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All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High-redshift millennium and astrid galaxies in effective field theory at the field level

Effective field theory (EFT) modeling is expected to be a useful tool in the era of future higher-redshift galaxy surveys such as DESI-II and Spec-S5 due to its robust description of various large-scale structure tracers. However, large values of EFT bias parameters of higher-redshift galaxies could jeopardize the convergence of the perturbative expansion. Here, in this paper we measure the bias parameters and other EFT coefficients from samples of two types of star-forming galaxies in the state-of-the-art MilleniumTNG and astrid hydrodynamical simulations. Our measurements are based on the field-level EFT forward model that allows for precision EFT parameter measurements by virtue of cosmic variance cancellation. Specifically, we consider approximately representative samples of Lyman-break galaxies (LBGs) and Lyman-𝛼 emitters (LAEs) that are consistent with the observed (angular) clustering and number density of these galaxies at 𝑧 = 3. Reproducing the linear biases and number densities observed from existing LAE and LBG data, we find quadratic bias parameters that are roughly consistent with those predicted from the halo model coupled with a simple halo occupation distribution model. We also find nonperturbative velocity contributions (fingers of God) of a similar size for LBGs to the familiar case of luminous red galaxies. However, these contributions are quite small for LAEs despite their large satellite fraction values of up to ∼ 30%. Our results indicate that the effective momentum reach 𝑘 max at 𝑧 = 3 for LAEs (LBGs) will be in the range 0.3−0.6⁢ℎ Mpc −1 (0.2−0.8⁢ℎ Mpc −1 ), suggesting that EFT will perform well for high-redshift galaxy clustering. This work provides the first step toward obtaining realistic simulation-based priors on EFT parameters for LAEs and LBGs.

Sullivan, James M. [Massachusetts Inst. of Technol↗
DOE OSTI2024

Study of e + e − → ω X ( 3872 ) and γ X ( 3872 ) from 4.66 to 4.95 GeV

Using data samples with an integrated luminosity of 4.5 fb − 1 collected by the BESIII detector at center-of-mass energies ranging from 4.66 GeV to 4.95 GeV, we study the processes of e + e − → ω X ( 3872 ) and e + e − → γ X ( 3872 ) . With the e + e − → ω X ( 3872 ) process, the branching fraction ratio R ≡ B ( X ( 3872 ) → γ J / ψ ) B ( X ( 3872 ) → π + π − J / ψ ) is measured to be 0.38 ± 0.2 0 stat ± 0.0 1 syst ( R < 0.83 at 90% confidence level). In addition, we measure the ratio of the average cross section of e + e − → ω X ( 3872 ) to e + e − → ω χ c 1 ( ω χ c 2 ) to be σ ω X ( 3872 ) / σ ω χ c 1 ( σ ω X ( 3872 ) / σ ω χ c 2 ) = 5.2 ± 1.0 stat ± 1.9 syst ( 5.5 ± 1.1 stat ± 2.4 syst ) . Finally, we search for the process of e + e − → γ X ( 3872 ) , and no obvious signal is observed. The upper limit on the ratio of the average cross section of e + e − → γ X ( 3872 ) to e + e − → ω X ( 3872 ) is set as σ γ X ( 3872 ) / σ ω X ( 3872 ) < 0.23 at 90% confidence level. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2024

Measurements of the branching fractions of semileptonic D s + decays via e + e − → D s * + D s * −

We measure the absolute branching fractions of semileptonic D s + decays via the e + e − → D s * + D s * − process using e + e − collision data corresponding to an integrated luminosity of 10.64 fb − 1 collected by the BESIII detector at center-of-mass energies between 4.237 and 4.699 GeV. The branching fractions are B ( D s + → η e + ν e ) = ( 2.35 ± 0.11 stat ± 0.10 syst ) % , B ( D s + → η ′ e + ν e ) = ( 0.82 ± 0.09 stat ± 0.04 syst ) % , B ( D s + → ϕ e + ν e ) = ( 2.21 ± 0.16 stat ± 0.11 syst ) % , B ( D s + → f 0 ( 980 ) e + ν e , f 0 ( 980 ) → π + π − ) = ( 0.15 ± 0.02 stat ± 0.01 syst ) % , B ( D s + → K 0 e + ν e ) = ( 0.24 ± 0.0 4 stat ± 0.0 1 syst ) % , and B ( D s + → K * 0 e + ν e ) = ( 0.19 ± 0.0 3 stat ± 0.0 1 syst ) % . These results are consistent with those measured via the e + e − → D s * ± D s ∓ process by BESIII and CLEO. Using two-parameter series expansion, the hadronic transition form factors of D s + → η e + ν e , D s + → η ′ e + ν e , and D s + → K 0 e + ν e are determined to be f + η ( 0 ) = 0.442 ± 0.02 2 stat ± 0.01 7 syst , f + η ′ ( 0 ) = 0.557 ± 0.06 2 stat ± 0.02 4 syst , and f + K 0 ( 0 ) = 0.677 ± 0.09 8 stat ± 0.02 3 syst . Published by the American Physical Society 2024

