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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

An improved daily standardized precipitation index dataset for mainland China from 1961 to 2018

The standardized precipitation index (SPI), one of the most commonly used drought indicators, is widely used in the research areas of drought analysis and drought prediction in different fields such as meteorology, agriculture, and hydrology. However, its main disadvantage is the relatively coarse time resolution of one month. To improve the time resolution of SPI to identify flash droughts, we have refined the traditional SPI calculation method and developed a new multi-scale daily SPI dataset based on data from 484 meteorological stations in mainland China from 1961 to 2018. SPI data from three different sites (located in Henan, Yunnan, and Fujian Provinces) at the three-month timescale were analyzed by comparing with historically recorded drought events. We found that the new multi-scale daily SPI can effectively capture drought events in different periods and locations and identify the specific start and end times of drought events. In short, our SPI dataset appears reasonable and capable of facilitating drought research in different fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Study of WH production through vector boson scattering and extraction of the relative sign of the W and Z couplings to the Higgs boson in proton-proton collisions at $\sqrt{s} = 13$ TeV

A search for the production of a W boson and a Higgs boson through vector boson scattering (VBS) is presented, using CMS data from proton-proton collisions at $\sqrt{s} = 13$ TeV collected from 2016 to 2018. The integrated luminosity of the data sample is 138 fb −1 . Selected events must be consistent with the presence of two jets originating from VBS, the leptonic decay of the W boson to an electron or muon, possibly also through an intermediate τ lepton, and a Higgs boson decaying into a pair of b quarks, reconstructed as either a single merged jet or two resolved jets. A measurement of the process as predicted by the standard model (SM) is performed alongside a study of beyond-the-SM (BSM) scenarios. The SM analysis sets an observed (expected) 95% co­fidence level upper limit of 14.3 (9.9) on the ratio of the measured VBS WH cross section to that expected by the SM. The BSM analysis, conducted within the so-called 𝜅 framework, excludes all scenarios with 𝜆 WZ < 0 that are consistent with current measurements, where 𝜆 WZ = 𝜅 W ∕𝜅 Z and 𝜅 W and 𝜅 Z are the HWW and HZZ coupling mod­fiers, respectively. The significance of the exclusion is beyond 5 standard deviations, and it is consistent with the SM expectation of 𝜆 WZ = 1.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Adjoint-Based Inversion of Geodetic Data for Sources of Deformation and Strain

An adjoint-based formulation leads to a particularly efficient approach for inverting geodetic measurements for the source of the deformation. Specifically, the quantities necessary to iteratively improve the fit to the observations can be computed with just three forward calculations, one to obtain the current residuals, another to solve the adjoint problem, and a third to compute the step length. An inversion algorithm utilizing the adjoint-based gradient is applied to a set of Interferometric Synthetic Aperture Radar (InSAR) data gathered between 2016 and 2018 over the Tulare Basin in California's Central Valley. Because the measured deformation is due to groundwater withdrawal, a penalty function is included in the inversion to avoid placing aquifer volume change in locations that are far from any documented wells. The solution of the inverse problem provides estimates of aquifer compaction that provide a match to the observed range changes while honoring the well data. The solution indicates an average aquifer volume loss of 2.17 km 3 /year over the two year period from January 2016 to January 2018, encompassing one drought year (2016) and one wet year (2017). Finally, this magnitude of lost volume is compatible with the 3.1 km 3 /year decrease in water volume for the entire Central Valley, estimated from GRACE satellite gravity data.

