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Colin T. Slater

Publications and source records attributed to Colin T. Slater.

At least 19 recordsLinked to original sources

A Deep Look at the Ultra-Faint Milky Way Satellite Virgo III with Rubin Observatory Data Preview 2

We analyze the ultra-faint Milky Way satellite Virgo III using data from the Vera C. Rubin Observatory Data Preview 2 (DP2). Virgo III was observed in the Rubin "Cosmic Treasure Chest" (M49) First Look field, which contains 924 visits in the u,g,r,i bands comprising ~10.5hrs of exposure time with LSSTCam. These data are considerably deeper than the majority of DP2, with a $5σ$ limiting magnitude that approaches the expected 10-year depth of LSST (~25.2-26.5mag, depending on band). We report the morphological and stellar population parameters of Virgo III measured with the maximum-likelihood-based package ugali. The depth of the Rubin imaging yields more than a factor of four increase in the number of candidate member stars ($N_* = 114^{+11}_{-11}$) relative to the Virgo III discovery results ($N_* = 25^{+5}_{-4}$), enabling significantly more precise morphological constraints. Our best-fit parameters broadly agree with previous measurements, further confirming that Virgo III has properties that are consistent with an ultra-faint dwarf galaxy ($M_V = -2.72^{+0.49}_{-0.70}$; $r_{1/2} = 53^{+10}_{-8}$) located at a heliocentric distance of $D_\odot = 151^{+8}_{-8}$. We also demonstrate that the depth and photometric quality of the DP2 data are sufficient to separate metal-poor and metal-rich stars in color-color space. We further present period estimates for the three known RR Lyrae member stars derived from the DP2 forced photometry; we use theoretical Period-Luminosity-Metallicity (PLZ) and Period-Wesenheit-Metallicity (PWZ) relations to obtain independent distance estimates. We find that our period and distance estimates are broadly consistent with previous measurements for these RR Lyrae. These results demonstrate the power of LSST data for the discovery and characterization of ultra-faint dwarf galaxies and motivate future searches for new satellites across the southern sky.

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The Star Formation History and Evolution of the Ultra-Diffuse M81 Satellite F8D1

We present deep HST imaging of one of the nearest ultra-diffuse galaxies (UDGs) outside of the Local Group: F8D1, a satellite of M81 known to be tidally disrupting. UDGs are an enigmatic and diverse population, with evolutionary pathways ranging from tidal processing to bursty feedback and high initial angular momentum. To determine F8D1's evolutionary drivers, we resolve stars in F8D1's central $\sim$1 kpc and in a parallel field $\sim$6 kpc along its major axis to deep photometric limits, reaching below the Red Clump. We also image eight shallower fields along F8D1's major and minor axes. We calculate the star formation history (SFH) in the two deep fields, finding that while currently quiescent, both regions experienced a substantial burst $\sim$2 Gyr ago and a smaller burst $\sim$500 Myr ago, which likely formed F8D1's nuclear star cluster. In the shallow fields, using the ratio of evolved Asymptotic Giant Branch and Red Giant Branch stars out to $\sim$13 kpc along F8D1's known stellar stream, we confirm that F8D1 was globally star-forming until at least $\sim$2 Gyr ago. We estimate a total progenitor stellar mass, including the stream, of $\sim$1.3$\times$10$^8 M_{\odot}$, with an average [M/H] $\sim$ $-$0.8. We compare F8D1's properties to those of Local Group galaxies with similar initial stellar mass. We find that F8D1 is consistent with a progenitor star-forming galaxy similar to NGC 6822 that is in the midst of a transition to a Sagittarius-like system. Notably, this evolutionary sequence can be accomplished through tidal processing alone in galaxies that have experienced sufficiently bursty feedback to have created cored profiles.

