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Galaxy Zoo is an online project to classify morphological features in extra-galactic imaging surveys with public voting. In this paper, we compare the classifications made for two different surveys, the Dark Energy Spectroscopic Instrument (DESI) imaging survey and a part of the Kilo-Degree Survey (KiDS), in the equatorial fields of the Galaxy And Mass Assembly (GAMA) survey. Our aim is to cross-validate and compare the classifications based on different imaging quality and depth. We find that generally the voting agrees globally but with substantial scatter i.e. substantial differences for individual galaxies. There is a notable higher voting fraction in favor of ``smooth'' galaxies in the DESI+\rev{{\sc zoobot}} classifications, most likely due to the difference between imaging depth. DESI imaging is shallower and slightly lower resolution than KiDS and the Galaxy Zoo images do not reveal details such as disk features \rev{and thus are missed in the {\sc zoobot} training sample}. \rev{We check against expert visual classifications and find good agreement with KiDS-based Galaxy Zoo voting.} We reproduce the results from Porter-Temple+ (2022), on the dependence of stellar mass, star-formation, and specific star-formation on the number of spiral arms. This shows that once corrected for redshift, the DESI Galaxy Zoo and KiDS Galaxy Zoo classifications agree well on population properties. The zoobot cross-validation increases confidence in its ability to compliment Galaxy Zoo classifications and its ability for transfer learning across surveys., Comment: 20 pages, 22 figures, 8 tables, accepted for publication in PASA

We present the Merian Survey, an optical imaging survey optimized for studying the physical properties of bright star-forming dwarf galaxies. Merian is carried out with two medium-band filters ($N708$ and $N540$, centered at $708$ and $540$ nm), custom-built for the Dark Energy Camera (DECam) on the Blanco telescope. Merian covers $\sim 750\,\mathrm{deg}^2$ of equatorial fields, overlapping with the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP) wide, deep, and ultra-deep fields. When combined with the HSC-SSP imaging data ($grizy$), the new Merian DECam medium-band imaging allows for photometric redshift measurements via the detection of H$\rm\alpha$ and [OIII] line emission flux excess in the $N708$ and $N540$ filters, respectively, at $0.06

We present the phase one report of the Bright Star Subtraction (BSS) pipeline for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). This pipeline is designed to create an extended PSF model by utilizing observed stars, followed by subtracting this model from the bright stars present in LSST data. Running the pipeline on Hyper Suprime-Cam (HSC) data shows a correlation between the shape of the extended PSF model and the position of the detector within the camera's focal plane. Specifically, detectors positioned closer to the focal plane's edge exhibit reduced circular symmetry in the extended PSF model. To mitigate this effect, we present an algorithm that enables users to account for the location dependency of the model. Our analysis also indicates that the choice of normalization annulus is crucial for modeling the extended PSF. Smaller annuli can exclude stars due to overlap with saturated regions, while larger annuli may compromise data quality because of lower signal-to-noise ratios. This makes finding the optimal annulus size a challenging but essential task for the BSS pipeline. Applying the BSS pipeline to HSC exposures allows for the subtraction of, on average, 100 to 700 stars brighter than 12th magnitude measured in g-band across a full exposure, with a full HSC exposure comprising ~100 detectors., Comment: 11 pages, 8 figures, published in Proc. SPIE 13101, Software and Cyberinfrastructure for Astronomy VIII, 131013N (25 July 2024)

We present the Bright Star Subtraction (BSS) pipeline for the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST). This pipeline generates an extended PSF model using observed stars and subtracts the model from the bright stars in LSST data. When testing the pipeline on Hyper Suprime-Cam (HSC) data, we find that the shape of the extended PSF model depends on the location of the detector on the camera's focal plane. The closer a detector is to the edge of the focal plane, the less the extended PSF model is circularly symmetric. We introduce an algorithm that allows the user to consider the location dependency of the model., Comment: 4 pages, 1 figure; Astronomical Data Analysis Software & Systems XXXIII proceeding

Almost Dark Galaxies are objects that have eluded detection by traditional surveys such as the Sloan Digital Sky Survey (SDSS). The low surface brightness of these galaxies ($\mu_r$(0)$>26$ mag/arcsec^2), and hence their low surface stellar mass density (a few solar masses per pc^2 or less), suggests that the energy density released by baryonic feedback mechanisms is inefficient in modifying the distribution of the dark matter halos they inhabit. For this reason, almost dark galaxies are particularly promising for probing the microphysical nature of dark matter. In this paper, we present the serendipitous discovery of Nube, an almost dark galaxy with $<\mu_V>$e~ 26.7 mag/arcsec^2. The galaxy was identified using deep optical imaging from the IAC Stripe82 Legacy Project. Follow-up observations with the 100m Green Bank Telescope strongly suggest that the galaxy is at a distance of 107 Mpc. Ultra-deep multi-band observations with the 10.4m Gran Telescopio Canarias favour an age of ~10 Gyr and a metallicity of [Fe/H]$\sim-1.1$. With a stellar mass of ~4x10^8 Msun and a half-mass radius of Re=6.9 kpc (corresponding to an effective surface density of ~0.9 Msun/pc^2), Nube is the most massive and extended object of its kind discovered so far. The galaxy is ten times fainter and has an effective radius three times larger than typical ultra-diffuse galaxies with similar stellar masses. Galaxies with comparable effective surface brightness within the Local Group have very low mass (~10^5 Msun) and compact structures (effective radius Re<1 kpc). Current cosmological simulations within the cold dark matter scenario, including baryonic feedback, do not reproduce the structural properties of Nube. However, its highly extended and flattened structure is consistent with a scenario where the dark matter particles are ultra-light axions with a mass of m$_B$=($0.8^{+0.4}_{-0.2}$)$\times10^{-23}$ eV.}, Comment: Accepted for publication in A&A. Main figures are 8, 9 and 12

