arXiv subjects

Brooke Simmons

Publications and source records attributed to Brooke Simmons.

At least 19 recordsLinked to original sources

arXiv2026

Brightness, Colour, Polarisation: A Multi-Instrument Observation Campaign of the Gorizont-6 Satellite

We present a coordinated multi-instrument photometric and polarimetric study of the defunct geosynchronous satellite, Gorizont-6. This observation campaign combined wide-field multi-colour observations with simultaneous multi-site photometry and linear polarimetry. Our results demonstrate that the combined simultaneous colour and polarimetric measurements aid in breaking the degeneracy between the fundamental spin period and its harmonics, enabling light curve features to be associated with specific reflecting surfaces. Using phase-dispersion minimisation with bootstrap resampling, we then measure a steadily increasing rotation period across six epochs spanning nine months, well described by a damped exponential curve consistent with Yarkovsky O'Keefe Radzievskii Paddack (YORP) driven spin-down. A geometrical analysis of the multi-site observations provides additional constraints on the spin-axis orientation based on paired glint events. Overall, multi-colour photometry yields efficient, robust period measurements compared with single-band data, while polarimetry supplies the decisive constraints needed for unambiguous rotation-state determination, highlighting the value of combined photometric-polarimetric strategies for characterising defunct satellites.

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arXiv2026

Spatio-Spectroscopic Representation Learning using Unsupervised Convolutional Long-Short Term Memory Networks

Integral Field Spectroscopy (IFS) surveys offer a unique new landscape in which to learn in both spatial and spectroscopic dimensions and could help uncover previously unknown insights into galaxy evolution. In this work, we demonstrate a new unsupervised deep learning framework using Convolutional Long-Short Term Memory Network Autoencoders to encode generalized feature representations across both spatial and spectroscopic dimensions spanning $19$ optical emission lines (3800A $< \lambda <$ 8000A) among a sample of $\sim 9000$ galaxies from the MaNGA IFS survey. As a demonstrative exercise, we assess our model on a sample of $290$ Active Galactic Nuclei (AGN) and highlight scientifically interesting characteristics of some highly anomalous AGN.

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arXiv2025

Galaxy Zoo Evo: 1 million human-annotated images of galaxies

We introduce Galaxy Zoo Evo, a labeled dataset for building and evaluating foundation models on images of galaxies. GZ Evo includes 104M crowdsourced labels for 823k images from four telescopes. Each image is labeled with a series of fine-grained questions and answers (e.g. "featured galaxy, two spiral arms, tightly wound, merging with another galaxy"). These detailed labels are useful for pretraining or finetuning. We also include four smaller sets of labels (167k galaxies in total) for downstream tasks of specific interest to astronomers, including finding strong lenses and describing galaxies from the new space telescope Euclid. We hope GZ Evo will serve as a real-world benchmark for computer vision topics such as domain adaption (from terrestrial to astronomical, or between telescopes) or learning under uncertainty from crowdsourced labels. We also hope it will support a new generation of foundation models for astronomy; such models will be critical to future astronomers seeking to better understand our universe.

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arXiv2024

Galaxy Zoo: Morphologies based on UKIDSS NIR Imaging for 71,052 Galaxies

We present morphological classifications based on Galaxy Zoo analysis of 71,052 galaxies with imaging from the United Kingdom Infrared Telescope Infrared Deep Sky Survey (UKIDSS). Galaxies were selected out of the Galaxy Zoo 2 (GZ2) sample, so also have gri imaging from the Sloan Digital Sky Survey. An identical classification tree, and vote weighting/aggregation was applied to both UKIDSS and GZ2 classifications enabling direct comparisons. With this Research Note we provide a public release of the GZ:UKIDSS morphologies and discuss some initial comparisons with GZ2.

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arXiv2024

Transfer learning for galaxy feature detection: Finding Giant Star-forming Clumps in low redshift galaxies using Faster R-CNN

Giant Star-forming Clumps (GSFCs) are areas of intensive star-formation that are commonly observed in high-redshift (z>1) galaxies but their formation and role in galaxy evolution remain unclear. High-resolution observations of low-redshift clumpy galaxy analogues are rare and restricted to a limited set of galaxies but the increasing availability of wide-field galaxy survey data makes the detection of large clumpy galaxy samples increasingly feasible. Deep Learning, and in particular CNNs, have been successfully applied to image classification tasks in astrophysical data analysis. However, one application of DL that remains relatively unexplored is that of automatically identifying and localising specific objects or features in astrophysical imaging data. In this paper we demonstrate the feasibility of using Deep learning-based object detection models to localise GSFCs in astrophysical imaging data. We apply the Faster R-CNN object detection framework (FRCNN) to identify GSFCs in low redshift (z<0.3) galaxies. Unlike other studies, we train different FRCNN models not on simulated images with known labels but on real observational data that was collected by the Sloan Digital Sky Survey Legacy Survey and labelled by volunteers from the citizen science project `Galaxy Zoo: Clump Scout'. The FRCNN model relies on a CNN component as a `backbone' feature extractor. We show that CNNs, that have been pre-trained for image classification using astrophysical images, outperform those that have been pre-trained on terrestrial images. In particular, we compare a domain-specific CNN -`Zoobot' - with a generic classification backbone and find that Zoobot achieves higher detection performance and also requires smaller training data sets to do so. Our final model is capable of producing GSFC detections with a completeness and purity of >=0.8 while only being trained on ~5,000 galaxy images.

