Galaxy Zoo JWST : up to 75 per cent of discs are featureless at 3 < z < 7
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R J Smethurst↗
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Radio Galaxy Zoo: observational evidence for environment as the cause of radio source asymmetry
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P E Rodman↗
Multi-species outbreak of SARS-CoV-2 Delta variant in a zoological institution, with the detection in two new families of carnivores
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has a worldwide distribution in humans and many other mammalian species. In late September 2021, 12 animals maintained by the Chicago Zoological Society's Brookfield Zoo were observed with variable clinical signs. The Delta variant of SARS-CoV-2 was detected in faeces and nasal swabs by qRT-PCR, including the first detection in animals from the families Procyonidae and Viverridae. Test positivity rate was 12.5% for 35 animals tested. All animals had been vaccinated with at least one dose of a recombinant vaccine designed for animals and all recovered with variable supportive treatment. Sequence analysis showed that six zoo animal strains were closely correlated with 18 human SARS-CoV-2 strains, suggestive of potential human-to-animal transmission events. This report documents the expanding host range of COVID-19 during the ongoing pandemic.
59 BASIC BIOLOGICAL SCIENCES↗
Multidrug-resistant Shigella flexneri outbreak affecting humans and non-human primates in New Mexico, USA
Shigellosis is a gastrointestinal infection caused by species of Shigella . A large outbreak of Shigella flexneri serotype 2a occurred in Albuquerque, New Mexico between May 2021 and November 2023 that involved humans and non-human primates (NHP) from a local zoo. We analyzed the genomes of 202 New Mexican isolates as well as 15 closely related isolates from other states, and four from NHP. The outbreak was initially detected within men who have sex with men but then predominantly affected people experiencing homelessness. Nearly 70% of cases were hospitalized and there was one human death. The outbreak extended into Albuquerque’s BioPark Zoo, causing high morbidity and six deaths in NHPs. All isolates were multidrug-resistant, including towards fluoroquinolones, a first line treatment option which led to treatment failures in human and NHP populations. We show the circulation of the same S. flexneri strain in humans and NHPs, causing fatalities in both populations. This study demonstrates the threat of antimicrobial resistant organisms to vulnerable human and NHP populations and emphasizes the value of genomic surveillance within a One Health framework.
59 BASIC BIOLOGICAL SCIENCES↗
Do Minor Interactions Trigger Star Formation in Galaxy Pairs?
Abstract We analyze the galaxy pairs in a set of volume limited samples from the Sloan Digital Sky Survey to study the effects of minor interactions on the star formation rate (SFR) and color of galaxies. We carefully design control samples of isolated galaxies by matching the stellar mass and redshift of the minor pairs. The SFR distributions and color distributions in the minor pairs differ from their controls at >99% significance level. We also simultaneously match the control galaxies in stellar mass, redshift and local density to assess the role of the environment. The null hypothesis can be rejected at >99% confidence level even after matching the environment. Our analysis shows a quenching in the minor pairs where the degree of quenching decreases with the increasing pair separation and plateaus beyond 50 kpc. We also prepare a sample of minor pairs with H α line information. We calculate the SFR of these galaxies using the H α line and repeat our analysis. We observe a quenching in the H α sample too. We find that the majority of the minor pairs are quiescent systems that could be quenched due to minor interactions. Combining data from the Galaxy Zoo and Galaxy Zoo 2, we find that only ∼1% galaxies have a dominant bulge, 4%–7% galaxies host a bar and 5%–10% of galaxies show active galactic nucleus (AGN) activity in minor pairs. This indicates that the presence of bulge, bar or AGN activity plays an insignificant role in quenching the galaxies in minor pairs. The more massive companion satisfies the criteria for mass quenching in most of the minor pairs. We propose that the stripping and starvation likely caused the quenching in the less massive companion at a later stage of evolution.
