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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Development of in-use engine speed/torque heat maps across multiple heavy-duty commercial vehicle vocations

The U.S. Department of Energy (DOE) established the SuperTruck program with the goal of achieving brake thermal efficiency (BTE) greater than or equal to 55% as demonstrated in an operational heavy-duty (HD) diesel engine at a 65-miles-per-hour (mph) cruise point. Beyond the line-haul application, HD engines operate in a wide range of speed and torque conditions that are unlikely to yield the same efficiency under real-world operation. Thereby, the in-use engine heat maps described in this paper are a valuable tool to illustrate whether the engine-efficiency “sweet spot” matches the most frequent operating conditions. In this study, NREL developed engine heat maps to quantify the important operating points for various vocations using our Fleet DNA database of commercial fleet vehicle operations data. These heat maps clearly show that high-frequency operating points vary significantly according to vehicle vocation, while only a few of them match the sweet spot. Beyond the illustration, engine in-use heat maps can also be leveraged to build up reduced-order engine-efficiency models, needed by many rapid powertrain simulations. As case studies, nine reduced-order models – including line-haul truck, transfer truck, transit bus, transit bus with compressed natural gas (CNG) engine, drayage, refuse pickup, local delivery, utility truck, and school bus with CNG engine – using a trust-region reflective algorithm to fit the on-road data extracted based on the engine in-use heat maps.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

Location Identifiers, Metadata, and Map for Field Measurements at the East-Taylor Watershed Community Observatory, Colorado, USA (Version 3.3)

This dataset contains identifiers, metadata, and a map of the locations where field measurements have been conducted at the East-Taylor Watershed Community Observatory located in the Upper Colorado River Basin, United States. This is version 3.3 of the dataset and replaces the prior version 3.2 (see below for details on changes between the versions). Dataset description: The East River-Taylor Watershed is the primary field site of the Watershed Function Scientific Focus Area (WFSFA) and the Rocky Mountain Biological Laboratory. Researchers from several institutions generate highly diverse hydrological, biogeochemical, climate, vegetation, geological, remote sensing, and model data at the East-Taylor Watershed in collaboration with the WFSFA. Thus, the purpose of this dataset is to maintain an inventory of the field locations and instrumentation to provide information on the field activities in the East-Taylor Watershed and coordinate data collected across different locations, researchers, and institutions. The dataset contains (1) a README file with information on the various files, (2) three csv files describing the metadata collected for each surface point location, plot and region registered with the WFSFA, (3) csv files with metadata and contact information for each surface point location registered with the WFSFA, (4) a csv file with with metadata and contact information for plots, (5) a csv file with metadata for geographic regions and sub-regions within the watershed, (6) a compiled xlsx file with all the data and metadata which can be opened in Microsoft Excel, (7) a kml map of the locations plotted in the watershed which can be opened in Google Earth, (8) a jpg image of the kml map which can be viewed in any photo viewer, and (9) a zipped file with the registration templates used by the SFA team to collect location metadata. The zipped template file contains two csv files with the blank templates (point and plot), two csv files with instructions for filling out the location templates, and one compiled xlsx file with the instructions and blank templates together. Additionally, the templates in the xlsx include drop down validation for any controlled metadata fields. Persistent location identifiers (Location_ID) are determined by the WFSFA data management team and are used to track data and samples across locations. Dataset uses: This location metadata is used to update the Watershed SFA’s publicly accessible Field Information Portal (an interactive field sampling metadata exploration tool; https://wfsfa-data.lbl.gov/watershed/), the kml map file included in this dataset, and other data management tools internal to the Watershed SFA team. Version Information: The latest version of this dataset publication is version 3.3. This version contains 167 new point locations, 1 new plot, and 2 new geographic regions. Overall, there are a total of 1439 point locations, 75 plots, and 54 geographic regions. Additionally, the kml map of locations and image now includes two boundaries (Upper Ohio Creek (UO) and Carbon Creek (CA)) outside of the East River watershed (USGS HUC-10) and accompanying stream network that represents areas of focus. Refer to methods for further details on the version history. This dataset will be updated on a periodic basis with new measurement location information. Researchers interested in having their East-Taylor Watershed measurement locations added to this list should reach out to the WFSFA data management team at wfsfa-data@googlegroups.com. Acknowledgments: Please cite this dataset if using any of the location metadata in other publications or derived products. If using the location metadata for the 2018 NEON hyperspectral campaign, additionally cite Chadwick et al. (2020). doi:10.15485/1618130. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. 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.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2025