Ablikim, M.↗
DOE OSTI2025

The BTSbot-nearby Discovery of SN 2024jlf: Rapid, Autonomous Follow-up Probes Interaction in an 18.5 Mpc Type IIP Supernova

We present observations of the Type IIP supernova (SN) SN 2024jlf, including spectroscopy beginning just 0.7 days (∼17 hr) after first light. Rapid follow-up was enabled by the new BTSbot-nearby program, which involves autonomously triggering target-of-opportunity requests for new transients in Zwicky Transient Facility data that are coincident with nearby (D < 60 Mpc) galaxies and identified by the BTSbot machine learning model. Early photometry and nondetections shortly prior to first light show that SN 2024jlf initially brightened by >4 mag day −1 , quicker than ∼90% of Type II SNe. Early spectra reveal weak flash ionization features: narrow, short-lived (1.3 < τ[days] < 1.8) emission lines of Hα, He II , and C IV . Assuming a wind velocity of v w = 50 km s −1 , these properties indicate that the red supergiant progenitor exhibited enhanced mass loss in the last year before explosion. We constrain the mass-loss rate to $1{0}^{-4}\lt \dot{M}\,[{M}_{\odot }\,{\mathrm{yr}}^{-1}]\lt 1{0}^{-3}$ by matching observations to model grids from two independent radiative hydrodynamics codes. BTSbot-nearby automation minimizes spectroscopic follow-up latency, enabling the observation of ephemeral early-time phenomena exhibited by transients.

core-collapse supernovae↗
DOE OSTI2026

Crowdsourcing the Frontier: Advancing Hybrid Physics‐ML Climate Simulation via a $\$$50,000 Kaggle Competition

Subgrid machine-learning (machine learning [ML]) parameterizations have the potential to introduce a new generation of climate models that incorporate the effects of higher-resolution physics without incurring the prohibitive computational cost associated with more explicit physics-based simulations. However, important issues, ranging from online instability to inconsistent online performance, have limited their operational use for long-term climate projections. To more rapidly drive progress in solving these issues, domain scientists and ML researchers opened up the offline aspect of this problem to the broader ML and data science community with the release of ClimSim, a NeurIPS Data sets and Benchmarks publication, and an associated Kaggle competition. This paper reports on the downstream results of the Kaggle competition by coupling emulators inspired by the winning teams' architectures to an interactive climate model (including full cloud microphysics, a regime historically prone to online instability) and systematically evaluating their online performance. Our results demonstrate that online stability in the low-resolution real-geography setting is reproducible across multiple diverse architectures, which we consider a key milestone. All tested architectures exhibit strikingly similar offline and online biases, though their responses to architecture-agnostic design choices (e.g., expanding the list of input variables) can differ significantly. Multiple Kaggle-inspired architectures achieve state-of-the-art results on certain metrics such as zonal mean bias patterns and global Root Mean Squared Error, indicating that crowdsourcing the essence of the offline problem is one path to improving online performance in hybrid physics-AI climate simulation.