Astronomy & Astrophysics↗
Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging
There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or an investigation for maximizing their effectiveness. We carry out a comparison between several common machine learning methods for galaxy classification [Convolutional Neural Network (CNN), K-nearest neighbour, logistic regression, Support Vector Machine, Random Forest, and Neural Networks] by using Dark Energy Survey (DES) data combined with visual classifications from the Galaxy Zoo 1 project (GZ1). Our goal is to determine the optimal machine learning methods when using imaging data for galaxy classification. We show that CNN is the most successful method of these ten methods in our study. Using a sample of ~2800 galaxies with visual classification from GZ1, we reach an accuracy of ~0.99 for the morphological classification of ellipticals and spirals. The further investigation of the galaxies that have a different ML and visual classification but with high predicted probabilities in our CNN usually reveals the incorrect classification provided by GZ1. We further find the galaxies having a low probability of being either spirals or ellipticals are visually lenticulars (S0), demonstrating that supervised learning is able to rediscover that this class of galaxy is distinct from both ellipticals and spirals. We confirm that ~2.5 percent galaxies are misclassified by GZ1 in our study. After correcting these galaxies’ labels, we improve our CNN performance to an average accuracy of over 0.99 (accuracy of 0.994 is our best result).
79 ASTRONOMY AND ASTROPHYSICS↗
Practical galaxy morphology tools from deep supervised representation learning
Astronomers have typically set out to solve supervised machine learning problems by creating their own representations from scratch. We show that deep learning models trained to answer every Galaxy Zoo DECaLS question learn meaningful semantic representations of galaxies that are useful for new tasks on which the models were never trained. We exploit these representations to outperform several recent approaches at practical tasks crucial for investigating large galaxy samples. The first task is identifying galaxies of similar morphology to a query galaxy. Given a single galaxy assigned a free text tag by humans (e.g. ‘#diffuse’), we can find galaxies matching that tag for most tags. The second task is identifying the most interesting anomalies to a particular researcher. Our approach is 100 per cent accurate at identifying the most interesting 100 anomalies (as judged by Galaxy Zoo 2 volunteers). The third task is adapting a model to solve a new task using only a small number of newly labelled galaxies. Models fine-tuned from our representation are better able to identify ring galaxies than models fine-tuned from terrestrial images (ImageNet) or trained from scratch. We solve each task with very few new labels; either one (for the similarity search) or several hundred (for anomaly detection or fine-tuning). This challenges the longstanding view that deep supervised methods require new large labelled data sets for practical use in astronomy. To help the community benefit from our pretrained models, we release our fine-tuning code zoobot. Zoobot is accessible to researchers with no prior experience in deep learning.
79 ASTRONOMY AND ASTROPHYSICS↗
Subaru Hyper Suprime-Cam revisits the large-scale environmental dependence on galaxy morphology over 360 deg2 at z = 0.3–0.6
This study investigates the role of large-scale environments on the fraction of spiral galaxies at z = 0.3–0.6 sliced to three redshift bins of Δz = 0.1. Here, we sample 276220 massive galaxies in a limited stellar mass of 5 × 1010 solar mass (~M*) over 360 deg2, as obtained from the Second Public Data Release of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP). By combining projected two-dimensional density information (Shimakawa et al. 2021, MNRAS, 503, 3896) and the CAMIRA cluster catalog (Oguri et al. 2018, PASJ, 70, S20), we investigate the spiral fraction across large-scale overdensities and in the vicinity of red sequence clusters. We adopt transfer learning to reduce the cost of labeling spiral galaxies significantly and then perform stacking analysis across the entire field to overcome the limitations of sample size. Here we employ a morphological classification catalog by the Galaxy Zoo Hubble (Willett et al., 2017, MNRAS, 464, 4176) to train the deep learning model. Based on 74103 sources classified as spirals, we find moderate morphology–density relations on a 10 comoving Mpc scale, thanks to the wide-field coverage of HSC-SSP. Clear deficits of spiral galaxies have also been confirmed, in and around 1136 red sequence clusters. Furthermore, we verify whether there is a large-scale environmental dependence on rest-frame u - r colors of spiral galaxies; such a tendency was not observed in our sample.