Flood Susceptibility Mapping Using Machine Learning and Geospatial-Sentinel-1 SAR Integration for Enhanced Early Warning Systems

This study presents a comprehensive framework for flood susceptibility mapping by integrating geospatial factors with both statistical and machine learning models. Thirteen Flood-related factors, including DEM, slope, TWI, NDVI, etc., are extracted as features of models, and historical flood data derived from Sentinel-1 SAR from 2018 to 2023 are used as the target variables of the models. These datasets are analyzed using a frequency-based statistical model and three machine learning models, including Random Forest, XGBoost, and CNN, to generate flood susceptibility maps. The performance of each model is evaluated through AUC; and SHAP scores are separately generated for Machine learning (ML) models to explain each feature contribution in the ML model. The generated susceptibility maps are validated by high-flood-risk locations monitored by flood sensors, BLE inundation models, and flood-prone areas suggested by the Local Community Task Force. The results indicate that the XGBoost model outperforms all other models, with an AUC of 0.92 and demonstrates the highest alignment with recommended high-flood-risk locations, while the frequency-based statistical model showed the weakest performance with an AUC of 0.65. SHAP value graphs highlight the elevation, slope, and TWI as the most influential features across all models. The susceptibility maps generated by the machine learning model show strong agreement with the BLE map and high-flood-risk areas identified by the local Community Task Force.

Google Engine↗
DOE OSTI2026

Using Visual Systems Mapping to Improve Transparency and Comparability of Life Cycle Assessment Baseline Scenarios

Visual systems mapping is a systems engineering approach used to represent complex processes and interactions. This study evaluates its application for documenting assumptions in life cycle assessment (LCA) baseline scenarios. In LCA, the baseline or reference case represents the business as usual system against which changes in impacts (e.g., emissions) are assessed. These baseline assumptions are particularly influential in biomass LCAs, yet they often vary across studies due to regional context, system boundaries, and simplifying assumptions that are not consistently or transparently documented. As a result, key feedbacks, omitted processes, and boundary choices may remain unclear, limiting comparability across studies and weakening their usefulness for decision-making. This study examines whether visual systems mapping can improve the transparency and comparability of biomass LCA baseline scenarios. A case study of five published biomass-related LCAs were reviewed, and their baseline scenarios were translated into visual system maps to identify included processes, omitted components, and underlying assumptions. The analysis demonstrates that visual systems mapping can make baseline assumptions more explicit, highlight excluded dynamics, and improve documentation of system boundaries. Based on these findings, the study recommends the use of visual systems mapping alongside open data repositories and reproducible workflows to support greater transparency, reproducibility, and comparability in LCAs. These improvements can strengthen the role of LCAs in informing decisions related to sustainable biomass systems.

Davis, Maggie [ORNL] (ORCID:0000000181319328)↗
DOE OSTI2020

The Newman-Penrose map and the classical double copy

Gauge-gravity duality is arguably our best hope for understanding quantum gravity. Considerable progress has been made in relating scattering amplitudes in certain gravity theories to those in gauge theories — a correspondence dubbed the double copy. Recently, double copies have also been realized in a classical setting, as maps between exact solutions of gauge theories and gravity. We present here a novel map between a certain class of real, exact solutions of Einstein’s equations and self-dual solutions of the flat-space vacuum Maxwell equations. This map, which we call the Newman-Penrose map, is well-defined even for non-vacuum, non-stationary spacetimes, providing a systematic framework for exploring gravity solutions in the context of the double copy that have not been previously studied in this setting. To illustrate this, we present here the Newman- Penrose map for the Schwarzschild and Kerr black holes, and Kinnersley’s photon rocket.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Quantitative trait locus mapping combined with variant and transcriptome analyses identifies a cluster of gene candidates underlying the variation in leaf wax between upland and lowland switchgrass ecotypes

