Timeline / Data.gov — Environment Datasets
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Evidence
| Source | Data.gov — Environment Datasets |
|---|---|
| Agency | Data.gov |
| URL | https://api.gsa.gov/technology/datagov/v4/search?q=environment&sort=last_harvested_date&per_page=100&api_key=${DATAGOV_API_KEY} |
| Observed by | Civic Memory, directly, on 2026-10-03T06:25:35+00:00 |
| Content type | application/json |
| Current object |
e7466994e17b0d4c3f5531c8cec258a8daae265e71486e5acf3126b80e50c4d5
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| Previous object |
7b960992c2aca03af79f8c31c6739402eb368da7d3ff2b402b8dd18936a7421f
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without loss. 2455 line(s) added, 2371 line(s) removed.
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During snow melt events, chloride concentrations can rapidly increase and exceed ecological thresholds, making it important to frequently determine chloride concentrations. However, traditional sampling poses difficulties to rapidly determining chloride concentrations due to timing constraints. To supplement traditional sampling, specific conductance, which is monitored remotely and at 15-minute intervals in many streams, has been used as a primary predictor of chloride concentrations in surrogate regression models. Prior to developing surrogate models, geochemical modeling can be used to calculate the percent contribution of chloride to specific conductance to determine if site-specific regression models are appropriate. In Chester County, Pennsylvania, chloride surrogate models have been previously published for three stream sites using streamflow and specific conductance as explanatory variables. The previously published models use data collected through late 2022/early 2023. However, these models were recalculated to include data through 2024. This data release contains supporting information for the publication titled \"Method to Rapidly Track Salinization in Surface Waters\", and included in the data release is code to complete the geochemical analysis, compare the published models both visually and statistically to newly calculated models that incorporate data collected through 2024, and to create figures evaluating the data. \nModeling data and code are included for 3 stream sites:\nValley Creek at PA Turnpike Bridge near Valley Forge, PA (USGS station 01473169) with discrete water-quality data from nearby downstream site Valley Creek at Wilson Road near Valley Forge, PA (USGS station 01473170);\nWhite Clay Creek near Strickersville, PA (USGS station 01478245); and \nBrandywine Creek at Chadds Ford, PA (USGS station 01481000).\nThis data release contains 11 files: \n1. \"READ_ME_SuppInfo_MethodTrackSalinization.txt\": This file contains important information about the data release files and should be read prior to using the data and code. \n2. \"GEOREF_SuppInfo_MethodTrackSalinization.txt\": This file contains information about the sites used in the analysis. \n3. \"PHREEQC_salinitycalcs.R\": This is the code to complete the geochemical analysis using PHREEQC. \n4-6. \"phreeq_xxxxxxxx.csv\": These are the input files for the \"PHREEQC_salinitycalcs.R\" script. These input files contain discrete water-quality data. xxxxxxxx refers to the three stream sites: USGS-01473170, USGS-01478245, USGS-01481000. \n7. \"models_ancova.R\": This is the code to develop the published and newly calculated chloride surrogate regression models. There is also code to complete an Analysis of Covariance to statistically compare the surrogate models. \n8. \"Prediction_Intervals_Plots_Flow_Duration_Curves.R\": This is the code to visually compare the published and newly calculated surrogate regression models, as well as to create flow duration curves. \n9-11. \"combined_data_xxxxxxxx.csv\": Three input files for the \"models_ancova.R\" script and the \"Prediction_Intervals_Plots_Flow_Duration_Curves.R\" script. These files contain chloride, specific conductance, and streamflow data. xxxxxxxx refers to the three stream sites: USGS-01473169, USGS-01478245, USGS-01481000.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P1QGVZCS", + "description": "Landing page for access to the data", + "format": "XML", + "mediaType": "application/http", + "title": "Digital Data" + }, + { + "@type": "dcat:Distribution", + "description": "The metadata original format", + "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.698be31bb66b01469f9c9f89.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_698be31bb66b01469f9c9f89", + "keyword": [ + "Chester County", + "Geochemistry", + "Pennsylvania", + "USGS:698be31bb66b01469f9c9f89", + "Water Quality", + "environment", + "inlandWaters" + ], + "modified": "2026-09-30T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-76.1400, 39.7200, -75.3700, 40.2500", + "theme": [ + "geospatial" + ], + "title": "Supporting information for publication titled \"Method to Rapidly Track Salinization in Surface Waters\"" + }, + "description": "In streams located throughout temperate regions of the United States, salinity and chloride concentrations have been increasing over time, which can threaten stream health and drinking water quality. During snow melt events, chloride concentrations can rapidly increase and exceed ecological thresholds, making it important to frequently determine chloride concentrations. However, traditional sampling poses difficulties to rapidly determining chloride concentrations due to timing constraints. To supplement traditional sampling, specific conductance, which is monitored remotely and at 15-minute intervals in many