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THE DETECTION AND STATISTICS OF GIANT ARCS BEHIND CLASH CLUSTERS

We developed an algorithm to find and characterize gravitationally lensed galaxies (arcs) to perform a comparison of the observed and simulated arc abundance. Observations are from the Cluster Lensing And Supernova survey with Hubble (CLASH). Simulated CLASH images are created using the MOKA package and also clusters selected from the high-resolution, hydrodynamical simulations, MUSIC, over the same mass and redshift range as the CLASH sample. The algorithm's arc elongation accuracy, completeness, and false positive rate are determined and used to compute an estimate of the true arc abundance. We derive a lensing efficiency of 4 ± 1 arcs (with length ≥6″ and length-to-width ratio ≥7) per cluster for the X-ray-selected CLASH sample, 4 ± 1 arcs per cluster for the MOKA-simulated sample, and 3 ± 1 arcs per cluster for the MUSIC-simulated sample. The observed and simulated arc statistics are in full agreement. We measure the photometric redshifts of all detected arcs and find a median redshift z{sub s} = 1.9 with 33% of the detected arcs having z{sub s} > 3. We find that the arc abundance does not depend strongly on the source redshift distribution but is sensitive to the mass distribution of the dark matter halos (e.g., the c–M relation). Our results show that consistency between the observed and simulated distributions of lensed arc sizes and axial ratios can be achieved by using cluster-lensing simulations that are carefully matched to the selection criteria used in the observations.

79 ASTRONOMY AND ASTROPHYSICS↗

The completed SDSS-IV extended Baryon Oscillation Spectroscopic Survey: cosmological implications from multitracer BAO analysis with galaxies and voids

We construct cosmic void catalogues with the dive void finder upon SDSS BOSS DR12 and eBOSS DR16 galaxy samples with BAO reconstruction, and perform a joint BAO analysis using different types of galaxies and the corresponding voids. The BAO peak is evident for the galaxy–galaxy, galaxy–void, and void–void correlation functions of all data sets, including the ones cross-correlating LRG and ELG samples. Two multitracer BAO fitting schemes are tested, one combining the galaxy and void correlation functions with a weight applied to voids, and the other using a single BAO dilation parameter for all clustering measurements. Both methods produce consistent results with mock catalogues, and on average ~10 per cent improvements of the BAO statistical uncertainties are observed for all samples, compared to the results from galaxies alone. By combining the clustering of galaxies and voids, the uncertainties of BAO measurements from the SDSS data are reduced by 5–15 per cent, yielding 0.9 per cent, 0.8 per cent, 1.1 per cent, 2.3 per cent, and 2.9 per cent constraints on the distance $D_{_{\rm V}}(z)$, at effective redshifts 0.38, 0.51, 0.70, 0.77, and 0.85, respectively. When combined with BAO measurements from SDSS MGS, QSO, and Lyα samples, as well as the BBN results, we obtain $H_0 = 67.58 \pm 0.91\, {\rm km}\, {\rm s}^{-1}\, {\rm Mpc}^{-1}$, Ω m = 0.290 ± 0.015, and $\Omega _\Lambda h^2 = 0.3241 \pm 0.0079$ in the flat-ΛCDM framework, where the 1σ uncertainties are around 6 per cent, 6 per cent, and 17 per cent smaller respectively, compared to constraints from the corresponding anisotropic BAO measurements without voids and LRG–ELG cross-correlations.

79 ASTRONOMY AND ASTROPHYSICS↗

Radio-bright versus radio-dark gamma-ray bursts – more evidence for distinct progenitors

ABSTRACT We analyse two distinct samples of gamma-ray bursts (GRBs), with and without radio afterglow emission. We use an updated sample of 211 GRBs and find, in agreement with previous results (although with a sample that is almost twice as large), that the intrinsic gamma-ray duration (Tint) and isotropic equivalent energy (Eiso) distributions between these two populations appear to be significantly different. This implies that the radio-bright GRBs are more energetic and last longer than radio-dark GRBs. The two samples’ redshift distributions (z) are not statistically different. We analyse several correlations between variables (Eiso, Tint, jet opening angle, and z), accounting for selection effects and redshift evolution using the Efron–Petrosian method. We find a statistically significant anticorrelation between the jet opening angle and redshift, as well as between Tint and redshift, for both radio-bright and radio-dark GRBs. Finally, in agreement with previous work, we find that very high energy (0.1–100 GeV) extended emission is present only in the radio-bright GRB sample. Our work supports the possibility that the radio-bright and radio-dark GRBs originate from different progenitors.

