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DOE OSTI2022

The Dark Energy Survey supernova program: cosmological biases from supernova photometric classification

ABSTRACT Cosmological analyses of samples of photometrically identified type Ia supernovae (SNe Ia) depend on understanding the effects of ‘contamination’ from core-collapse and peculiar SN Ia events. We employ a rigorous analysis using the photometric classifier SuperNNova on state-of-the-art simulations of SN samples to determine cosmological biases due to such ‘non-Ia’ contamination in the Dark Energy Survey (DES) 5-yr SN sample. Depending on the non-Ia SN models used in the SuperNNova training and testing samples, contamination ranges from 0.8 to 3.5 per cent, with a classification efficiency of 97.7–99.5 per cent. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension BBC (‘BEAMS with Bias Correction’), we produce a redshift-binned Hubble diagram marginalized over contamination and corrected for selection effects, and use it to constrain the dark energy equation-of-state, w. Assuming a flat universe with Gaussian ΩM prior of 0.311 ± 0.010, we show that biases on w are <0.008 when using SuperNNova, with systematic uncertainties associated with contamination around 10 per cent of the statistical uncertainty on w for the DES-SN sample. An alternative approach of discarding contaminants using outlier rejection techniques (e.g. Chauvenet’s criterion) in place of SuperNNova leads to biases on w that are larger but still modest (0.015–0.03). Finally, we measure biases due to contamination on w0 and wa (assuming a flat universe), and find these to be <0.009 in w0 and <0.108 in wa, 5 to 10 times smaller than the statistical uncertainties for the DES-SN sample.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

The Role of Data Filtering in Open Source Software Ranking and Selection

Faced with more than 100M open source projects, a more manageable small subset is needed for most empirical investigations. More than half of the research papers in leading venues investigated filtering projects by some measure of popularity with explicit or implicit arguments that unpopular projects are not of interest, may not even represent "real" software projects, or that less popular projects are not worthy of study. However, such filtering may have enormous effects on the results of the studies if and precisely because the sought-out response or prediction is in any way related to the filtering criteria.This paper exemplifies the impact of this common practice on research outcomes, specifically how filtering of software projects on GitHub based on inherent characteristics affects the assessment of their popularity. Using a dataset of over 100,000 repositories, we used multiple regression to model the number of stars -a commonly used proxy for popularity- based on factors such as the number of commits, the duration of the project, the number of authors and the number of core developers. Our control model included the entire dataset, while a second filtered model considered only projects with ten or more authors. The results indicated that while certain characteristics of the repository consistently predict popularity, the filtering process significantly alters the relationships between these characteristics and the response. We found that the number of commits exhibited a positive correlation with popularity in the control sample but showed a negative correlation in the filtered sample. These findings highlight the potential biases introduced by data filtering and emphasize the need for careful sample selection in empirical research of mining software repositories. We recommend that empirical work should either analyze complete datasets such as World of Code, or employ stratified random sampling from a complete dataset to ensure that filtering is not biasing the results.

Malviya Thakur, Addi↗

DOE OSTI2020

First Cosmology Results using Supernovae Ia from the Dark Energy Survey: Survey Overview, Performance, and Supernova Spectroscopy

We present details on the observing strategy, data-processing techniques, and spectroscopic targeting algorithms for the first three years of operation for the Dark Energy Survey Supernova Program (DES-SN). This five-year program using the Dark Energy Camera mounted on the 4 m Blanco telescope in Chile was designed to discover and follow supernovae (SNe) Ia over a wide redshift range (0.05 < z < 1.2) to measure the equation-of-state parameter of dark energy. We describe the SN program in full: strategy, observations, data reduction, spectroscopic follow-up observations, and classification. From three seasons of data, we have discovered 12,015 likely SNe, 308 of which have been spectroscopically confirmed, including 251 SNe Ia over a redshift range of 0.017 < z < 0.85. We determine the effective spectroscopic selection function for our sample and use it to investigate the redshift-dependent bias on the distance moduli of SNe Ia we have classified. The data presented here are used for the first cosmology analysis by DES-SN (“DES-SN3YR”), the results of which are given in Dark Energy Survey Collaboration et al. The 489 spectra that are used to define the DES-SN3YR sample are publicly available at https://des.ncsa.illinois.edu/releases/sn.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Dark Energy Survey year 6 results: Magnification modeling and its impact on galaxy clustering and galaxy-galaxy lensing cosmology

