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At least 865 records · Page 48

Dark energy survey year 3 results: miscentring calibration and X-ray-richness scaling relations in redMaPPer clusters

ABSTRACT We use Dark Energy Survey Year 3 (DES Y3) clusters with archival XMM–Newton and Chandra X-ray data to assess the centring performance of the redMaPPer cluster finder and to measure key richness observable scaling relations. We find that 10–20 per cent of redMaPPer clusters are miscentred, both when comparing to the X-ray peak position and to the visually identified central cluster galaxy. We find no significant difference in miscentring in bins of low versus high richness or redshift. The dominant reasons for miscentring include masked or missing data and the presence of other bright galaxies in the cluster. For half of the miscentred clusters, the correct central was one of the possible centrals identified by redMaPPer, while for ∼40 per cent of miscentred clusters, the correct central is not a redMaPPer member mostly due to masking. Additionally, we fit scaling relations of X-ray temperature and luminosity with richness. We find a TX–λ scatter of $0.21\pm 0.01$. While the scatter in TX–λ is consistent in redshift bins, we find modestly different slopes, with high-redshift clusters displaying a somewhat shallower relation. Splitting based on richness, we find a marginally larger scatter for our lowest richness bin, 20 < λ < 40. We note that the robustness of the scaling relations at lower richnesses is limited by the unknown selection function, but at λ > 75, we detect nearly all of the clusters falling within existing X-ray pointings. The X-ray properties of detected, serendipitous clusters are generally consistent with those of targeted clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

Robust inference of the Galactic Centre gamma-ray excess spatial properties

ABSTRACT The gamma-ray Fermi-LAT Galactic Centre excess (GCE) has puzzled scientists for over 15 yr. Despite ongoing debates about its properties, and especially its spatial distribution, its nature remains elusive. We scrutinize how the estimated spatial morphology of this excess depends on models for the Galactic diffuse emission, focusing particularly on the extent to which the Galactic plane and point sources are masked. Our main aim is to compare a spherically symmetric morphology – potentially arising from the annihilation of dark matter (DM) particles – with a boxy morphology – expected if faint unresolved sources in the Galactic bulge dominate the excess emission. Recent claims favouring a DM-motivated template for the GCE are shown to rely on a specific Galactic bulge template, which performs worse than other templates for the Galactic bulge. We find that a non-parametric model of the Galactic bulge derived from the VISTA Variables in the Via Lactea survey results in a significantly better fit for the GCE than DM-motivated templates. This result is independent of whether a galprop-based model or a more non-parametric ring-based model is used to describe the diffuse Galactic emission. This conclusion remains true even when additional freedom is added in the background models, allowing for non-parametric modulation of the model components and substantially improving the fit quality. When adopted, optimized background models provide robust results in terms of preference for a boxy bulge morphology for the GCE, regardless of the mask applied to the Galactic plane.

Astronomy & Astrophysics↗

Galaxy bias from the Dark Energy Survey Science Verification data: Combining galaxy density maps and weak lensing maps

We measure the redshift evolution of galaxy bias for a magnitude-limited galaxy sample by combining the galaxy density maps and weak lensing shear maps for a ~116 deg 2 area of the Dark Energy Survey (DES) Science Verification (SV) data. This method was first developed in Amara et al. and later re-examined in a companion paper with rigorous simulation tests and analytical treatment of tomographic measurements. In this work we apply this method to the DES SV data and measure the galaxy bias for a i < 22.5 galaxy sample. We find the galaxy bias and 1σ error bars in four photometric redshift bins to be 1.12 ± 0.19 (z = 0.2–0.4), 0.97 ± 0.15 (z = 0.4–0.6), 1.38 ± 0.39 (z = 0.6–0.8), and 1.45 ± 0.56 (z = 0.8–1.0). These measurements are consistent at the 2σ level with measurements on the same data set using galaxy clustering and cross-correlation of galaxies with cosmic microwave background lensing, with most of the redshift bins consistent within the 1σ error bars. In addition, our method provides the only σ8 independent constraint among the three. We forward model the main observational effects using mock galaxy catalogues by including shape noise, photo-z errors, and masking effects. We show that our bias measurement from the data is consistent with that expected from simulations. With the forthcoming full DES data set, we expect this method to provide additional constraints on the galaxy bias measurement from more traditional methods. Moreover, in the process of our measurement, we build up a 3D mass map that allows further exploration of the dark matter distribution and its relation to galaxy evolution.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Survey geometry and the internal consistency of recent cosmic shear measurements