streams, has been used as a primary predictor of chloride concentrations in surrogate regression models. Prior to developing surrogate models, geochemical modeling can be used to calculate the percent contribution of chloride to specific conductance to determine if site-specific regression models are appropriate. In Chester County, Pennsylvania, chloride surrogate models have been previously published for three stream sites using streamflow and specific conductance as explanatory variables. The previously published models use data collected through late 2022/early 2023. However, these models were recalculated to include data through 2024. This data release contains supporting information for the publication titled \"Method to Rapidly Track Salinization in Surface Waters\", and included in the data release is code to complete the geochemical analysis, compare the published models both visually and statistically to newly calculated models that incorporate data collected through 2024, and to create figures evaluating the data. \nModeling data and code are included for 3 stream sites:\nValley Creek at PA Turnpike Bridge near Valley Forge, PA (USGS station 01473169) with discrete water-quality data from nearby downstream site Valley Creek at Wilson Road near Valley Forge, PA (USGS station 01473170);\nWhite Clay Creek near Strickersville, PA (USGS station 01478245); and \nBrandywine Creek at Chadds Ford, PA (USGS station 01481000).\nThis data release contains 11 files: \n1. \"READ_ME_SuppInfo_MethodTrackSalinization.txt\": This file contains important information about the data release files and should be read prior to using the data and code. \n2. \"GEOREF_SuppInfo_MethodTrackSalinization.txt\": This file contains information about the sites used in the analysis. \n3. \"PHREEQC_salinitycalcs.R\": This is the code to complete the geochemical analysis using PHREEQC. \n4-6. \"phreeq_xxxxxxxx.csv\": These are the input files for the \"PHREEQC_salinitycalcs.R\" script. These input files contain discrete water-quality data. xxxxxxxx refers to the three stream sites: USGS-01473170, USGS-01478245, USGS-01481000. \n7. \"models_ancova.R\": This is the code to develop the published and newly calculated chloride surrogate regression models. There is also code to complete an Analysis of Covariance to statistically compare the surrogate models. \n8. \"Prediction_Intervals_Plots_Flow_Duration_Curves.R\": This is the code to visually compare the published and newly calculated surrogate regression models, as well as to create flow duration curves. \n9-11. \"combined_data_xxxxxxxx.csv\": Three input files for the \"models_ancova.R\" script and the \"Prediction_Intervals_Plots_Flow_Duration_Curves.R\" script. These files contain chloride, specific conductance, and streamflow data. xxxxxxxx refers to the three stream sites: USGS-01473169, USGS-01478245, USGS-01481000.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/abfde54f-145b-4591-941f-54f655dd9f8d", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/abfde54f-145b-4591-941f-54f655dd9f8d/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_698be31bb66b01469f9c9f89", + "keyword": [ + "Chester County", + "Geochemistry", + "Pennsylvania", + "USGS:698be31bb66b01469f9c9f89", + "Water Quality", + "environment", + "inlandWaters" + ], + "last_harvested_date": "2026-10-03T03:28:44.853683", + "organization": { + "aliases": [ + "dept" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "143529f7-2eef-4a07-b227-93ac9e84fad8", + "logo": "https://raw.githubusercontent.com/GSA/logo/master/doi.png", + "name": "Department of the Interior", + "organization_type": "Federal Government", + "slug": "doi" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "U.S. Geological Survey", + "slug": "supporting-information-for-publication-titled-method-to-rapidly-track-salinization-in-surf", + "spatial_centroid": { + "lat": 39.932, + "lon": -75.83200000000001 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -76.14, + 39.72 + ], + [ + -76.14, + 40.25 + ], + [ + -75.37, + 40.25 + ], + [ + -75.37, + 39.72 + ], + [ + -76.14, + 39.72 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Supporting information for publication titled \"Method to Rapidly Track Salinization in Surface Waters\"", + "type": "dataset" + }, + { + "_score": 8.429131, + "_sort": [ + 1790997783626, + 8.429131, + 0, + "5bcd15f4-547c-4efe-ba72-348ca92b37c0" + ], + "access_level": "public", + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Jason H Chase", + "hasEmail": "mailto:jhchase@usgs.gov" + }, + "description": "This data release includes five comma delimited tables that support sediment fingerprinting efforts within the Esopus Creek watershed. \"Catskills_source_sample_data.csv\" and \"Catskills_target_sample_data.csv\" contain elemental, stable isotope, and particle size analysis results to be used for sediment fingerprinting analysis. \"Catskills_source_sample_info.csv\" and \"Catskills_target_sample_info.csv\" contain additional sample information such as collection date and time, location, percent fine sediment, and sample comments. \"Reporting_limits.csv\" contains the elemental analysis reporting limits provided by the Minerals Analytical Chemistry Laboratory at the Geology, Geophysics, and Geochemistry Science Center in Lakewood, Colorado. 