solution structure, providing insights into the dynamics of nanocrystal attachment.

Viscosity↗