Environmental sciences↗
DOE OSTI2026

Enhancing segmentation fairness through curriculum learning and progressive loss: a centralized and federated perspective on radiograph analysis

Bias in medical image segmentation can lead to unequal performance across demographic subgroups, raising concerns about fairness and reliability in clinical AI systems. While deep learning models have achieved high segmentation accuracy, ensuring equitable performance across race and gender remains a significant challenge, particularly in privacy-sensitive healthcare environments. This study investigates fairness-aware medical image segmentation for hip and knee radiographs using deep learning models evaluated in both centralized and Federated Learning (FL) settings. We introduce Curriculum Learning (CL) strategies and Progressive Loss (PL) functions to regulate sample difficulty during training. In addition, we propose two novel fairness-oriented federated learning algorithms, Federated Intersection over Union (FedIoU) and Federated Intersection over Union with Outlier Analysis (FedIoUoutlier). Experiments are conducted using multiple segmentation backbones and simulated multi-site data partitions derived from the Osteoarthritis Initiative dataset. Model performance is evaluated using Intersection over Union (IoU), IoU standard deviation, Skewed Error Ratio (SER), and Min-Max Disparity across race and gender subgroups. Statistical significance was verified using paired t-tests to compare per-sample IoU performance against baseline configurations. Across both hip and knee segmentation tasks, curriculum learning and progressive loss strategies consistently improved segmentation accuracy and reduced demographic performance disparities in centralized training. In federated settings, fairness-aware aggregation further enhanced performance. Notably, FedIoUoutlier combined with balanced curriculum learning and tiered progressive loss achieved the highest mean IoU while yielding the lowest SER and Min-Max Disparity, indicating improved fairness without sacrificing accuracy. In several configurations, federated models matched or exceeded the performance of optimized centralized models, with statistically significant improvements in per-sample IoU over baseline configurations. The results demonstrate that structured training strategies and fairness-aware federated aggregation can jointly improve accuracy, stability, and demographic fairness in medical image segmentation. By integrating curriculum learning, progressive loss, and novel FL algorithms, this work provides a practical pathway toward equitable and privacy-preserving AI systems for medical imaging.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Observation of the W -Annihilation Process D s + → ω ρ + and Measurement of D s + → ϕ ρ + in D s + → π + π + π − π 0 π 0 Decays

We present the first amplitude analysis and branching fraction measurement of the decay D s + → π + π + π − π 0 π 0 , using e + e − collision data collected with the BESIII detector at center-of-mass energies between 4.128 and 4.226 GeV corresponding to an integrated luminosity of 7.33 fb − 1 , and report the first observation of the pure W -annihilation decay D s + → ω ρ + with a branching fraction of ( 0.99 ± 0.0 8 stat − 0.07 + 0.05 syst ) % . In comparison to the low significance of the D wave in the decay D s + → ϕ ρ + , the dominance of the D wave over the S and P waves, with a fraction of ( 51.85 ± 7.2 8 stat − 7.90 + 4.83 syst ) % observed in the decay D s + → ω ρ + , provides crucial information for the “polarization puzzle,” as well as for the understanding of charm meson decays. The branching fraction of D s + → π + π + π − π 0 π 0 is measured to be ( 4.41 ± 0.1 5 stat ± 0.1 3 syst ) % . Moreover, the branching fraction of D s + → ϕ ρ + is measured to be ( 3.98 ± 0.3 3 stat − 0.19 + 0.21 syst ) % , and the R ϕ = B ( ϕ → π + π − π 0 ) / B ( ϕ → K + K − ) is determined to be ( 0.222 ± 0.01 9 stat − 0.016 + 0.016 syst ), which is consistent with the previous measurement based on charm meson decays, but deviates from the results from e + e − annihilation and K − N scattering experiments by more than 3 σ . Published by the American Physical Society 2025

Ablikim, M.↗
DOE OSTI2024

Measurement of the branching fraction of D s + → ℓ + ν ℓ via e + e − → D s * + D s * −