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Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.", + "distribution_titles": [ + "Digital Data", + "Original Metadata" + ], + "harvest_record": "https://catalog.data.gov/harvest_record/70473e9e-aba0-4f07-8b14-806f2497178c", + "harvest_record_raw": "https://catalog.data.gov/harvest_record/70473e9e-aba0-4f07-8b14-806f2497178c/raw", + "has_download": true, + "has_spatial": true, + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6aac2b6a1ba49b6a17baa4f6", + "keyword": [ + "Catskills", + "Esopus Creek", + "New York", + "Stony Clove Creek", + "USGS:6aac2b6a1ba49b6a17baa4f6", + "United States", + "Woodland Creek", + "environment", + "erosion", + "geomorphology", + "grain-size analysis", + "light stable isotope analysis", + "metal elements", + "sediment transport" + ], + "last_harvested_date": "2026-10-03T03:23:03.626298", + "organization": { + "aliases": [ + "dept" + ], + "code_repo_exempt": false, + "code_repo_url": null, + "description": null, + "id": "143529f7-2eef-4a07-b227-93ac9e84fad8", + "logo": "https://raw.githubusercontent.com/GSA/logo/master/doi.png", + "name": "Department of the Interior", + "organization_type": "Federal Government", + "slug": "doi" + }, + "parent_identifier": null, + "popularity": 0, + "publisher": "U.S. Geological Survey", + "slug": "sediment-sample-data-for-identifying-and-monitoring-source-sediment-fingerprints-within-es", + "spatial_centroid": { + "lat": 42.03928, + "lon": -74.35983999999999 + }, + "spatial_shape": { + "coordinates": [ + [ + [ + -74.5422, + 41.9304 + ], + [ + -74.5422, + 42.2026 + ], + [ + -74.0863, + 42.2026 + ], + [ + -74.0863, + 41.9304 + ], + [ + -74.5422, + 41.9304 + ] + ] + ], + "type": "Polygon" + }, + "theme": [ + "geospatial" + ], + "title": "Sediment Sample Data for Identifying and Monitoring Source Sediment Fingerprints within Esopus Creek Watershed, Catskills, NY", + "type": "dataset" + }, + { + "_score": 9.540661, + "_sort": [ + 1790997483931, + 9.540661, + 0, + "d4e8f1e1-3a17-41ba-af3e-7c3f1b57bf8e" + ], + "access_level": "public", + "dcat": { + "accessLevel": "public", + "bureauCode": [ + "010:12" + ], + "contactPoint": { + "@type": "vcard:Contact", + "fn": "Jason H Chase", + "hasEmail": "mailto:jhchase@usgs.gov" + }, + "description": "This data release includes 18 JPEG files of imagery collected during a thermal infrared (TIR) survey on February 2nd, 2024, of an unnamed tributary to Midway Branch in Odenton, Maryland. Images include thermograms and collocated photographs of shallow groundwater seep locations. This data release also includes two comma delimited tables of groundwater seep information and references to associated JPEG imagery files. \"MidwayBr_TIR_points.csv\" contains supporting information such as seep identification numbers, associated imagery file names, date, time, temperature, additional notes, and collocated United States Geological Survey groundwater monitoring locations. \"MidwayBr_TIR_data_dictionary.csv\" contains relevant JPEG file information. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.", + "distribution": [ + { + "@type": "dcat:Distribution", + "accessURL": "https://doi.org/10.5066/P1JXX3GM", + "description": "Landing page for access to the data", + "format": "XML", + "mediaType": "application/http", + "title": "Digital Data" + }, + { + "@type": "dcat:Distribution", + "description": "The metadata original format", + "downloadURL": "https://data.usgs.gov/datacatalog/metadata/USGS.6aac2b431ba49b6a17baa4da.xml", + "format": "XML", + "mediaType": "text/xml", + "title": "Original Metadata" + } + ], + "identifier": "http://datainventory.doi.gov/id/dataset/USGS_6aac2b431ba49b6a17baa4da", + "keyword": [ + "Maryland", + "Patuxent Research Refuge", + "USGS:6aac2b431ba49b6a17baa4da", + "environment", + "groundwater and surface-water interaction", + "groundwater flow", + "thermal imaging", + "water temperature" + ], + "modified": "2026-09-30T00:00:00Z", + "publisher": { + "@type": "org:Organization", + "name": "U.S. Geological Survey" + }, + "spatial": "-76.733300, 39.072400, -76.720200, 39.082400", + "theme": [ + "geospatial" + ], + "title": "Thermal infrared survey imagery of shallow groundwater seeps along unnamed tributary to Midway Branch in Patuxent Research Refuge, Odenton, MD" + }, + "description": "This data release includes 18 JPEG files of imagery collected during a thermal infrared (TIR) survey on February 2nd, 2024, of an unnamed tributary to Midway Branch in Odenton, Maryland. Images include thermograms and collocated photographs of shallow groundwater seep locations. This data release also includes two comma delimited tables of groundwater seep information and references to associated JPEG imagery files. \"MidwayBr_TIR_points.csv\" contains supporting information such as seep identification numbers, associated imagery file names, date, time, temperature, additional notes, and collocated United States Geological Survey groundwater monitoring locations. \"MidwayBr_TIR_data_dictionary.csv\" contains relevant JPEG file information. 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This is one of many datasets used in Bromaghin et al. 2016 (https://doi.org/10.1111/2041-210X.12456). 