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At least 307 records · Page 17

Accurate estimation of angular power spectra for maps with correlated masks

A common procedure when analyzing maps of the cosmic microwave background (CMB) or other cosmological signals is the need to remove ("mask") regions of the maps that are heavily contaminated, e.g., by non-cosmological foreground emission. After applying such a mask, one must account for its effect when inferring statistical properties of interest, such as the angular power spectrum of the field in the original map. A widely used approach to correct for such mask-induced effects was presented by Hivon et al. (2002), now widely known as the "MASTER" formalism. However, it is often the case that the map and mask are correlated in some way, such as point source masks used in CMB analyses, which have nonzero correlation with CMB secondary anisotropy fields and other mm-wave sky signals. In such situations, the MASTER approach gives biased results, as it assumes that the unmasked map and mask have zero correlation. While such effects have been discussed before with regard to specific physical models, here we derive a completely general formalism for any case where the map and mask are correlated. We show that our result ("reMASTERed") reconstructs ensemble-averaged angular power spectra to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. An important consequence of our result is that for maps with correlated masks, it is no longer possible to invert a simple equation to obtain the true power spectrum from the observed (masked) power spectrum. Instead, our result necessitates the use of forward modeling from theory space into the observable domain of the masked power spectrum. We publicly release our software implementation of these results.

79 ASTRONOMY AND ASTROPHYSICS↗

Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM)

The common vulnerabilities and exposures (CVE) database was created with a mission to ``identify, define, and catalog publicly disclosed cybersecurity vulnerabilities''. This rich body of information can be used to enable rapid and efficient response to secure and defend cyber operations and protect critical cyber infrastructure. The main goal of this paper is to develop a visual analytics tool to enable deep analysis of CVEs using unsupervised clustering techniques. We enhance our analysis by first mapping CVEs to hierarchical-classes in Common Weakness Enumeration (CWE) using information in the National Vulnerability Database (NVD). Both the mapping and the numerical representation of CVEs are enabled by V2W-BERT, which uses natural language processing of the extensive information in NVD to generate a large tabular database of 137,226 CVE entries from 1999 to 2020, where each CVE is represented by a vector of 768 numerical features. The vectorized data is processed by Self-Organizing Maps (SOM), which is an unsupervised machine learning technique for dimensionality reduction, visual representation and clustering. Using a Torus map of 6417 units, we achieve ~10-fold data compression of ~140k CVEs using SOM. The trained map is further clustered using standard K-means clustering into 138 clusters of CVEs. We conducted a brief investigation of the rich mapping of CVEs to best-matching-units to K-means clusters, as well as CVEs to CWEs. For example, this novel mapping provided insight into the role of CWE-59 and CWE-264 in several CVEs that is otherwise hard to explore in the original data. We conclude that our this novel approach will not only enable deep analysis of the complex relationships between CVEs and CWEs, but also a mechanism to quickly respond to and design mitigation actions for rapidly evolving vulnerabilities that have not been mapped to existing CWEs.

Panchal, Khyati↗

A Flexible Field Mapping System for Accelerator Magnets

Magnetic field mapping is a fundamental magnetic measurement method that typically uses Hall and NMR sensors. In magnet measurement facilities, such systems are likely used in various configurations suitable for a specific task at hand. To address this diversity, the authors developed a flexible field mapping system capable of being configured and tailored to each particular measurement case. Further, the system needs to address the variability introduced by differences in sensors and their readout systems, probe positioning systems, power supply systems, and required mapping geometry (mapping space and grid, measurement steps and sequences). Although the discussed field mapping systems range from a self-propelled multi-sensor mapper of a large detector magnet to a single 3D Hall sensor system to scan a small permanent magnet, they were all built with the same core mapping system. The variability present in field mapping systems, the measurement system architecture addressing this variability, as well as examples of several field mapping systems built in this architecture are presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

MCTP system model based on linear programming optimization of apertures obtained from sequencing patient image data maps

