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At least 73 records · Page 4

Calculation of rf-induced temporal jitter in ultrafast electron diffraction

A significant contribution to the temporal resolution of an ultrafast electron diffraction (UED) instrument is arrival time jitter caused by amplitude and phase variation of radio-frequency (rf) cavities. In this paper, we present a semianalytical approach for calculating rf-induced temporal jitter from klystron and rf cavity parameters. Our approach allows fast estimation of temporal jitter for MeV-UED beamlines and can serve as a virtual timing tool when shot-to-shot measurements of rf amplitude and phase jitters are available. A simulation study for the SLAC MeV-UED instrument is presented, and the temporal resolution of several beamline configurations is compared.

47 OTHER INSTRUMENTATION↗

FPGA-accelerated SpeckleNN with SNL for real-time X-ray single-particle imaging

We present the implementation of a specialized version of our previously published unified embedding model, SpeckleNN, for real-time speckle pattern classification in X-ray Single-Particle Imaging (SPI), using the SLAC Neural Network Library (SNL) on an FPGA platform. This hardware realization transitions SpeckleNN from a prototypic model into a practical edge solution, optimized for running inference near the detector in high-throughput X-ray free-electron laser (XFEL) facilities, such as those found at the Linac Coherent Light Source (LCLS). To address the resource constraints inherent in FPGAs, we developed a more specialized version of SpeckleNN. The original model, which was designed for broader classification across multiple biological samples, comprised ~5.6 million parameters. The new implementation, while reducing the parameter count to 64.6K (a 98.8% reduction), focuses on maintaining the model's essential functionality for real-time operation, achieving an accuracy of 90%. Furthermore, we compressed the latent space from 128 to 50 dimensions. This implementation was demonstrated on the KCU1500 FPGA board, utilizing 71% of available DSPs, 75% of LUTs, and 48% of FFs, with an average power consumption of 9.4W according to the Vivado post-implementation report. The FPGA performed inference on a single image with a latency of 45.015 microseconds at a 200 MHz clock rate. In comparison, running the same inference on an NVIDIA A100 GPU resulted in an average power consumption of ~73W and an image processing latency of around 400 microseconds. Our FPGA-accelerated version of SpeckleNN demonstrated significant improvements, achieving an 8.9 × speedup and a 7.8 × reduction in power consumption compared to the GPU implementation. Key advancements include model specialization and dynamic weight loading through SNL, which eliminates the need for time-consuming FPGA design re-synthesis, allowing fast and continuous deployment of models (re)trained online. These innovations enable real-time adaptive classification and efficient vetoing of speckle patterns, making SpeckleNN more suited for deployment in XFEL facilities. This implementation has the potential to significantly accelerate SPI experiments and enhance adaptability to evolving experimental conditions.

47 OTHER INSTRUMENTATION↗

Deep learning-assisted modeling for χ (2) nonlinear optics

Modeling second-order (χ(2)) nonlinear optical processes remains computationally expensive due to the need to resolve fast field oscillations and simulate wave propagation using methods such as the split-step Fourier method (SSFM). This can become a bottleneck in real-time applications, such as high-repetition-rate laser systems requiring rapid feedback and control. We present a long short-term memory-based surrogate model trained on SSFM simulations generated from a start-to-end model of the photocathode drive laser at SLAC National Accelerator Laboratory’s Linac Coherent Light Source II. The model achieves over 250× speedup while maintaining high fidelity, enabling future real-time optimization and laying the foundation for data-integrated modeling frameworks and digital twins of laser systems.

