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At least 235 records · Page 13

Merger identification through photometric bands, colours, and their errors

Aims. We present the application of a fully connected neural network (NN) for galaxy merger identification using exclusively photometric information. Our purpose is not only to test the method’s efficiency, but also to understand what merger properties the NN can learn and what their physical interpretation is. Methods. We created a class-balanced training dataset of 5860 galaxies split into mergers and non-mergers. The galaxy observations came from SDSS DR6 and were visually identified in Galaxy Zoo. The 2930 mergers were selected from known SDSS mergers and the respective non-mergers were the closest match in both redshift and r magnitude. The NN architecture was built by testing a different number of layers with different sizes and variations of the dropout rate. We compared input spaces constructed using: the five SDSS filters: u, g, r, i, and z; combinations of bands, colours, and their errors; six magnitude types; and variations of input normalization. Results. We find that the fibre magnitude errors contribute the most to the training accuracy. Studying the parameters from which they are calculated, we show that the input space built from the sky error background in the five SDSS bands alone leads to 92.64 ± 0.15% training accuracy. We also find that the input normalization, that is to say, how the data are presented to the NN, has a significant effect on the training performance. Conclusions. We conclude that, from all the SDSS photometric information, the sky error background is the most sensitive to merging processes. This finding is supported by an analysis of its five-band feature space by means of data visualization. Moreover, studying the plane of the g and r sky error bands shows that a decision boundary line is enough to achieve an accuracy of 91.59%.

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Numerical image manipulation and display in solar astronomy

The paper describes the system configuration and data manipulation capabilities of a solar image display system which allows interactive analysis of visual images and on-line manipulation of digital data. Image processing features include smoothing or filtering of images stored in the display, contrast enhancement, and blinking or flickering images. A computer with a core memory of 28,672 words provides the capacity to perform complex calculations based on stored images, including computing histograms, selecting subsets of images for further analysis, combining portions of images to produce images with physical meaning, and constructing mathematical models of features in an image. Some of the processing modes are illustrated by some image sequences from solar observations.

Levine, R. H.↗

Analysis of Needlet Internal Linear Combination performance on B -mode data from sub-orbital experiments

The observation of primordial B modes in cosmic microwave background (CMB) polarisation data represents the main scientific goal of most of the future CMB experiments. This signal is predicted to be much lower than polarised Galactic emission (foregrounds) in any region of the sky, pointing to the need for effective component separation methods. Aims. Among all the techniques, the blind Needlet Internal Linear Combination (NILC) is of great relevance given our current limited knowledge of the B-mode foregrounds. In this work, we explore the possibility of employing NILC for the analysis of B modes reconstructed from partial-sky data, specifically addressing the complications that such an application yields such as E–B leakage, needlet filtering, and beam convolution. We consider two complementary simulated datasets of future experiments: the balloon-borne Short Wavelength Instrument for the Polarisation Explorer (SWIPE) of the Large Scale Polarisation Explorer, which targets the observation of both reionisation and recombination peaks of the primordial CMB B-mode angular power spectrum, and the ground-based Small Aperture Telescope of Simons Observatory, which, instead, is designed to observe only the recombination bump at ℓ ~ 80. We assessed the performance of the following two alternative techniques to correct for the CMB E–B leakage: the recycling technique and the Zhao-Baskaran method. We find that both techniques reduce the E–B leakage residuals at a negligible level given the sensitivity of the considered experiments, except for the recycling method in the SWIPE footprint at ℓ < 20. Thus, we implemented two extensions of the pipeline, the iterative B decomposition and the diffusive inpainting, which enabled us to recover the input CMB B-mode power for ℓ ≥ 5. For the considered experiments, we demonstrate that needlet filtering and beam convolution do not affect the CMB B-mode reconstruction. Finally, with an appropriate masking strategy, we find that NILC foregrounds subtraction allows one to achieve sensitivities on the tensor-to-scalar ratio in agreement with the targets of the considered CMB experiments.