Purpose: The authors present a hybrid direct multileaf collimator (MLC) aperture optimization model exclusively based on sequencing of patient imaging data to be implemented on a Monte Carlo treatment planning system (MC-TPS) to allow the explicit radiation transport simulation of advanced radiotherapy treatments with optimal results in efficient times for clinical practice. Methods: The planning system (called CARMEN) is a full MC-TPS, controlled through aMATLAB interface, which is based on the sequencing of a novel map, called “biophysical” map, which is generated from enhanced image data of patients to achieve a set of segments actually deliverable. In order to reduce the required computation time, the conventional fluence map has been replaced by the biophysical map which is sequenced to provide direct apertures that will later be weighted by means of an optimization algorithm based on linear programming. A ray-casting algorithm throughout the patient CT assembles information about the found structures, the mass thickness crossed, as well as PET values. Data are recorded to generate a biophysical map for each gantry angle. These maps are the input files for a home-made sequencer developed to take into account the interactions of photons and electrons with the MLC. For each linac (Axesse of Elekta and Primus of Siemens) and energy beam studied (6, 9, 12, 15 MeV and 6 MV), phase space files were simulated with the EGSnrc/BEAMnrc code. The dose calculation in patient was carried out with the BEAMDOSE code. This code is a modified version of EGSnrc/DOSXYZnrc able to calculate the beamlet dose in order to combine them with different weights during the optimization process. Results: Three complex radiotherapy treatments were selected to check the reliability of CARMEN in situations where the MC calculation can offer an added value: A head-and-neck case (Case I) with three targets delineated on PET/CT images and a demanding dose-escalation; a partial breast irradiation case (Case II) solved with photon and electron modulated beams (IMRT + MERT); and a prostatic bed case (Case III) with a pronounced concave-shaped PTV by using volumetric modulated arc therapy. In the three cases, the required target prescription doses and constraints on organs at risk were fulfilled in a short enough time to allow routine clinical implementation. The quality assurance protocol followed to check CARMEN system showed a high agreement with the experimental measurements. Conclusions: A Monte Carlo treatment planning model exclusively based on maps performed from patient imaging data has been presented. The sequencing of these maps allows obtaining deliverable apertures which are weighted for modulation under a linear programming formulation. The model is able to solve complex radiotherapy treatments with high accuracy in an efficient computation time.

60 APPLIED LIFE SCIENCES↗

Improving Hydrologic Modeling Using Cloud-Free MODIS Flood Maps

Flood mapping from satellites provides large-scale observations of flood events, but cloud obstruction in satellite optical sensors limits its practical usability. In this study, we implemented the Variational Interpolation (VI) algorithm to remove clouds from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) Snow-Covered Area (SCA) products. The VI algorithm estimated states of cloud-hindered pixels by constructing three-dimensional space–time surfaces based on assumptions of snow persistence. The resulting cloud-free flood maps, while maintaining the temporal resolution of the original MODIS product, showed an improvement of nearly 70% in average probability of detection (POD) (from 0.29 to 0.49) when validated with flood maps derived from Landsat-8 imagery. The second part of this study utilized the cloud-free flood maps for calibration of a hydrologic model to improve simulation of flood inundation maps. The results demonstrated the utility of the cloud-free maps, as simulated inundation maps had average POD, false alarm ratio (FAR), and Hanssen–Kuipers (HK) skill score of 0.87, 0.49, and 0.84, respectively, compared to POD, FAR, and HK of 0.70, 0.61, and 0.67 when original maps were used for calibration.