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47 Tuc in Rubin Data Preview 1: Exploring Early LSST Data and Science Potential

We present analyses of the early data from Rubin Observatory's Data Preview 1 (DP1) for the globular cluster 47 Tuc field. The DP1 dataset for 47 Tuc includes four nights of observations from the Rubin Commissioning Camera (LSSTComCam), covering multiple bands ($ugriy$). We address challenges of crowding in the inner region of the cluster and toward the SMC in DP1, and demonstrate improved star-galaxy separation by fitting fifth-degree polynomials to the stellar loci in color-color diagrams and applying multi-dimensional sigma clipping. We compile a catalog of 3,576 probable 47 Tuc member stars selected via a combination of isochrone, Gaia proper-motion, and color-color space matched filtering. We explore the sources of photometric scatter in the 47 Tuc color-color sequence, evaluating contributions from various potential sources, including differential extinction within the cluster. Finally, of the 72 well-characterized variables in the field, we recover five known variable stars, including three RR Lyrae and two eclipsing binaries, in the coadd-based object catalog, and identify 62 in the difference image-based object catalog. Although the DP1 lightcurves have sparse temporal sampling, they appear to follow the patterns of densely-sampled literature lightcurves well. Despite some data limitations for crowded-field stellar analysis, DP1 demonstrates the promising scientific potential for future LSST data releases.

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A Timeline of the M81 Group: Properties of the Extended Structures of M82 and NGC 3077

Mergers of and interactions between galaxies imprint a wide diversity of morphological, dynamical, and chemical characteristics in stellar halos and tidal streams. Measuring these characteristics elucidates aspects of the progenitors of the galaxies we observe today. The M81 group is the perfect galaxy group to understand the past, present, and future of a group of galaxies in the process of merging. Here we measure the end of star formation (t$_{90}$) and metallicity ([M/H]) of the stellar halo of M82 and the eastern tidal stream of NGC 3077 to: 1) test the idea that M82 possesses a genuine stellar halo, formed before any interaction with M81, 2) determine if NGC 3077's tidal disruption is related to the star formation history in its tails, and 3) create a timeline of the assembly history of the central trio in the M81 group. We argue that M82 possesses a genuine, metal poor ([M/H] ~ -1.62 dex) stellar halo, formed from the merger of a small satellite galaxy roughly 6.6 Gyr ago. We also find that the stars present in NGC 3077's tails formed before tidal disruption with M81, and possesses a roughly uniform metallicity as shown in Okamoto et. al. 2023 implying that NGC 3077's progenitor had significant population gradients. Finally, we present a timeline of the central trio's merger/interaction history.

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Origins of the Evil Eye: M64's Stellar Halo Reveals the Recent Accretion of an SMC-mass Satellite

M64, often called the "Evil Eye" galaxy, is unique among local galaxies. Beyond its dramatic, dusty nucleus, it also hosts an outer gas disk that counter-rotates relative to its stars. The mass of this outer disk is comparable to the gas content of the Small Magellanic Cloud (SMC), prompting the idea that it was likely accreted in a recent minor merger. Yet, detailed follow-up studies of M64's outer disk have shown no evidence of such an event, leading to other interpretations, such as a "flyby" interaction with the distant diffuse satellite Coma P. We present Subaru Hyper Suprime-Cam observations of M64's stellar halo, which resolve its stellar populations and reveal a spectacular radial shell feature, oriented $\sim$30$^{\circ}$ relative to the major axis and along the rotation axis of the outer gas disk. The shell is $\sim$45 kpc southeast of M64, while a similar but more diffuse plume to the northwest extends to $>$100 kpc. We estimate a stellar mass and metallicity for the southern shell of $M_{\star} {=} 1.80~{\pm}~0.54{\times}10^8~M_{\odot}$ and [M/H] $=$ $-$1.0, respectively, and a similar mass of $1.42~{\pm}~0.71{\times}10^8 M_{\odot}$ for the northern plume. Taking into account the accreted material in M64's inner disk, we estimate a total stellar mass for the progenitor satellite of $M_{\rm \star,prog}~{\simeq}~5{\times}10^8~M_{\odot}$. These results suggest that M64 is in the final stages of a minor merger with a gas-rich satellite strikingly similar to the SMC, in which M64's accreted counter-rotating gas originated, and which is responsible for the formation of its dusty inner star-forming disk.