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This project was a collaboration between NIST, NTIA / ITS, NASA and MITRE.", - "distribution": [ - { - "accessURL": "https://github.com/usnistgov/SEA-DATA", - "description": "The github repository that is used to build the nist.pages site.", - "format": "github repository", - "title": "SEA-Data Web Portal Github Repository" - }, - { - "accessURL": "https://pages.nist.gov/SEA-DATA/", - "description": "A static website describing how to access data from the NASCTN CBRS SEA program.", - "format": "html", - "title": "NASCTN CBRS SEA DATA INSTRUCTIONS" - } - ], - "identifier": "ark:/88434/mds2-4219", - "issued": "2026-06-24", - "keyword": [ - "CBRS", - "ESC", - "NASCTN", - "Naval Radar", - "RF", - "SAS", - "Wireless" - ], - "landingPage": "https://data.nist.gov/od/id/mds2-4219", - "language": [ - "en" - ], - "license": "https://www.nist.gov/open/license", - "modified": "2026-06-01 00:00:00", - "programCode": [ - "006:045" - ], - "publisher": { - "@type": "org:Organization", - "name": "National Institute of Standards and Technology" - }, - "references": [ - "https://nvlpubs.nist.gov/nistpubs/TechnicalNotes/NIST.TN.2359.pdf", - "https://www.mitre.org/sites/default/files/2026-01/PR-25-3159-spectrum-monitoring-sensor-radio-service-assessment.pdf" - ], - "theme": [ - "Advanced Communications:Wireless (RF)" - ], - "title": "SEA-DATA Web Portal" - }, - "description": "Data Access Instructions for The NASCTN CBRS SEA program. This web portal is built using the github repository at https://github.com/usnistgov/SEA-DATA.\nThe purpose of the National Advanced Spectrum and Communications Test Network (NASCTN) Citizens Broadband Radio Service (CBRS) Sharing Ecosystem Assessment (SEA) project is to provide data-driven insight into the CBRS sharing ecosystem’s effectiveness between commercial and Department of Defense (DoD) incumbent systems, and to track changes in the spectrum environment over time. CBRS is the “first of a kind” nationwide shared spectrum ecosystem in the 3550-3700 MHz band. The implementation of this project included the installation of sensor systems at selected sites on the east and the west coast of the United States, along with a control and prototyping system in Boulder, Colorado. This data provides time and frequency selective power measurements from 3530 MHz -3710 MHz from summer 2024 to summer of 2026. This data is targeted at the commercial, military and civilian stakeholders of Citizen's Broadband Radio Service (CBRS) that would benefit from in-depth real time and longitudinal analysis of a shared spectrum environment. These data were collected with sensors running the IEEE 802.15.22.3 Spectrum Characterization and Occupancy Sensing (SCOS) sensor system. In addition, the data is formatted and saved using SigMF (signal metadata format). This project was a collaboration between NIST, NTIA / ITS, NASA and MITRE.", - "distribution_titles": [ - "SEA-Data Web Portal Github Repository", - "NASCTN CBRS SEA DATA INSTRUCTIONS" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/4192cc43-3c9f-4fd1-853a-1668f407473d", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/4192cc43-3c9f-4fd1-853a-1668f407473d/raw", - "has_download": false, - "has_spatial": false, - "identifier": "ark:/88434/mds2-4219", - "keyword": [ - "CBRS", - "ESC", - "NASCTN", - "Naval Radar", - "RF", - "SAS", - "Wireless" - ], - "last_harvested_date": "2026-10-02T19:54:30.915186", - "organization": { - "aliases": [ - "dept", - "doc" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "16980d1c-5e8f-4188-b962-42446f2d3f63", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/commerce.png", - "name": "Department of Commerce", - "organization_type": "Federal Government", - "slug": "commerce" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "National Institute of Standards and Technology", - "slug": "sea-data-web-portal-71c99", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [ - "Advanced Communications:Wireless (RF)" - ], - "title": "SEA-DATA Web Portal", - "type": "dataset" - }, - { - "_score": 14.472305, - "_sort": [ - 1790970867906, - 14.472305, - 0, - "aebd735b-eb6d-4f16-821a-81c41ff63bcb" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "accrualPeriodicity": "irregular", - "bureauCode": [ - "006:55" - ], - "contactPoint": { - "fn": "Noah Schlossberger", - "hasEmail": "mailto:noah.schlossberger@nist.gov" - }, - "description": "We investigate the role of magnetic sublevels in Autler–Townes spectra of Rydberg atoms driven by radio-frequency (RF) fields with arbitrary polarization. While conventional treatments predict two symmetric sidebands from independent $m_J$ transitions, experiments have reported additional unexplained spectral features. We show that these arise from elliptical RF polarization, which coherently couples multiple magnetic sublevels and requires a full multi-level treatment.\nWe develop and diagonalize a Hamiltonian including all coupled m_J sublevels, predicting polarization-dependent degeneracies that produce two, three, or four resolved peaks. Using long-wavelength transitions and an anechoic environment we realize homogeneous RF fields that for the first time enable complete resolution of the m_J-dependent dressed states. We observe excellent agreement with theory as the RF ellipticity is varied.\nThese results demonstrate that RF polarization fundamentally modifies Autler–Townes spectra and provide a consistent framework for interpreting magnetic-sublevel structure, with implications for Rydberg-based RF electrometry and polarimetry.", - "distribution": [ - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4157/4157_README.txt", - "mediaType": "text/plain", - "title": "readme" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4157/Fig2.csv", - "mediaType": "text/csv", - "title": "Figure 2" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4157/Fig3.csv", - "mediaType": "text/csv", - "title": "Figure 3" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4157/Fig4.csv", - "mediaType": "text/csv", - "title": "Figure 4" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4157/Fig5.csv", - "mediaType": "text/csv", - "title": "Figure 5" - } - ], - "identifier": "ark:/88434/mds2-4157", - "issued": "2026-07-23", - "keyword": [ - "Rydberg atoms", - "atomic physics", - "electric field", - "fields