58 GEOSCIENCES↗
DOE OSTI2026

CHESS 2025: Waveform LiDAR data from NEON AOP surveys

This dataset provides Level 1 (L1) full-waveform light detection and ranging (LiDAR) data collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). These data were acquired to enable characterization of vegetation structure and other three-dimensional features of the land surface, and to evaluate structural changes that may have occurred between a prior LiDAR acquisition in 2018 and the 2025 overflight. Waveform LiDAR data can provide more detailed information about objects on the ground than discrete point clouds typically do, and they are often used for granular target segmentation and characterization of subcanopy vegetation. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. LiDAR data were acquired using the Optech Galaxy Prime Airborne LiDAR Terrain Mapper onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). These are the primary waveform LiDAR data delivered by NEON and are provided per flightline in compressed Pulsewaves format, an open-source binary file standard. A Pulsewaves object comprises a two files: a pulse (.pls) file, which stores the geographic origin, outgoing vector, and metadata for every laser pulse emitted by the scanner, and a wave file (.wvs), which stores the sequential amplitude samples of the outgoing pulse and the returning signals. The files are published here in their compressed forms (.plz, .wvz). All waveform data were processed following the theoretical workflow described in the NEON L0-to-L1 Waveform LiDAR Algorithm Theoretical Basis Document (Krause and Goulden 2022a); however, the Pulsewaves output format differs from a legacy format described in that document. Waveform amplitude samples are recorded at 1 nanosecond intervals. All coordinates are provided in meters. Horizontal coordinates are referenced in Universal Transverse Mercator (UTM) zone 13N and the World Geodetic System (WGS) 1984 ensemble datum. Elevations are referenced to Geoid12A. Waveform data for the UPTA survey area were collected without incident and the published records are complete. However, both the ALMO and CRBU collections experienced issues that resulted in incomplete data for those areas. On collection day 2018-06-16 a hardware failure caused the waveform digitizer to lose data from the eastern edge of the ALMO site (Figure 22). The waveform data for flightlines 2–20 could not be extracted from the digitizer, and the data proved unrecoverable. As a result, a portion of the site does not have coverage with waveform data. Although no hardware failure was observed during collection over the CRBU area, final waveform files generated by vendor software contained only ~25% of the expected number of return pulses. After discovery, NEON initiated troubleshooting with the vendor. The root cause of the data ablation had not been identified at the time of publication. Additional data will be published in an update to this package if further recovery proves successful. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2022

Measurement of the nuclear modification factor for muons from charm and bottom hadrons in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

Heavy-flavour hadron production provides information about the transport properties and microscopic structure of the quark–gluon plasma created in ultra-relativistic heavy-ion collisions. A measurement of the muons from semileptonic decays of charm and bottom hadrons produced in Pb+Pb and pp collisions at a nucleon–nucleon centre-of-mass energy of 5.02 TeV with the ATLAS detector at the Large Hadron Collider is presented. The Pb+Pb data were collected in 2015 and 2018 with sampled integrated luminosities of 208 μb –1 and 38 μb –1 , respectively, and pp data with a sampled integrated luminosity of 1.17 pb –1 were collected in 2017. Muons from heavy-flavour semileptonic decays are separated from the light-flavour hadronic background using the momentum imbalance between the inner detector and muon spectrometer measurements, and muons originating from charm and bottom decays are further separated via the muon track's transverse impact parameter. Differential yields in Pb+Pb collisions and differential cross sections in pp collisions for such muons are measured as a function of muon transverse momentum from 4 GeV to 30 GeV in the absolute pseudorapidity interval |n| < 2. Nuclear modification factors for charm and bottom muons are presented as a function of muon transverse momentum in intervals of Pb+Pb collision centrality. The bottom muon results are the most precise measurement of b quark nuclear modification at low transverse momentum where reconstruction of B hadrons is challenging. The measured nuclear modification factors quantify a significant suppression of the yields of muons from decays of charm and bottom hadrons, with stronger effects for muons from charm hadron decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Full spectrum (350-2500 nm) canopy spectral reflectance, Seward Peninsula, Alaska, 2018

Full-range (350-2500 nm) canopy reflectance spectra of various Arctic tundra ecosystem endmembers, including canopy-scale species endmember spectra, plot-scale spectra, and transect spectra as well as non-vegetated surface (NVS) spectra. The datasets were collected at the three core NGEE-Arctic watersheds, Kougarok, Teller, and Council, as well as the supplemental Kougarok Mile 80 site within the larger Seward Peninsula, Alaska region. The data were collected in July 2018 using a full-range Spectra Vista Corporation (SVC) HR-1024i spectroradiometer. Canopy-scale reflectance was collected with an 8-degree field-of-view (FOV) foreoptic lens. All spectral measurements were collected as calibrated surface radiance and converted to surface reflectance using a 99.99% reflective Spectralon white reference standard. For those canopy spectra collected with associated functional trait data, the FOV of the instrument was positioned to include the same leaves harvested for functional trait measurements, including leaf mass per area (LMA) and foliar carbon and nitrogen content (see associated dataset). Species included in the spectra and functional trait dataset include Alnus viridis, Betula nana, Betula glandulosa, Arctous alpina, and Salix pulchra. This data package includes 35 files in a variety of formats including processed canopy spectra (*.csv), processed dGPS locations (*.csv and *.kmz), digital photographs of spectral targets (*.jpg) and raw data from spectroradiometer and dGPS instruments (compressed as tar.gz). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA208_flmd.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Soil moisture and temperature data along the northeast facing hillslope at the Lower Montane site in the East River Watershed, Colorado