Switchgrass (Panicum virgatum L.) is a promising warm-season candidate energy crop. It occurs in two ecotypes, upland and lowland, which vary in a number of phenotypic traits, including leaf glaucousness. To initiate trait mapping, two F 2 mapping populations were developed by crossing two different F 1 sibs derived from a cross between the tetraploid lowland genotype AP13 and the tetraploid upland genotype VS16, and high-density linkage maps were generated. Quantitative trait locus (QTL) analyses of visually scored leaf glaucousness and of hydrophobicity of the abaxial leaf surface measured using a drop shape analyzer identified highly significant colocalizing QTL on chromosome 7K (Chr07K). Using a multipronged approach, we identified a cluster of genes including Pavir.7KG077009, which encodes a Type III polyketide synthase-like protein, and Pavir.7KG013754 and Pavir.7KG030500, two highly similar genes that encode putative acyl-acyl carrier protein (ACP) thioesterases, as strong candidates underlying the QTL. The lack of homoeologs for any of the three genes on Chr07N, the relatively low level of identity with other switchgrass KCS proteins and thioesterases, as well as the organization of the surrounding region suggest that Pavir.7KG077009 and Pavir.7KG013754/Pavir.7KG030500 were duplicated into a fast-evolving chromosome region, which led to their neofunctionalization. Furthermore, sequence analyses showed all three genes to be absent in the two upland compared to the two lowland accessions analyzed. This study provides an example of and practical guide for trait mapping and candidate gene identification in a complex genetic system by combining QTL mapping, transcriptomics and variant analysis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The Interstellar Mapping And Acceleration Probe High Energy (IMAP-Hi) Neutral Atom Imager

The IMAP-Hi Energetic Neutral Atom (ENA) Imager on NASA’s Interstellar Mapping and Acceleration Probe (IMAP) mission (McComas et al. 2018a, 2025) is designed to measure ENAs from the global interaction between the heliosphere and the local interstellar medium (LISM). These ENAs are initially plasma ions of solar wind origin that are neutralized by charge exchange with the cold neutral atoms of LISM that freely flow through the heliosphere-LISM interaction region. IMAP-Hi consists of two identical single-pixel sensors, each covering the ENA spectral range from 0.44 keV to 15.6 keV over nine contiguous energy passbands and having an approximately conical field-of-view (FOV) of 4.1o full width at half maximum (FWHM). The Hi-45 sensor points 45o relative to the spacecraft spin axis from the antisunward direction; each spacecraft spin, it measures ENA intensity over a circular swath with half-cone angle 45o centered on the ecliptic plane. The Hi-90 sensor points 90o relative to the spin axis; each spacecraft spin, it measures ENA intensity over a great circle in the sky, sampling both the north and south ecliptic poles. As the IMAP spin vector is re-pointed daily toward the Sun, the ecliptic longitude of the swaths moves daily by ∼1o such that a full sky map is acquired by Hi-90 every six months and a complete low latitude (−45o to +45o) map is acquired by Hi-45 annually. The IMAP-Hi sensor design has direct heritage from the IBEX-Hi imager on the Interstellar Boundary Explorer (IBEX) mission, with substantial improvements in energy range, energy resolution, angular resolution, signal-to-noise ratio, and, for ecliptic latitudes within ±45o, temporal resolution and exposure time. The global ENA maps acquired by IMAP-Hi partially overlap in energy and viewing with the ENA maps acquired by the IMAP-Lo and IMAP-Ultra ENA imagers, which we combine to answer fundamental questions about the structure and dynamics of the interaction of the heliosphere and the LISM.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Simulating water dynamics related to pedogenesis across space and time: Implications for four-dimensional digital soil mapping

Digital soil mapping (DSM) relies on machine-learning and geostatistics to represent soil property observations across space. DSM techniques are powerful but often empirical, being limited to the quality and density of point samples. Water dynamics are closely related to soil variability, and the physics that govern water movement are well known. Hydrological properties can hence be simulated by physical models through space and time, unveiling key characteristics about soils. We propose the use of hydrologic models to map soils across the surface (2D), depth (1D), and time (1D)–which provides a 4D approach to digital soil mapping (4DSM). The Distributed Hydrology Soil Vegetation Model (DHSVM) was applied to a watershed currently under pasture. Moisture sensors and wells were installed at different depths in the watershed on summit, sideslope and toeslope positions to validate the model. DHSVM simulations of soil moisture distribution and depth to saturation were performed during the hydrological year (October 2008-September 2009). Clusters of similar pixels based on soil moisture values were determined using Dynamic Time Warping (DTW) to align temporal data and K-means. Clustering was performed both seasonally and for the entire year. Temporal patterns simulated by DHSVM matched measurements given by moisture sensors and wells. Seasonal clusters differed from the annual cluster. Distinct clusters were observed for each season and with depth, showing that spatiotemporal soil variability is lost when statically assessing soils. Spatiotemporal clusters corroborated field observations of fragipan occurrence not explicitly spatially mapped by Soil Survey Geographic Database (SSURGO). If a connection can be made between water and soils, static and dynamic soil variability can be predicted using physically based hydrologic models. Hydrologic models can benefit soil mapping by enabling reliable 4D simulation of water dynamics, which are fundamental to soil variability and soil classification and directly relate to biological, physical and chemical soil processes not captured by typical soil sampling protocols.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Dynamics of McMillan mappings I. McMillan multipoles