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Ultrafaint Dwarf Galaxy Candidates in the M81 Group: Signatures of Group Accretion

The faint and ultrafaint dwarf galaxies in the Local Group form the observational bedrock upon which our understanding of small-scale cosmology rests. In order to understand whether this insight generalizes, it is imperative to use resolved-star techniques to discover similarly faint satellites in nearby galaxy groups. We describe our search for ultrafaint galaxies in the M81 group using deep ground-based resolved-star data sets from Subaru's Hyper Suprime-Cam. We present one new ultrafaint dwarf galaxy in the M81 group and identify five additional extremely low surface brightness candidate ultrafaint dwarfs that reach deep into the ultrafaint regime to $M_V \sim -6$ (similar to current limits for Andromeda satellites). These candidates' luminosities and sizes are similar to known Local Group dwarf galaxies Tucana B, Canes Venatici I, Hercules, and Boötes I. Most of these candidates are likely to be real, based on tests of our techniques on blank fields. Intriguingly, all of these candidates are spatially clustered around NGC 3077, which is itself an M81 group satellite in an advanced state of tidal disruption. This is somewhat surprising, as M81 itself and its largest satellite M82 are both substantially more massive than NGC 3077 and by virtue of their greater masses, would have been expected to host as many or more ultrafaint candidates. These results lend considerable support to the idea that satellites of satellites are an important contribution to the growth of satellite populations around Milky Way-mass galaxies.

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Faro: A framework for measuring the scientific performance of petascale Rubin Observatory data products

The Vera C. Rubin Observatory will advance many areas of astronomy over the next decade with its unique wide-fast-deep multi-color imaging survey, the Legacy Survey of Space and Time (LSST). The LSST will produce approximately 20TB of raw data per night, which will be automatically processed by the LSST Science Pipelines to generate science-ready data products -- processed images, catalogs and alerts. To ensure that these data products enable transformative science with LSST, stringent requirements have been placed on their quality and scientific fidelity, for example on image quality and depth, astrometric and photometric performance, and object recovery completeness. In this paper we introduce faro, a framework for automatically and efficiently computing scientific performance metrics on the LSST data products for units of data of varying granularity, ranging from single-detector to full-survey summary statistics. By measuring and monitoring metrics, we are able to evaluate trends in algorithmic performance and conduct regression testing during development, compare the performance of one algorithm against another, and verify that the LSST data products will meet performance requirements by comparing to specifications. We present initial results using faro to characterize the performance of the data products produced on simulated and precursor data sets, and discuss plans to use faro to verify the performance of the LSST commissioning data products.

astro-ph.IM

The Astronomy Commons Platform: A Deployable Cloud-Based Analysis Platform for Astronomy

We present a scalable, cloud-based science platform solution designed to enable next-to-the-data analyses of terabyte-scale astronomical tabular datasets. The presented platform is built on Amazon Web Services (over Kubernetes and S3 abstraction layers), utilizes Apache Spark and the Astronomy eXtensions for Spark for parallel data analysis and manipulation, and provides the familiar JupyterHub web-accessible front-end for user access. We outline the architecture of the analysis platform, provide implementation details, rationale for (and against) technology choices, verify scalability through strong and weak scaling tests, and demonstrate usability through an example science analysis of data from the Zwicky Transient Facility's 1Bn+ light-curve catalog. Furthermore, we show how this system enables an end-user to iteratively build analyses (in Python) that transparently scale processing with no need for end-user interaction. The system is designed to be deployable by astronomers with moderate cloud engineering knowledge, or (ideally) IT groups. Over the past three years, it has been utilized to build science platforms for the DiRAC Institute, the ZTF partnership, the LSST Solar System Science Collaboration, the LSST Interdisciplinary Network for Collaboration and Computing, as well as for numerous short-term events (with over 100 simultaneous users). A live demo instance, the deployment scripts, source code, and cost calculators are accessible at http://hub.astronomycommons.org/.

astro-ph.IM

New Globular Cluster Candidates in the M81 group

The study of outer halo globular cluster (GC) populations can give insight into galaxy merging, globular cluster accretion and the origin of GCs. We use archival Subaru Hyper Suprime-Cam (HSC) data in concert with space-based GALEX, IRAC and Gaia EDR3 data to select candidate Globular clusters (GCs) in the outer halo of the M81 group for confirmation and future study. We use a small sample of previously-discovered GCs to tune our selection criteria, finding that bright already-known GCs in the M81 group have sizes that are typically slightly larger than the Subaru PSF in our fields. In the optical bands, GCs appear to have colours that are only slightly different from stars. The inclusion of archival IRAC data yields dramatic improvements in colour separation, as the long wavelength baseline aids somewhat in the separation from stars and clearly separates GCs from many compact background galaxies. We show that some previously spectroscopically-identified GCs in the M81 group are instead foreground stars or background galaxies. GCs close to M82 have radial velocities suggesting that they fell into the M81 group along with M82. The overall M81 GC luminosity function is similar to the Milky Way and M31. M81's outer halo GCs are similar to the Milky Way in their metallicities and numbers, and much less numerous than M31's more metal-rich outer halo GC population. These properties reflect differences in the three galaxies' merger histories, highlighting the possibility of using outer halo GCs to trace merger history in larger samples of galaxies.