Astronomy & Astrophysics↗
The Effect of Environment on Galaxy Spiral Arms, Bars, Concentration, and Quenching
For a sample of 4378 nearby spiral and S0 galaxies, Yu & Ho used Fourier analysis of Sloan Digital Sky Survey images to show that the strengths of the spiral arms and the pitch angles of the arms are inversely correlated with central concentration. In the current study, we search for trends in the Yu & Ho spiral arm parameters with environment and specific star formation rate (sSFR). When comparing galaxies with similar concentrations, we do not find a significant difference in the arm strengths or pitch angles of spiral galaxies in clusters compared to field galaxies. When differences in concentration are taken into account, we also find no significant difference in the parameter f3 for cluster spirals compared to field spirals, where f3 is the normalized m = 3 Fourier amplitude. When concentration is held fixed, both arm strength and pitch angle are correlated with sSFR, but f3 is not. These relations support the suggestion by Davis et al. of a "fundamental plane" of spiral structure involving pitch angle, bulge stellar mass, and gas surface density. We discuss these results in terms of theories of spiral arm production and quenching in galaxies. To aid comparison with earlier studies based on Galaxy Zoo, we explore how the Yu & Ho parameters relate to similar parameters measured by Galaxy Zoo (i.e., f3 versus the number of arms, pitch angle versus winding parameter, and concentration versus bulge class).
79 ASTRONOMY AND ASTROPHYSICS↗
FAST discovery of an extremely radio-faint millisecond pulsar from the Fermi -LAT unassociated source 3FGL J0318.1+0252
High sensitivity radio searches of unassociated γ-ray sources have proven to be an effective way of finding new pulsars. Using the Five-hundred-meter Aperture Spherical radio Telescope (FAST) during its commissioning phase, we have carried out a number of targeted deep searches of Fermi Large Area Telescope (LAT) γ-ray sources. On February 27, 2018 we discovered an isolated millisecond pulsar (MSP), PSR J0318+0253, coincident with the unassociated γ-ray source 3FGL J0318.1+0252. PSR J0318+0253 has a spin period of 5.19 ms, a dispersion measure (DM) of 26 pc cm –3 corresponding to a DM distance of about 1.3 kpc, and a period-averaged flux density of (~11±2) µJy at L-band (1.05–1.45 GHz). Among all high energy MSPs, PSR J0318+0253 is the faintest ever detected in radio bands, by a factor of at least ~4 in terms of L-band fluxes. With the aid of the radio ephemeris, an analysis of 9.6 years of Fermi-LAT data revealed that PSR J0318+0253 also displays strong γ-ray pulsations. Follow-up observations carried out by both Arecibo and FAST suggest a likely spectral turn-over around 350 MHz. This is the first result from the collaboration between FAST and the Fermi-LAT teams as well as the first confirmed new MSP discovery by FAST, raising hopes for the detection of many more MSPs. Finally, such discoveries will make a significant contribution to our understanding of the neutron star zoo while potentially contributing to the future detection of gravitational waves, via pulsar timing array (PTA) experiments.
79 ASTRONOMY AND ASTROPHYSICS↗
tinyIFD: A High-Throughput Binding Pose Refinement Workflow Through Induced-Fit Ligand Docking
A critical step in structure-based drug discovery is predicting whether and how a candidate molecule binds to a model of a therapeutic target. However, substantial protein side chain movements prevent current screening methods, such as docking, from accurately predicting the ligand conformations and require expensive refinements to produce viable candidates. Here, we present the development of a high-throughput and flexible ligand pose refinement workflow, called “tinyIFD”. The main features of the workflow include the use of specialized high-throughput, small-system MD simulation code mdgx.cuda and an actively learning model zoo approach. We show the application of this workflow on a large test set of diverse protein targets, achieving 66% and 76% success rates for finding a crystal-like pose within the top-2 and top-5 poses, respectively. We also applied this workflow to the SARS-CoV-2 main protease (M pro ) inhibitors, where we demonstrate the benefit of the active learning aspect in this workflow.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Tests of the DFT Ladder for the Fulminic Acid Challenge
