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At least 361 records · Page 20

KSpaceNavigator (KSN)

Intuitive GUI for manipulating microscope stages, allowing to align crystallographic data with stages, allowing to align crystallographic data with stage coordinates and microscope images. Simulates kinematic diffraction patterns and Kikuchi line patterns. Simulated patterns can be displayed as overlay to actually measured data, allowing manual fingerprinting and angular alignment. Crystallographic data is fed to the program in form of CIF (crystallographic information file) files, which are available from many databases and cover virtually all crystal structure ever reported in any journal. Actual goniometer scales can be linearized by lookup tables, program can be used with any microscope goniometer, double tilt and tilt-rotation type. Software requirements: Win32 platform (XP); Compiler/Version: Borland C++ Builder 5; Type of files: Executable modules; Hardware requirement: PC

Duden, Thomas↗

gp_blendclass_singleband

The code used for the data preprocessing, image simulation, and model training and analysis reported in the paper "Gaussian Process Classification for Galaxy Blend Identification in LSST" (arXiv:2107.09246).

Buchanan, JamesJ.↗

DeepLensSBI: Deep inference of simulated strong lenses in ground-based surveys

This code is used to train and test machine learning models and generate results and plots presented in 2501.08524 [astro-ph.IM]. The code is written in python. The goal of this work is to train ML models trained on simulated images of strong gravitational lenses. The trained model can then quickly infer properties of the lensed objects with uncertainty quantification.

Poh, Jason [Univ. of Chicago, IL (United States)] ↗

DeepBench: A simulation package for physical benchmarking data

We introduce **DeepBench**, a python library that generates simple simulated image data from first principles, such as basic geometric shapes and astronomical objects. These data are highly valuable for developing (calibration, testing, and benchmarking) statistical and machine learning models because they make it possible to connect the final data product to physically interpretable inputs. This software includes tools to curate and store the datasets to maximize reproducibility.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Imaging of Phase Objects using Partially Coherent Illumination

Screening high-power laser optics for light intensifying phase objects that cause laserinduced damage on downstream optics is critical to sustaining laser operation. Identifying such flaws on large-apertures is quite challenging since they are relatively small and invisible to conventional inspection methods. A Linescan Phase Differential Imaging (LPDI) system was developed to rapidly identify these flaws on large-aperture optics within a single full-aperture dark-field image. We describe a two-step production phase object screening process consisting of LPDI mapping and image analysis, followed by high-resolution interferometry and propagation based evaluation of the downstream damage potential of identified flaws. An image simulation code capable of modeling the LPDI partially coherent illumination was used to optimize its phase object sensitivity.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Coupling a Lagrangian–Eulerian Spark-Ignition (LESI) model with LES combustion models for engine simulations

In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO 2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed.

33 ADVANCED PROPULSION SYSTEMS↗

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

The Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will survey the southern sky to create the largest galaxy catalog to date, and its statistical power demands an improved understanding of systematic effects such as source overlaps, also known as blending. In this work we study how blending introduces a bias in the number counts of galaxies (instead of the flux and colors), and how it propagates into galaxy clustering statistics. We use the 300 deg 2 DC2 image simulation and its resulting galaxy catalog (LSST Dark Energy Science Collaboration et al. 2021) to carry out this study. We find that, for a LSST Year 1 (Y1)-like cosmological analyses, the number count bias due to blending leads to small but statistically significant differences in mean redshift measurements when comparing an observed sample to an unblended calibration sample. In the two-point correlation function, blending causes differences greater than 3σ on scales below approximately 10', but large scales are unaffected. We fit Ω m and linear galaxy bias in a Bayesian cosmological analysis and find that the recovered parameters from this limited area sample, with the LSST Y1 scale cuts, are largely unaffected by blending. Our main results hold when considering photometric redshift and a LSST Year 5 (Y5)-like sample.

