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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Search for pair-produced vectorlike quarks coupling to light quarks in the lepton plus jets final state using 13 TeV p p collisions with the ATLAS detector

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 $\sqrt{s}$ = 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 $\mathscr{B}$⁡(Q →W⁢q) =1, an improvement of 840 GeV on the previous ATLAS limit.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Combined Measurement of the Higgs Boson Mass from the $H→γγ$ and $H→ZZ$*→ 4⁢ℓ Decay Channels with the ATLAS Detector Using $\sqrt{s}$ = 7, 8, and 13 TeV $pp$ Collision Data

A measurement of the mass of the Higgs boson combining the H → ZZ* → 4ℓ and H → γγ decay channels is presented. The result is based on 140 fb –1 of proton-proton collision data collected by the ATLAS detector during LHC run 2 at a centre-of-mass energy of 13 TeV combined with the run 1 ATLAS mass measurement, yielding a Higgs boson mass of 125.11 ± 0.09 (stat.) ± 0.06 (syst.) = 125.11 ± 0.11 GeV. This corresponds to a 0.09 % precision achieved on this fundamental parameter of the Standard Model of particle physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
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↗
DOE OSTI2024

Search for New Phenomena in Two-Body Invariant Mass Distributions Using Unsupervised Machine Learning for Anomaly Detection at s = 13 TeV with the ATLAS Detector

Searches for new resonances are performed using an unsupervised anomaly-detection technique. Events with at least one electron or muon are selected from 140 fb − 1 of p p collisions at s = 13 TeV recorded by ATLAS at the Large Hadron Collider. The approach involves training an autoencoder on data, and subsequently defining anomalous regions based on the reconstruction loss of the decoder. Studies focus on nine invariant mass spectra that contain pairs of objects consisting of one light jet or b jet and either one lepton ( e , μ ) , photon, or second light jet or b jet in the anomalous regions. No significant deviations from the background hypotheses are observed. Limits on contributions from generic Gaussian signals with various widths of the resonance mass are obtained for nine invariant masses in the anomalous regions. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Measurement of the Centrality Dependence of the Dijet Yield in p + Pb Collisions at s NN = 8.16 TeV with the ATLAS Detector

ATLAS measured the centrality dependence of the dijet yield using 165 nb − 1 of p + Pb data collected at s NN = 8.16 TeV in 2016. The event centrality, which reflects the p + Pb impact parameter, is characterized by the total transverse energy registered in the Pb-going side of the forward calorimeter. The central-to-peripheral ratio of the scaled dijet yields, R CP , is evaluated, and the results are presented as a function of variables that reflect the kinematics of the initial hard parton scattering process. The R CP shows a scaling with the Bjorken x of the parton originating from the proton, x p , while no such trend is observed as a function of x Pb . This analysis provides unique input to understanding the role of small proton spatial configurations in p + Pb collisions by covering parton momentum fractions from the valence region down to x p ∼ 10 − 3 and x Pb ∼ 4 × 10 − 4 . © 2024 CERN, for the ATLAS Collaboration 2024 CERN

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Combination of Searches for Resonant Higgs Boson Pair Production Using p p Collisions at s = 13 TeV with the ATLAS Detector

A combination of searches for a new resonance decaying into a Higgs boson pair is presented, using up to 139 fb − 1 of p p collision data at s = 13 TeV recorded with the ATLAS detector at the LHC. The combination includes searches performed in three decay channels: b b ¯ b b ¯ , b b ¯ τ + τ − , and b b ¯ γ γ . No excess above the expected Standard Model background is observed and upper limits are set at the 95% confidence level on the production cross section of Higgs boson pairs originating from the decay of a narrow scalar resonance with mass in the range 251 GeV–5 TeV. The observed (expected) limits are in the range 0.96–600 fb (1.2–390 fb). The limits are interpreted in the type-I two-Higgs-doublet model and the minimal supersymmetric standard model, and constrain parameter space not previously excluded by other searches. © 2024 CERN, for the ATLAS Collaboration 2024 CERN

Aad, G. (ORCID:0000000266654934)↗
DOE OSTI2024

Search for Light Long-Lived Particles in $pp$ Collisions at $\sqrt{s} =$ 13 TeV Using Displaced Vertices in the ATLAS Inner Detector