Soil moisture, temperature and electrical conductivity have been monitored with 5TE sensors (Decagon Inc.) located at 10 and 50 cm depth at 4 different locations along the northeast-facing slope at the Lower Montane site in the East River Watershed, Colorado from Oct 2016 to Oct 2018. The purpose of this data is to inform hydrobiogeochemical analyses for the Watershed Function Scientific Focus Area (SFA). The data is reported in 4 csv files labeled their by location identifiers (ER-SMN1-5) and location metadata is provided in SM_loc.csv. These data products are part of the Watershed Function Scientific Focus Area collection effort to further scientific understanding of biogeochemical dynamics from genome to watershed scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Search for $CP$ violation in D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ decays in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search is reported for charge-parity $CP$ violation in D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ decays, using data collected in proton-proton collisions at $\sqrt{s}$ = 13 TeV recorded by the CMS experiment in 2018. The analysis uses a dedicated data set that corresponds to an integrated luminosity of 41.6 fb$^{-1}$, which consists of about 10 billion events containing a pair of b hadrons, nearly all of which decay to charm hadrons. The flavor of the neutral D meson is determined by the pion charge in the reconstructed decays D$^{*+}$$\to$ D$^0\pi^+$ and D$^{*-}$$\to$ D$^0\pi^-$. The $CP$ asymmetry in D$^0$$\to$ K$^0_\mathrm{S}$K$^0_\mathrm{S}$ is measured to be $A_{CP}$(K$^0_\mathrm{S}$K$^0_\mathrm{S}$) = (6.2 $\pm$ 3.0 $\pm$ 0.2 $\pm$ 0.8)%, where the three uncertainties represent the statistical uncertainty, the systematic uncertainty, and the uncertainty in the measurement of the $CP$ asymmetry in the D$^0$ $\to$ K$^0_\mathrm{S}\pi^+\pi^-$ decay. This is the first $CP$ asymmetry measurement by CMS in the charm sector as well as the first to utilize a fully hadronic final state.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Dark Energy Survey Year 3 results: Cosmological constraints from galaxy clustering and weak lensing

We present the first cosmology results from large-scale structure using the full 5000 deg 2 of imaging data from the Dark Energy Survey (DES) Data Release 1. We perform an analysis of large-scale structure combining three two-point correlation functions ( 3 × 2 pt ): (i) cosmic shear using 100 million source galaxies, (ii) galaxy clustering, and (iii) the cross-correlation of source galaxy shear with lens galaxy positions, galaxy–galaxy lensing. To achieve the cosmological precision enabled by these measurements has required updates to nearly every part of the analysis from DES Year 1, including the use of two independent galaxy clustering samples, modeling advances, and several novel improvements in the calibration of gravitational shear and photometric redshift inference. The analysis was performed under strict conditions to mitigate confirmation or observer bias; we describe specific changes made to the lens galaxy sample following unblinding of the results and tests of the robustness of our results to this decision. We model the data within the flat Λ CDM and w CDM cosmological models, marginalizing over 25 nuisance parameters. We find consistent cosmological results between the three two-point correlation functions; their combination yields clustering amplitude S 8 = 0.77 6 - 0.017 + 0.017 and matter density Ω m = 0.33 9 - 0.031 + 0.032 in Λ CDM , mean with 68% confidence limits; S 8 = 0.77 5 - 0.024 + 0.026 , Ω m = 0.35 2 - 0.041 + 0.035 , and dark energy equation-of-state parameter w = - 0.9 8 - 0.20 + 0.32 in w CDM . These constraints correspond to an improvement in signal-to-noise of the DES Year 3 3 × 2 pt data relative to DES Year 1 by a factor of 2.1, about 20% more than expected from the increase in observing area alone. This combination of DES data is consistent with the prediction of the model favored by the Planck 2018 cosmic microwave background (CMB) primary anisotropy data, which is quantified with a probability-to-exceed p = 0.13 –0.48. We find better agreement between DES 3 × 2 pt and Planck than in DES Y1, despite the significantly improved precision of both. When combining DES 3 × 2 pt data with available baryon acoustic oscillation, redshift-space distortion, and type Ia supernovae data, we find p = 0.34 . Combining all of these datasets with Planck CMB lensing yields joint parameter constraints of S 8 = 0.81 2 - 0.008 + 0.008 , Ω m = 0.30 6 - 0.005 + 0.004 , h = 0.68 0 - 0.003 + 0.004 , and ∑ m ν < 0.13 eV (95% C.L.) in Λ CDM ; S 8 = 0.81 2 - 0.008 + 0.008 , Ω m = 0.30 2 - 0.006 + 0.006 , h = 0.68 7 - 0.007 + 0.006 , and w = - 1.03 1 - 0.027 + 0.030 in w CDM .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Chemistry data from soils and soil incubation experiments from the whole-soil warming experiment at Blodgett Forest, CA, 2018, from: “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile”