79 ASTRONOMY AND ASTROPHYSICS↗

The DECADE cosmic shear project I: A new weak lensing shape catalog of 107 million galaxies

We present the Dark Energy Camera All Data Everywhere (DECADE) weak lensing dataset: a catalog of 107 million galaxies observed by the Dark Energy Camera (DECam) in the northern Galactic cap. This catalog was assembled from public DECam data including survey and standard observing programs. These data were consistently processed with the Dark Energy Survey Data Management pipeline as part of the DECADE campaign and serve as the basis of the DECam Local Volume Exploration survey (DELVE) Early Data Release 3 (EDR3). We apply the Metacalibration measurement algorithm to generate and calibrate galaxy shapes. After cuts, the resulting cosmology-ready galaxy shape catalog covers a region of $5,\!412 \,\,{\rm deg}^2$ with an effective number density of $4.59\,\, {\rm arcmin}^{-2}$. The coadd images used to derive this data have a median limiting magnitude of $r = 23.6$, $i = 23.2$, and $z = 22.6$, estimated at ${\rm S/N} = 10$ in a 2 arcsecond aperture. We present a suite of detailed studies to characterize the catalog, measure any residual systematic biases, and verify that the catalog is suitable for cosmology analyses. In parallel, we build an image simulation pipeline to characterize the remaining multiplicative shear bias in this catalog, which we measure to be $m = (-2.454 \pm 0.124) \times10^{-2}$ for the full sample. Despite the significantly inhomogeneous nature of the data set, due to it being an amalgamation of various observing programs, we find the resulting catalog has sufficient quality to yield competitive cosmological constraints.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Galaxies into the Dark Ages

We consider the capabilities of current and future large facilities operating at 2–3 mm wavelength to detect and image the [C ii] 158 μm line from galaxies into the cosmic “dark ages” (z ∼ 10–20). The [C ii] line may prove to be a powerful tool in determining spectroscopic redshifts, and galaxy dynamics, for the first galaxies. We emphasize that the nature, and even existence, of such extreme redshift galaxies, remains at the frontier of open questions in galaxy formation. In 40 hr, the Atacama Large Millimeter Array has the sensitivity to detect the integrated [C ii] line emission from a moderate metallicity, active star-forming galaxy [Z{sub A}=0.2 Z{sub ⊙}; star formation rate (SFR)=5 M{sub ⊙} yr{sup −1}], at z = 10 at a significance of 6σ. The next-generation Very Large Array (ngVLA) will detect the integrated [C ii] line emission from a Milky Way–like SFR galaxy (Z{sub A}=0.2 Z{sub ⊙}, SFR=1 M{sub ⊙} yr{sup −1}), at z = 15 at a significance of 6σ. Imaging simulations show that the ngVLA can determine rotation dynamics for active star-forming galaxies at z∼15, if they exist. Based on our very limited knowledge of the extreme redshift universe, we calculate the count rate in blind, volumetric surveys for [C ii] emission at z∼10–20. The detection rates in blind surveys will be slow (of the order of unity per 40 hr pointing). However, the observations are well suited to commensal searches. We compare [C ii] with the [O iii] 88 μm line, and other ancillary information in high z galaxies that would aid these studies.

79 ASTRONOMY AND ASTROPHYSICS↗

Resolved Dwarf Galaxy Searches within ~5 Mpc with the Vera Rubin Observatory and Subaru Hyper Suprime-Cam*

We present a preview of the faint dwarf galaxy discoveries that will be possible with the Vera C. Rubin Observatory and Subaru Hyper Suprime-Cam in the next decade. In this work, we combine deep ground-based images from the Panoramic Imaging Survey of Centaurus and Sculptor (PISCeS) and extensive image simulations to investigate the recovery of faint, resolved dwarf galaxies in the Local Volume with a matched-filter technique. We adopt three fiducial distances - 1.5, 3.5, 5 Mpc, and quantitatively evaluate the effects on dwarf detection of varied stellar backgrounds, ellipticity, and Milky Way foreground contamination and extinction. We show that our matched-filter method is powerful for identifying both compact and extended systems, and near-future surveys will be able to probe at least ~4.5 mag below the tip of the red giant branch (TRGB) for a distance of up to 1.5 Mpc, and ~2 mag below the TRGB at 5 Mpc. This will push the discovery frontier for resolved dwarf galaxies to fainter magnitudes, lower surface brightnesses, and larger distances. Our simulations show the secure census of dwarf galaxies down to $M_{V}$$\approx$-5, -7, -8, will be soon within reach, out to 1.5 Mpc, 3.5 Mpc, and 5 Mpc, respectively, allowing us to quantify the statistical fluctuations in satellite abundances around hosts, and parse environmental effects as a function of host properties.