The Merian survey is mapping $\sim$ 850 degrees$^2$ of the Hyper Suprime-Cam Strategic Survey Program (HSC-SSP) wide layer with two medium-band filters on the 4-meter Victor M. Blanco telescope at the Cerro Tololo Inter-American Observatory, with the goal of carrying the first high signal-to-noise (S/N) measurements of weak gravitational lensing around dwarf galaxies. This paper presents the design of the Merian filter set: N708 ($\lambda_c = 7080 \unicode{x212B}$, $\Delta\lambda = 275\unicode{x212B}$) and N540 ($\lambda_c = 5400\unicode{x212B}$, $\Delta\lambda = 210\unicode{x212B}$). The central wavelengths and filter widths of N708 and N540 were designed to detect the $\rm H\alpha$ and $\rm [OIII]$ emission lines of galaxies in the mass range $8<\rm \log M_*/M_\odot<9$ by comparing Merian fluxes with HSC broad-band fluxes. Our filter design takes into account the weak lensing S/N and photometric redshift performance. Our simulations predict that Merian will yield a sample of $\sim$ 85,000 star-forming dwarf galaxies with a photometric redshift accuracy of $\sigma_{\Delta z/(1+z)}\sim 0.01$ and an outlier fraction of $\eta=2.8\%$ over the redshift range $0.058

The large-scale structure (LSS) of the Universe is comprised of galaxy filaments, tendrils, and voids. The majority of the Universe's volume is taken up by these voids, which exist as underdense, but not empty, regions. The galaxies found inside these voids are expected to be some of the most isolated objects in the Universe. This study, using the Galaxy and Mass Assembly (GAMA) and Galaxy Zoo surveys, aims to investigate basic physical properties and morphology of void galaxies versus field (filament and tendril) galaxies. We use void galaxies with stellar masses of $9.35 < log(M/M_\odot) < 11.25$, and this sample is split by identifying two redshift-limited regions, 0 < z < 0.075, and, $0.075 < z < 0.15$. To find comparable objects in the sample of field galaxies from GAMA and Galaxy Zoo, we identify "twins" of void galaxies as field galaxies within $\pm$0.05 dex and $\pm$0.15 dex of M and specific star formation rate. We determine the statistical significance of our results using the Kolmogorov-Smirnov (KS) test. We see that void galaxies, in contrast with field galaxies, seem to be disk-dominated and have predominantly round bulges (with > 50 percent of the Galaxy Zoo citizen scientists agreeing that bulges are present)., Comment: 13 pages, 16 figures, 3 tables, accepted by MNRAS

The Vera C. Rubin Observatory Wide-Fast Deep (WFD) sky survey will reach unprecedented surface brightness depths over tens of thousands of square degrees. Surface brightness photometry has traditionally been a challenge. Current algorithms which combine object detection with sky estimation systematically over-subtract the sky, biasing surface brightness measurements at the faint end and destroying or severely compromising low surface brightness light. While it has recently been shown that properly accounting for undetected faint galaxies and the wings of brighter objects can in principle recover a more accurate sky estimate, this has not yet been demonstrated in practice. Obtaining a consistent spatially smooth underlying sky estimate is particularly challenging in the presence of representative distributions of bright and faint objects. In this paper we use simulations of crowded and uncrowded fields designed to mimic Hyper Suprime-Cam data to perform a series of tests on the accuracy of the recovered sky. Dependence on field density, galaxy type and limiting flux for detection are all considered. Several photometry packages are utilised: Source Extractor, Gnuastro, and the LSST Science Pipelines. Each is configured in various modes, and their performance at extreme low surface brightness analysed. We find that the combination of the Source Extractor software package with novel source model masking techniques consistently produce extremely faint output sky estimates, by up to an order of magnitude, as well as returning high fidelity output science catalogues., Comment: Accepted for publication in MNRAS. 41 pages: 9 figures and 1 table in the main text, 11 figures and 2 tables in the appendix

