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At least 181 records · Page 10

Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog

Abstract We describe an updated calibration and diagnostic framework, Balrog , used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) data set. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant “source” galaxies and magnification biases of nearer “lens” galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ∼1–8 mmag, but for a small subset of objects, we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Performance of an asymmetric short annular diffuser with a nondiverging inner wall using suction

The performance of a short highly asymmetric annular diffuser equipped with wall bleed (suction) capability was evaluated at nominal inlet Mach numbers of 0.188, 0.264, and 0.324 with the inlet pressure and temperature at near ambient values. The diffuser had an area ratio of 2.75 and a length- to inlet-height ratio of 1.6. Results show that the radial profiles of diffuser exit velocity could be controlled from a severely hub peaked to a slightly tip biased form by selective use of bleed. At the same time, other performance parameters were also improved. These results indicate the possible application of the diffuser bleed technique to control flow profiles to gas turbine combustors.

Juhasz, A.↗

Calibration validation for the GEOS-3 altimeter

The absolute bias calibration for the GEOS-3 intensive mode altimeter was measured using two satellite passes whose groundtracks were within 1 km of the Bermuda laser station. The Bermuda laser tracked on the two passes, and was supported by two other NASA lasers on one pass and by the NASA Spacecraft Tracking and Data Network on the other pass. For each pass, the altimeter data around Bermuda was smoothed and extrapolated to the point closest to overhead at the laser site. After correcting for tide heights and sea state effects, the two passes give calibration biases which are in agreement to within 26 cm and have a weighted mean of -5.69 + or - 0.16m for correcting altimeter measurements to the center-of-mass of the spacecraft (i.e., including the antenna tracking point correction). It was found impossible to reconcile the two calibration passes, as well as a set of altimeter crossovers in the middle of the GEOS-3 calibration area, without allowing for a data time tag error. On the bias of a selected set of four crossovers, and an assessment of probable sources of timing error, it was concluded that one interpulse period (10.24 msec) should be added to the data time tags.

Martin, C. F.↗

Bias correction factors for near-Earth asteroids

Knowledge of the population size and physical characteristics (albedo, size, and rotation rate) of near-Earth asteroids (NEA's) is biased by observational selection effects which are functions of the population's intrinsic properties and the size of the telescope, detector sensitivity, and search strategy used. The NEA population is modeled in terms of orbital and physical elements: a, e, i, omega, Omega, M, albedo, and diameter, and an asteroid search program is simulated using actual telescope pointings of right ascension, declination, date, and time. The position of each object in the model population is calculated at the date and time of each telescope pointing. The program tests to see if that object is within the field of view (FOV = 8.75 degrees) of the telescope and above the limiting magnitude (V = +1.65) of the film. The effect of the starting population on the outcome of the simulation's discoveries is compared to the actual discoveries in order to define a most probable starting population.

Benedix, Gretchen K.↗

No Galaxy Left Behind: Measuring the Transfer Function of the Dark Energy Survey with Balrog

In this dissertation, we describe a calibration and diagnostic framework called Balrog which was used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) dataset. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with traditional generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant "source" galaxies and magnification biases of nearer "lens" galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the fiducial Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ~1-8 millimagnitudes, but for a small subset of objects we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. Finally, we discuss approaches to extend the current methodology to capture more aspects of the transfer function for future analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