Accelerator Physics (physics.acc-ph)↗

Correcting for Selection Biases in the Determination of the Hubble Constant from Time-Delay Cosmography

The time delay between multiple images of strongly lensed quasars has been used to infer the Hubble constant. The primary systematic uncertainty for time-delay cosmography is the mass-sheet transform (MST), which preserves the lensing observables while altering the inferred ⁠H 0 . The TDCOSMO collaboration used velocity dispersion measurements of lensed quasars and lensed galaxies to infer that mass sheets are present, which decrease the inferred H 0 by 8 per cent. Here, we test the assumption that the density profiles of galaxy–galaxy and galaxy–quasar lenses are the same. We use a composite star-plus-dark-matter mass profile for the parent deflector population and model the selection function for galaxy–galaxy and galaxy–quasar lenses. We find that a power-law density profile with an MST is a good approximation to a two-component mass profile around the Einstein radius, but we find that galaxy–galaxy lenses have systematically higher mass-sheet components than galaxy–quasar lenses. For individual systems, λ int correlates with the ratio of the half-light radius and Einstein radius of the lens. By propagating these results through the TDCOSMO hierarchical inference code, we find that H 0 is lowered by a further 3 per cent. Using a more recent measurement of velocity dispersions and our fiducial model for selection biases, we infer H 0 = 66 ± 4 (stat) ± 1 (model sys) ± 2 (measurement sys) km s -1 Mpc -1 for the TDCOSMO plus SLACS data set. The first residual systematic error is due to plausible alternative choices in modelling the selection function, and the second is an estimate of the remaining systematic error in the measurement of velocity dispersions for SLACS lenses. Accurate time-delay cosmography requires precise velocity dispersion measurements and accurate calibration of selection biases.

79 ASTRONOMY AND ASTROPHYSICS↗

Quantifying the line-of-sight halo contribution to the dark matter convergence power spectrum from strong gravitational lenses

Galaxy-galaxy strong gravitational lenses have become a popular probe of dark matter (DM) by providing a window into structure formation on the smallest scales. In particular, the convergence power spectrum of subhalos within lensing galaxies has been suggested as a promising observable to study DM. However, the distances involved in strong-lensing systems are vast, and we expect the relevant volume to contain line-of-sight (LOS) halos that are not associated with the main lens. We develop a formalism to calculate the effect of LOS halos as an effective convergence power spectrum. Here, the multilens plane equation couples the angular deflections of consecutive lens planes, but by assuming that the perturbations due to the LOS halos are small, we show that they can be projected onto the main-lens plane as effective subhalos. We test our formalism by simulating lensing systems using the full multiplane lens equation and find excellent agreement. We show how the relative contribution of LOS halos and subhalos depends on the source and lens redshift, as well as the assumed halo and subhalo mass functions. For a fiducial system with fraction of DM halo mass in substructure f sub = 0.4% for subhalo masses [10 5 –10 8 ]M ⊙ , the interloper contribution to the power spectrum is at least several times greater than that of subhalos for source redshifts z s ≳ 0.5. Furthermore, it is likely that for the SLACS and BELLS lenses the interloper contribution dominates: f sub ≳ 2% (4%) is needed for subhalos to dominate in SLACS (BELLS), which is higher than current upper bounds on f sub for our mass range. Since the halo mass function is better understood from first principles, the dominance of interlopers in galaxy-galaxy lenses with high-quality imaging can be seen as a significant advantage when translating this observable into a constraint on DM.

79 ASTRONOMY AND ASTROPHYSICS↗

The ePix10k 2-megapixel hard X-ray detector at LCLS

The ePix10ka2M (ePix10k) is a new large area detector specifically developed for X-ray free-electron laser (XFEL) applications. The hybrid pixel detector was developed at SLAC to provide a hard X-ray area detector with a high dynamic range, running at the 120 Hz repetition rate of the Linac Coherent Light Source (LCLS). The ePix10k consists of 16 modules, each with 352 × 384 pixels of 100 µm × 100 µm distributed on four ASICs, resulting in a 2.16 megapixel detector, with a 16.5 cm × 16.5 cm active area and ∼80% coverage. The high dynamic range is achieved with three distinct gain settings (low, medium, high) as well as two auto-ranging modes (high-to-low and medium-to-low). Here the three fixed gain modes are evaluated. The resulting dynamic range (from single photon counting to 10000 photons pixel −1 pulse −1 at 8 keV) makes it suitable for a large number of different XFEL experiments. The ePix10k replaces the large CSPAD in operation since 2011. The dimensions of the two detectors are similar, making the upgrade from CSPAD to ePix10k straightforward for most setups, with the ePix10k improving on experimental performance. The SLAC-developed ePix cameras all utilize a similar platform, are tailored to target different experimental conditions and are designed to provide an upgrade path for future high-repetition-rate XFELs. Here the first measurements on this new ePix10k detector are presented and the performance under typical XFEL conditions evaluated during an LCLS X-ray diffuse scattering experiment measuring the 9.5 keV X-ray photons scattered from a thin liquid jet.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Total metals & anion concentration data; Slate River floodplain, Crested Butte, CO; May 2020-September 2020