We explore the impact of an update to the typical approximation for the shape noise term in the analytic covariance matrix for cosmic shear experiments that assumes the absence of survey boundary and mask effects. We present an exact expression for the number of galaxy pairs in this term based on the survey mask, which leads to more than a factor of three increase in the shape noise on the largest measured scales for the Kilo-Degree Survey (KiDS-450) real-space cosmic shear data. We compare the result of this analytic expression to several alternative methods for measuring the shape noise from the data and find excellent agreement. This update to the covariance resolves any internal model tension evidenced by the previously large cosmological best-fitting χ 2 for the KiDS-450 cosmic shear data. The best-fitting χ 2 is reduced from 161 to 121 for 118 degrees of freedom. We also apply a correction to how the multiplicative shear calibration uncertainty is included in the covariance. This change shifts the inferred amplitude of the correlation function to higher values. In conclusion, we find that this improves agreement of the KiDS-450 cosmic shear results with Dark Energy Survey Year 1 and Planck results.

79 ASTRONOMY AND ASTROPHYSICS↗

Survey geometry and the internal consistency of recent cosmic shear measurements

Here, we explore the impact of an update to the typical approximation for the shape noise term in the analytic covariance matrix for cosmic shear experiments that assumes the absence of survey boundary and mask effects. We present an exact expression for the number of galaxy pairs in this term based on the the survey mask, which leads to more than a factor of three increase in the shape noise on the largest measured scales for the Kilo-Degree Survey (KIDS-450) real-space cosmic shear data. We compare the result of this analytic expression to several alternative methods for measuring the shape noise from the data and find excellent agreement. This update to the covariance resolves any internal model tension evidenced by the previously large cosmological best-fit $\chi^2$ for the KiDS-450 cosmic shear data. The best-fit $\chi^2$ is reduced from 161 to 121 for 118 degrees of freedom. We also apply a correction to how the multiplicative shear calibration uncertainty is included in the covariance. This change, along with a previously known update to the reported effective angular values of the data vector, jointly shift the inferred amplitude of the correlation function to higher values. Lastly, we find that this improves agreement of the KiDS-450 cosmic shear results with Dark Energy Survey Year 1 and Planck results.

79 ASTRONOMY AND ASTROPHYSICS↗

Dynamic Radioactive Source for Evaluating and Demonstrating Time-dependent Performance of Continuous Air Monitors

Evaluation of continuous air monitors in the presence of a plutonium aerosol is time intensive, expensive, and requires a specialized facility. The Radiation Protection Services Group at Los Alamos National Laboratory has designed a Dynamic Radioactive Source, intended to replace plutonium aerosol challenge testing. Furthermore, the Dynamic Radioactive Source is small enough to be inserted into the sampler filter chamber of a typical continuous air monitor. Time-dependent radioactivity is introduced from electroplated sources for real-time testing of a continuous air monitor where a mechanical wristwatch motor rotates a mask above an alpha-emitting electroplated disk source. The mask is attached to the watch’s minute hand, and as it rotates, more of the underlying source is revealed. The alpha activity we measured increases with time, simulating the arrival of airborne radioactive particulates at the air sampler inlet. The Dynamic Radioactive Source allows the temporal behavior of puff and chronic release conditions to be mimicked without the need for radioactive aerosols. The new system is configurable to different continuous air monitor designs and provides an in-house testing capability (benchtop compatible). It is a repeatable and reusable system and does not contaminate the tested air monitor. Test benefits include direct user control, realistic (plutonium) aerosol spectra, and iterative development of continuous air monitor alarm algorithms. We also used data obtained using the Dynamic Radioactive Source to elucidate alarm algorithms and to compare the response time of two commercial continuous air monitors.