Observations of compact sources in galaxy clusters using MUSTANG2

Compact sources can cause scatter in the scaling relationships between the amplitude of the thermal Sunyaev–Zel’dovich Effect (tSZE) in galaxy clusters and cluster mass. Estimates of the importance of this scatter vary – largely due to limited data on sources in clusters at the frequencies at which tSZE cluster surveys operate. In this paper, we present 90 GHz compact source measurements from a sample of 30 clusters observed using the MUSTANG2 instrument on the Green Bank Telescope. We present simulations of how a source’s flux density, spectral index, and angular separation from the cluster’s centre affect the measured tSZE in clusters detected by the Atacama Cosmology Telescope (ACT). By comparing the MUSTANG2 measurements with these simulations we calibrate an empirical relationship between 1.4 GHz flux densities from radio surveys and source contamination in ACT tSZE measurements. We find 3 per cent of the ACT clusters have more than a 20 per cent decrease in Compton-y but another 3 per cent have a 10 per cent increase in the Compton-y due to the matched filters used to find clusters. As sources affect the measured tSZE signal and hence the likelihood that a cluster will be detected, testing the level of source contamination in the tSZE signal using a tSZE-selected catalogue is inherently biased. We confirm this by comparing the ACT tSZE catalogue with optically and X-ray-selected cluster catalogues. Furthermore, there is a strong case for a large, high-resolution survey of clusters to better characterize their source population.

79 ASTRONOMY AND ASTROPHYSICS↗

Redshift-dependent RSD bias from intrinsic alignment with DESI Year 1 spectra

ABSTRACT We estimate the redshift-dependent, anisotropic clustering signal in the Dark Energy Spectroscopic Instrument (DESI) Year 1 Survey created by tidal alignments of Luminous Red Galaxies (LRGs) and a selection-induced galaxy orientation bias. To this end, we measured the correlation between LRG shapes and the tidal field with DESI’s Year 1 redshifts, as traced by LRGs and Emission-Line Galaxies. We also estimate the galaxy orientation bias of LRGs caused by DESI’s aperture-based selection, and find it to increase by a factor of seven between redshifts 0.4−1.1 due to redder, fainter galaxies falling closer to DESI’s imaging selection cuts. These effects combine to dampen measurements of the quadrupole of the correlation function (ξ2) caused by structure growth on scales of 10–80 h−1 Mpc by about 0.15 per cent for low redshifts (0.4 < z < 0.6) and 0.8 per cent for high (0.8 < z < 1.1), a significant fraction of DESI’s error budget. We provide estimates of the ξ2 signal created by intrinsic alignments that can be used to correct this effect, which is necessary to meet DESI’s forecasted precision on measuring the growth rate of structure. While imaging quality varies across DESI’s footprint, we find no significant difference in this effect between imaging regions in the Legacy Imaging Survey.

79 ASTRONOMY AND ASTROPHYSICS↗

Widespread misregulation of inter-species hybrid transcriptomes due to sex-specific and sex-chromosome regulatory evolution

When gene regulatory networks diverge between species, their dysfunctional expression in inter-species hybrid individuals can create genetic incompatibilities that generate the developmental defects responsible for intrinsic post-zygotic reproductive isolation. Both cis- and trans-acting regulatory divergence can be hastened by directional selection through adaptation, sexual selection, and inter-sexual conflict, in addition to cryptic evolution under stabilizing selection. Dysfunctional sex-biased gene expression, in particular, may provide an important source of sexually-dimorphic genetic incompatibilities. Here, we characterize and compare male and female/hermaphrodite transcriptome profiles for sibling nematode species Caenorhabditis briggsae and C. nigoni, along with allele-specific expression in their F 1 hybrids, to deconvolve features of expression divergence and regulatory dysfunction. Despite evidence of widespread stabilizing selection on gene expression, misexpression of sex-biased genes pervades F 1 hybrids of both sexes. This finding implicates greater fragility of male genetic networks to produce dysfunctional organismal phenotypes. Spermatogenesis genes are especially prone to high divergence in both expression and coding sequences, consistent with a “faster male” model for Haldane’s rule and elevated sterility of hybrid males. Moreover, underdominant expression pervades male-biased genes compared to female-biased and sex-neutral genes and an excess of cis-trans compensatory regulatory divergence for X-linked genes underscores a “large-X effect” for hybrid male expression dysfunction. Extensive regulatory divergence in sex determination pathway genes likely contributes to demasculinization of XX hybrids. The evolution of genetic incompatibilities due to regulatory versus coding sequence divergence, however, are expected to arise in an uncorrelated fashion. This study identifies important differences between the sexes in how regulatory networks diverge to contribute to sex-biases in how genetic incompatibilities manifest during the speciation process.