This dataset contains soil chemistry data of soils from the whole-soil warming experiment at Blodgett Forest in June 2018, and from laboratory incubation experiments conducted with a subset of those soils. Soil samples were collected at five different depths down to 80 cm from soil plots continuously heated by 4°C above ambient temperature for 4.5 years, and from the respective unheated control plots. Incubation experiments were conducted for 28 days with soils collected between 10-30 cm (“surface soils”) and 60-80 cm (“subsoils”) from heated and unheated field plots, amended in the laboratory with cellobiose (C, carbon amendment), or cellobiose plus ammonium and phosphate (CNP, combined carbon, nitrogen and phosphorus amendment). The dataset includes separate files for: (i) total carbon and nitrogen concentrations of initial field soils; (ii) carbon dioxide efflux rates at multiple times throughout the incubation experiments, and respective cumulative carbon dioxide efflux rates, as well as inorganic nitrogen concentrations at the beginning and end of the incubations, and net nitrogen mineralization rates and carbon use efficiency calculated at the end of the incubation. Analysis of these data has been published in Dove et al., (2021), “Metabolic capabilities mute positive response to direct and indirect impacts of warming throughout the soil profile. Nat. Commun. 12:2089”, https://doi.org/10.1038/s41467-021-22408-5. This research was performed as part of the TES Belowground Biogeochemistry SFA project at Lawrence Berkeley National Laboratory.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Search for heavy neutral leptons decaying into muon-pion pairs in the MicroBooNE detector

We present upper limits on the production of heavy neutral leptons (HNLs) decaying to $\mu \pi$ pairs using data collected with the MicroBooNE liquid-argon time projection chamber (TPC) operating at Fermilab. This search is the first of its kind performed in a liquid-argon TPC. We use data collected in 2017 and 2018 corresponding to an exposure of $2.0 \times 10^{20}$ protons on target from the Fermilab Booster Neutrino Beam, which produces mainly muon neutrinos with an average energy of $\approx 800$ MeV. HNLs with higher mass are expected to have a longer time-of-flight to the liquid-argon TPC than Standard Model neutrinos. The data are therefore recorded with a dedicated trigger configured to detect HNL decays that occur after the neutrino spill reaches the detector. We set upper limits at the $90\%$ confidence level on the element $\lvert U_{\mu4}\rvert^2$ of the extended PMNS mixing matrix in the range $\lvert U_{\mu4}\rvert^2<(6.6$-$0.9)\times 10^{-7}$ for Dirac HNLs and $\lvert U_{\mu4}\rvert^2<(4.7$-$0.7)\times 10^{-7}$ for Majorana HNLs, assuming HNL masses between $260$ and $385$ MeV and $\lvert U_{e 4}\rvert^2 = \lvert U_{\tau 4}\rvert^2 = 0$.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Autoencoder-Based Anomaly Detection System for Online Data Quality Monitoring of the CMS Electromagnetic Calorimeter