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BeyondPlanck X. Bandpass and beam leakage corrections

We discuss the treatment of bandpass and beam leakage corrections in the Bayesian BeyondPlanck CMB analysis pipeline as applied to the Planck LFI measurements. As a preparatory step, we first apply three corrections to the nominal LFI bandpass profiles including removal of a known systematic effect in the ground measuring equipment at 61 GHz; smoothing of standing wave ripples; and edge regularization. The main net impact of these modifications is an overall shift in the 70 GHz bandpass of +0.6 GHz; we argue that any analysis of LFI data products, either from Planck or BeyondPlanck, should use these new bandpasses. In addition, we fit a single free bandpass parameter for each radiometer of the form Δ i = Δ 0 + $δ$ i , where Δ 0 represents an absolute frequency shift per frequency band and $δ$i is a relative shift per detector. The absolute correction is only fitted at 30 GHz with a full $\chi$ 2 -based likelihood, resulting in a correction of Δ 30 = 0.24 ± 0.03 GHz. The relative corrections are fitted using a spurious map approach, fundamentally similar to the method pioneered by the WMAP team, but without introducing many additional degrees of freedom. All bandpass parameters are sampled using a standard Metropolis sampler within the main BeyondPlanck Gibbs chain, and bandpass uncertainties are thus propagated to all other data products in the analysis. In total, we find that our bandpass model significantly reduces leakage effects. For beam leakage corrections, we adopt the official Planck LFI beam estimates without additional degrees of freedom, and only marginalize over the underlying sky model. We note that this is the first-time leakage from beam mismatch has been included for Planck LFI maps.

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Some practicable applications of quadtree data structures/representation in astronomy

Development of quadtree as hierarchical data structuring technique for representing spatial data (like points, regions, surfaces, lines, curves, volumes, etc.) has been motivated to a large extent by storage requirements of images, maps, and other multidimensional (spatially structured) data. For many spatial algorithms, time-efficiency of quadtrees in terms of execution may be as important as their space-efficiency concerning storage conditions. Briefly, the quadtree is a class of hierarchical data structures which is based on the recursive partition of a square region into quadrants and sub-quadrants until a predefined limit. Beyond the wide applicability of quadtrees in image processing, spatial information analysis, and building digital databases (processes becoming ordinary for the astronomical community), there may be numerous further applications in astronomy. Some of these practicable applications based on quadtree representation of astronomical data are presented and suggested for further considerations. Examples are shown for use of point as well as region quadtrees. Statistics of different leaf and non-leaf nodes (homogeneous and heterogeneous sub-quadrants respectively) at different levels may provide useful information on spatial structure of astronomical data in question. By altering the principle guiding the decomposition process, different types of spatial data may be focused on. Finally, a sampling method based on quadtree representation of an image is proposed which may prove to be efficient in the elaboration of sampling strategy in a region where observations were carried out previously either with different resolution or/and in different bands.

Pasztor, L.↗

Unveiling the Universe with emerging cosmological probes

The detection of the accelerated expansion of the Universe has been one of the major breakthroughs in modern cosmology. Several cosmological probes (Cosmic Microwave Background, Supernovae Type Ia, Baryon Acoustic Oscillations) have been studied in depth to better understand the nature of the mechanism driving this acceleration, and they are being currently pushed to their limits, obtaining remarkable constraints that allowed us to shape the standard cosmological model. In parallel to that, however, the percent precision achieved has recently revealed apparent tensions between measurements obtained from different methods. These are either indicating some unaccounted systematic effects, or are pointing toward new physics. Following the development of CMB, SNe, and BAO cosmology, it is critical to extend our selection of cosmological probes. Novel probes can be exploited to validate results, control or mitigate systematic effects, and, most importantly, to increase the accuracy and robustness of our results. This review is meant to provide a state-of-art benchmark of the latest advances in emerging “beyond-standard” cosmological probes. We present how several different methods can become a key resource for observational cosmology. In particular, we review cosmic chronometers, quasars, gamma-ray bursts, standard sirens, lensing time-delay with galaxies and clusters, cosmic voids, neutral hydrogen intensity mapping, surface brightness fluctuations, stellar ages of the oldest objects, secular redshift drift, and clustering of standard candles. The review describes the method, systematics, and results of each probe in a homogeneous way, giving the reader a clear picture of the available innovative methods that have been introduced in recent years and how to apply them. The review also discusses the potential synergies and complementarities between the various probes, exploring how they will contribute to the future of modern cosmology.