Galaxies broadly fall into two categories: star-forming (blue) galaxies and quiescent (red) galaxies. In between, one finds the less populated ``green valley". Some of these galaxies are suspected to be in the process of ceasing their star-formation through a gradual exhaustion of gas supply or already dead and are experiencing a rejuvenation of star-formation through fuel injection. We use the Galaxy And Mass Assembly database and the Galaxy Zoo citizen science morphological estimates to compare the morphology of galaxies in the green valley against those in the red sequence and blue cloud. Our goal is to examine the structural differences within galaxies that fall in the green valley, and what brings them there. Previous results found disc features such as rings and lenses are more prominently represented in the green valley population. We revisit this with a similar sized data set of galaxies with morphology labels provided by the Galaxy Zoo for the GAMA fields based on new KiDS images. Our aim is to compare qualitatively the results from expert classification to that of citizen science. We observe that ring structures are indeed found more commonly in green valley galaxies compared to their red and blue counterparts. We suggest that ring structures are a consequence of disc galaxies in the green valley actively exhibiting characteristics of fading discs and evolving disc morphology of galaxies. We note that the progression from blue to red correlates with loosening spiral arm structure., Comment: 11 pages, 21 figures, accepted to MNRAS

We derive single S\'ersic fits and bulge-disk decompositions for 13096 galaxies at redshifts z < 0.08 in the GAMA II equatorial survey regions in the Kilo-Degree Survey (KiDS) g, r and i bands. The surface brightness fitting is performed using the Bayesian two-dimensional profile fitting code ProFit. We fit three models to each galaxy in each band independently with a fully automated Markov-chain Monte Carlo analysis: a single S\'ersic model, a S\'ersic plus exponential and a point source plus exponential. After fitting the galaxies, we perform model selection and flag galaxies for which none of our models are appropriate (mainly mergers/Irregular galaxies). The fit quality is assessed by visual inspections, comparison to previous works, comparison of independent fits of galaxies in the overlap regions between KiDS tiles and bespoke simulations. The latter two are also used for a detailed investigation of systematic error sources. We find that our fit results are robust across various galaxy types and image qualities with minimal biases. Errors given by the MCMC underestimate the true errors typically by factors 2-3. Automated model selection criteria are accurate to > 90 % as calibrated by visual inspection of a subsample of galaxies. We also present g-r component colours and the corresponding colour-magnitude diagram, consistent with previous works despite our increased fit flexibility. Such reliable structural parameters for the components of a diverse sample of galaxies across multiple bands will be integral to various studies of galaxy properties and evolution. All results are integrated into the GAMA database., Comment: 36 pages, 33 figures. Accepted for publication in MNRAS

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., Comment: 12 pages, 9 figues, Proc. SPIE 12189, Software and Cyberinfrastructure for Astronomy VII, Montreal, CA, July 2022

We present the capabilities of Galapagos--2 and Galfitm in the context of fitting 2-component profiles to galaxies, on the way to providing complete multi-band, multi-component fitting of large samples of galaxies in future surveys. We release both the code and the fit results to 234,239 objects from the DR3 of the Gama survey, a sample significantly deeper than previous works. We use stringent tests on both simulated and real data, as well as comparison to public catalogues to evaluate the advantages of using multi-band over single-band data. We show that multi-band fitting using Galfitm provides significant advantages when trying to decompose galaxies into their individual constituents, as more data are being used, by effectively being able to use the colour information buried in the individual exposures to its advantage. Using simulated data, we find that multi-band fitting significantly reduces the deviations from real parameter values, allows component sizes and S\'ersic indices to be recovered more accurately, and, by design, constrains the band-to-band variations of these parameters to more physical values. On both simulated and real data, we confirm that the SEDs of the 2 main components can be recovered to fainter magnitudes compared to using single-band fitting, which tends to recover disks and bulges to - on average - have identical SEDs when the galaxies become too faint, instead of the different SEDs they truly have. By comparing our results to those provided by other fitting codes, we confirm that they agree in general, but measurement errors can be significantly reduced by using the multi-band tools developed by the MegaMorph project. We conclude that the multi-band fitting employed by Galapagos-2 and Galfitm significantly improves the accuracy of structural galaxy parameters and enables much larger samples to be be used in a scientific analysis., Comment: 50 pages, 30 figures, accepted for publication in A&A

Galaxy populations show bimodality in a variety of properties: stellar mass, colour, specific star-formation rate, size, and S\'ersic index. These parameters are our feature space. We use an existing sample of 7556 galaxies from the Galaxy and Mass Assembly (GAMA) survey, represented using five features and the K-means clustering technique, showed that the bimodalities are the manifestation of a more complex population structure, represented by between 2 and 6 clusters. Here we use Self Organizing Maps (SOM), an unsupervised learning technique which can be used to visualize similarity in a higher dimensional space using a 2D representation, to map these five-dimensional clusters in the feature space onto two-dimensional projections. To further analyze these clusters, using the SOM information, we agree with previous results that the sub-populations found in the feature space can be reasonably mapped onto three or five clusters. We explore where the "green valley" galaxies are mapped onto the SOM, indicating multiple interstitial populations within the green valley population. Finally, we use the projection of the SOM to verify whether morphological information provided by GalaxyZoo users, for example, if features are visible, can be mapped onto the SOM-generated map. Voting on whether galaxies are smooth, likely ellipticals, or "featured" can reasonably be separated but smaller morphological features (bar, spiral arms) can not. SOMs promise to be a useful tool to map and identify instructive sub-populations in multidimensional galaxy survey feature space, provided they are large enough., Comment: 14 pages, 14 figures, accepted by MNRAS