The CMS detector is a general-purpose apparatus that detects high-energy collisions produced at the LHC. Online data quality monitoring of the CMS electromagnetic calorimeter is a vital operational tool that allows detector experts to quickly identify, localize, and diagnose a broad range of detector issues that could affect the quality of physics data. A real-time autoencoder-based anomaly detection system using semi-supervised machine learning is presented enabling the detection of anomalies in the CMS electromagnetic calorimeter data. A novel method is introduced which maximizes the anomaly detection performance by exploiting the time-dependent evolution of anomalies as well as spatial variations in the detector response. The autoencoder-based system is able to efficiently detect anomalies, while maintaining a very low false discovery rate. The performance of the system is validated with anomalies found in 2018 and 2022 LHC collision data. In addition, the first results from deploying the autoencoder-based system in the CMS online data quality monitoring workflow during the beginning of Run 3 of the LHC are presented, showing its ability to detect issues missed by the existing system.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2020

Automated Data Review of Analytical Laboratory Results at Los Alamos National Laboratory - 20299

Newport News Nuclear BWXT-Los Alamos, LLC (N3B) collects samples in support of the U.S. Department of Energy's (DOE) Office of Environmental Management (EM) Los Alamos Legacy Cleanup Contract (LLCC). N3B receives and reviews over 1.6 million sample data points annually in support of various ongoing environmental monitoring and remediation projects of the LLCC. N3B must demonstrate and document that reported external analytical laboratory data produced for the LLCC are of sufficient quality to fulfill their intended purpose and to support defensible decision making as described in EPA QA/G4 Guidance for the Data Quality Objectives Process 1994. In 2018, N3B assumed management of the LLCC along with the Environmental Information Management (EIM) database that contains all historical and current environmental data associated with the LLCC. The entire EIM database is shared between N3B, Triad National Security, LLC (Triad), and New Mexico Environment Department (NMED). These three parties jointly manage the database, its configuration, and changes / updates. All environmental data that are entered into EIM are updated and available, on a daily basis, in the linked public database Intellus New Mexico (Intellus). The quality and defensibility of the environmental data generated from sampling activities is a key component of an effective remediation process. Providing quality data is accomplished through a data assessment process that includes examination, verification, and validation. Examination is the assessment of completeness of the deliverables, identification of any reporting errors, and determining the usability of the data based on the laboratory's evaluation of its data as described in the case narrative received with the data. Verification consists of an evaluation of the Electronic Data Deliverables (EDD) data report to determine the extent to which the external analytical laboratories met method and contract-specific quality control and reporting requirements. Validation consists of determining the data quality and the extent to which the external analytical laboratories accurately and completely reported all sample and quality control results and satisfied all contract requirements. EIM contains an automatic Data Validation Module which performs automated data review (DVM ADR). DVM ADR is a tool to assist in the validation process. When DVM ADR is used in conjunction with manual examination of sample data packages, the combination of the two will meet and exceed the requirements of verification. N3B recognized an opportunity for process improvement, focusing on DVM ADR configuration and enhancements in EIM. Testing EIM's configuration provided proof of the DVM ADR's capabilities and flexibility to accurately perform routine data checks based on analytical methods and regulatory requirements. In addition, the DVM ADR module was improved through enhancements for all analytes, particularly upgrades for radiochemistry data. Extensive testing of the DVM ADR module occurred using EDDs from actual laboratory analyses on the EIM testing site. During this process, N3B manipulated EDD information to verify that the actual outcomes matched the expected outcomes. The results of this testing were shared with the database architects, and configuration improvements were identified to address these results. During this process, N3B identified that the radiochemical DVM ADR capabilities were underutilized, and so enhanced the DVM ADR functionality with respect to radioanalytical assessment. N3B environmental data uploads to Intellus on a daily basis from EIM, once the analytical data undergoes examination and verification. As such, it is important to have a high level of confidence in the quality and defensibility of the data. The process of manual examination, along with the DVM ADR, in conjunction with full validation of a percentage the data specified through the Data Quality Objectives greatly increases efficiency of data review and confidence level of the quality of the data, and gives the project managers, governmental offices, and the public expedited access to high-quality data. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Model-independent constraints on Ωm and H ( z ) from the link between geometry and growth

ABSTRACT We constrain the expansion history of the Universe and the cosmological matter density fraction in a model-independent way by exclusively making use of the relationship between background and perturbations under a minimal set of assumptions. We do so by employing a Gaussian process to model the expansion history of the Universe from present time to the recombination era. The expansion history and the cosmological matter density are then constrained using recent measurements from cosmic chronometers, Type-Ia supernovae, baryon acoustic oscillations, and redshift-space distortion data. Our results show that the evolution in the reconstructed expansion history is compatible with the Planck 2018 prediction at all redshifts. The current data considered in this study can constrain a Gaussian process on H(z) to an average $9.4 {{\ \rm per\ cent}}$ precision across redshift. We find Ωm = 0.224 ± 0.066, lower but statistically compatible with the Planck 2018 cosmology. Finally, the combination of future DESI measurements with the CMB measurement considered in this work holds the promise of $8 {{\ \rm per\ cent}}$ average constraints on a model-independent expansion history as well as a five-fold tighter Ωm constraint using the methodology developed in this work.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Performance of the CMS Level-1 trigger in proton-proton collisions at $\sqrt{s} =$ 13 TeV

