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Coleman Krawczyk

Publications and source records attributed to Coleman Krawczyk.

13 recordsLinked to original sources

Communicating the gravitational-wave discoveries of the LIGO-Virgo-KAGRA Collaboration

The LIGO-Virgo-KAGRA (LVK) Collaboration has made breakthrough discoveries in gravitational-wave astronomy, a new field that provides a different means of observing our Universe. Gravitational-wave discoveries are possible thanks to the work of thousands of people from across the globe working together. In this article, we discuss the range of engagement activities used to communicate LVK gravitational-wave discoveries and the stories of the people behind the science, using the activities surrounding the release of the third Gravitational-Wave Transient Catalog as a case study.

astro-ph.IM

How to Break the Mass Sheet Degeneracy with the Lightcurves of Microlensed Type Ia Supernovae

The standardizable nature of gravitationally lensed Type Ia supernovae (glSNe Ia) makes them an attractive target for time delay cosmography, since a source with known luminosity breaks the mass sheet degeneracy. It is known that microlensing by stars in the lensing galaxy can add significant stochastic uncertainty to the unlensed luminosity which is often much larger than the intrinsic scatter of the Ia population. In this work, we show how the temporal microlensing variations as the supernova disc expands can be used to improve the standardization of glSNe Ia. We find that SNe are standardizable if they do not cross caustics as they expand. We estimate that this will be the case for $\approx$6 doubly imaged systems and $\approx$0.3 quadruply imaged systems per year in LSST. At the end of the ten year LSST survey, these systems should enable us to test for systematics in $H_0$ due to the mass sheet degeneracy at the $1.00^{+0.07}_{-0.06}$\% level, or $1.8\pm0.2$\% if we can only extract time delays from the third of systems with counter images brighter than $i=24$ mag.

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Galaxy Zoo: Clump Scout -- Design and first application of a two-dimensional aggregation tool for citizen science

Galaxy Zoo: Clump Scout is a web-based citizen science project designed to identify and spatially locate giant star forming clumps in galaxies that were imaged by the Sloan Digital Sky Survey Legacy Survey. We present a statistically driven software framework that is designed to aggregate two-dimensional annotations of clump locations provided by multiple independent Galaxy Zoo: Clump Scout volunteers and generate a consensus label that identifies the locations of probable clumps within each galaxy. The statistical model our framework is based on allows us to assign false-positive probabilities to each of the clumps we identify, to estimate the skill levels of each of the volunteers who contribute to Galaxy Zoo: Clump Scout and also to quantitatively assess the reliability of the consensus labels that are derived for each subject. We apply our framework to a dataset containing 3,561,454 two-dimensional points, which constitute 1,739,259 annotations of 85,286 distinct subjects provided by 20,999 volunteers. Using this dataset, we identify 128,100 potential clumps distributed among 44,126 galaxies. This dataset can be used to study the prevalence and demographics of giant star forming clumps in low-redshift galaxies. The code for our aggregation software framework is publicly available at: https://github.com/ou-astrophysics/BoxAggregator

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Galaxy Zoo DECaLS: Detailed Visual Morphology Measurements from Volunteers and Deep Learning for 314,000 Galaxies

We present Galaxy Zoo DECaLS: detailed visual morphological classifications for Dark Energy Camera Legacy Survey images of galaxies within the SDSS DR8 footprint. Deeper DECaLS images (r=23.6 vs. r=22.2 from SDSS) reveal spiral arms, weak bars, and tidal features not previously visible in SDSS imaging. To best exploit the greater depth of DECaLS images, volunteers select from a new set of answers designed to improve our sensitivity to mergers and bars. Galaxy Zoo volunteers provide 7.5 million individual classifications over 314,000 galaxies. 140,000 galaxies receive at least 30 classifications, sufficient to accurately measure detailed morphology like bars, and the remainder receive approximately 5. All classifications are used to train an ensemble of Bayesian convolutional neural networks (a state-of-the-art deep learning method) to predict posteriors for the detailed morphology of all 314,000 galaxies. When measured against confident volunteer classifications, the networks are approximately 99% accurate on every question. Morphology is a fundamental feature of every galaxy; our human and machine classifications are an accurate and detailed resource for understanding how galaxies evolve.

astro-ph.GA

SkyPy: A package for modelling the Universe

SkyPy is an open-source Python package for simulating the astrophysical sky. It comprises a library of physical and empirical models across a range of observables and a command-line script to run end-to-end simulations. The library provides functions that sample realisations of sources and their associated properties from probability distributions. Simulation pipelines are constructed from these models using a YAML-based configuration syntax, while task scheduling and data dependencies are handled internally and the modular design allows users to interface with external software. SkyPy is developed and maintained by a diverse community of domain experts with a focus on software sustainability and interoperability. By fostering development, it provides a framework for correlated simulations of a range of cosmological probes including galaxy populations, large scale structure, the cosmic microwave background, supernovae and gravitational waves. Version 0.4 implements functions that model various properties of galaxies including luminosity functions, redshift distributions and optical photometry from spectral energy distribution templates. Future releases will provide additional modules, for example, to simulate populations of dark matter halos and model the galaxy-halo connection, making use of existing software packages from the astrophysics community where appropriate.