In this article, we consider two dynamical systems: the McMillan sextupole and octupole integrable mappings, originally proposed by Edwin McMillan. Both represent the simplest symmetric McMillan maps, characterized by a single intrinsic parameter. While these systems find numerous applications across various domains of mathematics and physics, some of their dynamical properties remain unexplored. We aim to bridge this gap by providing a comprehensive description of all stable trajectories, including the parametrization of invariant curves, Poincaré rotation numbers, and canonical action–angle variables. In the second part, we establish connections between these maps and general chaotic maps in standard form. Our investigation reveals that the McMillan sextupole and octupole serve as first-order approximations of the dynamics around the fixed point, akin to the linear map and quadratic invariant (known as the Courant–Snyder invariant in accelerator physics), which represents zeroth-order approximations (referred to as linearization). Furthermore, we propose a novel formalism for nonlinear Twiss parameters, which accounts for the dependence of rotation number on amplitude. This stands in contrast to conventional betatron phase advance used in accelerator physics, which remains independent of amplitude. Notably, in the context of accelerator physics, this new formalism demonstrates its capability in predicting dynamical aperture around low-order resonances for flat beams, a critical aspect in beam injection/extraction scenarios.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Pro‐ L * ‐ A Probabilistic L * Mapping Tool for Ground Observations

Abstract Both ground and space observations are used extensively in the modeling of space weather processes within the Earth’s magnetosphere. In radiation belt physics modeling, one of the key phase‐space coordinates is L *, which indicates the location of the drift paths of energetic electrons. Global magnetic field models allow a subset of locations on the ground (mainly subauroral) to be mapped along field lines to a location in space and transformed into L *, provided that the initial ground location maps to a closed drift path. This allows observations from ground, or low‐altitude space‐based platforms to be mapped into space in order to inform radiation belt modeling. Many data‐based magnetic field models exist; however, these models can significantly disagree on mapped L * values for a single point on the ground, during both quiet times and storms. We present a state of the art probabilistic L * mapping tool, Pro‐ L *, which produces probability distributions for L * corresponding to a given ground location. Pro‐ L * has been calculated for a high resolution magnetic latitude by magnetic local time grid in the Earth’s Northern Hemisphere. We have developed the probabilistic model using 11 years of L * calculations for seven widely used magnetic field models. Usage of the tool is highlighted for both event studies and statistical models, and we demonstrate a number of potential applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Three‐Dimensional Broadband Interferometric Mapping and Polarization (BIMAP‐3D) Observations of Lightning Discharge Processes

Abstract Following on our earlier single‐station, 2‐dimensional (2D) broadband interferometric mapping and polarization (BIMAP) observations of lightning discharges, we recently deployed two BIMAP stations at Los Alamos National Laboratory to map the lightning sources and their polarization in full 3‐dimensional (3D) space (BIMAP‐3D). The two stations are separated by 11.5‐km and each station consists of four antenna sets (instead of three for the original BIMAP) that form a Y ‐shaped array for improved interferometric performance. In this paper, we report the BIMAP‐3D system design, a generalized and analytical 2D interferometry technique for noncoplanar antenna array, a two‐stage 3D mapping technique based on geometric triangulation and baseline‐based differential time of arrival, and a technique to reconstruct the polarization orientation in 3D space by combining the 2D polarization results from the two‐station observations. Along with description of the techniques, we demonstrate and discuss the initial lightning results, including 3D maps for a hybrid intracloud and cloud‐to‐ground flash and for a normal intracloud flash, development of abnormal K‐change leaders, and polarization signatures for a K‐change leader. We find that with the two‐stage 3D mapping techniques, the sources can be located to meters accuracy for a favorable event that occurs between the two stations. We also find the polarization vectors for the example K leader are mostly orthogonal to the leader channel after the full 3D polarization analysis. The main purpose of this paper is to report the BIMAP‐3D techniques and capabilities. Detailed analysis of more specific discharge processes will be reported in later studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Geospatial mapping of distribution grid with machine learning and publicly-accessible multi-modal data