This data package includes processed and undiluted measurements for metal and anion concentrations from pore water (groundwater) samples from the Slate River floodplain of Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? Samples were collected between May and September of 2020. These measurements were all recorded at the Arizona Laboratory for Emerging Contaminants (ALEC) at the University of Arizona located in Tucson, AZ. Groundwater samples were extracted from a network of installed rhizon (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the river floodplain. All water samples were shaded from sun exposure during extraction from the subsurface and preserved at 4C until measured at ALEC.Analysis by ICP-MS:Measurements for total metals were made on the Agilent 7700x ICP-MS (for total metals) – Agilent Technologies, Santa Clara, CA.The analytical QA/QC protocol was adapted from US EPA Method 200.8 for analysis by ICP-MS. Calibration standards were prepared from multi-element stock solution (Sigma-Aldrich Multielement standard solution for ICP, St. Louis, MO) using matrix matched to sample solutions (either 2% HCl or HNO3 from AriStar Plus,grade acids from VWR Scientific). Calibration curves include at least 7 points with correlation coefficients > 0.995. The QC protocol includes a continuing calibration blank (CCB), a continuing calibration verification (CCV) solution and at least one quality control sample (QCS) to be analyzed just after calibration and again after every 12 samples and at the completion of the run. The QCS solutions are from an independent source, such as NIST SRM 1643e - Trace Elements in Water, or QCS solutions from High Purity Standards (Charleston, SC). Acceptable QC responses must be between 90 and 110% of the certified value. An internal standard (Rh) is added via on-line addition into the sample line using a mixing tee.Analysis by Ion Chromatography (Anions):The protocol follows Method 4110 in Standard Methods for Examination of Water and Wastewater.The instrument used is the Thermo Scientific Dionex ICS-6000 using AS+AG22 column set for anion analysis with isocratic method using sodium carbonate eluent. Detection is by chemical suppression of eluent conductivity. Quality control solutions and mixed analyte standards purchased from Inorganic Ventures, Christiansburg, VA.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

Specific conductivity, pH, dissolved oxygen, water temperature, alkalinity and sulfide in-situ data; Slate River floodplain, Crested Butte, CO; May 2020-October 2020

This data package includes a time-series of field measurements from May to October 2020 in groundwater and surface water from the Slate River floodplain in Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data packade includes 6 data files, one for each measured variable: specific conductivity, pH, dissolved oxygen, water temperature, alkalinity and sulfide. All measurements were recorded in the field immediately after water sampling. Groundwater samples were extracted from a network of installed rhizons (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the floodplain. In addition to the data files, there is a terminology file explaining the terms used, a file level metadata file, and a sensor file with metadata about the sensors used.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

Specific conductivity, pH, dissolved oxygen, water temperature and alkalinity in-situ data; Slate River floodplain, Crested Butte, CO; March 2021-October 2021

This data package includes a time-series of field measurements from March to October 2021 in groundwater and surface water from the Slate River floodplain in Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data package includes 5 data files, one for each measured variable: specific conductivity, pH, dissolved oxygen, water temperature and alkalinity. All measurements were recorded in the field immediately after water sampling. Groundwater samples were extracted from a network of installed rhizons (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the floodplain. In addition to the data files, there is a terminology file explaining the terms used, a file level metadata file, and a sensor file with metadata about the sensors used.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

Total metals, sulfur and organic carbon data; Slate River floodplain, Crested Butte, CO; March 2021-October 2021