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Galaxy Zoo: 3D -- Crowd-sourced Bar, Spiral and Foreground Star Masks for MaNGA Target Galaxies

The challenge of consistent identification of internal structure in galaxies - in particular disc galaxy components like spiral arms, bars, and bulges - has hindered our ability to study the physical impact of such structure across large samples. In this paper we present Galaxy Zoo: 3D (GZ: 3D) a crowdsourcing project built on the Zooniverse platform which we used to create spatial pixel (spaxel) maps that identify galaxy centres, foreground stars, galactic bars and spiral arms for 29831 galaxies which were potential targets of the MaNGA survey (Mapping Nearby Galaxies at Apache Point Observatory, part of the fourth phase of the Sloan Digital Sky Surveys or SDSS-IV), including nearly all of the 10,010 galaxies ultimately observed. Our crowd-sourced visual identification of asymmetric, internal structures provides valuable insight on the evolutionary role of non-axisymmetric processes that is otherwise lost when MaNGA data cubes are azimuthally averaged. We present the publicly available GZ:3D catalog alongside validation tests and example use cases. These data may in the future provide a useful training set for automated identification of spiral arm features. As an illustration, we use the spiral masks in a sample of 825 galaxies to measure the enhancement of star formation spatially linked to spiral arms, which we measure to be a factor of three over the background disc, and how this enhancement increases with radius.

astro-ph.GA

Galaxy Zoo Builder: Morphological Dependence of Spiral Galaxy Pitch Angle

Spiral structure is ubiquitous in the Universe, and the pitch angle of arms in spiral galaxies provide an important observable in efforts to discriminate between different mechanisms of spiral arm formation and evolution. In this paper, we present a hierarchical Bayesian approach to galaxy pitch angle determination, using spiral arm data obtained through the Galaxy Builder citizen science project. We present a new approach to deal with the large variations in pitch angle between different arms in a single galaxy, which obtains full posterior distributions on parameters. We make use of our pitch angles to examine previously reported links between bulge and bar strength and pitch angle, finding no correlation in our data (with a caveat that we use observational proxies for both bulge size and bar strength which differ from other work). We test a recent model for spiral arm winding, which predicts uniformity of the cotangent of pitch angle between some unknown upper and lower limits, finding our observations are consistent with this model of transient and recurrent spiral pitch angle as long as the pitch angle at which most winding spirals dissipate or disappear is larger than 10 degrees.

astro-ph.GA

Galaxy Zoo Builder: Four Component Photometric decomposition of Spiral Galaxies Guided by Citizen Science

Multi-component modelling of galaxies is a valuable tool in the effort to quantitatively understand galaxy evolution, yet the use of the technique is plagued by issues of convergence, model selection and parameter degeneracies. These issues limit its application over large samples to the simplest models, with complex models being applied only to very small samples. We attempt to resolve this dilemma of "quantity or quality" by developing a novel framework, built inside the Zooniverse citizen science platform, to enable the crowdsourcing of model creation for Sloan Digitial Sky Survey galaxies. We have applied the method, including a final algorithmic optimisation step, on a test sample of 198 galaxies, and examine the robustness of this new method. We also compare it to automated fitting pipelines, demonstrating that it is possible to consistently recover accurate models that either show good agreement with, or improve on, prior work. We conclude that citizen science is a promising technique for modelling images of complex galaxies, and release our catalogue of models.

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SDSS-IV MaNGA: Stellar Population Gradients Within Barred Galaxies

Bars in galaxies are thought to stimulate both inflow of material and radial mixing along them. Observational evidence for this mixing has been inconclusive so far however, limiting the evaluation of the impact of bars on galaxy evolution. We now use results from the MaNGA integral field spectroscopic survey to characterise radial stellar age and metallicity gradients along the bar and outside the bar in 128 strongly barred galaxies. We find that age and metallicity gradients are flatter in the barred regions of almost all barred galaxies when compared to corresponding disk regions at the same radii. Our results re-emphasize the key fact that by azimuthally averaging integral field spectroscopic data one loses important information from non-axisymmetric galaxy components such as bars and spiral arms. We interpret our results as observational evidence that bars are radially mixing material in galaxies of all stellar masses, and for all bar morphologies and evolutionary stages.