In Galaxy And Mass Assembly Data Release 4 (GAMA DR4), we make available our full spectroscopic redshift sample. This includes 248682 galaxy spectra, and, in combination with earlier surveys, results in 330542 redshifts across five sky regions covering ~250deg^2. The redshift density, is the highest available over such a sustained area, has exceptionally high completeness (95 per cent to r_KIDS=19.65mag), and is well suited for the study of galaxy mergers, galaxy groups, and the low redshift (z<0.25) galaxy population. DR4 includes 32 value-added tables or Data Management Units (DMUs) that provide a number of measured and derived data products including GALEX, ESO KiDS, ESO VIKING, WISE and Herschel Space Observatory imaging. Within this release, we provide visual morphologies for 15330 galaxies to z<0.08, photometric redshift estimates for all 18million objects to r_KIDS~25mag, and stellar velocity dispersions for 111830 galaxies. We conclude by deriving the total galaxy stellar mass function (GSMF) and its sub-division by morphological class (elliptical, compact-bulge and disc, diffuse-bulge and disc, and disc only). This extends our previous measurement of the total GSMF down to 10^6.75 M_sol h^-2_70 and we find a total stellar mass density of rho_*=(2.97+/-0.04)x10^8 M_sol h_70 Mpc^-3 or Omega_*=(2.17+/-0.03)x10^-3 h^-1_70. We conclude that at z<0.1, the Universe has converted 4.9+/-0.1 per cent of the baryonic mass implied by Big Bang Nucleosynthesis into stars that are gravitationally bound within the galaxy population., Comment: Accepted for publication in MNRAS. GAMA Data Release 4 is available at: http://www.gama-survey.org/dr4/

The role of the tensor part of the nuclear interaction is actively investigated in recent years due to experimental advancement yielding new data in nuclei far from the $\beta$-stability line. In this article we study the effect of this part of the nuclear interaction on deformed neutron magic numbers in the rare-earth region within the Skyrme energy-density functional for various TIJ \cite{lesinski:2007} parametrizations. Two quantities signaling magic numbers are considered: two-neutron separation energies and single-particle energies. They are calculated in isotopic series involving well-deformed rare-earth nuclei ranging from $Z=64$ to $Z=72$ in the $N=100$ region. Obtained results show that, whereas the neutron-proton tensor contribution to binding energies is important to reproduce neutron sub-shell closure at $N = 104$ in heavier rare earths Yb ($Z=70$) and Hf ($Z=72$) isotopes, like-particle tensor also plays a role in the single-particle spectrum around Fermi level and is even favored in lighter Gd ($Z=64$) and Dy ($Z=66$) rare-earth isotopes., Comment: 10 pages, 4 figures, to be submitted to Phys. Rev. C

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., Comment: Accepted by MNRAS July '21. Open access DOI below. Data at https://doi.org/10.5281/zenodo.4196266. Code at https://www.github.com/mwalmsley/zoobot. Docs at https://zoobot.readthedocs.io/. Interactive viewer at https://share.streamlit.io/mwalmsley/galaxy-poster/gz_decals_mike_walmsley.py

We estimate the Intracluster Light (ICL) component within a sample of 18 clusters detected in XMM Cluster Survey (XCS) data using deep ($\sim$ 26.8 mag) Hyper Suprime Cam Subaru Strategic Program DR1 (HSC-SSP DR1) $i$-band data. We apply a rest-frame ${\mu}_{B} = 25 \ \mathrm{mag/arcsec^{2}}$ isophotal threshold to our clusters, below which we define light as the ICL within an aperture of $R_{X,500}$ (X-ray estimate of $R_{500}$) centered on the Brightest Cluster Galaxy (BCG). After applying careful masking and corrections for flux losses from background subtraction, we recover $\sim$20% of the ICL flux, approximately four times our estimate of the typical background at the same isophotal level ($\sim$ 5%). We find that the ICL makes up about $\sim$ 24% of the total cluster stellar mass on average ($\sim$ 41% including the flux contained in the BCG within 50 kpc); this value is well-matched with other observational studies and semi-analytic/numerical simulations, but is significantly smaller than results from recent hydrodynamical simulations (even when measured in an observationally consistent way). We find no evidence for any links between the amount of ICL flux with cluster mass, but find a growth rate of $2-4$ for the ICL between $0.1 < z < 0.5$. We conclude that the ICL is the dominant evolutionary component of stellar mass in clusters from $z \sim 1$. Our work highlights the need for a consistent approach when measuring ICL alongside the need for deeper imaging, in order to unambiguously measure the ICL across as broad a redshift range as possible (e.g. 10-year stacked imaging from the Vera C. Rubin Observatory)., Comment: Accepted by MNRAS (05/01/2021), 20 pages, 17 figures