strength", - "receivers", - "volts/meter" - ], - "landingPage": "https://data.nist.gov/od/id/mds2-4157", - "language": [ - "en" - ], - "license": "https://www.nist.gov/open/license", - "modified": "2026-04-13 00:00:00", - "programCode": [ - "006:045" - ], - "publisher": { - "@type": "org:Organization", - "name": "National Institute of Standards and Technology" - }, - "theme": [ - "Physics:Atomic, molecular, and quantum", - "Physics:Spectroscopy" - ], - "title": "Data associated with \"Resolving magnetic-sublevel structure in Rydberg Autler-Townes spectra with arbitrary RF polarization\"" - }, - "description": "We investigate the role of magnetic sublevels in Autler–Townes spectra of Rydberg atoms driven by radio-frequency (RF) fields with arbitrary polarization. While conventional treatments predict two symmetric sidebands from independent $m_J$ transitions, experiments have reported additional unexplained spectral features. We show that these arise from elliptical RF polarization, which coherently couples multiple magnetic sublevels and requires a full multi-level treatment.\nWe develop and diagonalize a Hamiltonian including all coupled m_J sublevels, predicting polarization-dependent degeneracies that produce two, three, or four resolved peaks. Using long-wavelength transitions and an anechoic environment we realize homogeneous RF fields that for the first time enable complete resolution of the m_J-dependent dressed states. We observe excellent agreement with theory as the RF ellipticity is varied.\nThese results demonstrate that RF polarization fundamentally modifies Autler–Townes spectra and provide a consistent framework for interpreting magnetic-sublevel structure, with implications for Rydberg-based RF electrometry and polarimetry.", - "distribution_titles": [ - "readme", - "Figure 2", - "Figure 3", - "Figure 4", - "Figure 5" - ], - "harvest_record": "https://catalog.data.gov/harvest_record/16725e56-03f3-4a25-ae99-17ed227a8440", - "harvest_record_raw": "https://catalog.data.gov/harvest_record/16725e56-03f3-4a25-ae99-17ed227a8440/raw", - "has_download": true, - "has_spatial": false, - "identifier": "ark:/88434/mds2-4157", - "keyword": [ - "Rydberg atoms", - "atomic physics", - "electric field", - "fields strength", - "receivers", - "volts/meter" - ], - "last_harvested_date": "2026-10-02T19:54:27.906823", - "organization": { - "aliases": [ - "dept", - "doc" - ], - "code_repo_exempt": false, - "code_repo_url": null, - "description": null, - "id": "16980d1c-5e8f-4188-b962-42446f2d3f63", - "logo": "https://raw.githubusercontent.com/GSA/logo/refs/heads/master/commerce.png", - "name": "Department of Commerce", - "organization_type": "Federal Government", - "slug": "commerce" - }, - "parent_identifier": null, - "popularity": 0, - "publisher": "National Institute of Standards and Technology", - "slug": "data-associated-with-resolving-magnetic-sublevel-structure-in-rydberg-autler-townes-spectr-8191d", - "spatial_centroid": null, - "spatial_shape": null, - "theme": [ - "Physics:Atomic, molecular, and quantum", - "Physics:Spectroscopy" - ], - "title": "Data associated with \"Resolving magnetic-sublevel structure in Rydberg Autler-Townes spectra with arbitrary RF polarization\"", - "type": "dataset" - }, - { - "_score": 3.040184, - "_sort": [ - 1790970867331, - 3.040184, - 0, - "30009b2c-077b-47ab-ac27-2fae47312523" - ], - "access_level": "public", - "dcat": { - "@type": "dcat:Dataset", - "accessLevel": "public", - "accrualPeriodicity": "irregular", - "bureauCode": [ - "006:55" - ], - "contactPoint": { - "fn": "Yamil Simon", - "hasEmail": "mailto:yamil.simon@nist.gov" - }, - "description": "This mass spectrometry (MS) data set encompasses spectra of the extractables and leachables (E&L) of 100 polymer materials sourced from the Scientific Polymer Products Inc Polymer Samples Kit (see: SciPoly_PolymerSampleKit205_Items.xlsx). Extractions of these polymers were carried out using three HPLC-grade solvents of varying polarity (water, isopropanol, and hexane) with 10 mg polymer/mL solvent for 24 hours at 50 °C with shaking. To account for solvent volatility, extractions were carried out in 8 mL pressure tubes from Ace Glass Incorporated (Product #8648-25) (rated at 150 psig).\n\nExtraction solutions were subsequently analyzed using three ionization techniques: Electron Ionization (EI) with GC-MS and Electrospray Ionization (ESI) and Atmospheric Pressure Chemical Ionization (APCI) via LC-MS/MS on an Agilent QTOF 6530 and a Bruker timsTOF Pro 2, respectively.\n\nSeveral precautionary measures had to be taken following the extraction procedure. Extracts were centrifuged and filtered using 0.45-micron syringe filters to prevent prohibitively large particles from interfering with chromatography and MS analysis. Moreover, a guard column was used before the LC column to avoid contamination. As such, pressure build-up would often be a concern, so the LC and guard column had to be thoroughly flushed after each analysis batch.\n\nThousands of spectra were processed using in-house software, generating lists of identifications using the most recent versions of the NIST MS libraries via both direct and hybrid search methods. Some monomers were detected under the given extraction conditions, and many plastic additives (e.g., plasticizers, antioxidants, and processing agents) could be identified; some common examples found in many of the polymer standards include oleamide and palmitamide. High-quality unidentified spectra obtained from the extracts are included in a library of annotated recurrent unidentified spectra (ARUS).