79 ASTRONOMY AND ASTROPHYSICS↗

Deep Realistic Extragalactic Model (DREaM) Galaxy Catalogs: Predictions for a Roman Ultra-deep Field

In the next decade, deep galaxy surveys from telescopes such as the James Webb Space Telescope and Roman Space Telescope will provide transformational data sets that will greatly enhance the understanding of galaxy formation during the epoch of reionization (EoR). In this work, we present the Deep Realistic Extragalactic Model (DREaM) for creating synthetic galaxy catalogs. Our model combines dark matter simulations, subhalo abundance matching and empirical models, and includes galaxy positions, morphologies, and spectral energy distributions. The resulting synthetic catalog extends to redshifts z ~ 12, and galaxy masses log 10 (M/M ⊙ ) = 5 covering an area of 1 deg 2 on the sky. We use DREaM to explore the science returns of a 1 deg 2 Roman ultra-deep field (UDF), and to provide a resource for optimizing ultra-deep survey designs. We find that a Roman UDF to ~30 m AB will potentially detect more than 10 6 M UV < -17 galaxies, with more than 10 4 at redshifts z > 7, offering an unparalleled data set for constraining galaxy properties during the EoR. Our synthetic catalogs and simulated images are made publicly available to provide the community with a tool to prepare for upcoming data.

79 ASTRONOMY AND ASTROPHYSICS↗

Systematic Biases in Weak Lensing Cosmology with the Dark Energy Survey

This thesis sets out a practical guide to applying shear measurements as a cosmological tool. We first present one of two science-ready galaxy shape catalogues from Year 1 of the Dark Energy Survey (DES Y1), which covers 1500 square degrees in four bands $griz$, with a median redshift of $0.59$. We describe the shape measurement process implemented by the DES Y1 imshape catalogue, which contains 21.9 million high-quality $r$-band bulge/disc fits. In Chapter 3 a new suite of image simulations, referred to as Hoopoe, are presented. The Hoopoe dataset is tailored to DES Y1 and includes realistic blending, spatial masks and variation in the point spread function. We derive shear corrections, which we show are robust to changes in calibration method, galaxy binning and variance within the simulated dataset. Sources of systematic uncertainty in the simulation-based shear calibration are discussed, leading to a final estimate of the $1\sigma$ uncertainties in the residual multiplica tive bias after calibration of 0.025. Chapter 4 describes an extension of the analysis on the Hoopoe simulations into a detailed investigation of the impact of galaxy neighbours on shape measurement and shear cosmology. Four mechanisms by which neighbours can have a non-negligible influence on shear measurement are identified. These effects, if ignored, would contribute a net multiplicative bias of $m \sim 0.03 - 0.09$ in DES Y1, though the precise impact will depend on both the measurement code and the selection cuts applied. We use the cosmological inference pipeline of DES Y1 to explore the cosmological implications of neighbour bias and show that omitting blending from the calibration simulation for DES Y1 would bias the inferred clustering amplitude $S_8 \equiv \sigma_8 (\omegam /0.3)^{0.5}$ by $1.5 \sigma$ towards low values. Finally, we use the Hoopoe simulations to test the effect of neighbour-induced spatial correlations in the multiplicative bias. We find the cosmo logical impact to be subdominant to statistical error at the! current level of precision. Another major uncertainity in shear cosmology is the accuracy of our ensemble redshift distributions. Chapter 5 presents a numerical investigation into the combined constraining power of cosmic shear, galaxy clustering and their cross-correlation in DES Y1, and the potential for internal calibration of redshift errors. Introducing a moderate uniform bias into the redshift distributions used to model the weak lensing (WL) galaxies is shown to produce a $> 2\sigma$ bias in $S_8$. We demonstrate that this cosmological bias can be eliminated by marginalising over redshift error nuisance parameters. Strikingly, the cosmological constraint of the combined dataset is largely undiminished by the loss of prior information on the WL distributions. We demonstrate that this implicit self-calibration is the result of complementary degeneracy directions in the combined data. In Chapter 6 we present the preliminary results of an investigation into galaxy intrin sic alignments. Using the DES Y1 data, we show a clear dependence in alignment amplitude on galaxy type, in agreement with previous results. We subject these findings to a series of initial robustness tests. We conclude with a short overview of the work presented, and discuss prospects for the future.