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Optimization of the Observing Cadence for the Rubin Observatory Legacy Survey of Space and Time: a pioneering process of community-focused experimental design

Vera C. Rubin Observatory is a ground-based astronomical facility under construction, a joint project of the National Science Foundation and the U.S. Department of Energy, designed to conduct a multi-purpose 10-year optical survey of the southern hemisphere sky: the Legacy Survey of Space and Time. Significant flexibility in survey strategy remains within the constraints imposed by the core science goals of probing dark energy and dark matter, cataloging the Solar System, exploring the transient optical sky, and mapping the Milky Way. The survey's massive data throughput will be transformational for many other astrophysics domains and Rubin's data access policy sets the stage for a huge potential users' community. To ensure that the survey science potential is maximized while serving as broad a community as possible, Rubin Observatory has involved the scientific community at large in the process of setting and refining the details of the observing strategy. The motivation, history, and decision-making process of this strategy optimization are detailed in this paper, giving context to the science-driven proposals and recommendations for the survey strategy included in this Focus Issue.

astro-ph.IM

Checkpoint, Restore, and Live Migration for Science Platforms

We demonstrate a fully functional implementation of (per-user) checkpoint, restore, and live migration capabilities for JupyterHub platforms. Checkpointing -- the ability to freeze and suspend to disk the running state (contents of memory, registers, open files, etc.) of a set of processes -- enables the system to snapshot a user's Jupyter session to permanent storage. The restore functionality brings a checkpointed session back to a running state, to continue where it left off at a later time and potentially on a different machine. Finally, live migration enables moving running Jupyter notebook servers between different machines, transparent to the analysis code and w/o disconnecting the user. Our implementation of these capabilities works at the system level, with few limitations, and typical checkpoint/restore times of O(10s) with a pathway to O(1s) live migrations. It opens a myriad of interesting use cases, especially for cloud-based deployments: from checkpointing idle sessions w/o interruption of the user's work (achieving cost reductions of 4x or more), execution on spot instances w. transparent migration on eviction (with additional cost reductions up to 3x), to automated migration of workloads to ideally suited instances (e.g. moving an analysis to a machine with more or less RAM or cores based on observed resource utilization). The capabilities we demonstrate can make science platforms fully elastic while retaining excellent user experience.

astro-ph.IM

The Saga of M81: Global View of a Massive Stellar Halo in Formation

Recent work has shown that Milky Way-mass galaxies display an incredible range of stellar halo properties, yet the origin of this diversity is unclear. The nearby galaxy M81 $-$ currently interacting with M82 and NGC 3077 $-$ sheds unique light on this problem. We present a Subaru Hyper Suprime-Cam survey of the resolved stellar populations around M81, revealing M81's stellar halo in never-before-seen detail. We resolve the halo to unprecedented $V$-band equivalent surface brightnesses of 33 mag arcsec$^{-2}$, and produce the first-ever global stellar mass density map for a Milky Way-mass stellar halo outside of the Local Group. Using the minor axis, we confirm M81's halo as one of the lowest mass and metal-poorest known ($M_{\star} \simeq 1.16{\times}10^9 M_{\odot}$, [Fe/H] $\simeq {-}1.2$) $-$ indicating a relatively quiet prior accretion history. Yet, our global halo census finds that tidally unbound material from M82 and NGC 3077 provides a substantial infusion of metal-rich material ($M_{\star} \simeq 5.4{\times}10^8$ $M_{\odot}$, [Fe/H] $\simeq {-}$0.9). We further show that, following the accretion of its massive satellite M82 (and the LMC-like NGC 3077), M81 will host one of the most massive and metal-rich stellar halos in the nearby universe. Thus, the saga of M81: following a passive history, M81's merger with M82 will completely transform its halo from a low-mass, anemic halo rivaling the MW, to a metal-rich behemoth rivaled only by systems such as M31. This dramatic transformation indicates that the observed diversity in stellar halo properties is primarily driven by diversity in the largest mergers these galaxies have experienced.