Strong gravitational lenses are a rare and instructive type of astronomical object. Identification has long relied on serendipity, but different strategies -- such as mixed spectroscopy of multiple galaxies along the line of sight, machine learning algorithms, and citizen science -- have been employed to identify these objects as new imaging surveys become available. We report on the comparison between spectroscopic, machine learning, and citizen science identification of galaxy-galaxy lens candidates from independently constructed lens catalogs in the common survey area of the equatorial fields of the GAMA survey. In these, we have the opportunity to compare high-completeness spectroscopic identifications against high-fidelity imaging from the Kilo Degree Survey (KiDS) used for both machine learning and citizen science lens searches. We find that the three methods -- spectroscopy, machine learning, and citizen science -- identify 47, 47, and 13 candidates respectively in the 180 square degrees surveyed. These identifications barely overlap, with only two identified by both citizen science and machine learning. We have traced this discrepancy to inherent differences in the selection functions of each of the three methods, either within their parent samples (i.e. citizen science focuses on low-redshift) or inherent to the method (i.e. machine learning is limited by its training sample and prefers well-separated features, while spectroscopy requires sufficient flux from lensed features to lie within the fiber). These differences manifest as separate samples in estimated Einstein radius, lens stellar mass, and lens redshift. The combined sample implies a lens candidate sky-density $\sim0.59$ deg$^{-2}$ and can inform the construction of a training set spanning a wider mass-redshift space., Comment: 22 figures, 6 tables, accepted for publication in The Astronomical Journal

We use KiDS weak lensing data to measure variations in mean halo mass as a function of several key galaxy properties (namely: stellar colour, specific star formation rate, Sersic index, and effective radius) for a volume-limited sample of GAMA galaxies in a narrow stellar mass range ($M_* \sim 2$--$5 \times 10^{10}$ Msol). This mass range is particularly interesting, inasmuch as it is where bimodalities in galaxy properties are most pronounced, and near to the break in both the galaxy stellar mass function and the stellar-to-halo mass relation (SHMR). In this narrow mass range, we find that both size and Sersic index are better predictors of halo mass than either colour or SSFR, with the data showing a slight preference for Sersic index. In other words, we find that mean halo mass is more tightly correlated with galaxy structure than either past star formation history or current star formation rate. Our results lead to an approximate lower bound on the dispersion in halo masses among $\log M_* \approx {10.5}$ galaxies: we find that the dispersion is $\gtrsim 0.3$ dex. This would imply either that offsets from the mean SHMR are closely coupled to size/structure, or that the dispersion in the SHMR is larger than past results have suggested. Our results thus provide new empirical constraints on the relationship between stellar and halo mass assembly at this particularly interesting mass range., Comment: 16 pages, 7 figures; submitted to MNRAS; updated to reflect accepted version

In Sedgwick et al. (2019) we introduced and utilised a method to combat surface brightness and mass biases in galaxy sample selection, using core-collapse supernovae (CCSNe) as pointers towards their host galaxies, in order to: (i) search for low-surface brightness galaxies (LSBGs); (ii) assess the contributions of galaxies at a given mass to the star-formation-rate density (SFRD); and (iii) infer from this, using estimates of specific star-formation (SF) rate, the form of the SF-galaxy stellar mass function (GSMF). A CCSN-selection of SF-galaxies allows a probe of the form of the SFRD and GSMF deep into the dwarf galaxy mass regime. In the present work, we give improved constraints on our estimates of the SFRD and star-forming GSMF, in light of improved photometric redshift estimates required for estimates of galaxy stellar mass. The results are consistent with a power-law increase to SF-galaxy number density down to our low stellar mass limit of $\sim 10^{6.2}$ M$_{\odot}$. No deviation from the high-mass version of the surface brightness - mass relation is found in the dwarf mass regime. These findings imply no truncation to galaxy formation processes at least down to $\sim 10^{6.2}$ M$_{\odot}$., Comment: 6 pages, 1 figure. Submitted for publication in the proceedings of IAU Symposium No. 355, 2019, "The Realm of the Low-Surface-Brightness Universe"