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arXiv2023

Galaxy Zoo DESI: Detailed Morphology Measurements for 8.7M Galaxies in the DESI Legacy Imaging Surveys

We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer votes. Our models typically predict the fraction of volunteers selecting each answer to within 5-10\% for every answer to every GZ question. The models are trained on newly-collected votes for DESI-LS DR8 images as well as historical votes from GZ DECaLS. We also release the newly-collected votes. Extending our morphology measurements outside of the previously-released DECaLS/SDSS intersection increases our sky coverage by a factor of 4 (5,000 to 19,000 deg$^2$) and allows for full overlap with complementary surveys including ALFALFA and MaNGA.

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arXiv2023

Noise reduction on single-shot images using an autoencoder

We present an application of autoencoders to the problem of noise reduction in single-shot astronomical images and explore its suitability for upcoming large-scale surveys. Autoencoders are a machine learning model that summarises an input to identify its key features, then from this knowledge predicts a representation of a different input. The broad aim of our autoencoder model is to retain morphological information (e.g., non-parametric morphological information) from the survey data whilst simultaneously reducing the noise contained in the image. We implement an autoencoder with convolutional and maxpooling layers. We test our implementation on images from the Panoramic Survey Telescope and Rapid Response System (Pan-STARRS) that contain varying levels of noise and report how successful our autoencoder is by considering Mean Squared Error (MSE), Structural Similarity Index (SSIM), the second-order moment of the brightest 20 percent of the galaxy's flux M20, and the Gini coefficient, whilst noting how the results vary between the original images, stacked images, and noise reduced images. We show that we are able to reduce noice, over many different targets of observations, whilst retaining the galaxy's morphology, with metric evaluation on a target by target analysis. We establish that this process manages to achieve a positive result in a matter of minutes, and by only using one single shot image compared to multiple survey images found in other noise reduction techniques.

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arXiv2023

Galaxy Zoo: Kinematics of strongly and weakly barred galaxies

We study the bar pattern speeds and corotation radii of 225 barred galaxies, using IFU data from MaNGA and the Tremaine-Weinberg method. Our sample, which is divided between strongly and weakly barred galaxies identified via Galaxy Zoo, is the largest that this method has been applied to. We find lower pattern speeds for strongly barred galaxies than for weakly barred galaxies. As simulations show that the pattern speed decreases as the bar exchanges angular momentum with its host, these results suggest that strong bars are more evolved than weak bars. Interestingly, the corotation radius is not different between weakly and strongly barred galaxies, despite being proportional to bar length. We also find that the corotation radius is significantly different between quenching and star forming galaxies. Additionally, we find that strongly barred galaxies have significantly lower values for R, the ratio between the corotation radius and the bar radius, than weakly barred galaxies, despite a big overlap in both distributions. This ratio classifies bars into ultrafast bars (R < 1.0; 11% of our sample), fast bars (1.0 < R < 1.4; 27%) and slow bars (R > 1.4; 62%). Simulations show that R is correlated with the bar formation mechanism, so our results suggest that strong bars are more likely to be formed by different mechanisms than weak bars. Finally, we find a lower fraction of ultrafast bars than most other studies, which decreases the recently claimed tension with ΛCDM. However, the median value of R is still lower than what is predicted by simulations.