07 ISOTOPE AND RADIATION SOURCES↗

Band Energy Dependence of Defect Formation in the Topological Semimetal Cd3As2

Cadmium Arsenide (Cd3As2) is a prototypical Dirac semimetal that manifests topological properties in a 3D bulk material. In defect-free Cd3As2, the Fermi level lies at a minimum in the density of states at the Dirac point, but experimentally it forms with excess electron carriers and an elevated EF, thereby masking the topological features. To computationally study the self-doping of Cd3As2, we combine density functional theory (DFT) calculations for defect formation energies with quasi-particle self-consistent GW (QSGW) electronic structure calculations. We demonstrate an innate dependence of the point defect formation energies on carrier concentrations and use the QSGW calculated density of states to extrapolate formation energies to arbitrary electron concentrations. This approach allows the quantitative modeling of thermodynamic defect equilibria in topological semimetals and is used to predict how Cd3As2 growth conditions affect the position of EF relative to the Dirac point.

CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS↗

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. Validation on simulations

Beyond-two-point statistics contain additional information on cosmological as well as astrophysical and observational (systematics) parameters. In this methodology paper we provide an end-to-end simulationbased analysis of a set of Gaussian and non-Gaussian weak lensing statistics using detailed mock catalogs of the Dark Energy Survey (DES). Here, we implement: 1) second and third moments; 2) wavelet phase harmonics (WPH); 3) the scattering transform (ST). Our analysis is fully based on simulations, it spans a space of seven $νw$CDM cosmological parameters, and it forward models the most relevant sources of systematics of the data (masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration). We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a likelihood-free-inference approach. We validate the pipeline extensively, and we find that WPH exhibits the strongest performance when combined with second moments, followed by ST, and then by third moments. The combination of all the different statistics further enhances constraints with respect to second moments, up to 25 percent, 15 percent, and 90 percent for S 8 , Ω m , and the figure-of-merit FoM S8;Ωm , respectively. We further find that non-Gaussian statistics improve constraints on w and on the amplitude of intrinsic alignment with respect to second moments constraints. The methodological advances presented here are suitable for application to Stage IV surveys from Euclid, Rubin-LSST, and Roman with additional validation on mock catalogs for each survey. In a companion paper we present an application to DES Year 3 data.

79 ASTRONOMY AND ASTROPHYSICS↗

Dark Energy Survey Year 3 results: Simulation-based cosmological inference with wavelet harmonics, scattering transforms, and moments of weak lensing mass maps. II. cosmological results

Here, we present a simulation-based cosmological analysis using a combination of Gaussian and non-Gaussian statistics of the weak lensing mass (convergence) maps from the first three years of the Dark Energy Survey. We implement the following: (1) second and third moments; (2) wavelet phase harmonics; (3) the scattering transform. Our analysis is fully based on simulations, spans a space of seven 𝑤 Cold Dark Matter (𝑤⁢ CDM) cosmological parameters, and forward models the most relevant sources of systematics inherent in the data: masks, noise variations, clustering of the sources, intrinsic alignments, and shear and redshift calibration. We implement a neural network compression of the summary statistics, and we estimate the parameter posteriors using a simulation-based inference approach. Including and combining different non-Gaussian statistics is a powerful tool that strongly improves constraints over Gaussian statistics (in our case, the second moments); in particular, the figure of merit (𝑆 8 , Ω m ) is improved by 70% (Λ ⁢CDM) and 90% (𝑤 ⁢CDM). When all the summary statistics are combined, we achieve a 2% constraint on the amplitude of fluctuations parameter 𝑆 8 ≡ 𝜎 8 ⁢(Ω m /0.3) 0.5 , obtaining 𝑆 8 = 0.794 ±0.017 (Λ⁢ CDM) and 𝑆 8 = 0.817 ±0.021 (𝑤 ⁢CDM), and a ∼10% constraint on Ω m , obtaining Ω m =0.259 ±0.025 (Λ ⁢CDM) and Ω m = 0.273 ±0.029 (𝑤⁢ CDM). In the context of the 𝑤⁢ CDM scenario, these statistics also strengthen the constraints on the parameter 𝑤, obtaining 𝑤 <−0.72. The constraints from different statistics are shown to be internally consistent (with a 𝑝-value>0.1 for all combinations of statistics examined). We compare our results to other weak lensing results from the first three years of the Dark Energy Survey data, finding good consistency; we also compare with results from external datasets, such as planck constraints from the cosmic microwave background, finding statistical agreement, with discrepancies no greater than <2.2⁢𝜎.