Based on 10.64 fb − 1 of e + e − collision data taken at center-of-mass energies between 4.237 and 4.699 GeV with the BESIII detector, we study the leptonic D s + decays using the e + e − → D s * + D s * − process. The branching fractions of D s + → ℓ + ν ℓ ( ℓ = μ , τ ) are measured to be B D s + → μ + ν μ = ( 0.547 ± 0.02 6 stat ± 0.01 6 syst ) % and B D s + → τ + ν τ = ( 5.60 ± 0.1 6 stat ± 0.2 0 syst ) % , respectively. The product of the decay constant and Cabibbo-Kobayashi-Maskawa matrix element | V c s | is determined to be f D s + | V c s | = ( 246.5 ± 5.9 stat ± 3.6 syst ± 0.5 input ) μ ν and f D s + | V c s | = ( 252.7 ± 3.6 stat ± 4.5 syst ± 0.6 input ) τ ν MeV , respectively. Taking the value of | V c s | from a global fit in the Standard Model, we obtain f D s + = ( 253.2 ± 6.0 stat ± 3.7 syst ± 0.6 input ) μ ν and f D s + = ( 259.6 ± 3.7 stat ± 4.6 syst ± 0.6 input ) τ ν MeV , respectively. Conversely, taking the value for f D s + from the latest lattice quantum chromodynamics calculation, we obtain | V c s | = ( 0.986 ± 0.02 3 stat ± 0.01 4 syst ± 0.00 3 input ) μ ν and | V c s | = ( 1.011 ± 0.01 4 stat ± 0.01 8 syst ± 0.00 3 input ) τ ν , respectively. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2025

Scale-up Unlearnable Examples Learning with High-performance Computing

Recent advancements in AI models, like ChatGPT, are structured to retain user interactions, which could inadvertently include sensitive healthcare data. In the healthcare field, particularly when radiologists use AI-driven diagnostic tools hosted on online platforms, there is a risk that medical imaging data may be repurposed for future AI training without explicit consent, spotlighting critical privacy and intellectual property concerns around healthcare data usage. Addressing these privacy challenges, a novel approach known as Unlearnable Examples (UEs) has been introduced, aiming to make data unlearnable to deep learning models. A prominent method within this area, called Unlearnable Clustering (UC), has shown improved UE performance with larger batch sizes but was previously limited by computational resources (e.g., a single workstation). To push the boundaries of UE performance with theoretically unlimited resources, we scaled up UC learning across various datasets using Distributed Data Parallel (DDP) training on the Summit supercomputer. Our goal was to examine UE efficacy at high-performance computing (HPC) levels to prevent unauthorized learning and enhance data security, particularly exploring the impact of batch size on UE’s unlearnability. Utilizing the robust computational capabilities of the Summit, extensive experiments were conducted on diverse datasets such as Pets, MedMNist, Flowers, and Flowers102. Our findings reveal that both overly large and overly small batch sizes can lead to performance instability and affect accuracy. However, the relationship between batch size and unlearnability varied across datasets, highlighting the necessity for tailored batch size strategies to achieve optimal data protection. The use of Summit’s high-performance GPUs, along with the efficiency of the DDP framework, facilitated rapid updates of model parameters and consistent training across nodes. Our results underscore the critical role of selecting appropriate batch sizes based on the specific characteristics of each dataset to prevent learning and ensure data security in deep learning applications. The source code is publicly available at https: // github. com/ hrlblab/ UE_ HPC .

Zhu, Yanfan [Vanderbilt University, Nashville, TN,↗
DOE OSTI2023

Production of $Υ(nS)$ mesons in Pb + Pb and $pp$ collisions at 5.02 TeV

A measurement of the production of vector bottomonium states, $Υ$(1S), $Υ$(2S), and $Υ$(3S), in Pb + Pb and $pp$ collisions at a center-of-mass energy per nucleon pair of 5.02 TeV is presented. The data correspond to integrated luminosities of 1.38 nb –1 of Pb + Pb data collected in 2018, 0.44 nb –1 of Pb + Pb data collected in 2015, and 0.26 fb –1 of $pp$ data collected in 2017 by the ATLAS detector at the Large Hadron Collider. The measurements are performed in the dimuon decay channel for transverse momentum ${p}_{T}^{μμ}$ < 30 GeV, absolute rapidity |$y^{μμ}$| < 1.5, and Pb + Pb event centrality 0–80%. The production rates of the three bottomonium states in Pb + Pb collisions are compared with those in $pp$ collisions to extract the nuclear modification factors as functions of event centrality, ${p}_{T}^{μμ}$, and $|y^{μμ}|$. In addition, the suppression of the excited states relative to the ground state is studied. The results are compared with theoretical model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Flexible Siting Criteria and Staff Minimization for Micro-Reactors