Gravitational lensing magnification alters the observed spatial distribution of galaxies and must be accounted for to prevent biases in cosmological probes of the large-scale structure. We investigate its effects on the Dark Energy Survey Year 6 galaxy clustering and galaxy-galaxy lensing analyses using the fiducial lens (position tracer) sample M ag L im++. Magnification bias is parameterized by a coefficient that describes the response of the number of selected objects per unlensed area element to a change in the lensing convergence. We quantify this coefficient using the BALROG synthetic source injection catalog to account for the complexity of the selection function, and compare these results with simplified estimates. The resulting values of the magnification coefficients for each redshift bin are [3.16 ± 0.08, 2.76 ± 0.21, 4.09 ± 0.15, 4.42 ± 0.16, 4.90 ± 0.29, 4.83 ± 0.25]. Relative to Year 3, this analysis provides more precise and accurate magnification bias estimates through a larger BALROG area and reweighting to better match the data properties. Here, the cosmological results are robust when tested against various magnification parameter prior choices and also when adding cross-clustering between lens redshift bins. Neglecting magnification, however, introduces significant systematic shifts: relative to the fiducial analysis with Gaussian priors centered on the BALROG -derived estimates, we observe shifts of 1.37σ in S 8 and -0.84σ in Ω m (with cosmic shear included: -0.61σ in S 8 and -0.71σ in Ω m ), in agreement with findings from simulated data, demonstrating that magnification must be modeled to avoid biases. Freeing the magnification bias in lens bin 2 leads to unphysical negative values, further justifying its exclusion from the fiducial Year 6 analysis.

Cosmological parameters↗

NASA NTRS2001

Atmospheric Multiple Scattering Effects on GLAS Altimetry: Analysis of Expected Errors in Antarctic Altitude Measurements - Part 2

The altimetry bias in GLAS (Geoscience Laser Altimeter System) or other laser altimeters resulting from atmospheric multiple scattering is studied in relationship to current knowledge of cloud properties over the Antarctic Plateau. Estimates of seasonal and interannual changes in the bias are presented. Results show the bias in altitude from multiple scattering in clouds would be a significant error source without correction. The selective use of low optical depth clouds or cloudfree observations, as well as improved analysis of the return pulse such as by the Gaussian method used here, are necessary to minimize the surface altitude errors. The magnitude of the bias is affected by variations in cloud height, cloud effective particle size and optical depth. Interannual variations in these properties as well as in cloud cover fraction could lead to significant year-to-year variations in the altitude bias. Although cloud-free observations reduce biases in surface elevation measurements from space, over Antarctica these may often include near-surface blowing snow, also a source of scattering-induced delay. With careful selection and analysis of data, laser altimetry specifications can be met.

Mahesh, Ashwin↗

DOE OSTI2025

Reducing model error using optimized galaxy selection: weak lensing cluster mass estimation

Galaxy clusters are one of the most powerful probes to study extensions of General Relativity and the Standard Cosmological Model. Upcoming surveys like the Vera Rubin Observatory’s Legacy Survey of Space and Time are expected to revolutionise the field, by enabling the analysis of cluster samples of unprecedented size and quality. To reach this era of high-precision cluster cosmology, the mitigation of sources of systematic error is crucial. A particularly important challenge is bias in cluster mass measurements induced by the mismodelling of photometric redshift estimates of source galaxies. This work proposes a method to optimise the source sample selection in cluster weak lensing analyses drawn from wide-field survey lensing catalogs to reduce the bias on reconstructed cluster masses. We use a combinatorial optimisation scheme and methods from variational inference to select galaxies in latent space to produce a probabilistic galaxy source sample catalog for highly accurate cluster mass estimation. We show that our method reduces the critical surface mass density Σ crit relative modelling bias on the 60-70% level, while maintaining up to 90% of galaxies. We highlight that our methodology has applications beyond cluster mass estimation as an approach to jointly combine galaxy selection and model inference under sources of systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Unlocking the Dynamics of Ion Migration and Voltage Bias Stress Effects through Crystallite Engineering in Metal Halide Perovskites