79 ASTRONOMY AND ASTROPHYSICS↗

Evaluation of remote sensing in control of pink cotton bollworm

The author has identified the following significant results. This investigation is attempting to evaluate the use of a satellite in monitoring the cotton production regulation program of the State of California as an aid in controlling pink bollworm infestation in the southern deserts of California. Color combined images of ERTS-1 multispectral images simulating color infrared are being used in crop identification. The status of each field is mapped from the imagery and is then compared to ground surveys taken at the time of each ERTS-1 overflight. Correlation has been to date 100%. A computer analysis will be performed to compare field status with the crop calendar in order to identify crops. Correlation is expected to be 80 to 90%. Cotton fields, because of their state regulated season which is exactly coincident with no other crop, are expected to be easily identified.

Lewis, L. N.↗

Evaluation of remote sensing in control of pink bollworm in cotton

The author has identified the following significant results. The main objective is to evaluate the use of a satellite in monitoring the cotton production regulation program of the State of California as an aid in controlling pink bollworm infestation in the southern deserts of California. Color combined images of ERTS-1 multispectral images simulating color infrared are being used for crop identification. The status of each field (i.e., crop, bare, harvested, wet, plowed) is mapped from the imagery and is then compared to ground survey information taken at the time of ERTS-1 overflights. A computer analysis has been performed to compare field and satellite data to a crop calendar. Correlation to data has been 97% for field condition. Actual crop identification varies; cotton identification is only 63% due to lack of full season coverage.

Lewis, L. N.↗

Evaluation of remote sensing in control of pink bollworm in cotton

The author has identified the following significant results. This investigation is to evaluate the use of a satellite in monitoring the cotton production regulation program of the State of California as an aid in controlling pink bollworm infestation in the southern deserts of California. Color combined images of ERTS-1 multispectral images simulating color infrared are being used for crop identification. The status of each field (crop, bare, harvested, wet, plowed) is mapped from the imagery and is then compared to ground survey information taken at the time of ERTS-1 overflights. A computer analysis has been performed to compare field and satellite data to a crop calendar. Correlation to date has been 97% for field condition. Actual crop identification varies; cotton identification is only 63% due to lack of full season coverage.

Lewis, L. N.↗

Incidence angle considerations for spacecraft imaging radar

The value of radar imagery for most geologic applications is greatest when obtained with relatively large incidence angles. It is infeasible to attain these large angles from spacecraft altitudes. A study is being conducted to assess the usefulness of imagery collected at smaller angles. Radar image simulation is employed to create imagery for platform scenarios at numerous angles of incidence for specific geologic features. Preliminary analyses and results are provided.

Kaupp, V. H.↗

Optimization of radar imaging system parameters for geological analysis

The use of radar image simulation to model terrain variation and determine optimum sensor parameters for geological analysis is described. Optimum incidence angle is determined by the simulation, which evaluates separately the discrimination of surface features possible due to terrain geometry and that due to terrain scattering. Depending on the relative relief, slope, and scattering cross section, optimum incidence angle may vary from 20 to 80 degrees. Large incident angle imagery (more than 60 deg) is best for the widest range of geological applications, but in many cases these large angles cannot be achieved by satellite systems. Low relief regions require low incidence angles (less than 30 deg), so a satellite system serving a broad range of applications should have at least two selectable angles of incidence.

Waite, W. P.↗

Accomplishments of the NASA Johnson Space Center portion of the soil moisture project in fiscal year 1981

The NASA/JSC ground scatterometer system was used in a row structure and row direction effects experiment to understand these effects on radar remote sensing of soil moisture. Also, a modification of the scatterometer system was begun and is continuing, to allow cross-polarization experiments to be conducted in fiscal years 1982 and 1983. Preprocessing of the 1978 agricultural soil moisture experiment (ASME) data was completed. Preparations for analysis of the ASME data is fiscal year 1982 were completed. A radar image simulation procedure developed by the University of Kansas is being improved. Profile soil moisture model outputs were compared quantitatively for the same soil and climate conditions. A new model was developed and tested to predict the soil moisture characteristic (water tension versus volumetric soil moisture content) from particle-size distribution and bulk density data. Relationships between surface-zone soil moisture, surface flux, and subsurface moisture conditions are being studied as well as the ways in which measured soil moisture (as obtained from remote sensing) can be used for agricultural applications.

Paris, J. F.↗