\n\nLC Chromatographic Separation Method: LC runs were performed using reversed-phase chromatography with an ACQUITY UPLC CSH C18 column (130 Å (13.0 nm), 1.7 µm, 2.1 mm x 100 mm), mobile phase A: water, and mobile phase B: acetonitrile (both mobile phases containing 0.1 % formic acid). The chromatographic separation method was as follows: injection volume: 10 µL, column temperature: 35°C, flow rate: 0.400 mL/min, and gradient: initial condition of 1.00% B, hold for 1.00 min, linear ramp to 80.00% B in 8.00 min, linear ramp to 99.00% B in 3.00 min, hold for 1.50 min, linear ramp to 1.00% B in 0.50 min, hold for 1.00 min. GC Chromatographic Separation Method: Spectra were obtained using an Agilent 5977B instrument, with GC runs performed using a Restek Rxi-5Sil MS GC Capillary Column (15 m x 250 µm x 0.25 µm) under 2 mL/min He flow. The initial oven temperature was 40°C (held for 3 min), with a ramp rate of 20°C/min, final temperature of 320°C, and final hold time of 3.75 min. \n\nReferences:\n\nBerthelette, K.; Walter, T. H. Column screening for the UPLC separation of plastic additives as part of extractables and leachables workflows; 720006777EN; Waters Corporation, MA, USA, 2020.\n\nLee, P. J.; Di Gioia, A. J. Rapid analysis of 25 common polymer additives; 720002488EN; Waters Corporation, Milford, MA, USA, 2008.\n\nSimón-Manso, Y.; Erisman, E. P.; Mak, T. D.; Burke, M. C.; Zuber, A.; Yang, X.; Liang, Y.; Neta, P.; Bukhari, T.; Williams, A. J.; et al. NIST Mass Spectral Libraries in the Context of the Circular Economy of Plastics. J Am Soc Mass Spectrom 2025, 36 (2), 439–445. DOI: 10.1021/jasms.4c00349.\n", - "distribution": [ - { - "description": "The file contains a description of the dataset directory.", - "downloadURL": "https://data.nist.gov/od/ds/mds2-4147/4147_README.txt", - "format": ".txt", - "mediaType": "text/plain", - "title": "README" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4147/GC_MS_single_quad.zip", - "mediaType": "application/zip", - "title": "GC_MS_single_quad" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4147/QTOF_ESI.zip", - "mediaType": "application/zip", - "title": "QTOF_ESI" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4147/SciPoly_PolymerSampleKit205_Items.xlsx", - "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet", - "title": "SciPoly_PolymerSampleKit205_Items" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4147/timsTOF_APCI.zip", - "mediaType": "application/zip", - "title": "timsTOF_APCI" - } - ], - "identifier": "ark:/88434/mds2-4147", - "issued": "2026-05-13", - "keyword": [ - "APCI-LC-MS/MS", - "ESI-LC-MS/MS", - "GC-MS", - "extractables and leachables", - "ion mobility", - "mass spectrometry", - "plastic-related compounds", - "plastics", - "polymers", - "tandem mass spectrometry" - ], - "landingPage": "https://data.nist.gov/od/id/mds2-4147", - "language": [ - "en" - ], - "license": "https://www.nist.gov/open/license", - "modified": "2026-03-19 00:00:00", - "programCode": [ - "006:045" - ], - "publisher": { - "@type": "org:Organization", - "name": "National Institute of Standards and Technology" - }, - "theme": [ - "Chemistry", - "Chemistry:Analytical chemistry", - "Environment" - ], - "title": "LC-MS/MS and GC-MS Measurements of Extractables and Leachables (E&L) from Polymeric Materials" - }, - "description": "This mass spectrometry (MS) data set encompasses spectra of the extractables and leachables (E&L) of 100 polymer materials sourced from the Scientific Polymer Products Inc Polymer Samples Kit (see: SciPoly_PolymerSampleKit205_Items.xlsx). Extractions of these polymers were carried out using three HPLC-grade solvents of varying polarity (water, isopropanol, and hexane) with 10 mg polymer/mL solvent for 24 hours at 50 °C with shaking. To account for solvent volatility, extractions were carried out in 8 mL pressure tubes from Ace Glass Incorporated (Product #8648-25) (rated at 150 psig).\n\nExtraction solutions were subsequently analyzed using three ionization techniques: Electron Ionization (EI) with GC-MS and Electrospray Ionization (ESI) and Atmospheric Pressure Chemical Ionization (APCI) via LC-MS/MS on an Agilent QTOF 6530 and a Bruker timsTOF Pro 2, respectively.\n\nSeveral precautionary measures had to be taken following the extraction procedure. Extracts were centrifuged and filtered using 0.45-micron syringe filters to prevent prohibitively large particles from interfering with chromatography and MS analysis. Moreover, a guard column was used before the LC column to avoid contamination. As such, pressure build-up would often be a concern, so the LC and guard column had to be thoroughly flushed after each analysis batch.\n\nThousands of spectra were processed using in-house software, generating lists of identifications using the most recent versions of the NIST MS libraries via both direct and hybrid search methods. Some monomers were detected under the given extraction conditions, and many plastic additives (e.g., plasticizers, antioxidants, and processing agents) could be identified; some common examples found in many of the polymer standards include oleamide and palmitamide. High-quality unidentified spectra obtained from the extracts are included in a library of annotated recurrent unidentified spectra (ARUS).