Two fits of the pairing residual interaction in the rare-earth region are independently performed. One is made on the odd-even staggering of masses by comparing measured and explicitly calculated three-point binding-energy differences centered on odd-even nuclei. Another deals with the moments of inertia of the first 2+ states of well deformed even-even nuclei upon comparing experimental data with the results of Inglis-Belyaev moments (supplemented by a crude estimate of the so-called Thouless-Valatin corrections). The sample includes 24 even-even and 31 odd-mass nuclei selected according to two criteria: they should have good rotor properties and should not correspond to low pairing-correlation regimes in their ground states. Calculations are performed in the self-consistent Hartree-Fock plus BCS framework (implementing a self-consistent blocking in the case of odd-mass nuclei). The Skyrme SIII parametrization is used in the particle-hole channel and the fitted quantities are the strengths of |Tz|=1 proton and neutron seniority residual interactions. As a result, the two fits yield sets of strengths in excellent agreement: about 0.1% for the neutron parameters and 0.2% for protons. In contrast when one performs such a fit on odd-even staggering from quantities deduced from BCS gaps or minimal quasiparticle energies in even-even nuclei, as is traditional, one obtains results significantly different from those obtained in the same nuclei by a fit of moments of inertia. As a conclusion, beyond providing a phenomenological tool for microscopic calculations in this region, we have illustrated the proposition made in the seminal paper of Bohr, Mottelson and Pines that moments of inertia and odd-even staggering in selected nuclei were excellent measuring sticks of nuclear pairing correlations., Comment: Accepted for publication in Physical Review C

We introduce a method for producing a galaxy sample unbiased by surface brightness and stellar mass, by selecting star-forming galaxies via the positions of core-collapse supernovae (CCSNe). Whilst matching $\sim$2400 supernovae from the SDSS-II Supernova Survey to their host galaxies using IAC Stripe 82 legacy coadded imaging, we find $\sim$150 previously unidentified low surface brightness galaxies (LSBGs). Using a sub-sample of $\sim$900 CCSNe, we infer CCSN-rate and star-formation rate densities as a function of galaxy stellar mass, and the star-forming galaxy stellar mass function. Resultant star-forming galaxy number densities are found to increase following a power-law down to our low mass limit of $\sim10^{6.4}$ M$_{\odot}$ by a single Schechter function with a faint-end slope of $\alpha = -1.41$. Number densities are consistent with those found by the EAGLE simulations invoking a $\Lambda$-CDM cosmology. Overcoming surface brightness and stellar mass biases is important for assessment of the sub-structure problem. In order to estimate galaxy stellar masses, a new code for the calculation of galaxy photometric redshifts, zMedIC, is also presented, and shown to be particularly useful for small samples of galaxies., Comment: 18 pages, 14 figures, accepted for publication in MNRAS

A fundamental bimodality of galaxies in the local Universe is apparent in many of the features used to describe them. Multiple sub-populations exist within this framework, each representing galaxies following distinct evolutionary pathways. Accurately identifying and characterising these sub-populations requires that a large number of galaxy features be analysed simultaneously. Future galaxy surveys such as LSST and Euclid will yield data volumes for which traditional approaches to galaxy classification will become unfeasible. To address this, we apply a robust $k$-means unsupervised clustering method to feature data derived from a sample of 7338 local-Universe galaxies selected from the Galaxy And Mass Assembly (GAMA) survey. This allows us to partition our sample into $k$ clusters without the need for training on pre-labelled data, facilitating a full census of our high dimensionality feature space and guarding against stochastic effects. We find that the local galaxy population natively splits into $2$, $3$, $5$ and a maximum of $6$ sub-populations, with each corresponding to a distinct ongoing evolutionary mechanism. Notably, the impact of the local environment appears strongly linked with the evolution of low-mass ($M_{*} < 10^{10}$ M$_{\odot}$) galaxies, with more massive systems appearing to evolve more passively from the blue cloud onto the red sequence. With a typical run time of $\sim3$ minutes per value of $k$ for our galaxy sample, we show how $k$-means unsupervised clustering is an ideal tool for future analysis of large extragalactic datasets, being scalable, adaptable, and providing crucial insight into the fundamental properties of the local galaxy population., Comment: 27 pages, 28 figures, 8 tables. Accepted for publication in the Monthly Notices of the Royal Astronomical Society

Using a sample of 472 local Universe (z<0.06) galaxies in the stellar mass range 10.25 < log M*/M_sun < 10.75, we explore the variation in galaxy structure as a function of morphology and galaxy colour. Our sample of galaxies is sub-divided into red, green and blue colour groups and into elliptical and non-elliptical (disk-type) morphologies. Using KiDS and VIKING derived postage stamp images, a group of eight volunteers visually classified bars, rings, morphological lenses, tidal streams, shells and signs of merger activity for all systems. We find a significant surplus of rings ($2.3\sigma$) and lenses ($2.9\sigma$) in disk-type galaxies as they transition across the green valley. Combined, this implies a joint ring/lens green valley surplus significance of $3.3\sigma$ relative to equivalent disk-types within either the blue cloud or the red sequence. We recover a bar fraction of ~44% which remains flat with colour, however, we find that the presence of a bar acts to modulate the incidence of rings and (to a lesser extent) lenses, with rings in barred disk-type galaxies more common by ~20-30 percentage points relative to their unbarred counterparts, regardless of colour. Additionally, green valley disk-type galaxies with a bar exhibit a significant $3.0\sigma$ surplus of lenses relative to their blue/red analogues. The existence of such structures rules out violent transformative events as the primary end-of-life evolutionary mechanism, with a more passive scenario the favoured candidate for the majority of galaxies rapidly transitioning across the green valley., Comment: 17 pages, 9 figures, accepted for publication in MNRAS