Understanding the interplay between crystal engineering and the coupled electronic-ionic charge transport properties of metal halide perovskites remains a critical issue in the field. In this work, we developed an experimental approach to tune the crystallite orientation of methylammonium lead iodide (CH 3 NH 3 PbI 3 ) while maintaining their overall crystal structure. This approach allows us to selectively manipulate crystallite orientations to control out-ofplane ion migration and mitigate voltage bias stress effects in CH 3 NH 3 PbI 3 thin films. By employing advanced diffraction and spectroscopic techniques, we achieved a comprehensive characterization of the anisotropic crystallite properties in CH 3 NH 3 PbI 3 thin films with distinct preferred orientations. Our findings reveal that specific crystallite orientations, particularly those that limit halide ion migration pathways along the (200) crystallographic plane, significantly suppress out-of-plane ion migration. This suppression reduces hysteresis and alleviates voltage bias stress effects in CH 3 NH 3 PbI 3 solar cells, ultimately enhancing device stability and performance. These insights not only deepen our understanding of the relationship between crystallite orientation and device functionality but also highlight a promising strategy for regulating ion migration in MHP-based devices. This approach holds significant potential for advancing the stability and efficiency of perovskite solar cells and extending its applicability to other optoelectronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

A new method to construct a horizontal resolution-dependent wind speed adjustment factor for tropical cyclones in global climate model simulations

A new method to construct a horizontal resolution-dependent wind speed adjustment factor for evaluating tropical cyclones (TCs) in global climate models (GCMs) is presented here. In contrast to the previous studies that used idealized axisymmetric wind fields, this study analyzes 48 hours of 10-second surface wind fields from 1-km TC simulations. The adjustment factor is derived from filtering the simulated TC wind fields onto various horizontal grid spacings typical of those used in GCMs. The new adjustment factor leads to TCs with greater intensity than the existing adjustment factors for horizontal grid spacings smaller than 30 km. This difference is attributed to more realistic wind fields in the TC simulations that contain highly asymmetric, localized patches of higher wind speeds instead of axisymmetric wind fields. Applying the new adjustment factor to select GCM simulations suggests the common interpretation of low-intensity bias in GCM-simulated TCs might be slightly exaggerated.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

The LSST DESC data challenge 1: generation and analysis of synthetic images for next-generation surveys

Data Challenge 1 (DC1) is the first synthetic data set produced by the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC). DC1 is designed to develop and validate data reduction and analysis and to study the impact of systematic effects that will affect the LSST data set. DC1 is comprised of r -band observations of 40 deg 2 to 10 yr LSST depth. In this paper, we present each stage of the simulation and analysis process: (a) generation, by synthesizing sources from cosmological N -body simulations in individual sensor-visit images with different observing conditions; (b) reduction using a development version of the LSST Science Pipelines; and (c) matching to the input cosmological catalogue for validation and testing. We verify that testable LSST requirements pass within the fidelity of DC1. We establish a selection procedure that produces a sufficiently clean extragalactic sample for clustering analyses and we discuss residual sample contamination, including contributions from inefficiency in star–galaxy separation and imperfect deblending. We compute the galaxy power spectrum on the simulated field and conclude that: (i) survey properties have an impact of 50 per cent of the statistical uncertainty for the scales and models used in DC1; (ii) a selection to eliminate artefacts in the catalogues is necessary to avoid biases in the measured clustering; and (iii) the presence of bright objects has a significant impact (2σ–6σ) in the estimated power spectra at small scales (ℓ > 1200), highlighting the impact of blending in studies at small angular scales in LSST.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1984

A comparison of Landsat point and rectangular field training sets for land-use classification

Rectangular training fields of homogeneous spectroreflectance are commonly used in supervised pattern recognition efforts. Trial image classification with manually selected training sets gives irregular and misleading results due to statistical bias. A self-verifying, grid-sampled training point approach is proposed as a more statistically valid feature extraction technique. A systematic pixel sampling network of every ninth row and ninth column efficiently replaced the full image scene with smaller statistical vectors which preserved the necessary characteristics for classification. The composite second- and third-order average classification accuracy of 50.1 percent for 331,776 pixels in the full image substantially agreed with the 51 percent value predicted by the grid-sampled, 4,100-point training set.

Tom, C. H.↗

NASA NTRS1994

Surface Brightness Profiles and Energetics of Intracluster Gas in Cool Galaxy Clusters and ROSAT Observations of Bright, Early-Type Galaxies

Preliminary results on the elliptical galaxy NGC 1407 were published in the proceedings of the first ROSAT symposium. NGC 1407 is embedded in diffuse X-ray-emitting gas which is extensive enough that it is likely to be related to the surrounding group of galaxies, rather than just NGC 1407. Spectral data for NGC 1407 (AO2) and IC 1459 (AO3) are also included in a complete sample of elliptical galaxies I compiled in collaboration with David Davis. This allowed us to construct the first complete X-ray sample of optically-selected elliptical galaxies. The complete sample allows us to apply Malmquist bias corrections to the observed correlation between X-ray and optical luminosities. I continue to work on the implications of this first complete X-ray sample of elliptical galaxies. Paul Eskridge Dave Davis and I also analyzed three long ROSAT PSPC observations of the small (but not dwarf) elliptical galaxy M32. We found the X-ray spectra and variability to be consistent with either a Low Mass X-Ray Binary (LMXRB) or a putative 'micro"-AGN.