\n\nLC Chromatographic Separation Method: LC runs were performed using reversed-phase chromatography with an ACQUITY UPLC CSH C18 column (130 Å (13.0 nm), 1.7 µm, 2.1 mm x 100 mm), mobile phase A: water, and mobile phase B: acetonitrile (both mobile phases containing 0.1 % formic acid). The chromatographic separation method was as follows: injection volume: 10 µL, column temperature: 35°C, flow rate: 0.400 mL/min, and gradient: initial condition of 1.00% B, hold for 1.00 min, linear ramp to 80.00% B in 8.00 min, linear ramp to 99.00% B in 3.00 min, hold for 1.50 min, linear ramp to 1.00% B in 0.50 min, hold for 1.00 min. GC Chromatographic Separation Method: Spectra were obtained using an Agilent 5977B instrument, with GC runs performed using a Restek Rxi-5Sil MS GC Capillary Column (15 m x 250 µm x 0.25 µm) under 2 mL/min He flow. The initial oven temperature was 40°C (held for 3 min), with a ramp rate of 20°C/min, final temperature of 320°C, and final hold time of 3.75 min. \n\nReferences:\n\nBerthelette, K.; Walter, T. H. Column screening for the UPLC separation of plastic additives as part of extractables and leachables workflows; 720006777EN; Waters Corporation, MA, USA, 2020.\n\nLee, P. J.; Di Gioia, A. J. Rapid analysis of 25 common polymer additives; 720002488EN; Waters Corporation, Milford, MA, USA, 2008.\n\nSimón-Manso, Y.; Erisman, E. P.; Mak, T. D.; Burke, M. C.; Zuber, A.; Yang, X.; Liang, Y.; Neta, P.; Bukhari, T.; Williams, A. J.; et al. NIST Mass Spectral Libraries in the Context of the Circular Economy of Plastics. J Am Soc Mass Spectrom 2025, 36 (2), 439–445. 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In this work, we demonstrate a solution to this problem by using a frequency multiplier to drive the qubit with room-temperature control pulses at half or one third of the qubit frequency fQB. The control pulses are up-converted inside the cryogenic environment using a frequency multiplier based on a high-kinetic inductance nonlinear transmission line. We evaluated the success of the up-conversion technique by comparing the randomized benchmarking error-per-gate metrics to that of a standard direct qubit driving technique. The fQB/2 drive technique achieved error rates consistent with the direct drive, with a minimum error-per-gate of 3.5x10−3±0.4x10−3. The fQB/3 drive technique resulted in a minimum error per gate of 7.6x10−3±0.81x10−3. While this demonstration is based around a fQB = 4.836 GHz qubit so that a direct drive comparison is possible, this technique will allow higher-frequency qubits to be tested using existing radio-frequency (RF) infrastructure.", - "distribution": [ - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/4118_README.txt", - "mediaType": "text/plain", - "title": "4118_README" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig2.json", - "mediaType": "application/json", - "title": "fig2" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig3.json", - "mediaType": "application/json", - "title": "fig3" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig5_left.txt", - "mediaType": "text/plain", - "title": "fig5_left" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig5_right.txt", - "mediaType": "text/plain", - "title": "fig5_right" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig6_direct_drive.txt", - "mediaType": "text/plain", - "title": "fig6_direct_drive" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig6_doubler.txt", - "mediaType": "text/plain", - "title": "fig6_doubler" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig6_tripler.txt", - "mediaType": "text/plain", - "title": "fig6_tripler" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig7.json", - "mediaType": "application/json", - "title": "fig7" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4118/fig8.json", - "mediaType": "application/json", - "title": "fig8" - } - ], - "identifier": "ark:/88434/mds2-4118", - "issued": "2026-05-05", - "keyword": [ - "Frequency conversion.", - "Superconductors", - "kinetic inductance" - ], - "landingPage": "https://data.nist.gov/od/id/mds2-4118", - "language": [ - "en" - ], - "license": "https://www.nist.gov/open/license", - "modified": "2026-02-26 00:00:00", - "programCode": [ - "006:045" - ], - "publisher": { - "@type": "org:Organization", - "name": "National Institute of Standards and Technology" - }, - "theme": [ - "Electronics:Superconducting electronics" - ], - "title": "Superconducting Qubit Control Using Cryogenic Frequency Conversion" - }, - "description": "Dataset for the APL paper \"Superconducting Qubit Control Using Cryogenic Frequency Conversion\".\n\nAbstract:\nExpanding to higher qubit frequencies introduces the challenge of routing > 20 GHz signals into a dilution refrigerator without adding excess thermal load or frequency-dependent loss. In this work, we demonstrate a solution to this problem by using a frequency multiplier to drive the qubit with room-temperature control pulses at half or one third of the qubit frequency fQB. The control pulses are up-converted inside the cryogenic environment using a frequency multiplier based on a high-kinetic inductance nonlinear transmission line. We evaluated the success of the up-conversion technique by comparing the randomized benchmarking error-per-gate metrics to that of a standard direct qubit driving technique. The fQB/2 drive technique achieved error rates consistent with the direct drive, with a minimum error-per-gate of 3.5x10−3±0.4x10−3. The fQB/3 drive technique resulted in a minimum error per gate of 7.6x10−3±0.81x10−3. 