We present a sample of 329 low to intermediate redshift ($0.05 < z < 0.3$) brightest cluster galaxies (BCGs) in X-ray selected clusters from the SPectroscopic IDentification of eRosita Sources (SPIDERS) survey, a spectroscopic survey within Sloan Digital Sky Survey-IV (SDSS-IV). We define our BCGs by simultaneous consideration of legacy X-ray data from ROSAT, maximum likelihood outputs from an optical cluster-finder algorithm and visual inspection. Using SDSS imaging data, we fit S\'ersic profiles to our BCGs in three bands (\textit{g}, \textit{r}, \textit{i}) with \textsc{SIGMA}, a \textsc{GALFIT}-based software wrapper. We examine the reliability of our fits by running our pipeline on ${\sim}10^{4}$ psf-convolved model profiles injected into 8 random cluster fields, we then use the results of this analysis to create a robust subsample of 198 BCGs. We outline three cluster properties of interest: overall cluster X-ray luminosity ($L_{X}$), cluster richness as estimated by \textsc{redMaPPer} ($ \lambda $) and cluster halo mass ($M_{200}$), which is estimated via velocity dispersion. In general, there are significant correlations with BCG stellar mass between all three environmental properties, but no significant trends arise with either S\'ersic index or effective radius. There is no major environmental dependence on the strength of the relation between effective radius and BCG stellar mass. Stellar mass therefore arises as the most important factor governing BCG morphology. Our results indicate that our sample consists of a large number of relaxed, mature clusters containing broadly homogeneous BCGs up to $z \sim 0.3$, suggesting that there is little evidence for much ongoing structural evolution for BCGs in these systems., Comment: 25 pages, 17 figures, 11 tables - accepted in MNRAS

We apply four statistical learning methods to a sample of $7941$ galaxies ($z<0.06$) from the Galaxy and Mass Assembly (GAMA) survey to test the feasibility of using automated algorithms to classify galaxies. Using $10$ features measured for each galaxy (sizes, colours, shape parameters \& stellar mass) we apply the techniques of Support Vector Machines (SVM), Classification Trees (CT), Classification Trees with Random Forest (CTRF) and Neural Networks (NN), returning True Prediction Ratios (TPRs) of $75.8\%$, $69.0\%$, $76.2\%$ and $76.0\%$ respectively. Those occasions whereby all four algorithms agree with each other yet disagree with the visual classification (`unanimous disagreement') serves as a potential indicator of human error in classification, occurring in $\sim9\%$ of ellipticals, $\sim9\%$ of Little Blue Spheroids, $\sim14\%$ of early-type spirals, $\sim21\%$ of intermediate-type spirals and $\sim4\%$ of late-type spirals \& irregulars. We observe that the choice of parameters rather than that of algorithms is more crucial in determining classification accuracy. Due to its simplicity in formulation and implementation, we recommend the CTRF algorithm for classifying future galaxy datasets. Adopting the CTRF algorithm, the TPRs of the 5 galaxy types are : E, $70.1\%$; LBS, $75.6\%$; S0-Sa, $63.6\%$; Sab-Scd, $56.4\%$ and Sd-Irr, $88.9\%$. Further, we train a binary classifier using this CTRF algorithm that divides galaxies into spheroid-dominated (E, LBS \& S0-Sa) and disk-dominated (Sab-Scd \& Sd-Irr), achieving an overall accuracy of $89.8\%$. This translates into an accuracy of $84.9\%$ for spheroid-dominated systems and $92.5\%$ for disk-dominated systems., Comment: 30 pages, 21 figures, accepted for publication in MNRAS

We use the energy-balance code MAGPHYS to determine stellar and dust masses, and dust corrected star-formation rates for over 200,000 GAMA galaxies, 170,000 G10-COSMOS galaxies and 200,000 3D-HST galaxies. Our values agree well with previously reported measurements and constitute a representative and homogeneous dataset spanning a broad range in stellar mass (10^8---10^12 Msol), dust mass (10^6---10^9 Msol), and star-formation rates (0.01---100 Msol per yr), and over a broad redshift range (0.0 < z < 5.0). We combine these data to measure the cosmic star-formation history (CSFH), the stellar-mass density (SMD), and the dust-mass density (DMD) over a 12 Gyr timeline. The data mostly agree with previous estimates, where they exist, and provide a quasi-homogeneous dataset using consistent mass and star-formation estimators with consistent underlying assumptions over the full time range. As a consequence our formal errors are significantly reduced when compared to the historic literature. Integrating our cosmic star-formation history we precisely reproduce the stellar-mass density with an ISM replenishment factor of 0.50 +/- 0.07, consistent with our choice of Chabrier IMF plus some modest amount of stripped stellar mass. Exploring the cosmic dust density evolution, we find a gradual increase in dust density with lookback time. We build a simple phenomenological model from the CSFH to account for the dust mass evolution, and infer two key conclusions: (1) For every unit of stellar mass which is formed 0.0065---0.004 units of dust mass is also formed; (2) Over the history of the Universe approximately 90 to 95 per cent of all dust formed has been destroyed and/or ejected., Comment: Accepted for publication in MNRAS

