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At least 865 records · Page 48

Prospects for Higgs and di-Higgs measurements at the ATLAS experiment

The large dataset of about 3000 {fb}^{-1} f b − 1 that will be collected at the High Luminosity LHC (HL-LHC) will be used to measure Higgs boson processes in detail. This large dataset will also provide sensitivity to di-Higgs processes and will allow for the improvement of the constraints on the Higgs boson self coupling. Studies based on current ATLAS analyses using LHC Run 2 data have been carried out to understand the expected precision and limitations of the Higgs and di-Higgs measurements at the HL-LHC. This paper presents the ATLAS prospects for Higgs and di-Higgs results at the HL-LHC.

Betti, Alessandra↗

Search for New Physics with Top and Bottom Quarks with ATLAS

The studies performed by the principal investigator during the period of the grant constitute the ground work for search for new physics in channels including top and bottom quarks with the ATLAS detector at the Large Hadron Collider. The PI has been involved in search for heavy charged Higgs bosons decaying into top and bottom quark pairs, and top quark rare decays involving Higgs bosons and c -quarks. Both channels have the top quark pair production as their main background, which was studied in detail. The search for heavy charged Higgs and top quark rare decays requires significant amount of data accumulated by the experiment. In case no signal is observed in the present data sample collected by ATLAS (5 fb -1 of integrated luminosity at proton-anti proton center-of-mass energy of 7 TeV and 20 fb -1 at 8 TeV), data from the upgraded detector running at 14 TeV needs to be analyzed. The PI has been working on physics and performance studies at upgraded detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Compilation of the ``Atlas of Gamma-rays from the Inelastic Scattering of Reactor Fast Neutrons'' (1978DE41) by A.M. Demidov, L.I. Govor, Yu. K. Cherepantsev, M.R. Ahmed, S. Al-Najjar, M.A. Al-Amili, N. Al-Assafi, and N. Rammo

A Structured Query Language (SQL) relational database has been developed based on the original (n,n'gamma) work carried out by A.M. Demidov et al., at the Nuclear Research Institute in Baghdad, Iraq [``Atlas of Gamma-Ray Spectra from the Inelastic Scattering of Reactor Fast Neutrons'', Nuclear Research Institute, Baghdad, Iraq (Moscow, Atomizdat 1978)] for 105 independent measurements comprising 76 elemental samples of natural composition and 29 isotopically-enriched samples. The information from this ATLAS includes: gamma-ray energies and intensities; nuclide and level data corresponding to where the gamma-ray originated from; target (sample) experimental-measurement data. Taken together, this information allows for the extraction of the flux-weighted (n,n'gamma) cross sections for a given transition relative to a defined value. Currently, we are using the fast-neutron flux-weighted partial gamma-ray cross section from ENDF/B-VII.1 for the production of the 847-keV transition from the first excited 2+ state to the 0+ ground state in 56Fe, 468 mb. This value also takes into account contributions to the 847-keV transition following beta(-) decay of 56Mn formed in the 56Fe(n,p) reaction. However, this value can easily be adjusted to accommodate the user preference. The (n,n'gamma) data has been compiled into a series of ASCII comma separated value tables and a suite of Python scripts and C modules are provided to build the database. Upon building, the database can then be interacted with directly via the SQLite engine or accessed via the Jupyter Notebook Python-browser interface. Several examples exploiting these utilities are also provided with the complete software package.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Performance of b Jet Identification at $\sqrt{s}$ = 13 TeV with the ATLAS Detector at CERN [Slides]

The efficient identification of jets from bottom quarks (b-jets) is one of the most important techniques for many physics analyses at the Large Hadron Collider, including studies of the Higgs boson, the top quark, and searches beyond the Standard Model. The performance is characterized by b-tagging efficiency (probability to identify a b-jet as such) and the mistag rate (probability to mistakenly accept a non-b-jet).The mistag occurs as a result of finite detector resolution, presence of long-lived particles, and material interactions. As these effects can be different between the experimental data and Monte Carlo (MC) simulation, it is important to measure the b-tagging performance in data and derive the MC correction factors. I will describe various methods to measure the performance of b jet identification in pp collisions at √s = 13 TeV with the ATLAS detector and will report on Direct Tag method which is recently developed in the ATLAS collaboration for Light jet calibration.

43 PARTICLE ACCELERATORS↗

A Letter of Intent for MATHUSLA: a dedicated displaced vertex detector above ATLAS or CMS.