White, Raymond E., III↗

NASA NTRS2013

Assessing the Impact of Pre-gpm Microwave Precipitation Observations in the Goddard WRF Ensemble Data Assimilation System

The forthcoming Global Precipitation Measurement (GPM) Mission will provide next generation precipitation observations from a constellation of satellites. Since precipitation by nature has large variability and low predictability at cloud-resolving scales, the impact of precipitation data on the skills of mesoscale numerical weather prediction (NWP) is largely affected by the characterization of background and observation errors and the representation of nonlinear cloud/precipitation physics in an NWP data assimilation system. We present a data impact study on the assimilation of precipitation-affected microwave (MW) radiances from a pre-GPM satellite constellation using the Goddard WRF Ensemble Data Assimilation System (Goddard WRF-EDAS). A series of assimilation experiments are carried out in a Weather Research Forecast (WRF) model domain of 9 km resolution in western Europe. Sensitivities to observation error specifications, background error covariance estimated from ensemble forecasts with different ensemble sizes, and MW channel selections are examined through single-observation assimilation experiments. An empirical bias correction for precipitation-affected MW radiances is developed based on the statistics of radiance innovations in rainy areas. The data impact is assessed by full data assimilation cycling experiments for a storm event that occurred in France in September 2010. Results show that the assimilation of MW precipitation observations from a satellite constellation mimicking GPM has a positive impact on the accumulated rain forecasts verified with surface radar rain estimates. The case-study on a convective storm also reveals that the accuracy of ensemble-based background error covariance is limited by sampling errors and model errors such as precipitation displacement and unresolved convective scale instability.

microwave observations↗

NASA NTRS2019

A Double Bootstrap Approach to Superposed Epoch Analysis to Evaluate Response Uncertainty

The association between climate variability and episodic events, such as the antecedent moisture conditions prior to wildfire or the cooling following volcanic eruptions, is commonly assessed using Superposed Epoch Analysis (SEA). In SEA the epochal response is typically calculated as the average climate conditions prior to and following all event years or their deviation from climatology. However, the magnitude and significance of the inferred climate association may be sensitive to the selection or omission of individual key years, potentially resulting in a biased assessment of the relationship between these events and climate. Here we describe and test a modified double-bootstrap SEA that generates multiple unique draws of the key years and evaluates the sign, magnitude, and significance of event-climate relationships within a probabilistic framework. This multiple resampling helps quantify multiple uncertainties inherent in conventional applications of SEA within dendrochronology and paleoclimatology. We demonstrate our modified SEA by evaluating the volcanic cooling signal in a Northern Hemisphere tree-ring temperature reconstruction and the link between drought and wildfire events in the western United States. Finally, we make our Matlab and R code available to be adapted for future SEA applications.

Dendroclimatology↗

NASA NTRS1980

Intra-ocular pressure normalization technique and equipment

A method and apparatus for safely reducing abnormally high intraocular pressure in an eye during a predetermined time interval is presented. This allows maintenance of normal intraocular pressure during glaucoma surgery. According to the invention, a pressure regulator of the spring biased diaphragm type is provided with additional bias by a column of liquid. The height of the column of liquid is selected such that the pressure at a hypodermic needle connected to the output of the pressure regulator is equal to the measured pressure of the eye. The hypodermic needle can then be safely inserted into the anterior chamber of the eye. Liquid is then bled out of the column to reduce the bias on the diaphragm of the pressure regulator and, consequently, the output pressure of the regulator. This lowering pressure of the regulator also occurs in the eye by means of a small second bleed path provided between the pressure regulator and the hypodermic needle. Alternately, a second hypodermic needle may be inserted into the eye to provide a controlled leak off path for excessive pressure and clouded fluid from the anterior chamber.

Mcgannon, W. J.↗

NASA NTRS1983

Some dynamical design considerations for momentum biased spacecraft

This paper discusses some of the dynamical aspects that affect the attitude behavior of a spacecraft placed in a near earth polar orbit. The parameters such as atmospheric density variation, super-rotation of upper atmosphere, pitch equilibrium angle, and trim boom length selection to reduce pitch axis drift are considered. These parameters are studied with reference to two momentum biased satellities (Magsat and Dynamics Explorer-2) and the analyses are correlated with observed flight data. It is found that the design model of certain parameters has to be improved by including other phenomena so that flight data and the analytical model predictions have good correlations. The effects of mass imbalance on the orbital and nutational modes of the spacecraft attitude are discussed.