Properties of the historically pivotal fulminic acid (HCNO) molecule have been computed with a panoply of 473 density functionals of all varieties, providing a snapshot of the performance of contemporary density functional theory (DFT) for a challenging chemical system. Exhaustive tabulations and statistical analyses have been carried out for geometric parameters, vibrational frequencies, barriers to linearity, and the HCN–O dissociation energy. As the DFT ladder is climbed, confusion rather than consensus ensues regarding the details of the distinctive, extremely flat H–C–N bending potential of fulminic acid and whether the equilibrium structure is linear or bent. While high-ranking DFT functionals produce the smallest errors for the HCN + O( 3 P) → HCNO reaction energy, lower rungs emerge as the best performers for many of the bond distances and harmonic vibrational frequencies. This research shows that the current DFT zoo of approximations does not constitute a transparent ladder of increasingly accurate methods that consistently converges on definitive predictions for various properties of HCNO. Additional analyses are performed on the side effects of popular dispersion corrections on the covalently bonded properties and thermochemistry of HCNO.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Galápagos tortoise stable isotope ecology and the 1850s Floreana Island Chelonoidis niger niger extinction
A consequence of over 400 years of human exploitation of Galápagos tortoises (Chelonoidis niger ssp.) is the extinction of several subspecies and the decimation of others. As humans captured, killed, and/or removed tortoises for food, oil, museums, and zoos, they also colonized the archipelago resulting in the introduction of invasive plants, animals, and manipulated landscapes for farming, ranching, and infrastructure. Given current conservation and revitalization efforts for tortoises and their habitats, here we investigate nineteenth and twentieth century Galápagos tortoise dietary ecology using museum and archaeological specimens coupled with analysis of carbon (δ 13 C collagen and δ 13 Capatite), nitrogen (δ 15 N), hydrogen (δD) and oxygen (δ 18 O apatite ) stable isotopes and radiocarbon dating. We identify that Galápagos tortoise diets vary between and within islands over time, and that long-term anthropogenic impacts influenced change in tortoise stable isotope ecology by using 57 individual tortoises from 10 different subspecies collected between 1833 and 1967—a 134-year period. On lower elevation islands, which are often hotter and drier, tortoises tend to consume more C 4 vegetation (cacti and grasses). Our research suggests human exploitation of tortoises and anthropogenic impacts on vegetation contributed to the extinction of the Floreana Island tortoise (C. n. niger) in the 1850s.
59 BASIC BIOLOGICAL SCIENCES↗
Merger identification through photometric bands, colours, and their errors
Aims. We present the application of a fully connected neural network (NN) for galaxy merger identification using exclusively photometric information. Our purpose is not only to test the method’s efficiency, but also to understand what merger properties the NN can learn and what their physical interpretation is. Methods. We created a class-balanced training dataset of 5860 galaxies split into mergers and non-mergers. The galaxy observations came from SDSS DR6 and were visually identified in Galaxy Zoo. The 2930 mergers were selected from known SDSS mergers and the respective non-mergers were the closest match in both redshift and r magnitude. The NN architecture was built by testing a different number of layers with different sizes and variations of the dropout rate. We compared input spaces constructed using: the five SDSS filters: u, g, r, i, and z; combinations of bands, colours, and their errors; six magnitude types; and variations of input normalization. Results. We find that the fibre magnitude errors contribute the most to the training accuracy. Studying the parameters from which they are calculated, we show that the input space built from the sky error background in the five SDSS bands alone leads to 92.64 ± 0.15% training accuracy. We also find that the input normalization, that is to say, how the data are presented to the NN, has a significant effect on the training performance. Conclusions. We conclude that, from all the SDSS photometric information, the sky error background is the most sensitive to merging processes. This finding is supported by an analysis of its five-band feature space by means of data visualization. Moreover, studying the plane of the g and r sky error bands shows that a decision boundary line is enough to achieve an accuracy of 91.59%.