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Model independent approach for calculating galaxy rotation curves for low S/N MaNGA galaxies

Internal kinematics of galaxies, traced through the stellar rotation curve or two dimensional velocity map, carry important information on galactic structure and dark matter. With upcoming surveys, the velocity map may play a key role in the development of kinematic lensing as an astrophysical probe. Here, we improve techniques for extracting velocity information from integral field spectroscopy at low signal-to-noise (S/N), without a template, and demonstrate substantial advantages over the standard Penalized PiXel-Fitting method (pPXF) approach. Robust rotation curves can be derived down to S/N ≈ 2 using our method.

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The PAU Survey: Photometric redshifts using transfer learning from simulations

In this paper, we introduce the DEEPZ deep learning photometric redshift (photo-z) code. As a test case, we apply the code to the PAU survey (PAUS) data in the COSMOS field. DEEPZ reduces the σ68 scatter statistic by 50 percent at iAB = 22.5 compared to existing algorithms. This improvement is achieved through various methods, including transfer learning from simulations where the training set consists of simulations as well as observations, which reduces the need for training data. The redshift probability distribution is estimated with a mixture density network (MDN), which produces accurate redshift distributions. Our code includes an autoencoder to reduce noise and extract features from the galaxy SEDs. It also benefits from combining multiple networks, which lowers the photo-z scatter by 10 percent. Furthermore, training with randomly constructed coadded fluxes adds information about individual exposures, reducing the impact of photometric outliers. In addition to opening up the route for higher redshift precision with narrow bands, these machine learning techniques can also be valuable for broad-band surveys.

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DeepMerge – II. Building robust deep learning algorithms for merging galaxy identification across domains

In astronomy, neural networks are often trained on simulation data with the prospect of being used on telescope observations. Unfortunately, training a model on simulation data and then applying it to instrument data leads to a substantial and potentially even detrimental decrease in model accuracy on the new target dataset. Simulated and instrument data represent different data domains, and for an algorithm to work in both, domain-invariant learning is necessary. Here we employ domain adaptation techniques— Maximum Mean Discrepancy (MMD) as an additional transfer loss and Domain Adversarial Neural Networks (DANNs)— and demonstrate their viability to extract domain-invariant features within the astronomical context of classifying merging and non-merging galaxies. Additionally, we explore the use of Fisher loss and entropy minimization to enforce better in-domain class discriminability. We show that the addition of each domain adaptation technique improves the performance of a classifier when compared to conventional deep learning algorithms. We demonstrate this on two examples: between two Illustris-1 simulated datasets of distant merging galaxies, and between Illustris-1 simulated data of nearby merging galaxies and observed data from the Sloan Digital Sky Survey. The use of domain adaptation techniques in our experiments leads to an increase of target domain classification accuracy of up to ~20%. With further development, these techniques will allow astronomers to successfully implement neural network models trained on simulation data to efficiently detect and study astrophysical objects in current and future large-scale astronomical surveys.

galaxies: interactions↗

The halo light-cone catalogues of ABACUSSUMMIT

We describe a method for generating halo catalogues on the light-cone using the AbacusSummit suite of N-body simulations. The main application of these catalogues is the construction of realistic mock galaxy catalogues and weak lensing maps on the sky. Our algorithm associates the haloes from a set of coarsely spaced snapshots with their positions at the time of light-cone crossing by matching halo particles to on-the-fly light-cone particles. It then records the halo and particle information into an easily accessible product, which we call the AbacusSummit halo light-cone catalogues. Our recommended use of this product is in the halo mass regime of M halo > 2.1 x 10 11 M ⊙ h -1 for the base resolution simulations, i.e. haloes containing at least 100 particles, where the interpolated halo properties are most reliable. To test the validity of the obtained catalogues, we perform various visual inspections and consistency checks. In particular, we construct galaxy mock catalogues of emission-line galaxies (ELGs) at z ~ 1 by adopting a modified version of the AbacusHOD script, which builds on the standard halo occupation distribution (HOD) method by including various extensions. We find that the multipoles of the autocorrelation function are consistent with the predictions from the full-box snapshot, implicitly validating our algorithm. In addition, we compute and output CMB convergence maps and find that the auto- and cross-power spectrum agrees with the theoretical prediction at the sub-per-cent level.