Abstract Detailed and location-aware distribution grid information is a prerequisite for various power system applications such as renewable energy integration, wildfire risk assessment, and infrastructure planning. However, a generalizable and scalable approach to obtain such information is still lacking. In this work, we develop a machine-learning-based framework to map both overhead and underground distribution grids using widely-available multi-modal data including street view images, road networks, and building maps. Benchmarked against the utility-owned distribution grid map in California, our framework achieves > 80% precision and recall on average in the geospatial mapping of grids. The framework developed with the California data can be transferred to Sub-Saharan Africa and maintain the same level of precision without fine-tuning, demonstrating its generalizability. Furthermore, our framework achieves a R 2 of 0.63 in measuring the fraction of underground power lines at the aggregate level for estimating grid exposure to wildfires. We offer the framework as an open tool for mapping and analyzing distribution grids solely based on publicly-accessible data to support the construction and maintenance of reliable and clean energy systems around the world.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Learned magnetic map cues and two mechanisms of magnetoreception in turtles

Growing evidence indicates that migratory animals exploit the magnetic field of the Earth for navigation, both as a compass to determine direction and as a map to determine geographical position. It has long been proposed that, to navigate using a magnetic map, animals must learn the magnetic coordinates of the destination, yet the pivotal hypothesis that animals can learn magnetic signatures of geographical areas has, to our knowledge, yet to be tested. Here, in this work, we report that an iconic navigating species, the loggerhead turtle ( Caretta caretta ), can learn such information. When fed repeatedly in magnetic fields replicating those that exist in particular oceanic locations, juvenile turtles learned to distinguish magnetic fields in which they encountered food from magnetic fields that exist elsewhere, an ability that might underlie foraging site fidelity. Conditioned responses in this new magnetic map assay were unaffected by radiofrequency oscillating magnetic fields, a treatment expected to disrupt radical-pair-based chemical magnetoreception, suggesting that the magnetic map sense of the turtle does not rely on this mechanism. By contrast, orientation behaviour that required use of the magnetic compass was disrupted by radiofrequency oscillating magnetic fields. The findings provide evidence that two different mechanisms of magnetoreception underlie the magnetic map and magnetic compass in sea turtles.

animal behaviour↗
DOE OSTI2024

Cryo2StructData: A Large Labeled Cryo-EM Density Map Dataset for AI-based Modeling of Protein Structures

The advent of single-particle cryo-electron microscopy (cryo-EM) has brought forth a new era of structural biology, enabling the routine determination of large biological molecules and their complexes at atomic resolution. The high-resolution structures of biological macromolecules and their complexes significantly expedite biomedical research and drug discovery. However, automatically and accurately building atomic models from high-resolution cryo-EM density maps is still time-consuming and challenging when template-based models are unavailable. Artificial intelligence (AI) methods such as deep learning trained on limited amount of labeled cryo-EM density maps generate inaccurate atomic models. To address this issue, we created a dataset called Cryo2StructData consisting of 7,600 preprocessed cryo-EM density maps whose voxels are labelled according to their corresponding known atomic structures for training and testing AI methods to build atomic models from cryo-EM density maps. Cryo2StructData is larger than existing, publicly available datasets for training AI methods to build atomic protein structures from cryo-EM density maps. We trained and tested deep learning models on Cryo2StructData to validate its quality showing that it is ready for being used to train and test AI methods for building atomic models.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Sharp, high numerical aperture (NA), nanoimprinted bare pyramid probe for optical mapping