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arXiv2022

Observations of the Initial Formation and Evolution of Spiral galaxies at $1 < z < 3$ in the CANDELS fields

Many aspects concerning the formation of spiral and disc galaxies remain unresolved, despite their discovery and detailed study over the past $150$ years. As such, we present the results of an observational search for proto-spiral galaxies and their earliest formation, including the discovery of a significant population of spiral-like and clumpy galaxies at $z>1$ in deep \textit{Hubble Space Telescope} CANDELS imaging. We carry out a detailed analysis of this population, characterising their number density evolution, masses, star formation rates and sizes. Overall, we find a surprisingly high overall number density of massive $M_{*} >10^{10}\mathrm{M}_{\odot}$ spiral-like galaxies (including clumpy spirals) at $z > 1$ of $0.18\,{\rm per}\, \mathrm{arcmin}^{-2}$. We measure and characterise the decline in the number of these systems at higher redshift using simulations to correct for redshift effects in identifications, finding that the true fraction of spiral-like galaxies grows at lower redshifts as $\sim$ $(1+z)^{-1.1}$. This is such that the absolute numbers of spirals increases by a factor of $\sim 10$ between $z = 2.5$ and $z = 0.5$. We also demonstrate that these spiral-like systems have large sizes at $z>2$, and high star formation rates, above the main-sequence, These galaxies represent a major mode of galaxy formation in the early universe, perhaps driven by the spiral structure itself. We finally discuss the origin of these systems, including their likely formation through gas accretion and minor mergers, but conclude that major mergers are an unlikely cause.

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arXiv2022

Galaxy Zoo: Clump Scout: Surveying the Local Universe for Giant Star-forming Clumps

Massive, star-forming clumps are a common feature of high-redshift star-forming galaxies. How they formed, and why they are so rare at low redshift, remains unclear. In this paper we identify the largest yet sample of clumpy galaxies (7,052) at low redshift using data from the citizen science project \textit{Galaxy Zoo: Clump Scout}, in which volunteers classified over 58,000 Sloan Digital Sky Survey (SDSS) galaxies spanning redshift $0.02 < z < 0.15$. We apply a robust completeness correction by comparing with simulated clumps identified by the same method. Requiring that the ratio of clump-to-galaxy flux in the SDSS $u$ band be greater than 8\% (similar to clump definitions used by other works), we estimate the fraction of local galaxies hosting at least one clump ($f_{clumpy}$) to be $2.68_{-0.30}^{+0.33}\%$. We also compute the same fraction with a less stringent cut of 3\% ($11.33_{-1.16}^{+0.89}\%$), as the higher number count and lower statistical noise of this fraction permits sharper comparison with future low-redshift clumpy galaxy studies. Our results reveal a sharp decline in $f_{clumpy}$ over $0 < z < 0.5$. The minor merger rate remains roughly constant over the same span, so we suggest that minor mergers are unlikely to be the primary driver of clump formation. Instead, the rate of galaxy turbulence is a better tracer for $f_{clumpy}$ over $0 < z < 1.5$ for galaxies of all masses, which supports the idea that clump formation is primarily driven by violent disk instability for all galaxy populations during this period.

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arXiv2021

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.

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arXiv2021

Galaxy Zoo: Stronger bars facilitate quenching in star forming galaxies

We have used Galaxy Zoo DECaLS (GZD) to study strong and weak bars in disk galaxies. Out of the 314,000 galaxies in GZD, we created a volume-limited sample (0.01 < z < 0.05, Mr < -18.96) which contains 1,867 galaxies with reliable volunteer bar classifications in the ALFALFA footprint. In keeping with previous Galaxy Zoo surveys (such as GZ2), the morphological classifications from GZD agree well with previous morphological surveys. GZD considers galaxies to either have a strong bar (15.5%), a weak bar (28.1%) or no bar (56.4%), based on volunteer classifications on images obtained from the DECaLS survey. This places GZD in a unique position to assess differences between strong and weak bars. We find that the strong bar fraction is typically higher in quiescent galaxies than in star forming galaxies, while the weak bar fraction is similar. Moreover, we have found that strong bars facilitate the quenching process in star forming galaxies, finding higher fibre SFRs, lower gas masses and shorter depletion timescales in these galaxies compared to unbarred galaxies. However, we also found that any differences between strong and weak bars disappear when controlling for bar length. Based on this, we conclude that weak and strong bars are not fundamentally different phenomena. Instead, we propose that there is a continuum of bar types, which varies from 'weakest' to 'strongest'.

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arXiv2021

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.

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arXiv2021

Investigating Clumpy Galaxies in the Sloan Digital Sky Survey Stripe 82 using the Galaxy Zoo

Giant, star-forming clumps are a common feature prevalent amongst high-redshift star-forming galaxies and play a critical role in shaping their chaotic morphologies and yet, their nature and role in galaxy evolution remains to be fully understood. A majority of the effort to study clumps has been focused at high redshifts, and local clump studies have often suffered from small sample sizes. In this work, we present an analysis of clump properties in the local universe, and for the first time, performed with a statistically significant sample. With the help of the citizen science-powered Galaxy Zoo: Hubble project, we select a sample of 92 $z<0.06$ clumpy galaxies in Sloan Digital Sky Survey Stripe 82 galaxies. Within this sample, we identify 543 clumps using a contrast-based image analysis algorithm and perform photometry as well as estimate their stellar population properties. The overall properties of our $z<0.06$ clump sample are comparable to the high-redshift clumps. However, contrary to the high-redshift studies, we find no evidence of a gradient in clump ages or masses as a function of their galactocentric distances. Our results challenge the inward migration scenario for clump evolution for the local universe, potentially suggesting a larger contribution of ex-situ clumps and/or longer clump migration timescales.