59 BASIC BIOLOGICAL SCIENCES↗

Bias structure to efficiently package a magnetic bubble domain device

A single, compact bias structure to efficiently package a plurality of magnetic bubble domain device chips having different bias requirements. The vertical magnetic field distribution within the bias structure air gap is selectively controlled by a magnetically soft field adjusting assembly suitably attached within the bias structure. The size and configuration of the field adjusting assembly tailors local field variations within the air gap to correspond with the bias requirements of the bubble domain chips disposed therein.

Chen, Thomas T.↗

Detect and correct bias in multi-site neuroimaging datasets

The desire to train complex machine learning algorithms and to increase the statistical power in association studies drives neuroimaging research to use ever-larger datasets. The most obvious way to increase sample size is by pooling scans from independent studies. However, simple pooling is often ill-advised as selection, measurement, and confounding biases may creep in and yield spurious correlations. In this work, we combine 35,320 magnetic resonance images of the brain from 17 studies to examine bias in neuroimaging. In the first experiment, Name That Dataset, we provide empirical evidence for the presence of bias by showing that scans can be correctly assigned to their respective dataset with 71.5% accuracy. Given such evidence, we take a closer look at confounding bias, which is often viewed as the main shortcoming in observational studies. In practice, we neither know all potential confounders nor do we have data on them. Hence, we model confounders as unknown, latent variables. Kolmogorov complexity is then used to decide whether the confounded or the causal model provides the simplest factorization of the graphical model. Finally, we present methods for dataset harmonization and study their ability to remove bias in imaging features. In particular, we propose an extension of the recently introduced ComBat algorithm to control for global variation across image features, inspired by adjusting for unknown population stratification in genetics. Overall, our results demonstrate that harmonization can reduce dataset-specific information in image features. Further, confounding bias can be reduced and even turned into a causal relationship. However, harmonization also requires caution as it can easily remove relevant subject-specific information. Code is available at https://github.com/ai-med/Dataset-Bias.

42 ENGINEERING↗

Fracture trace expression and analysis in radar imagery of rain forest terrain (Peru)

Mapping of minor lineaments from radar imagery of the rain forest in southeast Peru is biased due to the selective suppression of some topography which results from the observation geometry of the imaging radar system and the varied perception of lineaments on the imagery by different interpreters. Team analysis of the imagery compensates for several of the sources of bias, and results in the clear recognition of differing regimes within the regional fracture field in the study area.

Martin-Kaye, P. H. A.↗

Investigating Tropical Versus Extratropical Influences on the Southern Hemisphere Tropical Edge in the Unified Model

Abstract Since the late 1970s, observations have shown a widening of the tropical Hadley cell (HC) circulation. State‐of‐the‐art climate models reproduce the general trend along with a projected continuous expansion. Discrepancies in expansion rates of observation‐ and model‐based studies have been attributed to differences in applied methods, natural variability and model shortcomings. Furthermore, the driving influence of tropical or extratropical processes on these changes is not well understood. All of this highlights the dynamical mechanisms and the region of origin controlling the tropical width are still insufficiently understood. Here we examine the influence of systematic model biases of the atmosphere‐only Unified Model (UM) onto the simulation of the Southern Hemisphere (SH) tropical edge. We utilize nudged experiments with prescribed sea surface temperatures, where potential temperature and horizontal winds are relaxed back to ERA‐Interim reanalysis for a 20‐year period in selected regions. Correcting model biases in the tropics and extratropics separately allows us to dissect the dominant remote impacts of present model errors onto the SH tropical edge simulation. The experiments are applied to established tropical width metrics ranging from near‐surface to upper‐level metrics capturing the poleward flank of the HC. We find both regions work remotely to reduce errors in the UM fields and location of the tropical edge. Surprisingly, correcting the extratropical biases, south of 45°S, more consistently improves the tropical width across the metrics and seasons than nudging the tropics (10°N–10°S). These findings demonstrate the substantial role of extratropical influences in locating the SH tropical edge.