54 ENVIRONMENTAL SCIENCES↗

rmap: An R package to plot and compare tabular data on customizable maps across scenarios and time

`rmap` is an R package that allows users to easily plot tabular data (CSV or R data frames) on maps without any Geographic Information Systems (GIS) knowledge. Maps produced by `rmap` are `ggplot` objects and thus capitalize on the flexibility and advancements of the `ggplot2` package and all elements of each map are thus fully customizable. Additionally `rmap` automatically detects and produces comparison maps if the data has multiple scenarios or time periods as well as animations for time series data. Advanced users can load their own shapefiles if desired. `rmap` comes with a range of pre-built color palettes but users can also provide any `R` color palette or create their own as needed. Four different legend types are available to highlight different kinds of data distributions. The input spatial data can be both gridded or polygon data. `rmap` is desgined in particular for comparing spatial data across scenarios and time periods and comes preloaded with standard country, state, and basin maps as well as custom maps compatible with the Global Change Analysis Model (GCAM) spatial boundaries. `rmap` has a growing number of users and its products have been used in multiple multisector dynamics publications as well as a required dependency in other R packages such as `rfasst` and `metis`. `rmap's` automatic processing of tabular data using pre-built map selection, difference map calculations, faceting, and animations offers unique functionality which makes it a powerful and yet simple tool for users looking to explore multi-sector, multi-scenario data across space and time.

58 GEOSCIENCES↗

Rainwater Harvesting Potential Maps

Alternative waters are sustainable sources of water, not supplied from fresh surface water or groundwater, that offset the demand for freshwater. Alternative water can serve as a vital water supply to federal agencies in support of water resilience by providing diverse water sources. One type of alternative water, rainwater harvesting, involves capturing, diverting, and storing rainwater from rooftops for later use. Uses for rainwater include landscape irrigation, ornamental pond and fountain filling, cooling tower make-up, and toilet and urinal flushing. The Federal Energy Management Program has developed a series of alternative water source maps. The first map, developed in 2015 and updated in 2019, is a state-level rainwater harvesting regulations map that visually represents the rainwater harvesting policies across the country and provides general information on state programs, if applicable. This map allows the user to quickly discern where rainwater harvesting is supported and regulated by the state. As a complement to this first map, Pacific Northwest National Laboratory (PNNL) created two additional rainwater harvesting maps to help federal agencies strategically identify locations in the U.S. that are conducive to rainwater harvesting projects. The first map shows the relative potential for capturing rainwater for any use. The second map specifically identifies areas in the U.S. that have potential for supplying rainwater for irrigation.

54 ENVIRONMENTAL SCIENCES↗

A Flexible Field Mapping System for Accelerator Magnets

Magnetic field mapping is a fundamental magnetic measurement method that typically uses Hall and NMR sensors. In magnet measurement facilities, such systems are likely used in various configurations suitable for a specific task at hand. To address this diversity, the authors developed a flexible field mapping system capable of being configured and tailored to each particular measurement case. The system needs to address the variability introduced by differences in sensors and their readout systems, probe positioning systems, power supply systems and in required mapping geometry (mapping space and grid, measurement steps and sequences). Although the discussed field mapping systems range from a self-propelled, multi-sensor mapper of a large detector magnet to a single 3D Hall sensor system to scan a small permanent magnet, they were all built with the same core mapping system. The variability present in field mapping systems and the measurement system architecture addressing this variability, as well as examples of several field mapping systems built in this architecture are presented.

43 PARTICLE ACCELERATORS↗

Stellar reddening map from DESI imaging and spectroscopy

We present new Galactic reddening maps of the high Galactic latitude sky using DESI imaging and spectroscopy. We directly measure the reddening of 2.6 million stars by comparing the observed stellar colors in $g-r$ and $r-z$ from DESI imaging with the synthetic colors derived from DESI spectra from the first two years of the survey. The reddening in the two colors is on average consistent with the Fitzpatrick (1999) extinction curve with $R_\mathrm{V}=3.1$ . We find that our reddening maps differ significantly from the commonly used Schlegel et al. (1998) (SFD) reddening map (by up to 80 mmag in $E(B-V)$ ), and we attribute most of this difference to systematic errors in the SFD map. To validate the reddening map, we select a galaxy sample with extinction correction based on our reddening map, and this yields significantly better uniformity than the SFD extinction correction. Finally, we discuss the potential systematic errors in the DESI reddening measurements, including the photometric calibration errors that are the limiting factor on our accuracy. The $E(g-r)$ and $E(r-z)$ maps presented in this work, and for convenience their corresponding $E(B-V)$ maps with SFD calibration, are publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