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.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Search for Magnetic Monopole Pair Production in Ultraperipheral Pb + Pb Collisions at s NN = 5.36 TeV with the ATLAS Detector at the LHC

This Letter presents a search for highly ionizing magnetic monopoles in 262 μ b − 1 of ultraperipheral Pb + Pb collision data at s NN = 5.36 TeV collected by the ATLAS detector at the LHC. A new methodology that exploits the properties of clusters of hits reconstructed in the innermost silicon detector layers is introduced to study highly ionizing particles in heavy-ion data. No significant excess above the background, which is estimated using a data-driven technique, is observed. Using a nonperturbative semiclassical model, upper limits at 95% confidence level are set on the cross section for pair production of monopoles with a single Dirac magnetic charge in the mass range of 20–150 GeV. Depending on the model, monopoles with a single Dirac magnetic charge and mass below 80–120 GeV are excluded. © 2025 CERN, for the ATLAS Collaboration 2025 CERN

Aad, G. (ORCID:0000000266654934)↗
DOE OSTI2025

Search for Dark Matter Produced in Association with a Dark Higgs Boson in the b b ¯ Final State Using p p Collisions at s = 13 TeV with the ATLAS Detector

A search is performed for dark matter particles produced in association with a resonantly produced pair of b -quarks with 30 < m b b < 150 GeV using 140 fb − 1 of proton-proton collisions at a center-of-mass energy of 13 TeV recorded by the ATLAS detector at the LHC. This signature is expected in extensions of the standard model predicting the production of dark matter particles, in particular those containing a dark Higgs boson s that decays into b b ¯ . The highly boosted s → b b ¯ topology is reconstructed using jet reclustering and a new identification algorithm. This search places stringent constraints across regions of the dark Higgs model parameter space that satisfy the observed relic density, excluding dark Higgs bosons with masses between 30 and 150 GeV in benchmark scenarios with Z ′ mediator masses up to 4.8 TeV at 95% confidence level. © 2025 CERN, for the ATLAS Collaboration 2025 CERN

Aad, G. (ORCID:0000000266654934)↗
DOE OSTI2023

The Coastal Carbon Library and Atlas: Open source soil data and tools supporting blue carbon research and policy

Abstract Quantifying carbon fluxes into and out of coastal soils is critical to meeting greenhouse gas reduction and coastal resiliency goals. Numerous ‘blue carbon’ studies have generated, or benefitted from, synthetic datasets. However, the community those efforts inspired does not have a centralized, standardized database of disaggregated data used to estimate carbon stocks and fluxes. In this paper, we describe a data structure designed to standardize data reporting, maximize reuse, and maintain a chain of credit from synthesis to original source. We introduce version 1.0.0. of the Coastal Carbon Library, a global database of 6723 soil profiles representing blue carbon‐storing systems including marshes, mangroves, tidal freshwater forests, and seagrasses. We also present the Coastal Carbon Atlas, an R‐shiny application that can be used to visualize, query, and download portions of the Coastal Carbon Library. The majority (4815) of entries in the database can be used for carbon stock assessments without the need for interpolating missing soil variables, 533 are available for estimating carbon burial rate, and 326 are useful for fitting dynamic soil formation models. Organic matter density significantly varied by habitat with tidal freshwater forests having the highest density, and seagrasses having the lowest. Future work could involve expansion of the synthesis to include more deep stock assessments, increasing the representation of data outside of the U.S., and increasing the amount of data available for mangroves and seagrasses, especially carbon burial rate data. We present proposed best practices for blue carbon data including an emphasis on disaggregation, data publication, dataset documentation, and use of standardized vocabulary and templates whenever appropriate. To conclude, the Coastal Carbon Library and Atlas serve as a general example of a grassroots F.A.I.R. (Findable, Accessible, Interoperable, and Reusable) data effort demonstrating how data producers can coordinate to develop tools relevant to policy and decision‐making.