54 ENVIRONMENTAL SCIENCES↗

Differential sea-state bias: A case study using TOPEX/POSEIDON data

We used selected data from the NASA altimeter TOPEX/POSEIDON to calculate differences in range measured by the C and Ku-band altimeters when the satellite overflew 5 to 15 m waves late at night. The range difference is due to free electrons in the ionosphere and to errors in sea-state bias. For the selected data the ionospheric influence on Ku range is less than 2 cm. Any difference in range over short horizontal distances is due only to a small along-track variability of the ionosphere and to errors in calculating the differential sea-state bias. We find that there is a barely detectable error in the bias in the geophysical data records. The wave-induced error in the ionospheric correction is less than 0.2% of significant wave height. The equivalent error in differential range is less than 1% of wave height. Errors in the differential sea-state bias calculations appear to be small even for extreme wave heights that greatly exceed the conditions on which the bias is based. The results also improved our confidence in the sea-state bias correction used for calculating the geophysical data records. Any error in the correction must influence Ku and C-band ranges almost equally.

Stewart, Robert H.↗

A statistical analysis of the broadband 0.1 to 3.5 keV spectral properties of X-ray-selected active galactic nuclei

We survey the broadband spectral properties of approximately 500 X-ray-selected active galactic nuclei (AGNs) observed with the Einstein Observatory. Included in this survey are the approximately 450 AGNs in the Extended Medium Sensitivity Survey (EMSS) of Gioia et al. (1990) and the approximately 50 AGNs in the Ultrasoft Survey of Cordova et al. (1992). We present a revised version of the latter sample, based on the post publication discovery of a software error in the Einstein Rev-1b processing. We find that the mean spectral index of the AGNs between 0.1 and 0.6 keV is softer, and the distribution of indices wider, than previous estimates based on analyses of the X-ray spectra of optically selected AGNs. A subset of these AGNs exhibit flux variabiulity, some on timescales as short as 0.05 days. A correlation between radio and hard X-ray luminosity is confirmed, but the data do not support a correlation between the radio and soft X-ray luminosities, or between radio loudness and soft X-ray spectral slope. Evidence for physically distinct soft and hard X-ray components is found, along with the possibility of a bias in previous optically selected samples toward selection of AGNs with flatter X-ray spectra.

Thompson, R. J.↗

The miniJPAS survey: A search for extreme emission-line galaxies

Context. Galaxies with extreme emission lines (EELGs) may play a key role in the evolution of the Universe, as well as in our understanding of the star formation process itself. For this reason an accurate determination of their spatial density and fundamental properties in different epochs of the Universe will constitute a unique perspective towards a comprehensive picture of the interplay between star formation and mass assembly in galaxies. In addition to this, EELGs are also interesting in order to explain the reionization of the Universe, since their interstellar medium (ISM) could be leaking ionizing photons, and thus they could be low z, analogous of extreme galaxies at high z . Aims. This paper presents a method to obtain a census of EELGs over a large area of the sky by detecting galaxies with rest-frame equivalent widths ≥300 Å in the emission lines [O II]λλ3727,3729Å, [O III]λ5007Å, and Hα. For this, we aim to use the J-PAS survey, which will image an area of ≈8000 deg 2 with 56 narrow band filters in the optical. As a pilot study, we present a methodology designed to select EELGs on the miniJPAS images, which use the same filter dataset as J-PAS, and thus will be exportable to this larger survey. Methods. We make use of the miniJPAS survey data, conceived as a proof of concept of J-PAS, and covering an area of ≈1 deg 2 . Objects were detected in the r SDSS images and selected by imposing a condition on the flux in a given narrow-band J-PAS filter with respect to the contiguous ones, which is analogous to requiring an observed equivalent width larger than 300 Å in a certain emission line within the filter bandwidth. The selected sources were then classified as galaxies or quasi-stellar objects (QSOs) after a comparison of their miniJPAS fluxes with those of a spectral database of objects known to present strong emission lines. This comparison also provided a redshift for each source, which turned out to be consistent with the spectroscopic redshifts when available (|Δz/(1 + z spec )| ≤ 0.01). Results. The selected candidates were found to show a compact appearance in the optical images, some of them even being classified as point-like sources according to their stellarity index. After discarding sources classified as QSOs, a total of 17 sources turned out to exhibit EW 0 ≥ 300 Å in at least one emission line, thus constituting our final list of EELGs. Our counts are fairly consistent with those of other samples of EELGs in the literature, although there are some differences, which were expected due to biases resulting from different selection criteria.