High-Density Single Nucleotide Polymorphism Linkage Maps of Lowland Switchgrass using Genotyping-by-Sequencing

Switchgrass (Panicum virgatum L.) is a warm-season perennial grass with promising potential as a bioenergy crop in the United States. However, the lack of genomic resources has slowed the development of plant lines with optimal characteristics for sustainable feedstock production. We generated high-density single nucleotide polymorphism (SNP) linkage maps using a reduced-representation sequencing approach by genotyping 231 F 1 progeny of a cross between two parents of lowland ecotype from the cultivars Kanlow and Alamo. Over 350 million reads were generated and aligned, which enabled identification and ordering of 4611 high-quality SNPs. The total lengths of the resulting framework maps were 1770 cM for the Kanlow parent and 2059 cM for the Alamo parent. These maps show collinearity with maps generated with polymerase chain reaction (PCR)-based simple-sequence repeat (SSR) markers, and new SNP markers were identified in previously unpopulated regions of the genome. Transmission segregation distortion affected all linkage groups (LGs) to differing degrees, and ordering of distorted markers highlighted several regions of unequal inheritance. Framework maps were adversely affected by the addition of distorted markers with varying severity, but distorted maps were of higher marker density and provided additional information for analysis. Alignment of these linkage maps with a draft version of the switchgrass genome assembly demonstrated high levels of collinearity and provides greater confidence in the validity of both resources. This methodology has proven to be a rapid and cost-effective way to generate high-quality linkage maps of an outcrossing species.

59 BASIC BIOLOGICAL SCIENCES↗

MAPS OF EVOLVING CLOUD STRUCTURES IN LUHMAN 16AB FROM HST TIME-RESOLVED SPECTROSCOPY

WISE J104915.57-531906.1 is the nearest brown dwarf binary to our solar system, consisting of two brown dwarfs in the L / T transition: Luhman 16A and B. In this paper, we present the first map of Luhman 16A, and maps of Luhman 16B for two epochs. Our maps were created by applying Aeolus , a Markov-Chain Monte Carlo code that maps the top-of-the-atmosphere (TOA) structure of brown dwarf and other ultracool atmospheres, to light curves of Luhman 16A and B using the Hubble Space Telescope ’s G141 and G102 grisms. Aeolus retrieved three or four spots in the TOA of Luhman 16A and B, with a surface coverage of 19%–32% (depending on an assumed rotational period of 5 hr or 8 hr) or 21%–38.5% (depending on the observational epoch), respectively. The brightness temperature of the spots of the best-fit models was ∼200 K hotter than the background TOA. We compared our Luhman 16B map with the only previously published map. Interestingly, our map contained a large TOA spot that was cooler (Δ T ∼ 51 K) than the background, which lay at low latitudes, in agreement with the previous Luhman 16B map. Finally, we report the detection of a feature reappearing in Luhman 16B light curves that are separated by tens of hundreds of rotations from each other. We speculate that this feature is related to TOA structures of Luhman 16B.