Holmquist, James R.↗
DOE OSTI2024

Nutri‐cereal tissue‐specific transcriptome atlas during development: Functional integration of gene expression to identify mineral uptake pathways in little millet ( Panicum sumatrense )

SUMMARY Little millet (Panicum sumatrenseRoth ex Roem. & Schult.) is an essential minor millet of southeast Asia and Africa's temperate and subtropical regions. The plant is stress‐tolerant, has a short life cycle, and has a mineral‐rich nutritional profile associated with unique health benefits. We report the developmental gene expression atlas of little millet (genotype JK‐8) from ten tissues representing different stages of its life cycle, starting from seed germination and vegetative growth to panicle maturation. The developmental transcriptome atlas led to the identification of 342 827 transcripts. The BUSCO analysis and comparison with the transcriptomes of related species confirm that this study presents high‐quality, in‐depth coverage of the little millet transcriptome. In addition, the eFP browser generated here has a user‐friendly interface, allowing interactive visualizations of tissue‐specific gene expression. Using these data, we identified transcripts, the orthologs of which inArabidopsisand rice are involved in nutrient acquisition, transport, and response pathways. The comparative analysis of the expression levels of these transcripts holds great potential for enhancing the mineral content in crops, particularly zinc and iron, to address the issue of “hidden hunger” and to attain nutritional security, making it a valuable asset for translational research.

Plant Sciences↗
DOE OSTI2014

SU-E-J-220: Evaluation of Atlas-Based Auto-Segmentation (ABAS) in Head-And-Neck Adaptive Radiotherapy

Purpose: Evaluate the accuracy of atlas-based auto segmentation of organs at risk (OARs) on both helical CT (HCT) and cone beam CT (CBCT) images in head and neck (HN) cancer adaptive radiotherapy (ART). Methods: Six HN patients treated in the ART process were included in this study. For each patient, three images were selected: pretreatment planning CT (PreTx-HCT), in treatment CT for replanning (InTx-HCT) and a CBCT acquired in the same day of the InTx-HCT. Three clinical procedures of auto segmentation and deformable registration performed in the ART process were evaluated: a) auto segmentation on PreTx-HCT using multi-subject atlases, b) intra-patient propagation of OARs from PreTx-HCT to InTx-HCT using deformable HCT-to-HCT image registration, and c) intra-patient propagation of OARs from PreTx-HCT to CBCT using deformable CBCT-to-HCT image registration. Seven OARs (brainstem, cord, L/R parotid, L/R submandibular gland and mandible) were manually contoured on PreTx-HCT and InTx-HCT for comparison. In addition, manual contours on InTx-CT were copied on the same day CBCT, and a local region rigid body registration was performed accordingly for each individual OAR. For procedures a) and b), auto contours were compared to manual contours, and for c) auto contours were compared to those rigidly transferred contours on CBCT. Dice similarity coefficients (DSC) and mean surface distances of agreement (MSDA) were calculated for evaluation. Results: For procedure a), the mean DSC/MSDA of most OARs are >80%/±2mm. For intra-patient HCT-to-HCT propagation, the Resultimproved to >85%/±1.5mm. Compared to HCT-to-HCT, the mean DSC for HCT-to-CBCT propagation drops ∼2–3% and MSDA increases ∼0.2mm. This Resultindicates that the inferior imaging quality of CBCT seems only degrade auto propagation performance slightly. Conclusion: Auto segmentation and deformable propagation can generate OAR structures on HCT and CBCT images with clinically acceptable accuracy. Therefore, they can be reliably implemented in the clinical HN ART process.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

SU-E-T-49: Automatic Beam Angle Determination for Lung IMRT Planning Using a Beam Configuration Atlas