This data package includes processed and undiluted measurements for metal, sulfur and organic carbon concentrations from pore water (groundwater) samples from the Slate River floodplain of Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? Samples were collected between March and October of 2021. These measurements were all recorded at the Environmental Measurements Facility (EM-1) at Stanford University in Stanford, CA. Groundwater samples were extracted from a network of installed rhizon (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the river floodplain. All water samples were shaded from sun exposure during extraction from the subsurface and preserved at 2C until measured at EM-1.Analysis by ICP-MS:Measurements for total metals were performed on an inductively coupled plasma optical emission spectrometer (ICP-OES; iCAP 6300, Thermo Scientific, Cambridge, U.K.). Calibration standards were prepared from the mulit element stock solution (Sigma-Aldrich Multielement standard for ICP, St. Louis, MO) using matrix matched to sample solutions (2% HNO3). Calibration curves included 5 points with correlation coefficients of >0.99. The QC protocol includes a continuing calibration blank and quality control samples that are analyzed just after calibration and again every 20 samples and at the completion of the run. Acceptable QC responses must be between 90-110% of the certified value. Analysis by Total Organic Carbon:Dissolved organic carbon concentrations were quantified on a total organic carbon (TOC) analyzer (TOC-L, Shimadzu, Kyoto, Japan) running the NPOC method. Standard curves were developed using an Organic Carbon Standard from RICCA Chemical Company (Arlington,TX). A series of 4 to 6 standards were automatically diluted by the instrument in a concentration range that spans that of the samples. A blank sample was run just after the calibration curve and at the end of the run. A QC sample was run every 25 samples. Acceptable QC responses must be between 90-110% of the certified value.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

In-situ electrochemical and water quality data; Slate River and East River floodplains, Crested Butte, CO; May 2022-September 2022

This data package includes a time-series of field measurements from May to September 2022 in groundwater and surface water from the Slate River and East River floodplains in Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data package includes 5 data files, one for each measured variable: specific conductivity, pH, dissolved oxygen, water temperature and alkalinity. All measurements were recorded in the field immediately after water sampling. Groundwater samples were extracted from a network of installed rhizons (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the floodplain. In addition to the data files, there is a terminology file explaining the terms used, a file level metadata file, and a sensor file with metadata about the sensors used.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

Groundwater level elevation and temperature data, Oct 2018-Dec 2021, Slate River Floodplain, Crested Butte, CO

This data package includes a time series of water level and temperature measurements from October 2018 to December 2021 in groundwater and surface water from the Slate River floodplain outside Crested Butte, CO, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The data were recorded by pressure transducers were installed in four types of piezometers: 1) a network of gravel bed ("GB") drive-point piezometers with a 6-inch screen interval installed all at ~330 cm below ground surface. 2) a network of piezometers screened across the water table, used to measure evapotranspiration ("ET") using the White method. Each of these piezometers is screened along almost its entire length.3) a suite nested piezometers used the measure the vertical hydraulic gradient ("VHG") across the fines-cobble interface. Each of these piezometers uses a 6-inch screen length.4) a group of piezometers scattered across the boundaries of the floodplain, used to monitor boundary conditions ("BC") flowing into and out of the floodplain. With the exception of "SR-BD-WT", each of these piezometers is screened along its entire length. Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 11 "*data.csv" files, one for each piezometer type for each calendar year. Because piezometers have been added over time, not every sensor has data dating back to Oct 2018. Each "*data.csv" file has a corresponding "*_InstallationMethods.csv" file that describes the location, elevation, screen depth, sediment type and sensor metadata for each piezometer and pressure transducer.

54 ENVIRONMENTAL SCIENCES↗

Soil water content, matric potential, carbon dioxide and oxygen concentrations, Oct 2018-Dec 2021, Slate River Floodplain, Crested Butte, Colorado