astro-ph.GA

Morphological Star-Galaxy Separation

We discuss the statistical foundations of morphological star-galaxy separation. We show that many of the star-galaxy separation metrics in common use today (e.g. by SDSS or SExtractor) are closely related both to each other, and to the model odds ratio derived in a Bayesian framework by Sebok (1979). While the scaling of these algorithms with the noise properties of the sources varies, these differences do not strongly differentiate their performance. We construct a model of the performance of a star-galaxy separator in a realistic survey to understand the impact of observational signal-to-noise ratio (or equivalently, 5-sigma limiting depth) and seeing on classification performance. The model quantitatively demonstrates that, assuming realistic densities and angular sizes of stars and galaxies, 10% worse seeing can be compensated for by approximately 0.4 magnitudes deeper data to achieve the same star-galaxy classification performance. We discuss how to probabilistically combine multiple measurements, either of the same type (e.g., subsequent exposures), or differing types (e.g., multiple bandpasses), or differing methodologies (e.g., morphological and color-based classification). These methods are increasingly important for observations at faint magnitudes, where the rapidly rising number density of small galaxies makes star-galaxy classification a challenging problem. However, because of the significant role that the signal-to-noise ratio plays in resolving small galaxies, surveys with large-aperture telescopes, such as LSST, will continue to see improving star-galaxy separation as they push to these fainter magnitudes.

astro-ph.IM

AXS: A framework for fast astronomical data processing based on Apache Spark

We introduce AXS (Astronomy eXtensions for Spark), a scalable open-source astronomical data analysis framework built on Apache Spark, a widely used industry-standard engine for big data processing. Building on capabilities present in Spark, AXS aims to enable querying and analyzing almost arbitrarily large astronomical catalogs using familiar Python/AstroPy concepts, DataFrame APIs, and SQL statements. We achieve this by i) adding support to Spark for efficient on-line positional cross-matching and ii) supplying a Python library supporting commonly-used operations for astronomical data analysis. To support scalable cross-matching, we developed a variant of the ZONES algorithm (Gray et al. 2004) capable of operating in distributed, shared-nothing architecture. We couple this to a data partitioning scheme that enables fast catalog cross-matching and handles the data skew often present in deep all-sky data sets. The cross-match and other often-used functionalities are exposed to the end users through an easy-to-use Python API. We demonstrate AXS' technical and scientific performance on SDSS, ZTF, Gaia DR2, and AllWise catalogs. Using AXS we were able to perform on-the-fly cross-match of Gaia DR2 (1.8 billion rows) and AllWise (900 million rows) data sets in ~ 30 seconds. We discuss how cloud-ready distributed systems like AXS provide a natural way to enable comprehensive end-user analyses of large datasets such as LSST.

astro-ph.IM

An Overview of the LSST Image Processing Pipelines

The Large Synoptic Survey Telescope (LSST) is an ambitious astronomical survey with a similarly ambitious Data Management component. Data Management for LSST includes processing on both nightly and yearly cadences to generate transient alerts, deep catalogs of the static sky, and forced photometry light-curves for billions of objects at hundreds of epochs, spanning at least a decade. The algorithms running in these pipelines are individually sophisticated and interact in subtle ways. This paper provides an overview of those pipelines, focusing more on those interactions than the details of any individual algorithm.