Purpose: To present a technique to automatically determine beam angle configurations for lung IMRT planning based on the patient-specific anatomy and tumor geometry. Methods: The relationship between individual patient anatomy and proper beam configurations was learned from high quality clinical plans in three steps. First, a beam configuration atlas was obtained by classifying 60 lung IMRT plans into 6 beam configuration clusters based on a dissimilarity measure defined between different beam configurations. A beam configuration template was extracted from each cluster to form an atlas. Second, a beam efficiency index map (EI map) was constructed to characterize the geometry of the tumor relative to the lungs, the body and other OARs along each candidate beam direction. Finally, the EI maps of the clinical cases and the cluster assignments of their beam configurations were paired to train a Bayesian classification model. This technique was validated by leave-one-out cross validation with 16 cases randomly selected from the original dataset. An IMRT plan (autobeam plan) for each test case was generated using the beam configuration template according to the cluster assignment given by the model and was compared with the corresponding clinical plan. Results: The dosimetric parameters (mean±S.D. in percentage of prescription dose) in the auto-beam plans and in the clinical plans, respectively, and the p-values by a paired ttest (in parenthesis) are: lung Dmean: 16.3±9.3, 18.6±7.4 (0.48), esophagus Dmean: 28.4±18, 30.7±19.3 (0.02), Heart Dmean: 21.5±17.5,21.1±17.2 (0.76), Spinal Cord D2%: 48±23, 51.2±21.8 (0.01), PTV dose homogeneity (D2%–D99%): 22±27.4, 20.4±12.8 (0.10).The dose reductions by the autobeam plans in esophagus Dmean and cord D02 are statistically significant but the differences (<4%) may not be clinically significant. The other dosimetric parameters are not statistically different. Conclusion: Plans generated by the automatic beam angle determination method can achieve dosimetric quality equivalent to that of clinical plans. Partially supported by NIH/NCI under grant #R21CA161389 and a master research grant by Varian Medical System.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-J-111: A Novel Distance-Dose Weighting Method for Label Fusion in Multi- Atlas Segmentation for Prostate Radiation Therapy

Purpose: A novel distance-dose weighting method for label fusion was developed to increase segmentation accuracy in dosimetrically important regions for prostate radiation therapy. Methods: Label fusion as implemented in the original SIMPLE (OS) for multi-atlas segmentation relies iteratively on the majority vote to generate an estimated ground truth and DICE similarity measure to screen candidates. The proposed distance-dose weighting puts more values on dosimetrically important regions when calculating similarity measure. Specifically, we introduced distance-to-dose error (DDE), which converts distance to dosimetric importance, in performance evaluation. The DDE calculates an estimated DE error derived from surface distance differences between the candidate and estimated ground truth label by multiplying a regression coefficient. To determine the coefficient at each simulation point on the rectum, we fitted DE error with respect to simulated voxel shift. The DEs were calculated by the multi-OAR geometry-dosimetry training model previously developed in our research group. Results: For both the OS and the distance-dose weighted SIMPLE (WS) results, the evaluation metrics for twenty patients were calculated using the ground truth segmentation. The mean difference of DICE, Hausdorff distance, and mean absolute distance (MAD) between OS and WS have shown 0, 0.10, and 0.11, respectively. In partial MAD of WS which calculates MAD within a certain PTV expansion voxel distance, the lower MADs were observed at the closer distances from 1 to 8 than those of OS. The DE results showed that the segmentation from WS produced more accurate results than OS. The mean DE error of V75, V70, V65, and V60 were decreased by 1.16%, 1.17%, 1.14%, and 1.12%, respectively. Conclusion: We have demonstrated that the method can increase the segmentation accuracy in rectum regions adjacent to PTV. As a result, segmentation using WS have shown improved dosimetric accuracy than OS. The WS will provide dosimetrically important label selection strategy in multi-atlas segmentation. CPRIT grant RP150485.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-JeP2-02: A Unifying Multi-Atlas Approach to Electron Density Mapping Using Multi-Parametric MRI for Radiation Treatment Planning

Purpose: MRI has a number of advantages over CT as a primary modality for radiation treatment planning (RTP). However, one key bottleneck problem still remains, which is the lack of electron density information in MRI. In the work, a reliable method to map electron density is developed by leveraging the differential contrast of multi-parametric MRI. Methods: We propose a probabilistic Bayesian approach for electron density mapping based on T1 and T2-weighted MRI, using multiple patients as atlases. For each voxel, we compute two conditional probabilities: (1) electron density given its image intensity on T1 and T2-weighted MR images, and (2) electron density given its geometric location in a reference anatomy. The two sources of information (image intensity and spatial location) are combined into a unifying posterior probability density function using the Bayesian formalism. The mean value of the posterior probability density function provides the estimated electron density. Results: We evaluated the method on 10 head and neck patients and performed leave-one-out cross validation (9 patients as atlases and remaining 1 as test). The proposed method significantly reduced the errors in electron density estimation, with a mean absolute HU error of 138, compared with 193 for the T1-weighted intensity approach and 261 without density correction. For bone detection (HU>200), the proposed method had an accuracy of 84% and a sensitivity of 73% at specificity of 90% (AUC = 87%). In comparison, the AUC for bone detection is 73% and 50% using the intensity approach and without density correction, respectively. Conclusion: The proposed unifying method provides accurate electron density estimation and bone detection based on multi-parametric MRI of the head with highly heterogeneous anatomy. This could allow for accurate dose calculation and reference image generation for patient setup in MRI-based radiation treatment planning.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