79 ASTRONOMY AND ASTROPHYSICS↗

QSL Squasher: A Fast Quasi-separatrix Layer Map Calculator

Quasi-Separatrix Layers (QSLs) are a useful proxy for the locations where current sheets can develop in the solar corona, and give valuable information about the connectivity in complicated magnetic field configurations. However, calculating QSL maps, even for two-dimensional slices through three-dimensional models of coronal magnetic fields, is a non-trivial task, as it usually involves tracing out millions of magnetic field lines with immense precision. Thus, extending QSL calculations to three dimensions has rarely been done until now. In order to address this challenge, we present QSL Squasher—a public, open-source code, which is optimized for calculating QSL maps in both two and three dimensions on graphics processing units. The code achieves large processing speeds for three reasons, each of which results in an order-of-magnitude speed-up. (1) The code is parallelized using OpenCL. (2) The precision requirements for the QSL calculation are drastically reduced by using perturbation theory. (3) A new boundary detection criterion between quasi-connectivity domains is used, which quickly identifies possible QSL locations that need to be finely sampled by the code. That boundary detection criterion relies on finding the locations of abrupt field-line length changes, which we do by introducing a new Field-line Length Edge (FLEDGE) map. We find FLEDGE maps useful on their own as a quick-and-dirty substitute for QSL maps. QSL Squasher allows construction of high-resolution 3D FLEDGE maps in a matter of minutes, which is two orders of magnitude faster than calculating the corresponding 3D QSL maps. We include a sample of calculations done using QSL Squasher to demonstrate its capabilities as a QSL calculator, as well as to compare QSL and FLEDGE maps.

79 ASTRONOMY AND ASTROPHYSICS↗

Improved Diffuse Foreground Subtraction with the ILC Method: CMB Map and Angular Power Spectrum Using Planck and WMAP Observations

We report an improved technique for diffuse foreground minimization from Cosmic Microwave Background (CMB) maps using a new multiphase iterative harmonic space internal-linear-combination (HILC) approach. Our method nullifies a foreground leakage that was present in the old and usual iterative HILC method. In phase 1 of the multiphase technique, we obtain an initial cleaned map using the single iteration HILC approach over the desired portion of the sky. In phase 2, we obtain a final CMB map using the iterative HILC approach; however, now, to nullify the leakage, during each iteration, some of the regions of the sky that are not being cleaned in the current iteration are replaced by the corresponding cleaned portions of the phase 1 map. We bring all input frequency maps to a common and maximum possible beam and pixel resolution at the beginning of the analysis, which significantly reduces data redundancy, memory usage, and computational cost, and avoids, during the HILC weight calculation, the deconvolution of partial sky harmonic coefficients by the azimuthally symmetric beam and pixel window functions, which in a strict mathematical sense, are not well defined. Using WMAP 9 year and Planck 2015 frequency maps, we obtain foreground-cleaned CMB maps and a CMB angular power spectrum for the multipole range 2⩽ℓ⩽2500. Our power spectrum matches the published Planck results with some differences at different multipole ranges. We validate our method by performing Monte Carlo simulations. Finally, we show that the weights for HILC foreground minimization have the intrinsic characteristic that they also tend to produce a statistically isotropic CMB map.

79 ASTRONOMY AND ASTROPHYSICS↗

A 2500 deg 2 CMB Lensing Map from Combined South Pole Telescope and Planck Data

We present a cosmic microwave background (CMB) lensing map produced from a linear combination of South Pole Telescope (SPT) and \emph{Planck} temperature data. The 150 GHz temperature data from the $2500\ {\rm deg}^{2}$ SPT-SZ survey is combined with the \emph{Planck} 143 GHz data in harmonic space, to obtain a temperature map that has a broader $\ell$ coverage and less noise than either individual map. Using a quadratic estimator technique on this combined temperature map, we produce a map of the gravitational lensing potential projected along the line of sight. We measure the auto-spectrum of the lensing potential $C_{L}^{\phi\phi}$, and compare it to the theoretical prediction for a $\Lambda$CDM cosmology consistent with the \emph{Planck} 2015 data set, finding a best-fit amplitude of $0.95_{-0.06}^{+0.06}({\rm Stat.})\! _{-0.01}^{+0.01}({\rm Sys.})$. The null hypothesis of no lensing is rejected at a significance of $24\,\sigma$. One important use of such a lensing potential map is in cross-correlations with other dark matter tracers. We demonstrate this cross-correlation in practice by calculating the cross-spectrum, $C_{L}^{\phi G}$, between the SPT+\emph{Planck} lensing map and Wide-field Infrared Survey Explorer (\emph{WISE}) galaxies. We fit $C_{L}^{\phi G}$ to a power law of the form $p_{L}=a(L/L_{0})^{-b}$ with $a=2.15 \times 10^{-8}$, $b=1.35$, $L_{0}=490$, and find $\eta^{\phi G}=0.94^{+0.04}_{-0.04}$, which is marginally lower, but in good agreement with $\eta^{\phi G}=1.00^{+0.02}_{-0.01}$, the best-fit amplitude for the cross-correlation of \emph{Planck}-2015 CMB lensing and \emph{WISE} galaxies over $\sim67\%$ of the sky. The lensing potential map presented here will be used for cross-correlation studies with the Dark Energy Survey (DES), whose footprint nearly completely covers the SPT $2500\ {\rm deg}^2$ field.