79 ASTRONOMY AND ASTROPHYSICS↗

Bayesian optimized collection strategies for fatigue strength testing

Abstract A statistical framework is presented enabling optimal sampling and analysis of constant life fatigue data. Protocols using Bayesian maximum entropy sampling are built based on conventional staircase and stress step methods, reducing the requirement of prior knowledge for data collection. The Bayesian Staircase method shows improved parameter estimation efficiency, and the Bayesian Stress Step method shows equal accuracy to the standard method at larger step size allowing experimentalists to lessen concerns of loading history. Statistical methods for determining model suitability are shown, highlighting the influence of protocol. Experimental validation is performed, showing the applicability of the methods in laboratory testing.

36 MATERIALS SCIENCE↗

Vacuum Strength of Two Candidate Glasses for a Space Observatory

The strengths of two candidate glass types for use in a space observatory were measured. Samples of ultra-low expansion glass (ULE) and borosilicate (Pyrex) were tested in air and in vacuum at room temperature (20 degrees C) and in vacuum after being heated to 200 degrees C. Both glasses tested in vacuum showed a significant increase in strength over those tested in air. However, there was no statistical difference between the strength of samples tested in vacuum at room temperature and those tested in vacuum after heating to 200 degrees C.

Manning, Timothy Andrew↗

A coronagraphic search for brown dwarfs around nearby stars

Brown dwarf companions have been searched for around stars within 10 pc of the Sun using the Johns-Hopkins University Adaptive Optics Coronagraph (AOC), a stellar coronagraph with an image stabilizer. The AOC covers the field around the target star with a minimum search radius of 1 sec .5 and a field of view of 1 arcmin sq. We have reached an unprecedented dynamic range of Delta m = 13 in our search for faint companions at I band. Comparison of our survey with other brown dwarf searches shows that the AOC technique is unique in its dynamic range while at the same time just as sensitive to brown dwarfs as the recent brown dwarf surveys. The present survey covered 24 target stars selected from the Gliese catalog. A total of 94 stars were detected in 16 fields. The low-latitude fields are completely dominated by background star contamination. Kolmogorov-Smirnov tests were carried out for a sample restricted to high latitudes and a sample with small angular separations. The high-latitude sample (b greater than or equal to 44 deg) appears to show spatial concentration toward target stars. The small separation sample (Delta Theta less than 20 sec) shows weaker dependence on Galactic coordinates than field stars. These statistical tests suggest that both the high-latitude sample and the small separation sample can include a substantial fraction of true companions. However, the nature of these putative companions is mysterious. They are too faint to be white dwarfs and too blue for brown dwarfs. Ignoring the signif icance of the statistical tests, we can reconcile most of the detections with distant main-sequence stars or white dwarfs except for a candidate next to GL 475. Given the small size of our sample, we conclude that considerably more targets need to be surveyed before a firm conclusion on the possibility of a new class of companions can be made.

Nakajima, T.↗

pop-cosmos : redshifts and physical properties of KiDS-1000 galaxies

ABSTRACT Principled Bayesian inference of galaxy properties has not previously been performed for wide-area weak-lensing surveys with millions of sources. We address this gap by applying the pop-cosmos generative model to perform spectral energy distribution (SED) fitting for 4 million KiDS (Kilo-Degree Survey)-1000 galaxies. Calibrated on deep COSMOS2020 photometric data, pop-cosmos specifies a physically motivated prior over the galaxy population up to $z \simeq 6$ in stellar population synthesis (SPS) parameter space. Using the Speculator SPS emulator with GPU (graphics processing unit)-accelerated Markov Chain Monte Carlo sampling, we perform full posterior inference at 8.2 GPU seconds per galaxy, obtaining joint constraints on galaxy redshifts and physical properties. We validate photometric redshifts against $\sim \!185\,\!000$ KiDS galaxies cross-matched to Dark Energy Spectroscopic Instrument Data Release 1 spectroscopic samples, achieving low bias ($2\times 10^{-3}$), scatter ($\sigma _{\mathrm{MAD}}=0.03$), and outlier fraction (3.2 per cent) for the Bright Galaxy Survey, with comparable performance (bias $3\times 10^{-2}$, $\sigma _{\mathrm{MAD}}=0.05$, 1.0 per cent outliers) for luminous red galaxies (LRGs). Within the LRG sample, we identify massive, dusty, star-forming contaminants at $z \simeq 0.4$ satisfying standard colour selections for quenched populations. We infer trends in stellar mass, star formation, metallicity, and dust across five tomographic redshift bins consistent with established scaling relations. Using specific star formation rate constraints, we identify $\sim$7 per cent of KiDS-1000 galaxies as quenched, versus 37 per cent implied by conservative colour cuts. This enables the construction of weak-lensing samples defined by physical properties while mitigating intrinsic alignment systematics and preserving statistical power. Our analysis validates pop-cosmos out of sample, establishing it as a scalable approach for galaxy evolution and cosmological analyses with photometric surveys.