astro-ph.GA

A direct test of density wave theory in a grand-design spiral galaxy

The exact nature of the arms of spiral galaxies is still an open question. It has been widely assumed that spiral arms in galaxies with two distinct symmetrical arms are the products of density waves that propagate around the disk, with the spiral arms being visibly enhanced by the star formation that is triggered as the passing wave compresses gas in the galaxy disk. Such a persistent wave would propagate with an approximately constant angular speed, its pattern speed Op. The quasi-stationary density wave theory can be tested by measuring this quantity and showing that it does not vary with radius in the galaxy. Unfortunately, this measurement is difficult because Op is only indirectly connected to observables such as the stellar rotation speed. Here, we use the detailed information on stellar populations of the grand-design spiral galaxy UGC 3825, extracted from spectral mapping, to measure the offset between young stars of a known age and the spiral arm in which they formed, allowing the first direct measure of Op at a range of radii. The offset in this galaxy is found to be as expected for a pattern speed that varies little with radius, indicating consistency with a quasi-stationary density wave, and lending credence to this new method.

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The Astropy Problem

The Astropy Project (http://astropy.org) is, in its own words, "a community effort to develop a single core package for Astronomy in Python and foster interoperability between Python astronomy packages." For five years this project has been managed, written, and operated as a grassroots, self-organized, almost entirely volunteer effort while the software is used by the majority of the astronomical community. Despite this, the project has always been and remains to this day effectively unfunded. Further, contributors receive little or no formal recognition for creating and supporting what is now critical software. This paper explores the problem in detail, outlines possible solutions to correct this, and presents a few suggestions on how to address the sustainability of general purpose astronomical software.

astro-ph.IM

Galaxy Zoo: Quantitative Visual Morphological Classifications for 48,000 galaxies from CANDELS

We present quantified visual morphologies of approximately 48,000 galaxies observed in three Hubble Space Telescope legacy fields by the Cosmic And Near-infrared Deep Extragalactic Legacy Survey (CANDELS) and classified by participants in the Galaxy Zoo project. 90% of galaxies have z < 3 and are observed in rest-frame optical wavelengths by CANDELS. Each galaxy received an average of 40 independent classifications, which we combine into detailed morphological information on galaxy features such as clumpiness, bar instabilities, spiral structure, and merger and tidal signatures. We apply a consensus-based classifier weighting method that preserves classifier independence while effectively down-weighting significantly outlying classifications. After analysing the effect of varying image depth on reported classifications, we also provide depth-corrected classifications which both preserve the information in the deepest observations and also enable the use of classifications at comparable depths across the full survey. Comparing the Galaxy Zoo classifications to previous classifications of the same galaxies shows very good agreement; for some applications the high number of independent classifications provided by Galaxy Zoo provides an advantage in selecting galaxies with a particular morphological profile, while in others the combination of Galaxy Zoo with other classifications is a more promising approach than using any one method alone. We combine the Galaxy Zoo classifications of "smooth" galaxies with parametric morphologies to select a sample of featureless disks at 1 < z < 3, which may represent a dynamically warmer progenitor population to the settled disk galaxies seen at later epochs.

astro-ph.GA

Re-examining Larson's Scaling Relationships in Galactic Molecular Clouds

The properties of Galactic molecular clouds tabulated by Solomon etal (1987) (SRBY) are re-examined using the Boston University-FCRAO Galactic Ring Survey of 13CO J=1-0 emission. These new data provide a lower opacity tracer of molecular clouds and improved angular and spectral resolution than previous surveys of molecular line emission along the Galactic Plane. We calculate GMC masses within the SRBY cloud boundaries assuming LTE conditions throughout the cloud and a constant H2 to 13CO abundance, while accounting for the variation of the 12C/13C with Galacto-centric radius. The LTE derived masses are typically five times smaller than the SRBY virial masses. The corresponding median mass surface density of molecular hydrogen for this sample is 42 Msun/pc^2, which is significantly lower than the value derived by SRBY (median 206 Msun/pc^2) that has been widely adopted by most models of cloud evolution and star formation. This discrepancy arises from both the extrapolation by SRBY of velocity dispersion, size, and CO luminosity to the 1K antenna temperature isophote that likely overestimates the GMC masses and our assumption of constant 13CO abundance over the projected area of each cloud. Owing to the uncertainty of molecular abundances in the envelopes of clouds, the mass surface density of giant molecular clouds could be larger than the values derived from our 13CO measurements. From velocity dispersions derived from the 13CO data, we find that the coefficient of the cloud structure functions, vo=sigma_v/R^{1/2}, is not constant, as required to satisfy Larson's scaling relationships, but rather systematically varies with the surface density of the cloud as Sigma^{0.5} as expected for clouds in self-gravitational equlibrium.

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