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Empirically Driven multiwavelength K-c orrections at low redshift

K -corrections – a necessary ingredient for converting between flux in observed bands to flux in rest-frame bands – are critical for comparing galaxies at differing redshifts. These corrections often rely on fits to empirical or theoretical spectral energy distribution (SED) templates of galaxies. However, templates can only produce reliable K-corrections in regimes where SED models are robust. For instance, the templates utilized in some popular software packages are not well-constrained in some bands (e.g. WISE W4 in KCORRECT ), which results in ill-behaved K -corrections. We address this shortcoming by developing an empirically driven approach to K -corrections that limits the dependence on SED templates. We perform a polynomial fit for the K -correction as a function of a galaxy’s rest-frame colour determined in a pair of well-constrained bands (e.g. 0 (g − r)) and redshift, exploiting the fact that galaxy SEDs can be approximated as a one-parameter family at low redshift. For bands well-constrained by SED templates, our empirically driven K -corrections yield results comparable to the SED fitting methods used by KCORRECT and the GSWLC-M2 catalogue (the updated medium-deep GALEX–SDSS–WISE Legacy Catalogue). However, our method dramatically outperforms Kcorrect derived K -corrections for WISE W4 . Our method is also robust to incorrect template assumptions outside of the optical bands and enforces that the K -correction must be zero at z = 0. Our K -corrected photometry and code are publicly available.

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Decoding the age–chemical structure of the Milky Way disc: an application of copulas and elicitable maps

In the Milky Way, the distribution of stars in the [α/Fe] versus [Fe/H] and [Fe/H] versus age planes holds essential information about the history of star formation, accretion, and dynamical evolution of the Galactic disc. We investigate these planes by applying novel statistical methods called copulas and elicitable maps to the ages and abundances of red giants in the Apache Point Observatory Galactic Evolution Experiment survey. We find that the high- and low-α disc stars have a clean separation in copula space and use this to provide an automated separation of the α sequences using a purely statistical approach. This separation reveals that the high-α disc ends at the same [α/Fe] and age at high [Fe/H] as the low-[Fe/H] start of the low-α disc, thus supporting a sequential formation scenario for the high- and low-α discs. We then combine copulas with elicitable maps to precisely obtain the correlation between stellar age τ and metallicity [Fe/H] conditional on Galactocentric radius R and height z in the range 0 < R < 20 kpc and |z| < 2 kpc. The resulting trends in the age–metallicity correlation with radius, height, and [α/Fe] demonstrate a ≈0 correlation wherever kinematically cold orbits dominate, while the naively expected negative correlation is present where kinematically hot orbits dominate. This is consistent with the effects of spiral-driven radial migration, which must be strong enough to completely flatten the age–metallicity structure of the low-α disc.

79 ASTRONOMY AND ASTROPHYSICS↗

Accurate estimation of angular power spectra for maps with correlated masks

A common procedure when analyzing maps of the cosmic microwave background (CMB) or other cosmological signals is the need to remove ("mask") regions of the maps that are heavily contaminated, e.g., by non-cosmological foreground emission. After applying such a mask, one must account for its effect when inferring statistical properties of interest, such as the angular power spectrum of the field in the original map. A widely used approach to correct for such mask-induced effects was presented by Hivon et al. (2002), now widely known as the "MASTER" formalism. However, it is often the case that the map and mask are correlated in some way, such as point source masks used in CMB analyses, which have nonzero correlation with CMB secondary anisotropy fields and other mm-wave sky signals. In such situations, the MASTER approach gives biased results, as it assumes that the unmasked map and mask have zero correlation. While such effects have been discussed before with regard to specific physical models, here we derive a completely general formalism for any case where the map and mask are correlated. We show that our result ("reMASTERed") reconstructs ensemble-averaged angular power spectra to effectively exact precision, with significant improvements over traditional estimators for cases where the map and mask are correlated. An important consequence of our result is that for maps with correlated masks, it is no longer possible to invert a simple equation to obtain the true power spectrum from the observed (masked) power spectrum. Instead, our result necessitates the use of forward modeling from theory space into the observable domain of the masked power spectrum. We publicly release our software implementation of these results.