This data package includes a time series of soil sensor data (temperature, water content, bulk electrical conductivity, porewater dissolved oxygen and porewater dissolved carbon dioxide) in a vertical profile from the Slate River floodplain outside Crested Butte, Colorado, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The package includes: (1) soil temperature, volumetric water content and electrical conductivity at 40, 60 and 82.5 cm depth; (2) soil matric potential at 40, 60, 79 and 100 cm depth; (3) soil CO2 concentrations at 40, 60 and 82.5 cm depth; and (4) soil oxygen concentrations at 60, 82.5, 100, 135, 170 and 182 cm depth. Both the carbon dioxide and oxygen sensors are optical sensors that can measure the partial pressure of oxygen in both saturated and unsaturated conditions. Unfortunately, soil CO2 in the profile is unexpectedly high and above the sensor calibration range (0-25,000 ppm). In addition, soil CO2 sensors failed within a year of deployment, so we only report CO2 data from 2019-2020.Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 4 "*data.csv" files, one for each calendar year in the dataset. Each "*data.csv" file has a corresponding "*_InstallationMethods.csv" file that describes the location, sensor model, sensor serial number and other metadata corresponding for each measured parameter. Because sensors have been added over time, not every sensor has data dating back to Oct 2018. Note that there is a data gap over winter 2019-2020 due to a power outage. While this repository currently only contains data through December 2021, the dataset will be updated as additional years are collected and processed.

54 ENVIRONMENTAL SCIENCES↗

Meteorological, reference evapotranspiration and estimated transpiration data, July 2020-Dec 2021, Slate River Floodplain, Crested Butte, Colorado

This data package includes a time series of meteorological data (air temperature, relative humidity, barometric pressure, precipitation, wind speed, soil heat flux, incoming shortwave radiation, incoming longwave radiation, outgoing shortwave radiation and outgoing longwave radiation) from the Slate River floodplain outside Crested Butte, Colorado, a focus field site for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? The package also includes reference evapotranspiration calculated via the Penman-Monteith equation and an estimate of willow (Salix spp.) evapotranspiration using the method of Irmak et al., J. Hydrology, 2013. Due to two malfunctioning sensors (incoming shortwave radiation from Oct 2020-May 2021 and incoming longwave radiation from May 2021-March 2022), observed net radiation and calculated evapotranspiration are only included from July-October 2020. However, users may be able to extend calculated evapotranspiration using estimates of these two parameters from other sources. Both sensors have been replaced and data beyond 2021 be uploaded to this repository when it is available.Within the data package, "FLMD.csv" describes file-level metadata and "dd.csv" defines column headers and universal terms across the dataset. The data package includes 3 "*data.csv" files, two for meteorological data for 2020 and 2021 and one for reference evapotranspiration and transpiration data from 2020 ("SLT_OBJ2_PenmanMonteith_2020_data.csv"). Each "*data.csv" file of meteorological data has a corresponding "*_InstallationMethods.csv" file that describes the location, sensor model, sensor serial number and other metadata corresponding to each measured parameter. We also include a Jupyter notebook ("PenmanMonteithET_Calculations.ipynb") that details the assumptions and equations used to calculate daily and hourly reference evapotranspiration and daily willow transpiration from raw meteorological data.

54 ENVIRONMENTAL SCIENCES↗

Total metals, carbon, nitrogen & anion concentration data; Slate River & East River floodplains, Crested Butte, CO; May 2022-October 2022