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A Lonely Giant: The Sparse Satellite Population of M94 Challenges Galaxy Formation

The dwarf satellites of `giant' Milky Way (MW)-mass galaxies are our primary probes of low-mass dark matter halos. The number and velocities of the satellite galaxies of the MW and M31 initially puzzled galaxy formation theorists, but are now reproduced well by many models. Yet, are the MW's and M31's satellites representative? Were galaxy formation models `overfit'? These questions motivate deep searches for satellite galaxies outside the Local Group. We present a deep survey of the `classical' satellites ($M_{\star}$$\geqslant$4$\times$10$^5 M_{\odot}$) of the MW-mass galaxy M94 out to 150 kpc projected distance. We find $only\ two$ satellites, each with $M_{\star}{\sim}10^6 M_{\odot}$, compared with 6-12 such satellites in the four other MW-mass systems with comparable data (MW, M31, M81, M101). Using a `standard' prescription for occupying dark matter halos (taken from the fully hydrodynamical EAGLE simulation) with galaxies, we find that such a sparse satellite population occurs in $<$0.2% of MW-mass systems $-$ a $<$1% probability among a sample of five (known systems + M94). In order to produce an M94-like system more frequently we make satellite galaxy formation much more stochastic than is currently predicted by dramatically increasing the slope and scatter of the stellar mass-halo mass (SMHM) relation. Surprisingly, the SMHM relation must be altered even for halos masses up to 10$^{11}M_{\odot} -$ significantly above the mass scales predicted to have increased scatter from current hydrodynamical models. The sparse satellite population of this `lonely giant' thus advocates for an important modification to ideas of how the satellites around MW-mass galaxies form.

astro-ph.GA

APO Time Resolved Color Photometry of Highly-Elongated Interstellar Object 1I/'Oumuamua

We report on $g$, $r$ and $i$ band observations of the Interstellar Object 'Oumuamua (1I) taken on 2017 October 29 from 04:28 to 08:40 UTC by the Apache Point Observatory (APO) 3.5m telescope's ARCTIC camera. We find that 1I's colors are $g-r=0.41\pm0.24$ and $r-i=0.23\pm0.25$, consistent with the visible spectra of Masiero (2017), Ye et al. (2017) and Fitzsimmons et al. (2017), and most comparable to the population of Solar System C/D asteroids, Trojans, or comets. We find no evidence of any cometary activity at a heliocentric distance of 1.46 au, approximately 1.5 months after 1I's closest approach distance to the Sun. Significant brightness variability was seen in the $r$ observations, with the object becoming notably brighter towards the end of the run. By combining our APO photometric time series data with the Discovery Channel Telescope (DCT) data of Knight et al. (2017), taken 20 h later on 2017 October 30, we construct an almost complete light curve with a most probable lightcurve period of $P \simeq 4~{\rm h}$. Our results imply a double peaked rotation period of 8.1 $\pm$ 0.02 h, with a peak-to-peak amplitude of 1.5 - 2.1 mags. Assuming that 1I's shape can be approximated by an ellipsoid, the amplitude constraint implies that 1I has an axial ratio of 3.5 to 10.3, which is strikingly elongated. Assuming that 1I is rotating above its critical break up limit, our results are compatible with 1I having having modest cohesive strength and may have obtained its elongated shape during a tidal disruption event before being ejected from its home system. Astrometry useful for constraining 1I's orbit was also obtained and published in Weaver et al. (2017).

astro-ph.EP

The Large Synoptic Survey Telescope as a Near-Earth Object Discovery Machine

Using the most recent prototypes, design, and as-built system information, we test and quantify the capability of the Large Synoptic Survey Telescope (LSST) to discover Potentially Hazardous Asteroids (PHAs) and Near-Earth Objects (NEOs). We empirically estimate an expected upper limit to the false detection rate in LSST image differencing, using measurements on DECam data and prototype LSST software and find it to be about $450$~deg$^{-2}$. We show that this rate is already tractable with current prototype of the LSST Moving Object Processing System (MOPS) by processing a 30-day simulation consistent with measured false detection rates. We proceed to evaluate the performance of the LSST baseline survey strategy for PHAs and NEOs using a high-fidelity simulated survey pointing history. We find that LSST alone, using its baseline survey strategy, will detect $66\%$ of the PHA and $61\%$ of the NEO population objects brighter than $H=22$, with the uncertainty in the estimate of $\pm5$ percentage points. By generating and examining variations on the baseline survey strategy, we show it is possible to further improve the discovery yields. In particular, we find that extending the LSST survey by two additional years and doubling the MOPS search window increases the completeness for PHAs to $86\%$ (including those discovered by contemporaneous surveys) without jeopardizing other LSST science goals ($77\%$ for NEOs). This equates to reducing the undiscovered population of PHAs by additional $26\%$ ($15\%$ for NEOs), relative to the baseline survey.

astro-ph.EP