[Abridged] Typical disc galaxies forming in a LambdaCDM cosmology encounter a violent environment, where they often experience mergers with massive satellites. The fact that disc galaxies are ubiquitous in the local Universe suggests that a quiescent history is not necessary for their formation. Modern cosmological simulations can now obtain relatively realistic populations of disc galaxies, but it still remains to be clarified how discs manage to survive massive mergers. Here we use a suite of high-resolution hydrodynamical simulations set in a LambdaCDM cosmology to elucidate the fate of discs encountering massive mergers. We extract a sample of approximately 100 disc galaxies and follow the changes in their post-merger morphologies, as tracked by their disc-to-total ratios (D/T). We also examine the relations between their present-day morphology, assembly history and gas fractions. We find that approximately half of present-day disc galaxies underwent at least one merger with a satellite of total mass exceeding the host system's stellar mass, a third had mergers with satellites of mass exceeding 3 times the host's stellar mass, and approximately one-sixth had mergers with satellites of mass exceeding 10 times of the host's stellar mass. These mergers lead to a sharp, but often temporary, decrease in the D/T of the hosts, implying that discs are usually disrupted but then quickly re-grow. To do so, high cold gas fractions are required post-merger, as well as a relatively quiescent recent history (over a few Gyrs before z=0). Our results show that discs can form via diverse merger pathways and that quiescent histories are not the dominant mode of disc formation., Comment: 21 pages, PASA, in press

We present the results of two-component (disc+bar) and three-component (disc+bar+bulge) multiwavelength 2D photometric decompositions of barred galaxies in five SDSS bands ($ugriz$). This sample of $\sim$3,500 nearby ($z<0.06$) galaxies with strong bars selected from the Galaxy Zoo citizen science project is the largest sample of barred galaxies to be studied using photometric decompositions which include a bar component. With detailed structural analysis we obtain physical quantities such as the bar- and bulge-to-total luminosity ratios, effective radii, S\'ersic indices and colours of the individual components. We observe a clear difference in the colours of the components, the discs being bluer than the bars and bulges. An overwhelming fraction of bulge components have S\'ersic indices consistent with being pseudobulges. By comparing the barred galaxies with a mass-matched and volume-limited sample of unbarred galaxies, we examine the connection between the presence of a large-scale galactic bar and the properties of discs and bulges. We find that the discs of unbarred galaxies are significantly bluer compared to the discs of barred galaxies, while there is no significant difference in the colours of the bulges. We find possible evidence of secular evolution via bars that leads to the build-up of pseudobulges and to the quenching of star formation in the discs. We identify a subsample of unbarred galaxies with an inner lens/oval and find that their properties are similar to barred galaxies, consistent with an evolutionary scenario in which bars dissolve into lenses. This scenario deserves further investigation through both theoretical and observational work., Comment: 26 pages, 21 figures; accepted for publication in MNRAS

We present the evolution of the Cosmic Spectral Energy Distribution (CSED) from $z = 1 - 0$. Our CSEDs originate from stacking individual spectral energy distribution fits based on panchromatic photometry from the Galaxy and Mass Assembly (GAMA) and COSMOS datasets in ten redshift intervals with completeness corrections applied. Below $z = 0.45$, we have credible SED fits from 100 nm to 1 mm. Due to the relatively low sensitivity of the far-infrared data, our far-infrared CSEDs contain a mix of predicted and measured fluxes above $z = 0.45$. Our results include appropriate errors to highlight the impact of these corrections. We show that the bolometric energy output of the Universe has declined by a factor of roughly four -- from $5.1 \pm 1.0$ at $z \sim 1$ to $1.3 \pm 0.3 \times 10^{35}~h_{70}$~W~Mpc$^{-3}$ at the current epoch. We show that this decrease is robust to cosmic variance, SED modelling and other various types of error. Our CSEDs are also consistent with an increase in the mean age of stellar populations. We also show that dust attenuation has decreased over the same period, with the photon escape fraction at 150~nm increasing from $16 \pm 3$ at $z \sim 1$ to $24 \pm 5$ per cent at the current epoch, equivalent to a decrease in $A_\mathrm{FUV}$ of 0.4~mag. Our CSEDs account for $68 \pm 12$ and $61 \pm 13$ per cent of the cosmic optical and infrared backgrounds respectively as defined from integrated galaxy counts and are consistent with previous estimates of the cosmic infrared background with redshift., Comment: 19 pages, 14 figures, accepted by MNRAS