At the start of Run 2 in 2015, the LHC delivered proton-proton collisions at a center-of-mass energy of 13\TeV. During Run 2 (years 2015–2018) the LHC eventually reached a luminosity of 2.1× 1034 cm-2s-1, almost three times that reached during Run 1 (2009–2013) and a factor of two larger than the LHC design value, leading to events with up to a mean of about 50 simultaneous inelastic proton-proton collisions per bunch crossing (pileup). The CMS Level-1 trigger was upgraded prior to 2016 to improve the selection of physics events in the challenging conditions posed by the second run of the LHC. This paper describes the performance of the CMS Level-1 trigger upgrade during the data taking period of 2016–2018. The upgraded trigger implements pattern recognition and boosted decision tree regression techniques for muon reconstruction, includes pileup subtraction for jets and energy sums, and incorporates pileup-dependent isolation requirements for electrons and tau leptons. In addition, the new trigger calculates high-level quantities such as the invariant mass of pairs of reconstructed particles. The upgrade reduces the trigger rate from background processes and improves the trigger efficiency for a wide variety of physics signals.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Results of the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC)

Abstract Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Advanced Fuel Cycle Cost Basis Report: Module D1-2 LWR Pelletized MOX Fuel Fabrication

Nature of this 2021 Module update from previous AFC-CBRs: Use of U,Pu MOX life cycle cost data from late 1970s Non-proliferation Assessment Systems Analysis Program (NASAP). This archived data has been updated in 2018-2019 to reflect today’s regulatory and economic conditions and is presented in 2017. For the lower unit cost MOX fabrication case the PuO 2 from the reprocessed LWR SNF is assumed to be fabricated immediately after aqueous PUREX reprocessing, thus minimizing the time for undesirable actinide radioisotopes, from the standpoint of radiation safety, to build in. Fabricated MOX utilizing separated and multi-year stored Pu from aqueously reprocessed SNF has also been added to this Module as a second LWR MOX fabrication variant, requiring additional and more costly glovebox design and operations to protect personnel. This new NASAP-informed data augments historical data and unit cost projections appearing in the 2009 (Shropshire et al 2009), 2012 (Dixon et al 2012), and 2017 Dixon et al 2017) AFC-CBRs. The “What-it-takes” 2017 unit fabrication cost values based on the updated NASAP studies are escalated to 2020$ for this 2021 Update Report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Status, Challenges, and Plans for Consistent Modeling and Evaluation of Fission Data: Nubar, PFNS, and FPY [Slides]

This presentation discusses the importance of consistent evaluations for fission observables. Currently, prompt fission quantities (e.g., neutron multiplicity, neutron energy spectrum, and fission product yields) are evaluated independently of one another, either with separate models or data-only/non-model evaluations (few – if any – shared model inputs) and inconsistencies can arise in evaluated data (e.g. NSE 190, 258 (2018)). They have found that consistent, model-based evaluations lead to more physical constraints on free parameters in the model, more robust predictions for other observables and other isotopes, that there are correlations between the uncertainties on different observables, and that uncertainties can be propagated to unmeasured quantities. They are working on developing models to the point where fission observables are calculated at the quality needed for an evaluation. They are striving to consistently calculate fission observables, such as $\bar{v}$, PFNS, and FPY, to a quality suitable for an evaluation. Current evaluations for fission observables use separate models for each observable (with minimal shared input) or are purely data driven. LANL models, such as the Monte Carlo CGMF and deterministic BeoH, have different strengths; the similar fission fragment initial conditions and decay models leads to consistency between the two codes (FPY can be connected to $\bar{v}$ and PFNS, even when calculated by different codes). Work is underway by Lovell to optimize the models and Neudecker is working to perform detailed uncertainty quantification. The PFNS, in particular, presents a significant challenge.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