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Plasma and radio waves from Neptune: Source mechanisms and propagation

This report summarizes results obtained through the support of NASA Grant NAGW-2412. The objective of this project is to conduct a comprehensive investigation of the radio wave emission observed by the planetary radio astronomy (PRA) instrument on board Voyager 2 as if flew by Neptune. This study has included data analysis, theoretical and numerical calculations, ray tracing, and modeling to determine the possible source mechanism(s) and locations of the Neptune radio emissions. We have completed four papers, which are included in the appendix. The paper 'Modeling of Whistler Ray Paths in the Magnetosphere of Neptune' investigated the propagation and dispersion of lighting-generated whistler in the magnetosphere of Neptune by using three dimensional ray tracing. The two papers 'Numerical Simulations of Bursty Radio Emissions from Planetary Magnetospheres' and 'Numerical Simulations of Bursty Planetary Radio Emissions' employed numerical simulations to investigate an alternate source mechanism of bursty radio emissions in addition to the cyclotron maser instability. We have also studied the possible generation of Z and whistler mode waves by the temperature anisotropic beam instability and the result was published in 'Electron Cyclotron Wave Generation by Relativistic Electrons.' Besides the aforementioned studies, we have also collaborated with members of the PRA team to investigate various aspects of the radio wave data. Two papers have been submitted for publication and the abstracts of these papers are also listed in the appendix.

Wong, H. K.↗

Plasma and radio waves from Neptune: Source mechamisms and propagation

The purpose of this project was to conduct a comprehensive investigation of the radio wave emission observed by the planetary radio astronomy (PRA) instrument on board Voyager 2 as it flew by Neptune. The study has included data analysis, theoretical and numerical calculations, and ray tracing to determine the possible source mechanisms and locations of the radiation, including the narrowband bursty and smooth components of the Neptune radio emission.

Menietti, J. Douglas↗

The catalog-to-cosmology framework for weak lensing and galaxy clustering for LSST

We present TXPipe, a modular, automated and reproducible pipeline for ingesting catalog data and performing all the calculations required to obtain quality-assured two-point measurements of lensing and clustering, and their covariances, with the metadata necessary for parameter estimation. The pipeline is developed within the Rubin Observatory Legacy Survey of Space and Time (LSST) Dark Energy Science Collaboration (DESC), and designed for cosmology analyses using LSST data. In this paper, we present the pipeline for the so-called 3x2pt analysis -- a combination of three two-point functions that measure the auto- and cross-correlation between galaxy density and shapes. We perform the analysis both in real and harmonic space using TXPipe and other LSST-DESC tools. We validate the pipeline using Gaussian simulations and show that it accurately measures data vectors and recovers the input cosmology to the accuracy level required for the first year of LSST data under this simplified scenario. We also apply the pipeline to a realistic mock galaxy sample extracted from the CosmoDC2 simulation suite (Korytov et al. 2019). TXPipe establishes a baseline framework that can be built upon as the LSST survey proceeds. Furthermore, the pipeline is designed to be easily extended to science probes beyond the 3x2pt analysis.

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The Alcock–Paczynski effect from Lyman- α forest correlations: analysis validation with synthetic data

The three-dimensional distribution of the Ly α forest has been extensively used to constrain cosmology through measurements of the baryon acoustic oscillations (BAO) scale. However, more cosmological information could be extracted from the full shapes of the Ly α forest correlations through the Alcock–Paczynski (AP) effect. In this work, we prepare for a cosmological analysis of the full shape of the Ly α forest correlations by studying synthetic data of the extended Baryon Oscillation Spectroscopic Survey (eBOSS). We use a set of 100 eBOSS synthetic data sets in order to validate such an analysis. These mocks undergo the same analysis process as the real data. We perform a full-shape analysis on the mean of the correlation functions measured from the 100 eBOSS realizations, and find that our model of the Ly α correlations performs well on current data sets. We show that we are able to obtain an unbiased full-shape measurement of D M /D H (z eff ), where D M is the transverse comoving distance, D H is the Hubble distance, and z eff is the effective redshift of the measurement. We test the fit over a range of scales, and decide to use a minimum separation of r min = 25 h –1 Mpc. Here, we also study and discuss the impact of the main contaminants affecting Ly α forest correlations, and give recommendations on how to perform such analysis with real data. While the final eBOSS Ly α BAO analysis measured D M /D H (z eff = 2.33) with 4 per cent statistical precision, a full-shape fit of the same correlations could provide an $\sim 2~{{\ \rm per\ cent}}$ measurement.

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