59 BASIC BIOLOGICAL SCIENCES↗

A Mixed-Method Design Approach for Empirically Based Selection of Unbiased Data Annotators

Implicit bias embedded in the annotated data is by far the greatest impediment in the effectual use of supervised machine learning models in tasks involving race, ethics, and geopolitical polarization. For societal good and demonstrable positive impact on wider society, it is paramount to carefully select data annotators and rigorously validate the annotation process. Current approaches to selecting annotators are not sufficiently grounded in scientific principles and are limited at the policy-guidance level, thereby rendering them unusable for machine learning practitioners. This work proposes a new approach based on the mixed-methods design that is functional, adaptable, and simpler to implement in selecting unbiased annotators for any machine learning problem. By demonstrating it on a real-world geopolitical problem, we also identified and ranked key inane profile characteristics towards an empirically-based selection of unbiased data annotators.

Thakur, Gautam Malviya↗

Non-Uniform Bias Enhancement of a Varactor-Tuned FSS used with a Low Profile 2.4 GHz Dipole Antenna

In this paper a low profile antenna using a nonuniformly biased varactor-tuned frequency selective surface (FSS) is presented. The tunable FSS avoids the use of vias and has a simplified DC bias network. The voltages to the DC bias ports can be varied independently allowing adjustment in the frequency response and enhanced radiation properties. The measured data demonstrate tunability from 2.15 GHz to 2.63 GHz with peak efficiencies that range from 50% to 90% and instantaneous bandwidths of 50 MHz to 280 MHz within the tuning range. The total antenna thickness is approximately lambda/45.

Cure, David↗

Systematic Evaluation of Atmospheric Forcing, Surface Datasets, and Mesh Effects on Kilometer-Scale Land Surface and River Modeling

Earth system models are advancing toward kilometer-scale resolution to capture local climate impacts and extremes. High-resolution land and river modeling depends on multiple factors, including mesh, surface datasets, and atmospheric forcing, but their relative effects at kilometer scales remain unquantified. We evaluated five Energy Exascale Earth System Model land and river configurations over the Mid-Atlantic region using two mesh (1/8° structured versus variable-resolution unstructured mesh), two surface datasets (default versus newly developed), and three atmospheric forcings (NLDAS2, MSWX, GSWP). Evaluation against satellite, reanalysis, and in situ benchmarks across water, energy, and carbon cycles quantifies how these factors affect model performance. Forcing selection produces the largest bias reductions (12-99% across variables), followed by surface datasets (7-75%) and mesh (up to 21%). Forcing effects vary by variable, with MSWX reducing biases for snow water equivalent, evapotranspiration, albedo, temperature, and gross primary productivity, GSWP for snow cover and runoff, and NLDAS for soil moisture and streamflow. The use of newly developed surface datasets improves gross primary productivity (58% bias reduction) and evapotranspiration but increase soil moisture and albedo biases due to current modeling limitations. Variable-resolution unstructured mesh improves the simulation of small-basin streamflow through better capturing drainage networks, though mesh minimally affects other land variables. These findings provide important guidance for high-resolution modeling development and actionable science.

Land and River modeling↗