Halder, Anik [Institute of Astronomy and Kavli Ins↗

Field application of pathogen detection technologies

Over the last 10 years there has been a significant increase in commercial products designed for field-based detection of microbial pathogens. This is due, in part, to the anthrax attacks in the United States in 2001, and the need for first responders to quickly identify the composition of suspected white powders and other potential biothreats. Demand for rapid detection is also driven by the need to ensure safe food, water, and environmental systems. From a technology perspective, rapid identification methods have largely capitalized on PCR and other molecular recognition techniques that can be deployed as robust field instrumentation. Examples of the relevant needs include the ability to: 1) declare a water distribution system free of microbial pathogens after a pipe/main break repair; 2) assess risks of contamination such as when produce production and processing plants are located near concentrated animal feeing operations; 3) evaluate the safety of ready-to-eat products; 4) determine the extent of potential serious disease outbreaks in remote and/or disaster stricken areas where access to clinical laboratories is not an immediate option; and 5) quickly assess credible biological terrorism events. Many of the principles underlying rapid detection methods are derived from methods for environmental microbiology, but there is a dearth of literature describing and evaluating field-based detection systems. Thus, the aims of this chapter are to: 1) summarize the different kinds of commercially available sampling kits and field-based biological detectors; 2) highlight some of the continued challenges of sample preparation to stimulate new research towards minimizing the impact of inhibitors on PCR-based detection systems; 3) describe our general rationale and statistically-based approach for instrument evaluation; 4) provide statistical and spatial guidelines for developing valid sampling plans; and 5) summarize some current needs and emerging technologies. This information is presented both to highlight the state of the field, and to also highlight major questions that students may wish to consider investigating further. Where possible we will cite studies that have been conducted and published either in traditional peer-reviewed or other literature (e.g., AOAC International Methods).

Straub, Tim M.↗

Use of Unlabeled Samples for Mitigating the Hughes Phenomenon

The use of unlabeled samples in improving the performance of classifiers is studied. When the number of training samples is fixed and small, additional feature measurements may reduce the performance of a statistical classifier. It is shown that by using unlabeled samples, estimates of the parameters can be improved and therefore this phenomenon may be mitigated. Various methods for using unlabeled samples are reviewed and experimental results are provided.

Landgrebe, David A.↗

The velocity distribution function of galaxy clusters as a cosmological probe

We present a new approach for quantifying the abundance of galaxy clusters and constraining cosmological parameters using dynamical measurements. In the standard method, galaxy line-of-sight velocities, v, or velocity dispersions are used to infer cluster masses, M, to quantify the halo mass function (HMF), dn(M)/dlog(M), which is strongly affected by mass measurement errors. In our new method, the probability distributions of velocities for each cluster in the sample are summed to create a new statistic called the velocity distribution function (VDF), dn(v)/dv. The VDF can be measured more directly and precisely than the HMF and can be robustly predicted with cosmological simulations that capture the dynamics of subhalos or galaxies. We apply these two methods to realistic (ideal) mock cluster catalogs with (without) interlopers and forecast the bias and constraints on the matter density parameter Ω{sub m} and the amplitude of matter fluctuations σ{sub 8} in flat ΛCDM cosmologies. For an example observation of 200 massive clusters, the VDF with (without) interloping galaxies constrains the parameter combination σ{sub 8} Ω{sub m}{sup 0.29(0.29)}=0.589±0.014 (0.584±0.011) and shows only minor bias. However, the HMF with interlopers is biased to low Ω{sub m} and high σ{sub 8} and the fiducial model lies well outside of the forecast constraints, prior to accounting for Eddington bias. When the VDF is combined with constraints from the cosmic microwave background, the degeneracy between cosmological parameters can be significantly reduced. Upcoming spectroscopic surveys that probe larger volumes and fainter magnitudes will provide clusters for applying the VDF as a cosmological probe.