In this Letter of Intent we propose the construction of MATHUSLA (MAssive Timing Hodoscope for Ultra-Stable neutraL pArticles), a dedicated large-volume displaced vertex detector (DV) for the HL-LHC on the surface above ATLAS or CMS. Such a detector, which can be built using existing technologies with a reasonable budget in time for the HL-LHC upgrade, could search for neutral long-lived particles (LLPs) without trigger limitations and with very low or zero backgrounds, allowing it to probe LLP cross sections and lifetimes up to several orders of magnitude beyond the reach of ATLAS or CMS. MATHUSLA would also act as a cutting-edge cosmic ray telescope at CERN, exploring many open questions in cosmic ray and astro-particle physics.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Search for New Physics with Top Quarks and Upgrade to the ATLAS Liquid Argon Calorimeter

The recent successful discovery of the Higgs boson at the Large Hadron Collider (LHC) at the European Center for Nuclear Research (CERN) in Geneva, Switzerland provides a long sought-after key to the Standard Model of particle physics. However, the existence (and mass) of this fundamental scalar does not resolve the tension between the electroweak and Planck scales, hinting at the possibility of new physics that may be accessible at the LHC. The objective of this research is to search for signs of such new physics, in particular for the existence of a supersymmetric partner to the top quark, using the ATLAS (A Toroidal LHC ApparatuS) detector at the LHC to reconstruct signatures of top quarks and missing energy from corresponding undetected particles. Furthermore, in order to ensure that the full potential of the LHC is harnessed in future searches for new physics, the project also entails the upgrade of the ATLAS Liquid Argon Calorimeter read-out electronics, thereby improving the performance of boosted objects, jets, and missing energy triggers for planned higher luminosity running conditions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Information on Subsequent Updates to Regional Atlas - SECARB Virtual

During 2020, SSEB worked with its SECARB partners to develop an update for the sixth version of the Atlas to be published as a virtual-only edition by NETL. The following report provides content that was sent to NETL for the SECARB portions of Atlas VI. This report satisfies the requirements for Work Product 1.9.a.

54 ENVIRONMENTAL SCIENCES↗

Global Soil Virus (GSV) Atlas

Historically neglected by microbial ecologists, soil viruses are now thought to be critical to global biogeochemical cycles. However, our understanding of their global distribution, activities, and interactions with the soil microbiome remains limited. Here, we present the Global Soil Virus (GSV) Atlas, a comprehensive dataset from 2,953 soils that comprises 616,935 uncultivated virus genomes (UViGs) and 38,508 unique viral operational taxonomic units (vOTUs). Rarefaction curves from the GSV Atlas indicate that most soil viral diversity remains unexplored, further underscored by high spatial turnover and low rates of shared vOTUs across samples. By examining genes associated with biogeochemical functions, we also demonstrate the viral potential to impact soil carbon and nutrient cycling. This study represents the most extensive characterization of soil viral diversity to date and provides a foundation for developing testable hypotheses regarding the role of the virosphere in the soil microbiome and global biogeochemistry.

Graham, Emily B↗

Toward a tomographic analysis of the cross-correlation between planck CMB lensing and H-ATLAS galaxies

We present an improved and extended analysis of the cross-correlation between the map of the cosmic microwave background (CMB) lensing potential derived from the Planck mission data and the high-redshift galaxies detected by the Herschel Astrophysical Terahertz Large Area Survey (H-ATLAS) in the photometric redshift range z{sub ph}⩾1.5. We compare the results based on the 2013 and 2015 Planck datasets, and investigate the impact of different selections of the H-ATLAS galaxy samples. Significant improvements over our previous analysis have been achieved thanks to the higher signal-to-noise ratio of the new CMB lensing map recently released by the Planck collaboration. The effective galaxy bias parameter, b, for the full galaxy sample, derived from a joint analysis of the cross-power spectrum and of the galaxy auto-power spectrum is found to be b=3.54{sub −0.14}{sup +0.15}. Furthermore, a first tomographic analysis of the cross-correlation signal is implemented by splitting the galaxy sample into two redshift intervals: 1.5⩽z{sub ph}<2.1 and z{sub ph}⩾2.1. A statistically significant signal was found for both bins, indicating a substantial increase with redshift of the bias parameter: b=2.89±0.23 for the lower and b=4.75{sub −0.25}{sup +0.24} for the higher redshift bin. Consistent with our previous analysis, we find that the amplitude of the cross-correlation signal is a factor of 1.45{sub −0.13}{sup +0.14} higher than expected from the standard ΛCDM model for the assumed redshift distribution. The robustness of our results against possible systematic effects has been extensively discussed, although the tension is mitigated by passing from 4 to 3σ.

79 ASTRONOMY AND ASTROPHYSICS↗

Disintegration of Long-period Comet C/2019 Y4 (ATLAS). I. Hubble Space Telescope Observations

The near-Sun comet C/2019 Y4 (ATLAS) is the first member of a long-period comet group observed to disintegrate well before perihelion. Here we present our investigation into this disintegration event using images obtained in a three-day Hubble Space Telescope campaign. We identify two fragment clusters produced by the initial disintegration event, corresponding to fragments C/2019 Y4-A and C/2019 Y4-B identified in ground-based data. These two clusters started with similar integrated brightness but exhibit different evolutionary behavior. C/2019 Y4-A was much shorter-lived compared to C/2019 Y4-B and showed signs of significant mass loss and changes in size distribution throughout the three-day campaign. The cause of the initial fragmentation is undetermined by the limited evidence but crudely compatible with either the spin-up disruption of the nucleus or runaway sublimation of subsurface supervolatile ices, either of which would lead to the release of a large amount of gas as inferred from the significant bluing of the comet observed shortly before its disintegration. Gas can only be produced by the sublimation of volatile ices, which must have survived at least one perihelion passage at a perihelion distance of q = 0.25 au. We speculate that Comet ATLAS is derived from the ice-rich interior of a nonuniform, kilometer-wide progenitor that split during its previous perihelion. This suggests that comets down to a few kilometers in diameter can still possess complex, nonuniform interiors that can protect ices against intense solar heating.