79 ASTRONOMY AND ASTROPHYSICS↗

Foreground-Immune Cosmic Microwave Background Lensing with Shear-Only Reconstruction

Cosmic microwave background (CMB) lensing from current and upcoming wide-field CMB experiments such as AdvACT, SPT-3G and Simons Observatory relies heavily on temperature (versus polarization). In this regime, foreground contamination to the temperature map produces significant lensing biases, which cannot be fully controlled by multifrequency component separation, masking, or bias hardening. Here in this Letter, we split the standard CMB lensing quadratic estimator into a new set of optimal “multipole” estimators. On large scales, these multipole estimators reduce to the known magnification and shear estimators, and a new shear B-mode estimator. We leverage the different symmetries of the lensed CMB and extragalactic foregrounds to argue that the shear-only estimator should be approximately immune to extragalactic foregrounds. We build a new method to compute, separately and without noise, the primary, secondary, and trispectrum biases to CMB lensing from foreground simulations. Using this method, we demonstrate that the shear estimator is, indeed, insensitive to extragalactic foregrounds, even when applied to a single-frequency temperature map contaminated with cosmic infrared background, thermal Sunyaev-Zel’dovich, kinematic Sunyaev-Zel’dovich, and radio point sources. This dramatic reduction in foreground biases allows us to include higher temperature multipoles than with the standard quadratic estimator, thus, increasing the total lensing signal-to-noise ratio beyond the quadratic estimator. In addition, magnification-only and shear B-mode estimators provide useful diagnostics for potential residuals.

79 ASTRONOMY AND ASTROPHYSICS↗

Diamonds in the rough: a strong case for the inclusion of weak-intensity X-ray diffraction data

Here, new evidence is provided to show that the inclusion of weak-intensity, high-resolution X-ray diffraction data helps to improve the quality of experimental phases by imposing proper constraints on electron-density models during noncrystallographic symmetry averaging. Overwhelming evidence exists to show that the inclusion of weak-intensity, high-resolution X-ray diffraction data helps improve the refinement of atomic models by imposing strong constraints on individual and overall temperature B factors and thus the quality of crystal structures. Some researchers consider these data to be of little value and opt to discard them during data processing, particularly at medium and low resolution, at which individual B factors of atomic models cannot be refined. Here, new evidence is provided to show that the inclusion of these data helps to improve the quality of experimental phases by imposing proper constraints on electron-density models during noncrystallographic symmetry (NCS) averaging. Using electron-density correlation coefficients as criteria, the resolution of data has successfully been extended from 3.1 to 2.5 Å resolution with redundancy-independent merging R factors from below 100% to about 310%. It is further demonstrated that phase information can be fully extracted from observed amplitudes through de novo NCS averaging. Averaging starts with uniform density inside double-shelled spherical masks and NCS matrices that are derived from bound heavy-atom clusters at the vertices of cuboctahedrally symmetric protein particles.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

A Weakly-Supervised, Multitask Deep Learning Framework for Shadow Mitigation in Remote Sensing Imagery

We propose a weakly-supervised, multitask framework for training a convolutional neural network to solve the problem of cloud shadow mitigation given only cloud and shadow masks as labels. The network minimizes the Wasserstein distance between shadows and their proximal sunlit neighborhoods, generating a supervisory signal directly from within the input image. We extract further utility from the shadow mask through multitask learning by introducing an auxiliary task of shadow segmentation. Our approach is advantageous since it performs mitigation in an end-to-end framework which requires only a shadowed image for inference. We apply this process to the Landsat 8 OLI SPARCS validation data set and demonstrate plausible results.

Couwenhoven, Scott↗

Understanding and Mitigating the Contamination of Intrinsic poly-Si Gaps in Passivated IBC Solar Cells

We investigate factors that are critical for the performance of interdigitated back contact (IBC) solar cells based on polycrystalline silicon (poly-Si) passivated contacts. During patterning of doped lines using direct plasma deposition through a shadow mask, we show that the intrinsic poly-Si gap becomes contaminated with dopants, leading to shunting. Possible contamination mechanisms during masked deposition and high- temperature annealing are tested. Strategies developed to mitigate the contamination, such as reactive ion etching after deposition and amorphous to poly-Si crystallization in oxygen, will lead to improved IBC fabrication methods.