79 ASTRONOMY AND ASTROPHYSICS↗

The Field Substellar Mass Function Based on the Full-sky 20 pc Census of 525 L, T, and Y Dwarfs

We present final Spitzer trigonometric parallaxes for 361 L, T, and Y dwarfs. We combine these with prior studies to build a list of 525 known L, T, and Y dwarfs within 20 pc of the Sun, 38 of which are presented here for the first time. Using published photometry and spectroscopy as well as our own follow-up, we present an array of color–magnitude and color–color diagrams to further characterize census members, and we provide polynomial fits to the bulk trends. Using these characterizations, we assign each object a T(eff) value and judge sample completeness over bins of T(eff) and spectral type. Except for types ≥T8 and T(eff) < 600 K, our census is statistically complete to the 20 pc limit. We compare our measured space densities to simulated density distributions and find that the best fit is a power law (dN/dM ∝ M^(-α) with α = 0.6 ± 0.1. We find that the evolutionary models of Saumon & Marley correctly predict the observed magnitude of the space density spike seen at 1200 K < T(eff) < 1350 K, believed to be caused by an increase in the cooling timescale across the L/T transition. Defining the low-mass terminus using this sample requires a more statistically robust and complete sample of dwarfs ≥Y0.5 and with T(eff) < 400 K. We conclude that such frigid objects must exist in substantial numbers, despite the fact that few have so far been identified, and we discuss possible reasons why they have largely eluded detection.

J. Davy Kirkpatrick↗

Global Sensitivity Analysis with Small Sample Sizes: Ordinary Least Squares Approach

A new version of global sensitivity analysis is developed in this paper. This new version coupled with tools from statistics, machine learning, and optimization can devise small sample sizes that allow for the accurate ordering of sensitivity coefficients for the first 10-30 most sensitive chemical reactions in complex chemical-kinetic mechanisms, and is particularly useful for studying the chemistry in realistic devices. A key part of the paper is calibration of these small samples. Because these small sample sizes are developed for use in realistic combustion devices, the calibration is done over the ranges of conditions in such devices, with a test case being the operating conditions of a compression ignition engine studied earlier. Compression ignition engines operate under low-temperature combustion conditions with quite complicated chemistry making this calibration difficult, leading to the possibility of false positives and false negatives in the ordering of the reactions. So an important aspect of the paper is showing how to handle the trade-off between false positives and false negatives using ideas from the multiobjective optimization literature. The combination of the new global sensitivity method and the calibration are sample sizes a factor of approximately 10 times smaller than were available with our previous algorithm.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Bayesian operator inference for data-driven reduced-order modeling

This work proposes a Bayesian inference method for the reduced-order modeling of time-dependent systems. Informed by the structure of the governing equations, the task of learning a reduced-order model from data is posed as a Bayesian inverse problem with Gaussian prior and likelihood. The resulting posterior distribution characterizes the operators defining the reduced-order model, hence the predictions subsequently issued by the reduced-order model are endowed with uncertainty. The statistical moments of these predictions are estimated via a Monte Carlo sampling of the posterior distribution. Since the reduced models are fast to solve, this sampling is computationally efficient. Furthermore, the proposed Bayesian framework provides a statistical interpretation of the regularization term that is present in the deterministic operator inference problem, and the empirical Bayes approach of maximum marginal likelihood suggests a selection algorithm for the regularization hyperparameters. The proposed method is demonstrated on two examples: the compressible Euler equations with noise-corrupted observations, and a single-injector combustion process.

97 MATHEMATICS AND COMPUTING↗

Sensitivity of neutron observables to the model input in simulations of 252 Cf ( sf )

Within the framework of $FREYA$ event-by-event fission simulations, we study the sensitivity of various neutron observables to the input yield function $Y$ ($A,Z,$TKE) on which the fission event sampling is based. We first perform a statistical analysis of the available fission data in order to determine the distribution of possible yield functions $Y$ ($A,Z$,TKE) and we then construct a sample of 15,000 such yield functions. For each of these, $FREYA$ is used to generate one million fission events, leading to a corresponding ensemble of fission observables, including the neutron multiplicity distribution and its factorial moments, the neutron energy spectrum, and the neutron-neutron angular correlation. This procedure allows us to study the sensitivity of those neutron observables to the uncertainty in the experimental data. Particular attention is given to the pronounced anticorrelation between the mean neutron multiplicity $\bar{v}$ and the mean total fragment kinetic energy TKE. Because the former observable is very well determined experimentally, it is possible to exploit that inherent anticorrelation to derive a significantly stricter tolerance on TKE. In addition, we study the sensitivity to the various $FREYA$ parameters and we introduce a method for determining a A-dependent x parameter, $x$($A$), based on the measured A-dependent neutron multiplicity, ($A$).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Divide and conquer: using RhizoVision Explorer to aggregate data from multiple root scans using image concatenation and statistical methods