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For large (sparse) feature matrices, especially ones with binary-valued entries, techniques to figure out the underlying structure of the feature space are widely varied, and different communities have widely different practices and assumptions for what is an appropriate approach. Affinis provides reference implementations for many of these methods, with a consistent API to enable community adoption and a shared benchmarking environment.", - "distribution": [ - { - "accessURL": "https://github.com/usnistgov/affinis", - "description": "via USNISTGOV organization on GitHub", - "format": "plain-text, python code", - "title": "Code Repository" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4107/README-affinis.md", - "format": "markdown", - "mediaType": "text/markdown", - "title": "README" - } - ], - "identifier": "ark:/88434/mds2-4107", - "issued": "2026-05-08", - "keyword": [ - "binary data", - "covariance shrinkage", - "edge prediction", - "feature learning", - "filtering", - "graph theory", - "multi-label", - "network analysis", - "scientific-software", - "sparse matrix", - "structure learning", - "tools" - ], - "landingPage": "https://data.nist.gov/od/id/mds2-4107", - "language": [ - "en" - ], - "license": "https://www.nist.gov/open/license", - "modified": "2026-02-17 00:00:00", - "programCode": [ - "006:045" - ], - "publisher": { - "@type": "org:Organization", - "name": "National Institute of Standards and Technology" - }, - "theme": [ - "Information Technology:Complex systems", - "Information Technology:Computational science", - "Information Technology:Data and informatics", - "Manufacturing:Systems engineering", - "Mathematics and Statistics:Mathematical knowledge management", - "Mathematics and Statistics:Modeling and simulation research", - "Mathematics and Statistics:Numerical methods and software", - "Mathematics and Statistics:Statistical analysis", - "Mathematics and Statistics:Uncertainty quantification" - ], - "title": "Affinis: tools for inferring relations from co-occurrence data" - }, - "description": "Affinis is a tool for assisting in unsupervised structure learning on sparse, binary data. 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From numerical simulations of SWAP using our laser beam geometry, we find that SWAP provides greater cooling than triangle wave frequency modulation despite the complex polarization environment of a grating MOT. The simulation is confirmed by experimental results, which show a factor of two improvement in transfer efficiency between a dipole-allowed transition grating MOT and an intercombination transition grating MOT.\nThe data show that the intercombination line grating MOT can trap up to three million strontium atoms at an average temperature of 4.9 microkelvin with a lifetime of approximately 0.7 seconds.\n\nInstructions on reproducing the figures in the manuscript are included in 4097_README.txt.", - "distribution": [ - { - "description": "README file for the .zip archive.", - "downloadURL": "https://data.nist.gov/od/ds/mds2-4097/4097_README.txt", - "format": ".txt", - "mediaType": "text/plain", - "title": "README" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4097/figure_generation_data.zip", - "mediaType": "application/zip", - "title": "figure_generation_data" - } - ], - "identifier": "ark:/88434/mds2-4097", - "issued": "2026-05-21", - "keyword": [ - "atomic physics", - "laser cooling", - "quantum physics" - ], - "landingPage": "https://data.nist.gov/od/id/mds2-4097", - "language": [ - "en" - ], - "license": "https://www.nist.gov/open/license", - "modified": "2026-02-09 00:00:00", - "programCode": [ - "006:045" - ], - "publisher": { - "@type": "org:Organization", - "name": "National Institute of Standards and Technology" - }, - "references": [ - "https://doi.org/10.48550/arXiv.2602.06230" - ], - "theme": [ - "Physics:Atomic, molecular, and quantum" - ], - "title": "Data associated with \"Sawtooth wave adiabatic passage in a grating magneto-optical trap\"" - }, - "description": "Numerical values of data points and figure generation scripts for manuscript \"Sawtooth wave adiabatic passage in a grating magneto-optical trap\" submitted for publication and available on ArXiv (2602.06230).\n\nThis data set demonstrates sawtooth wave adiabatic passage (SWAP) in a grating magneto-optical trap (MOT) operating on the intercombination transition of neutral strontium. From numerical simulations of SWAP using our laser beam geometry, we find that SWAP provides greater cooling than triangle wave frequency modulation despite the complex polarization environment of a grating MOT. 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The hybrid chamber consists of an anechoic chamber along with movable metallic spheres that provide discrete reconfigurable multipath components. The chamber is characterized by a synthetic-aperture system providing a reference measurement that captures the non-idealities of the chamber along with the intended spatial multipath, completing characterization of the test environment. A key feature of our approach is the propagation of correlated uncertainties through to the final system response – including uncertainties specific to synthetic apertures such as cable bending due to scanning and inexact positioner locations. The uncertainty analysis provides statistically accurate knowledge of the environment, allowing separation of measurement errors from errors related to the device or system under test. We have also extracted three exemplar channels that capture key features of a work-cell-sized industrial environment from measurements made with the same synthetic aperture.", - "distribution": [ - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4030/Data%2FExemplar_1%2FV_calibrated_data_Scan1A.mat", - "mediaType": "application/x-matlab-data", - "title": "Data/Exemplar_1/V_calibrated_data_Scan1A" - }, - { - "downloadURL": "https://data.nist.gov/od/ds/mds2-4030/Data%2FExemplar_1%2FV_calibrated_data_Scan1B.mat", - "mediaType": "application/x-matlab-data", - "title": "Data/Exempl + "