The economic potential of micro-reactors is vast and underestimated. Commonly-emphasized applications include niche markets such as remote communities, mines and military bases. However, micro-reactors could be used as flexible energy generators also for larger markets, such as mobile and containerized agriculture and manufacturing facilities, district heating, micro-grids for data centers, sea ports, airports and hospitals. The implication is that micro-reactors may have to be deployed also in non-remote locations. Successful implementation of micro-reactors needs a navigable and predictable licensing process, technology-appropriate siting restrictions, risk-informed emergency and safety requirements, and practical operating and maintenance requirements. The primary goal of this project was to develop siting criteria that are tailored to micro-reactors deployable in densely-populated areas, e.g., urban environments. To achieve that goal, we compared the characteristics of the MIT research reactor (MITR) with those of leading micro-reactor concepts (e.g., eVinci, USNC, Aurora), and evaluated whether and how the MITR design basis (e.g., inherent safety features, engineered safety systems, source term, emergency planning and emergency operating procedures) and associated regulations may be applicable to these new micro-reactors as well. What makes MITR a unique analogue in this context is its small power rating (6 MWt) and physical size, mode of operations (24/7 with a somewhat more commercial flavor than typical university reactors), and especially its urban location. Of course significant differences exist, such as mission (power production vs. research) and the reactor design itself. Leveraging the MITR experience, this project was able to generate criteria that will allow micro-reactors to realize their full economic potential as flexible heat and electricity generators for a diverse portfolio of applications in non-remote locations. As such, the outcome of this project might encourage investment in and use of micro-reactors. A second goal of the project was to conceptualize a model of operations for micro-reactors that would minimize the staffing requirements, and thus reduce the cost of electricity and heat generated by these systems. Here too our approach was to systematically review the MITR experience and requirements, as well as survey the innovations in autonomous control technologies and monitoring (e.g., advanced sensors, drones, robotics, AI) that would permit a dramatic reduction in staffing at future micro-reactor installations. The scope of work was expanded after the start date to include also an evaluation of micro-reactor security, using the so-called consequence-based analysis, and the development of a methodology to perform dynamic risk assessment for micro-reactors, using system theory and modeling and simulation.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Observation of Significant Flavor-SU(3) Breaking in the Kaon Wave Function at 12 < Q 2 < 25 GeV 2 and Discovery of the Charmless Decay ψ ( 3770 ) → K S 0 K L 0

We present cross sections for the reaction e + e − → K S 0 K L 0 at center-of-mass energies ranging from 3.51 to 4.95 GeV using data samples collected in the BESIII experiment, corresponding to a total integrated luminosity of 26.5 fb − 1 . The ratio of neutral-to-charged kaon form factors at large momentum transfers ( 12 < Q 2 < 25 GeV 2 ) is determined to be 0.21 ± 0.01 , which indicates a small but significant effect of flavor-SU(3) breaking in the kaon wave function, and, consequently, excludes the possibility that flavor-SU(3) breaking is the primary reason for the strong experimental violation of the pQCD prediction | F ( π ± ) | / | F ( K ± ) | = f π 2 / f K 2 , where F ( π ± ) and F ( K ± ) are the form factors, and f π and f K are the decay constants of charged pions and kaons, respectively. We also observe a significant signal for the charmless decay ψ ( 3770 ) → K S 0 K L 0 for the first time. Within a 1 σ contour of the likelihood value, the branching fraction for ψ ( 3770 ) → K S 0 K L 0 is determined to be B = ( 2.6 3 − 1.59 + 1.40 ) × 10 − 5 , and the relative phase between the continuum and ψ ( 3770 ) amplitudes is ϕ = ( − 0.3 9 − 0.10 + 0.05 ) π . The branching fraction is in good agreement with the S - and D -wave charmonia mixing scheme proposed in the interpretation of the “ ρ π puzzle” between J / ψ and ψ ( 3686 ) decays. Published by the American Physical Society 2024

Physics↗
DOE OSTI2024

Search for Rare Decays of D s + to Final States π + e + e − , ρ + e + e − , π + π 0 e + e − , K + π 0 e + e − , and K S 0 π + e + e −