79 ASTRONOMY AND ASTROPHYSICS↗

Identification, definition and mapping of terrestrial ecosystems in interior Alaska

The author has identified the following significant results. The vegetation map in preparation at the time of the last report was refined and labeled. This map is presented as an indication of the spatial and classificatory detail possible from interpretations of enlarged ERTS-1 color photographs. Using this map, areas covered by the several vegetation types characterized by white spruce were determined by planimetry. A 1:63,360 scale land use map of the Juneau area was drawn. This map incorporates the land use classification system now under development by the U.S. Geological Survey. The ERTS-1 images used in making the Juneau map were used to determine changes in surface area of the terminal zones of advancing and receding glaciers, the Taku, Norris, and Mendenhall. A new 1:63,360 scale land use map of the Bonanza Creek Experimental Forest and vicinity was drawn. Several excellent new sciences of test areas were received from NASA in color-infrared transparency format. These are being used for making photographic prints for analysis and mapping according to procedures outlined in this report.

Anderson, J. H.↗

Proposal for a study of computer mapping of terrain using multispectral data from ERTS-A for the Yellowstone National Park test site

The author has identified the following significant results. A terrain map of Yellowstone National Park showed plant community types and other classes of ground cover in what is basically a wild land. The map comprised 12 classes, six of which were mapped with accuracies of 70 to 95%. The remaining six classes had spectral reflectances that overlapped appreciably, and hence, those were mapped less accurately. Techniques were devised for quantitatively comparing the recognition map of the park with control data acquired from ground inspection and from analysis of sidelooking radar images, a thermal IR mosaic, and IR aerial photos of several scales. Quantitative analyses were made in ten 40 sq km test areas. Comparison mechanics were performed by computer with the final results displayed on line printer output. Forested areas were mapped by computer using ERTS data for less than 1/4 the cost of the conventional forest mapping technique for topographic base maps.

Smedes, H. W.↗

Impact of cell size on inventory and mapping errors in a cellular geographic information system

The author has identified the following significant results. The effect of grid position was found insignificant for maps but highly significant for isolated mapping units. A modelable relationship between mapping error and cell size was observed for the map segment analyzed. Map data structure was also analyzed with an interboundary distance distribution approach. Map data structure and the impact of cell size on that structure were observed. The existence of a model allowing prediction of mapping error based on map structure was hypothesized and two generations of models were tested under simplifying assumptions.

Wehde, M. E.↗

Mapping of wildlife habitat in Farmington Bay, Utah

Mapping was accomplished through the interpretation of high-altitude color infrared photography. The feasibility of utilizing LANDSAT digital data to augment the analysis was explored; complex patterns of wildlife habitat and confusion of spectral classes resulted in the decision to make limited use of LANDSAT data in the analysis. The final product is a map which delineates wildlife habitat at a scale of 1:24,000. The map is registered to and printed on a screened U.S.G.S. quadrangle base map. Screened delineations of shoreline contours, mapped from a previous study, are also shown on the map. Intensive field checking of the map was accomplished for the Farmington Bay Waterfowl Management Area in August 1981; other areas on the map received only spot field checking.

Jaynes, R. A.↗