14 SOLAR ENERGY↗

Crack Identification and Characterization in Deformed Nb3Sn Rutherford Cable Stacks Using Machine Learning

An investigation of instance segmentation of cracks in Nb3Sn 4-stack 40-strand Rutherford cables using machine learning is presented. Three samples were uniaxially and biaxially loaded before metallographic inspections were performed. The Mask R-CNN model was used in the Detectron2 framework with pre-trained weights but fine-tuned to detect and segment cracks. The model detected cracks with bounding box and mask average precisions (AP) of 42.8 and 27.9, respectively, and was used for instance segmentation of all cracks in the three samples. More cracks were found in the sample pre-loaded along the z-axis (i.e., along the cable length). Pre-loading along the x-axis (i.e., on the cables edges) reduced the number of cracks and changed the crack orientation distribution, away from being highly aligned with the y-axis (i.e., normal to the cables broad faces), i.e., the direction with the highest applied load. Fine-tuning of the Segment Anything Model (SAM) was also studied but performed poorly without human-provided prompts. However, the zero-shot capability of SAM showed high promises to accelerate the image annotation process for applications beyond this study.

Croteau, Jean-Francois↗

Stretchable Mould Interconnect Optimization: Peeling Automation and Carrierless Techniques

The primary bottleneck of the stretchable mold interconnect (SMI) technology is its reliance on carrier boards. These are necessary to handle the meandered circuit during production and to ensure dimensional stability of the flexible circuit board before encapsulation. However, for all the problems it solves, it also introduces a new major problem by requiring a peeling step – which is difficult to automate. This manuscript aims to present some of the work that went into eliminating this problem, discussing both unsuccessful and functioning methods to tackle this conundrum and some of the experimental work that went into verifying these techniques. First, alterations to the design to simplify peeling are considered, followed by adhesivebased peeling processes and mechanical pin-based systems. Next, masking and structuring of the carrier board adhesive are considered. Finally, two carrierless methods which circumvent the problems are discussed, a two-step process – which cuts temporary support structures after partial encapsulation – and a technique whereby the frame is designed to fail in a controlled manner during the first use of the circuit, creating a carrierless process feasible for high-volume production.

Plovie, Bart↗

Software resilience and the effectiveness of software mitigation in microcontrollers

Commercially available microprocessors could be useful to the space community for noncritical computations. There are many possible components that are smaller, lower-power, and less expensive than traditional radiation-hardened microprocessors. Many commercial microprocessors have issues with single-event effects (SEEs), such as single-event upsets (SEUs) and single-event transients (SETs), that can cause the microprocessor to calculate an incorrect result or crash. In this paper we present the Trikaya technique for masking SEUs and SETs through software mitigation techniques. Furthermore, test results show that this technique can be very effective at masking errors, making it possible to fly these microprocessors for a variety of missions.

97 MATHEMATICS AND COMPUTING↗

Robust Duplication with Comparison Methods in Microcontrollers

Commercial microprocessors could be useful computational platforms in space systems, as long as the risk is bound. Many spacecraft are computationally constrained because all of the computation is done on a single radiation-hardened microprocessor. It is possible that a commercial microprocessor could be used for configuration, monitoring and background tasks that are not mission critical. Most commercial microprocessors are affected by radiation, including single-event effects (SEEs) that could be destructive to the component or corrupt the data. Part screening can help designers avoid components with destructive failure modes, and mitigation can suppress data corruption. We have been experimenting with a method for masking radiation-induced faults through the software executing on the microprocessor. While triple-modular redundancy (TMR) techniques are very effective at masking faults in software, the increased amount of execution time to complete the computation is not desirable. Here in this article we present a technique for combining duplication with compare (DWC) with TMR that decreases observable errors by as much as 145 times with only a 2.35 time decrease in performance.

97 MATHEMATICS AND COMPUTING↗

Algorithms for Non-Negative Matrix Factorization on Noisy Data With Negative Values

Non-negative matrix factorization (NMF) is a dimensionality reduction technique that has shown promise for analyzing noisy data, especially astronomical data. For these datasets, the observed data may contain negative values due to noise even when the true underlying physical signal is strictly positive. Prior NMF work has not treated negative data in a statistically consistent manner, which becomes problematic for low signal-to-noise data with many negative values. In this paper we present two algorithms, Shift-NMF and Nearly-NMF, that can handle both the noisiness of the input data and also any introduced negativity. Both of these algorithms use the negative data space without clipping or masking and recover non-negative signals without any introduced positive offset that occurs when clipping or masking negative data. We demonstrate this numerically on both simple and more realistic examples, and prove that both algorithms have monotonically decreasing update rules.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