WE-H-207A-07: Image-Based Versus Atlas-Based Internal Dosimetry

Purpose: Monte Carlo (MC) simulation is known as the gold standard method for internal dosimetry. It requires radionuclide distribution from PET or SPECT and body structure from CT for accurate dose calculation. The manual or semi-automatic segmentation of organs from CT images is a major obstacle. The aim of this study is to compare the dosimetry results based on patient’s own CT and a digital humanoid phantom as an atlas with pre-specified organs. Methods: SPECT-CT images of a 50 year old woman who underwent bone pain palliation with Samarium-153 EDTMP for osseous metastases from breast cancer were used. The anatomical date and attenuation map were extracted from SPECT/CT and three XCAT digital phantoms with different BMIs (i.e. matched (38.8) and unmatched (35.5 and 36.7) with patient’s BMI that was 38.3). Segmentation of patient’s organs in CT image was performed using itk-SNAP software. GATE MC Simulator was used for dose calculation. Specific absorbed fractions (SAFs) and S-values were calculated for the segmented organs. Results: The differences between SAFs and S-values are high using different anatomical data and range from −13% to 39% for SAF values and −109% to 79% for S-values in different organs. In the spine, the clinically important target organ for Samarium Therapy, the differences in the S-values and SAF values are higher between XCAT phantom and CT when the phantom with identical BMI is employed (53.8% relative difference in S-value and 26.8% difference in SAF). However, the whole body dose values were the same between the calculations based on the CT and XCAT with different BMIs. Conclusion: The results indicated that atlas-based dosimetry using XCAT phantom even with matched BMI for patient leads to considerable errors as compared to image-based dosimetry that uses the patient’s own CT Patient-specific dosimetry using CT image is essential for accurate results.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A reference tissue atlas for the human kidney

Kidney Precision Medicine Project (KPMP) is building a spatially specified human kidney tissue atlas in health and disease with single-cell resolution. Here, we describe the construction of an integrated reference map of cells, pathways, and genes using unaffected regions of nephrectomy tissues and undiseased human biopsies from 56 adult subjects. We use single-cell/nucleus transcriptomics, subsegmental laser microdissection transcriptomics and proteomics, near-single-cell proteomics, 3D and CODEX imaging, and spatial metabolomics to hierarchically identify genes, pathways, and cells. Integrated data from these different technologies coherently identify cell types/subtypes within different nephron segments and the interstitium. These profiles describe cell-level functional organization of the kidney following its physiological functions and link cell subtypes to genes, proteins, metabolites, and pathways. They further show that messenger RNA levels along the nephron are congruent with the subsegmental physiological activity. This reference atlas provides a framework for the classification of kidney disease when multiple molecular mechanisms underlie convergent clinical phenotypes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Improvements in simulation of multiple scattering effects in ATLAS fast simulation

Fast ATLAS Tracking Simulation (Fatras) package was verified on single layer geometry with respect to full simulation with GEANT4. Fatras hadronic interactions and multiple scattering simulation were studied in comparison with GEANT4. Disagreement was found in multiple scattering distributions of primary charged particles (μ, π, e). A new model for multiple scattering simulation was implemented in Fatras. The model was based on R. Frühwirth’s mixture models. New model was tested on single layer geometry and a good agreement with GEANT4 was achieved. Also a comparison of reconstructed tracks’ parameters was performed for Inner Detector geometry, and Fatras with new multiple scattering model proved to have better agreement with GEANT4. New model of multiple scattering was added as a part of Fatras package in the development release of ATLAS software—ATHENA.

74 ATOMIC AND MOLECULAR PHYSICS↗