The ability to correlate optical hyperspectral mapping and high resolution topographic imaging is critically important to gain deep insight into the structure–function relationship of nanomaterial systems. Scanning near-field optical microscopy can achieve this goal, but at the cost of significant effort in probe fabrication and experimental expertise. To overcome these two limitations, we have developed a low-cost and high-throughput nanoimprinting technique to integrate a sharp pyramid structure on the end facet of a single-mode fiber that can be scanned with a simple tuning-fork technique. The nanoimprinted pyramid has two main features: (1) a large taper angle (~70°), which determines the far-field confinement at the tip, resulting in a spatial resolution of 275 nm, an effective numerical aperture of 1.06, and (2) a sharp apex with a radius of curvature of ~20 nm, which enables high resolution topographic imaging. Optical performance is demonstrated through evanescent field distribution mapping of a plasmonic nanogroove sample, followed by hyperspectral photoluminescence mapping of nanocrystals using a fiber-in-fiber-out light coupling mode. Through comparative photoluminescence mapping on 2D monolayers, we also show a threefold improvement in spatial resolution over chemically etched fibers. These results show that the bare nanoimprinted near-field probes provide simple access to spectromicroscopy correlated with high resolution topographic mapping and have the potential to advance reproducible fiber-tip-based scanning near-field microscopy.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Hyperspectral radiance mapping and chromatic correction for temperature measurement in laser-heated diamond anvil cells

In laser-heated diamond anvil cell (DAC) experiments, the effective heated region typically decreases in size with increasing pressure, leading to steeper thermal gradients. Under these conditions, chromatic aberration in the optical path from sample to detector can significantly create bias in spectro-radiometric temperature measurement. We present a radiance-mapping approach using a hyperspectral camera that records 25 spectral channels spanning 605–875 nm at each pixel in a single exposure, providing spatially and spectrally resolved radiance in each frame. This enables chromatic effects to be recorded and corrected in data processing. We developed a procedure for hyperspectral mapping, involving per-camera calibration, crosstalk removal, measured spectral throughput functions, and optional sub-pixel co-registration to minimize chromatic distortion. The calibrated radiance maps are then used to derive temperature maps of the laser-heated hotspots. For smaller heating spots, the radiance mapping approach reveals chromatic shifts that conventional spectro-radiometric methods cannot quantify. Ambient-pressure heating experiments confirm accurate temperature retrieval. At high pressure, application of the hyperspectral system to a platinum-heating experiment at 12 GPa demonstrates stable temperature reconstruction under steep thermal gradients. Beyond mitigating chromatic aberrations, the ability to diagnose optical artifacts separately from emissivity variations during controlled test experiments or in situ suggests a path toward more rigorous spectral emissivity analysis and improved modeling of thermal transport in laser-heated DAC experiments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Precise magnetic field mapping of the EMPHATIC Phase 1 magnet with COMSOL

A compact Halbach array magnet is used to measure the momentum of the secondary particles in EMPHATIC(Experiment to Measure the Production ofHadrons At a Test beam InChicagoland). Hall probe data was taken for the central cylindrical bore of the magnet and a field map was constructed. COMSOL Multiphysics® Software is used for modeling the magnet and constructing the corresponding magnetic field map. Here, we present a fitting approach where the hall probe data is used to determine a 1mm-spacing map of the entire volume of the magnet using COMSOL. The new map will allow for linear interpolation within the volume, and expand the map to outside the measurement volume, thus increasing the acceptance and precision of EMPHATIC's tracking system.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

The Atacama Cosmology Telescope: a CMB lensing mass map over 2100 square degrees of sky and its cross-correlation with BOSS-CMASS galaxies

In this work, we construct cosmic microwave background lensing mass maps using data from the 2014 and 2015 seasons of observations with the Atacama Cosmology Telescope (ACT). These maps cover 2100 square degrees of sky and overlap with a wide variety of optical surveys. The maps are signal dominated on large scales and have fidelity such that their correlation with the cosmic infrared background is clearly visible by eye. We also create lensing maps with thermal Sunyaev-Zel’dovich contamination removed using a novel cleaning procedure that only slightly degrades the lensing signal-to-noise ratio. The cross-spectrum between the cleaned lensing map and the BOSS CMASS galaxy sample is detected at 10σ significance, with an amplitude of A = 1.02 ± 0.10 relative to the Planck best-fitting Lambda cold dark matter cosmological model with fiducial linear galaxy bias. Our measurement lays the foundation for lensing cross-correlation science with current ACT data and beyond.

79 ASTRONOMY AND ASTROPHYSICS↗