79 ASTRONOMY AND ASTROPHYSICS↗
Review: knots and other new topological effects in liquid crystals and colloids
Abstract Humankind has been obsessed with knots in religion, culture and daily life for millennia, while physicists like Gauss, Kelvin and Maxwell already involved them in models centuries ago. Nowadays, colloidal particles can be fabricated to have shapes of knots and links with arbitrary complexity. In liquid crystals, closed loops of singular vortex lines can be knotted by using colloidal particles and laser tweezers, as well as by confining nematic fluids into micrometer-sized droplets with complex topology. Knotted and linked colloidal particles induce knots and links of singular defects, which can be interlinked (or not) with colloidal particle knots, revealing the diversity of interactions between topologies of knotted fields and topologically nontrivial surfaces of colloidal objects. Even more diverse knotted structures emerge in nonsingular molecular alignment and magnetization fields in liquid crystals and colloidal ferromagnets. The topological solitons include hopfions, skyrmions, heliknotons, torons and other spatially localized continuous structures, which are classified based on homotopy theory, characterized by integer-valued topological invariants and often contain knotted or linked preimages, nonsingular regions of space corresponding to single points of the order parameter space. A zoo of topological solitons in liquid crystals, colloids and ferromagnets promises new breeds of information displays and a plethora of data storage, electro-optic and photonic applications. Their particle-like collective dynamics echoes coherent motions in active matter, ranging from crowds of people to schools of fish. This review discusses the state of the art in the field, as well as highlights recent developments and open questions in physics of knotted soft matter. We systematically overview knotted field configurations, the allowed transformations between them, their physical stability and how one can use one form of knotted fields to model, create and imprint other forms. The large variety of symmetries accessible to liquid crystals and colloids offer insights into stability, transformation and emergent dynamics of fully nonsingular and singular knotted fields of fundamental and applied importance. The common thread of this review is the ability to experimentally visualize these knots in real space. The review concludes with a discussion of how the studies of knots in liquid crystals and colloids can offer insights into topologically related structures in other branches of physics, with answers to many open questions, as well as how these experimentally observable knots hold a strong potential for providing new inspirations to the mathematical knot theory.
Physics↗
Pre-training Vision Models for the Classification of Alerts from Wide-field Time-domain Surveys
Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.
79 ASTRONOMY AND ASTROPHYSICS↗
Toroidal modeling of Alfvén eigenmodes excited by runaway electrons in DIII-D and ITER
The non-perturbative MHD-kinetic hybrid code MARS-K (Liu et al 2014 Phys. Plasmas 21 056105) is updated to include relativistic effects for kinetic fast particles, enabling the code to model excitation of Alfvén eigenmodes (AEs) by runaway electrons (REs) in post-disruption tokamak plasmas. Applying the updated code to RE beams in both DIII-D and ITER, a zoo of AE modes triggered by trapped REs due to precessional drift-kinetic resonances is computed while scanning the RE energy. At fixed RE energy, multiple unstable roots are also excited. These AE modes possess radially different eigenmode structures, ranging from global modes to core-localized ones. The computed mode frequency is in the Alfvén frequency range, increasing with the assumed RE energy in a staircase fashion and quantitatively matching the experimental measurement (in DIII-D). At the (more relevant) high-frequency range (above 1 MHz), the modeled eigenmodes are identified as compressional AEs (CAEs) in DIII-D and a mixture of CAE and shear Alfvén waves in ITER.
Alfvén eigenmodes↗
Clues on the history of early-type galaxies from SDSS spectra and GALEX photometry
ABSTRACT Stellar population studies of early-type galaxies (ETGs) based on their optical stellar continuum suggest that these are quiescent systems. However, emission lines and ultraviolet photometry reveal a diverse population. We use a new version of the starlight spectral synthesis code and state-of-the-art stellar population models to simultaneously fit Sloan Digital Sky Survey spectra and Galaxy Evolution Explorer photometry for a sample of 3453 galaxies at z < 0.1 with near ultraviolet (NUV) − r > 5 that are classified as elliptical by Galaxy Zoo. We reproduce far ultraviolet (FUV) magnitudes for 80 per cent of UV upturn galaxies selected using criteria from the literature, suggesting that additional stellar population ingredients such as binaries and extreme horizontal branch stars may have a limited contribution to the UV upturn. The addition of ultraviolet data leads to a broadening of the distributions of mean stellar ages, metallicities, and attenuation. Stellar populations younger than $1\,$ Gyr are required to reproduce the ultraviolet emission in 17 per cent of our sample. These systems represent 43 per cent of the sample at 5 < NUV − r < 5.5 and span the same stellar mass range as other ETGs in our sample. ETGs with young stellar components have larger H α equivalent widths (WH α) and larger dust attenuation. Emission line ratios and WH α indicate that the ionizing source in these systems is a mixture of young and old stellar populations. Their young stellar populations are metal-poor, especially for high-mass galaxies, indicating recent star formation associated with rejuvenation events triggered by external processes, such as minor mergers.
Werle, A.↗