Using 7.33 fb − 1 of e + e − collision data collected by the BESIII detector at center-of-mass energies in the range of s = 4.128 – 4.226 GeV , we search for the rare decays D s + → h + ( h 0 ) e + e − , where h represents a kaon or pion. By requiring the e + e − invariant mass to be consistent with a ϕ ( 1020 ) , 0.98 < M ( e + e − ) < 1.04 GeV / c 2 , the decay D s + → π + ϕ , ϕ → e + e − is observed with a statistical significance of 7.8 σ , and evidence for the decay D s + → ρ + ϕ , ϕ → e + e − is found for the first time with a statistical significance of 4.4 σ . The decay branching fractions are measured to be B ( D s + → π + ϕ , ϕ → e + e − ) = ( 1.1 7 − 0.21 + 0.23 ± 0.03 ) × 10 − 5 , and B ( D s + → ρ + ϕ , ϕ → e + e − ) = ( 2.4 4 − 0.62 + 0.67 ± 0.16 ) × 10 − 5 , where the first uncertainties are statistical and the second systematic. No significant signals for the three four-body decays of D s + → π + π 0 e + e − , D s + → K + π 0 e + e − , and D s + → K S 0 π + e + e − are observed. For D s + → π + π 0 e + e − , the ϕ mass region is vetoed to minimize the long-distance effects. The 90% confidence level upper limits set on the branching fractions of these decays are in the range of ( 7.0 – 8.1 ) × 10 − 5 . Published by the American Physical Society 2024

Physics↗
DOE OSTI2024

Measurements of Born cross sections for e + e − → Λ c + Λ ¯ c ( 2595 ) − + c . c . and e + e − → Λ c + Λ ¯ c ( 2625 ) − + c . c . at s = 4918.0 and 4950.9 MeV

Using e + e − collision data collected with the BESIII detector operating at the BEPCII collider, the Born cross sections of e + e − → Λ c + Λ ¯ c ( 2595 ) − + c . c . and e + e − → Λ c + Λ ¯ c ( 2625 ) − + c . c . are measured for the first time at center-of-mass energies of s = 4918.0 and 4950.9 MeV. Nonzero cross sections are observed very close to the production threshold. The measured Born cross sections of e + e − → Λ c + Λ ¯ c ( 2625 ) − + c . c . are about 2–3 times greater than those of e + e − → Λ c + Λ ¯ c ( 2595 ) − + c . c . , providing the similar behavior as semileptonic decays of Λ b 0 , but different behavior from that in the hadronic decays of Λ b 0 . The Born cross sections are 15.6 ± 3.1 ± 0.9 pb and 29.4 ± 3.7 ± 2.7 pb for e + e − → Λ c + Λ ¯ c ( 2595 ) − + c . c . , and are 43.4 ± 4.0 ± 4.1 pb and 76.8 ± 6.5 ± 4.2 pb for e + e − → Λ c + Λ ¯ c ( 2625 ) − + c . c . at s = 4918.0 and 4950.9 MeV, respectively. Based on the polar angle distributions of the Λ ¯ c ( 2625 ) − and Λ c ( 2625 ) + , the form-factor ratios | G E | 2 + 3 | G M | 2 / | G C | are determined for e + e − → Λ c + Λ ¯ c ( 2625 ) − + c . c . for the first time, which are 5.95 ± 4.07 ± 0.15 and 0.94 ± 0.32 ± 0.02 at s = 4918.0 and 4950.9 MeV, respectively. All of these first uncertainties are statistical and second systematic. Published by the American Physical Society 2024

Astronomy & Astrophysics↗
DOE OSTI2020

Search for new non-resonant phenomena in high-mass dilepton final states with the ATLAS detector

A search for new physics with non-resonant signals in dielectron and dimuon final states in the mass range above 2 TeV is presented. This is the first search for non-resonant signals in dilepton final states at the LHC to use a background estimate from the data. The data, corresponding to an integrated luminosity of 139 fb –1 , were recorded by the ATLAS experiment in proton-proton collisions at a center-of-mass energy of √s = 13 TeV during Run 2 of the Large Hadron Collider. The benchmark signal signature is a two-quark and two-lepton contact interaction, which would enhance the dilepton event rate at the TeV mass scale. To model the contribution from background processes a functional form is fit to the dilepton invariant-mass spectra in data in a mass region below the region of interest. It is then extrapolated to a high-mass signal region to obtain the expected background there. No significant deviation from the expected background is observed in the data. Upper limits at 95% CL on the number of events and the visible cross-section times branching fraction for processes involving new physics are provided. Observed (expected) 95% CL lower limits on the contact interaction energy scale reach 35.8 (37.6) TeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Deformable phrase level attention: A flexible approach for improving AI based medical coding