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arXiv2020

An old stellar population or diffuse nebular continuum emission discovered in green pea galaxies

We use new HST images of nine Green Pea Galaxies (GPGs) to study their resolved structure and color. The choice of filters, F555W and F850LP, together with the redshift of the galaxies ($z\sim 0.25$), minimizes the contribution of the nebular [O\thinspace{\sc iii}] and H$α$ emission lines to the broad-band images. While these galaxies are typically very blue in color, our analysis reveals that it is only the dominant stellar clusters that are blue. Each GPG does clearly show the presence of at least one bright and compact star-forming region, but these are invariably superimposed on a more extended and lower surface brightness emission. Moreover, the colors of the star forming regions are on average bluer than those of the diffuse emission, reaching up to 0.6 magnitudes bluer. Assuming that the diffuse and compact components have constant and single burst Star Formation Histories, respectively, the observed colors imply that the diffuse components (possibly the host galaxy of the star-formation episode) have, on average, old stellar ages ($>1$Gyr), while the star-clusters are younger than 500Myrs. We also discuss the possibility that the diffuse red emission is due to a varying relative contribution of nebular continuum, rather than a different stellar population. With the available data, however, it is not possible to distinguish between these two interpretations. A substantial presence of old stars would indicate that the mechanisms that allow large escape fractions in these local galaxies may be different from those at play during the reionization epoch.

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arXiv2020

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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arXiv2020

The X-ray and radio activity of typical and luminous Lya emitters from z~2 to z~6: evidence for a diverse, evolving population

Despite recent progress in understanding Lyman-alpha (Lya) emitters (LAEs), relatively little is known regarding their typical black hole activity across cosmic time. Here, we study the X-ray and radio properties of ~4000 LAEs at 2.2 3) and find an average luminosity of 10^{44.31+-0.01} erg/s and an average black hole accretion rate (BHAR) of 0.72+-0.01 Msun/yr, consistent with moderate to high accreting AGN. We detect 120 sources in deep radio data (radio AGN fraction of 3.2%+-0.3%). The global AGN fraction (8.6%+-0.4%) rises with Lya luminosity and declines with increasing redshift. For X-ray detected LAEs, Lya luminosities correlate with the BHARs, suggesting that Lya luminosity becomes an accretion rate indicator. Most LAEs (93.1+-0.6%) at 2<z<6 have no detectable X-ray emission (BHARs<0.017 Msun/yr). The median star formation rate (SFR) of star-forming LAEs from Lya and radio luminosities is 7.6^{+6.6}_{-2.8} Msun/yr. The black hole to galaxy growth ratio (BHAR/SFR) for LAEs is <0.0022, consistent with typical star forming galaxies and the local BHAR/SFR relation. We conclude that LAEs at 2<z<6 include two different populations: an AGN population, where Lya luminosity traces BHAR, making them bright in Lya, and another with low SFRs which remain undetected in even the deepest X-ray stacks but is detected in the radio stacks.

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arXiv2020

Galactic Conformity in both Star-formation and Morphological Properties

We investigate one-halo galactic conformity (the tendency for satellite galaxies to mirror the properties of their central) in both star-formation and morphology using a sample of 8230 galaxies in 1266 groups with photometry and spectroscopy from the Sloan Digital Sky Survey, morphologies from Galaxy Zoo and group memberships as determined by Yang et al. This is the first paper to investigate galactic conformity in both star-formation and visual morphology properties separately. We find that the signal of galactic conformity is present at low significance in both star-formation and visual morphological properties, however it is stronger in star-formation properties. Over the entire halo mass range we find that groups with star-forming (spiral) centrals have, on average, a fraction 0.18+-0.08 (0.08+-0.06) more star-forming (spiral) satellites than groups with passive (early-type) centrals at a similar halo mass. We also consider conformity in groups with four types of central: passive early-types, star-forming spirals, passive spirals and star-forming early-types (which are very rarely centrals), finding that the signal of morphological conformity is strongest around passive centrals regardless of morphology; although blue spiral centrals are also more likely than average to have blue spiral satellites. We interpret these observations of the relative size of the conformity signal as supporting a scenario where star-formation properties are relatively easily changed, while morphology changes less often/more slowly for galaxies in the group environment.

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