47 OTHER INSTRUMENTATION↗

The Great Observatories All-Sky LIRG Survey: Herschel Image Atlas and Aperture Photometry

Far-infrared images and photometry are presented for 201 Luminous and Ultraluminous Infrared Galaxies [LIRGs: log (L{sub IR}/L{sub ⊙})=11.00--11.99, ULIRGs: log (L{sub IR}/L{sub ⊙})=12.00--12.99], in the Great Observatories All-Sky LIRG Survey (GOALS), based on observations with the Herschel Space Observatory Photodetector Array Camera and Spectrometer (PACS) and the Spectral and Photometric Imaging Receiver (SPIRE) instruments. The image atlas displays each GOALS target in the three PACS bands (70, 100, and 160 μm) and the three SPIRE bands (250, 350, and 500 μm), optimized to reveal structures at both high and low surface brightness levels, with images scaled to simplify comparison of structures in the same physical areas of ∼100 × 100 kpc{sup 2}. Flux densities of companion galaxies in merging systems are provided where possible, depending on their angular separation and the spatial resolution in each passband, along with integrated system fluxes (sum of components). This data set constitutes the imaging and photometric component of the GOALS Herschel OT1 observing program, and is complementary to atlases presented for the Hubble Space Telescope, Spitzer Space Telescope, and Chandra X-ray Observatory. Collectively, these data will enable a wide range of detailed studies of active galactic nucleus and starburst activity within the most luminous infrared galaxies in the local universe.

79 ASTRONOMY AND ASTROPHYSICS↗

Upgrades of the ATLAS Zero Degree Calorimeter System for Run 3 at the Large Hadron Collider

Experimental studies of ultra-relativistic heavy ion collisions at the Large Hadron Collider (LHC) depend crucially on Zero Degree Calorimeters (ZDCs) that measure neutrons produced at near-beam rapidity in nucleus-nucleus collisions. In hadronic nuclear collisions these neutrons are mainly spectator neutrons, those that do not scatter from opposing nucleons during the collision. As a result, the ZDCs provide a vital probe of heavy ion collision geometry. The ZDCs are also essential in the study of ultra-peripheral collisions that are initiated by photons associated with the electric fields of one or both nuclei. Coherent photon emission typically leaves the photon emitter intact, making the observation of no ZDC signal, on one or both sides, a tag of such processes. The ATLAS ZDCs, built prior to Run 1 were substantially upgraded for LHC Run 3. The primary upgrades included replacement of the quartz Cherenkov radiator with $\text{H}_2$-doped fused silica rods; installation of fast air-core signal cables between the ZDC and the ATLAS USA15 cavern; new LED-based calibration system; and new electronics implemented for readout and fully-digital triggering. The ZDCs were also augmented with new "Reaction Plane Detectors" (RPDs) designed to measure the transverse centroid of multi-neutron showers to allow event-by-event reconstruction of the directed-flow plane in nuclear collisions. The Run~3 ZDC detectors, including the RPDs, are described in detail with emphasis on aspects that are new for Run~3.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor↗

Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.

Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.

, Genes, DNA Constructs↗

Flight performance of Atlas-Agena launch vehicles in support of the Lunar Orbiter missions 3, 4, and 5

Atlas-Agena launch vehicles successfully boosted a series of five Lunar Orbiters into proper lunar transfer trajectories. This report discusses the flight performance of the last three Atlas-Agenda launch vehicles (for Lunar Orbiters 111, IV, and V) from lift-off through the Agenda retromaneuver. The objective of these flights was to perform seleno- graphic investigations including photography of the lunar surface. Lunar Orbiter V, launched in August 1967, concluded the Lunar Orbiter missions

Source record↗

Atlas-Centaur AC-17 performance for applications technology satellite ATS-D mission

The Atlas-Centaur launch vehicle (AC-17) with Applications Technology Satellite-D (ATS-D) was launched from Cape Kennedy in August 1968. Mission objectives were not achieved because the Centaur main engine failed to start for the second powered phase. An evaluation is reported of the performance of the Atlas-Centaur systems, from lift off through the Centaur restart attempt. A brief analysis of the Centaur failure is included.

Source record↗

The Copernicus ultraviolet spectral atlas Tau Scorpii

An ultraviolet spectral atlas was presented for the B0 V star, Tau Scorpii. It was scanned from 949 to 1560 A by the Princeton spectrometer aboard the Copernicus satellite. From 949 to 1420 A the observations have a nominal resolution of 0.05 A. At the longer wavelengths, the resolution was 0.1 A. The atlas was presented in both tables and graphs.

Rogerson, J. B., Jr.↗