Objective: Improving the AI-driven automated medical encoding of clinical text plays a vital role in gathering information on the occurrence of diseases to improve population-level health. This work presents a novel attention mechanism designed to enhance text classification models and ensure appropriate classification of medical concepts in unstructured electronic health records. Materials and Methods: We developed a deformable, phrase-level attention mechanism to identify important lexical word-level and contextual phrase-level information from clinical text documents. We evaluated conventional and transformer-based deep learning models that we extended with our attention mechanism on the extraction of critical cancer information (e.g., site, subsite, laterality, histology, behavior) from 629,908 electronic pathology reports and on the automated medical encoding of 52,722 hospital discharge summaries. Results: Transformer-based models with the deformable, phrase-level attention mechanism achieved the best performance on the extraction of critical cancer information from pathology reports. Conventional- and transformer-based models show similar or better performance than their baseline counterparts on the automated medical encoding of clinical documents. Discussion: The addition of phrase-level information allowed models extended with our proposed method to outperform standard word-level attention. Our method showed favorable properties for the real-world application in terms of model robustness and phenotyping. These results indicate that our method is promising for automated data harmonization for common data models. Conclusion: This work proposes a novel deformable, phrase-level attention mechanism that enhances text classification models in the extraction of medical concepts from clinical text documents. We demonstrate strong performances on two clinical text datasets and showcase real-world deployability of our method.

Automated medical encoding↗
DOE OSTI2025

The Artificial Intelligence Ontology: LLM-Assisted Construction of AI Concept Hierarchies

The Artificial Intelligence Ontology (AIO) is a systematization of artificial intelligence (AI) concepts, methodologies, and their interrelations. Developed via manual curation, with the additional assistance of large language models (LLMs), AIO aims to address the rapidly evolving landscape of AI by providing a comprehensive framework that encompasses both technical and ethical aspects of AI technologies. The primary audience for AIO includes AI researchers, developers, and educators seeking standardized terminology and concepts within the AI domain. We use the term “branches” for classes, and their subclasses, in our ontology that are subclasses of owl:Thing. AIO contains eight branches: Bias, Layer, Machine Learning Task, Mathematical Function, Model, Network, Preprocessing, and Training Strategy, each designed to support the modular composition of AI methods and facilitate a deeper understanding of deep learning architectures and ethical considerations in AI. AIO uses the Ontology Development Kit (ODK) for its creation and maintenance, with its content being more easily updated through AI-driven curation support. This approach not only ensures the ontology's relevance amidst the fast-paced advancements in AI but also significantly enhances its utility for researchers, developers, and educators by simplifying the integration of new AI concepts and methodologies. The ontology's utility is demonstrated through the annotation of AI methods data in a catalog of AI research publications and the integration into the BioPortal ontology resource, highlighting its potential for cross-disciplinary research. The AIO ontology is open source and is available on GitHub ( https://w3id.org/aio/ ) and BioPortal ( https://bioportal.bioontology.org/ontologies/AIO ).

Joachimiak, Marcin P. [Biosystems Data Science Dep↗
DOE OSTI2024

Observation of W Z γ Production in p p Collisions at s = 13 TeV with the ATLAS Detector

This Letter reports the observation of W Z γ production and a measurement of its cross section using 140.1 ± 1.2 fb − 1 of proton-proton collision data recorded at a center-of-mass energy of 13 TeV by the ATLAS detector at the Large Hadron Collider. The W Z γ production cross section, with both the W and Z bosons decaying leptonically, p p → W Z γ → ℓ ′ ± ν ℓ + ℓ − γ ( ℓ ( ′ ) = e , μ ), is measured in a fiducial phase-space region defined such that the leptons and the photon have high transverse momentum and the photon is isolated. The cross section is found to be 2.01 ± 0.30 ( stat ) ± 0.16 ( syst ) fb . The corresponding standard model predicted cross section calculated at next-to-leading order in perturbative quantum chromodynamics and at leading order in the electroweak coupling constant is 1.50 ± 0.06 fb . The observed significance of the W Z γ signal is 6.3 σ , compared with an expected significance of 5.0 σ . © 2024 CERN, for the ATLAS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