Roots are important in agricultural and natural systems for determining plant productivity and soil carbon inputs. Sometimes, the amount of roots in a sample is too much to fit into a single scanned image, so the sample is divided among several scans, and there is no standard method to aggregate the data. Here, we describe and validate two methods for standardizing measurements across multiple scans: image concatenation and statistical aggregation. We developed a Python script that identifies which images belong to the same sample and returns a single, larger concatenated image. These concatenated images and the original images were processed with RhizoVision Explorer, a free and open-source software. An R script was developed, which identifies rows of data belonging to the same sample and applies correct statistical methods to return a single data row for each sample. These two methods were compared using example images from switchgrass, poplar, and various tree and ericaceous shrub species from a northern peatland and the Arctic. Most root measurements were nearly identical between the two methods except median diameter, which cannot be accurately computed by statistical aggregation. We believe the availability of these methods will be useful to the root biology community.

59 BASIC BIOLOGICAL SCIENCES↗

Inferring subhalo effective density slopes from strong lensing observations with neural likelihood-ratio estimation

ABSTRACT Strong gravitational lensing has emerged as a promising approach for probing dark matter (DM) models on sub-galactic scales. Recent work has proposed the subhalo effective density slope as a more reliable observable than the commonly used subhalo mass function. The subhalo effective density slope is a measurement independent of assumptions about the underlying density profile and can be inferred for individual subhaloes through traditional sampling methods. To go beyond individual subhalo measurements, we leverage recent advances in machine learning and introduce a neural likelihood-ratio estimator to infer an effective density slope for populations of subhaloes. We demonstrate that our method is capable of harnessing the statistical power of multiple subhaloes (within and across multiple images) to distinguish between characteristics of different subhalo populations. The computational efficiency warranted by the neural likelihood-ratio estimator over traditional sampling enables statistical studies of DM perturbers and is particularly useful as we expect an influx of strong lensing systems from upcoming surveys.

Astronomy & Astrophysics↗

A comparison of compact, presumably young with extended, evolved radio active galactic nuclei

Context.The triggering and evolution of active galactic nuclei (AGNs) and the interaction of the AGN with its host galaxy is an important topic in extragalactic astrophysics. Radio sources with peaked spectra (peaked spectrum sources, PSS) and compact symmetric objects (CSO) are powerful, compact, and presumably young AGNs and therefore particularly suitable to study aspects of the AGN-host connection. Aims.We use a statistical approach to investigate properties of a PSS-CSO sample that are related to host galaxies and could potentially shed light on the link between host galaxies and AGNs. The main goal is to compare the PSS-CSO sample with a matching comparison sample of extended sources (ECS) to see if the two have significant differences. Methods.We analysed composite spectra, diagnostic line diagrams, multi-band spectral energy distributions (MBSEDs), star formation (SF) indicators, morphologies, and cluster environments for a sample of 121 PSSs and CSOs for which spectra are available from the Sloan Digital Sky Survey (SDSS). The statistical results were compared with those of the ECS sample, where we generally considered the two subsamples of quasi-stellar objects (QSOs) and radio galaxies separately. The analysis is based on a large set of archival data in the spectral range from the ultraviolet to mid-infrared. Results.We find significant differences between the PSS-CSO and the ECS sample. In particular, we find that the ECS sample has a higher proportion of passive galaxies with a lower star formation activity. This applies to both sub-samples (QSOs or radio galaxies) as well as to the entire sample. The star formation rates of the PSS-CSO host galaxies with available data are typically in the range ∼0 to 5 ℳ ⊙ yr −1 , and the stellar masses are in the range 3 × 10 11 to 10 12 ℳ ⊙ . Secondly, in agreement with previous results, we find a remarkably high proportion of PSS-CSO host galaxies with merger signatures. The merger fraction of the PSS-CSO sample is 0.61 ± 0.07, which is significantly higher than that of the comparison sample (0.15 ± 0.06). We suggest that this difference can be explained by assuming that the majority of the PSSs and CSOs cannot evolve to extended radio sources and are therefore not represented in our comparison sample.

Astronomy & Astrophysics↗