Sellappan, R. G.↗

DOE OSTI2022

Light sources with bias tunable spectrum based on van der Waals interface transistors

Light-emitting electronic devices are ubiquitous in key areas of current technology, such as data communications, solid-state lighting, displays, and optical interconnects. Controlling the spectrum of the emitted light electrically, by simply acting on the device bias conditions, is an important goal with potential technological repercussions. However, identifying a material platform enabling broad electrical tuning of the spectrum of electroluminescent devices remains challenging. Here, we propose light-emitting field-effect transistors based on van der Waals interfaces of atomically thin semiconductors as a promising class of devices to achieve this goal. We demonstrate that large spectral changes in room-temperature electroluminescence can be controlled both at the device assembly stage –by suitably selecting the material forming the interfaces– and on-chip, by changing the bias to modify the device operation point. Even though the precise relation between device bias and kinetics of the radiative transitions remains to be understood, our experiments show that the physical mechanism responsible for light emission is robust, making these devices compatible with simple large areas device production methods.

36 MATERIALS SCIENCE↗

NASA NTRS2002

SHEEP: The Search for the High Energy Extragalactic Population

We present the SHEEP survey for serendipitously-detected hard X-ray sources in ASCA GIS images. In a survey area of approx. 40 sq deg, 69 sources were detected in the 5-10 keV band to a limiting flux of approx. 10(exp -13) erg/sq cm/s. The number counts agree with those obtained by the similar BeppoSAX HELLAS survey, and both are in close agreement with ASCA and BeppoSAX 2-10 keV surveys. Spectral analysis of the SHEEP sample reveals that the 2-10 and 5-10 keV surveys do not sample the same populations, however, as we find considerably harder spectra, with an average Gamma approx. 1.0 assuming no absorption. The implication is that the agreement in the number counts is coincidental, with the 5-10 keV surveys gaining approximately as many hard sources as they lose soft ones, when compared to the 2-10 keV surveys. This is hard to reconcile with standard AGN "population synthesis" models for the X-ray background, which posit the existence of a large population of absorbed sources. We find no evidence of the population hardening at faint fluxes, with the exception that the few very brightest objects are anomalously soft. 53 of the SHEEP sources have been covered by ROSAT in the pointed phase. Of these 32 were detected. An additional 3 were detected in the RASS. As expected the sources detected with ROSAT are systematically softer than those detected with ASCA alone, and of the sample as a whole. Although they represent a biased subsample, the ROSAT positions allow relatively secure catalog identifications to be made. We find associations with a wide variety of AGN and a few clusters and groups. At least two X-ray sources identified with high-z QSOs present very hard X-ray spectra indicative of absorption, despite the presence of broad optical lines. A possible explanation for this is that we are seeing relatively dust-free "warm absorbers" in high luminosity/redshift objects. Our analysis defines a new, hard X-ray selected sample of objects - mostly active galactic nuclei - which is less prone to bias due to obscuration than previous optical or soft X-ray samples. They are therefore more representative of the population of AGN in the universe in general, and the SHEEP survey should produce bright examples of the sources that make up the hard X-ray background, the majority of which has recently been resolved by Chandra. This should help elucidate the nature of the new populations.

Nandra, K.↗

DOE OSTI2020

Operando Microscopy Characterization of Perovskite Solar Cells

In this work, we developed operando Kelvin probe force microscopy (KPFM) to study the electrostatic potential distribution across perovskite cells under light and forward bias to gain a deeper understanding of device operation physics. As a case study, we selected perovskite cells with a SnO 2 -based electron-selective layer (ESL), which showed great potential for fabricating high-efficiency, hysteresis-free devices due to the deeper conduction band and higher electron mobility of SnO 2 . The as-made device showed a main junction at the perovskite/spiro interface. After light soaking and applying forward bias, the junction quality improved, possibly explained by filling trap states at the interfaces and by the perovskite absorber perhaps having a self-poling effect; the main junction is observed at the ESL/perovskite interface. The results are consistent with current-voltage measurements, device performance improves mainly with fill factor enhancement. The operando KPFM results should more closely reflect the real case during current density-voltage measurements or solar cell operation. The operando KPFM technique that we have developed can be a powerful tool to provide a deeper understanding of the device operation mechanism and to further optimize the device.

14 SOLAR ENERGY↗