This data package includes processed and undiluted measurements for metal, total carbon, total nitrogen, and anion concentrations from pore water (groundwater) and surface water samples from the Slate River and East River floodplains of Crested Butte, CO, focus field sites for the SLAC Floodplain Hydro-Biogeochemistry SFA. The data was generated as part of the work targeting the overarching research question for the SLAC SFA: How do ubiquitous subsurface interfaces mediate molecular-scale biogeochemical processes and groundwater quality in floodplains and watersheds? Samples were collected between May and October of 2022. These measurements were all recorded at the Arizona Laboratory for Emerging Contaminants (ALEC) at the University of Arizona located in Tucson, AZ. Groundwater samples were extracted from a network of installed rhizon (Rhizosphere Research Products, part no. 19.60.21F, 0.6 micrometer mesh size) and piezometer wells within the river floodplain. All water samples were shaded from sun exposure during extraction from the subsurface and preserved at 4C until measured at ALEC.Analysis by ICP-MS (metals):Measurements for total metals were made on the Agilent 7700x ICP-MS (for total metals) – Agilent Technologies, Santa Clara, CA. The analytical QA/QC protocol was adapted from US EPA Method 200.8 for analysis by ICP-MS. Calibration standards were prepared from multi-element stock solutions (SPEX Certiprep, Metuchen, NJ). Calibration curves include at least 7 points with correlation coefficients > 0.995. The QC protocol includes a continuing calibration blank (CCB), a continuing calibration verification (CCV) solution and at least one quality control sample (QCS) to be analyzed just after calibration and again after every 12 samples and at the completion of the run. The QCS solutions are from an independent source, such as NIST SRM 1643e - Trace elements in water, or QCS solutions from High Purity Standards (Charleston, SC). Acceptable QC responses must be between 90 and 110% of the certified value. Lastly, a suitable internal standard (usually Rh, In, Ga or Ge) is added using on-line addition into the sample line and mixing tee.Analysis by Shimadzu TOC-L (TOC/TN):The TOC-L system is a combustion technique where liquid samples are injected and combusted into CO2 for carbon detection by non-dispersive infrared (NDIR) and NO for detection by chemiluminescence. A calibration curve using five standard solutions between 0.1 and 7 ppm for carbon and 0.05 and 3.5 ppm for nitrogen is made for each type of measurement with a linearity >0.99. All samples, standards, and QC’s are prepared in 24mL scintillation vials that have been baked for 4hrs at 475 Cº and made using RO water (18.2mΩ). QC’s include a calibration blank check (CCB), continuing calibration check (CCC), and a certified reference material check (CRM). All QC’s are within ±10% error and are run before and after each batch of samples. Samples are diluted and rerun if any measurement concentrations are above the highest standard.Analysis by Ion Chromatography (Anions):The instrument used is the Thermo Scientific Dionex ICS-6000 using AS+AG22 column set for anion analysis with sodium carbonate eluent. A calibration curve using five standard solutions between 5 and 250 umol/L is made with a linearity >0.99. Standards and QC’s are prepared in 15mL polypropylene conical tubes, pipetted along with the samples into 1.5mL polypropylene vials. Dilutions are made using RO water (18.2mΩ). QC’s include a calibration blank check (CCB), continuing calibration check (CCC), and a certified reference material check (CRM). All QC’s are within ±10% error and are run before and after each batch of samples. Samples are diluted and rerun if any measurement concentrations are above the highest standard.All files are in csv format.

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June to October 2020)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June to October 2020 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 30 cm depth below surface to just above the cobble layer (~190-250 cm depth) at discrete depths every 40 cm for microbial analyses. A total of 35 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2848 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (September 2019)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken September 2019 at one locations (OBJ1) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 50 to 150 cm depth below surface at discrete depths every 20 cm for microbial analyses. A total of 6 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 2562 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗

Metagenome-assembled genomes from Slate River floodplain sediments near Crested Butte, CO, USA (June 2018)

Microorganisms play a key role in cycling nutrients and contaminants in the terrestrial environment depending on their genetic potential. Here, we present metagenome-assembled genomes (MAGs) for the bacterial and archaeal community in floodplain sediment samples taken June 2018 at two locations (OBJ1 and OBJ2) near the confluence of the Oh-Be-Joyful Creek and Slate River. The site is one of the field sites in focus for the SLAC National Accelerator Laboratory Groundwater Quality Science Focus Area (SFA) program. Sediment samples from a deep soil pit were collected from 50 to 150 cm depth below surface at discrete depths every 20 cm for microbial analyses. A total of 12 metagenomes were sequenced through the Joint Genome Institute (JGI) and can be found under Genomes Online Database (GOLD) sequencing project: Gs0142591. Metagenomes were assembled, binned, and refined using metawrap to generate MAGs (>50% complete and < 10% contamination based on checkM scores). This dataset includes a zip file of 1233 MAG fasta files and a csv file with quality, taxonomic classification (Genome Taxonomy Database Release RS220), and metagenome accessions for MAGs. This dataset also includes a file-level metadata (flmd.csv) file that lists each file contained in the dataset with associated metadata and a data dictionary (dd.csv) file that contains column/row headers used throughout the files along with a definition, units, and data type.Part of this work was performed at SLAC Accelerator Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-76SF00515.

54 ENVIRONMENTAL SCIENCES↗