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We study the intracluster light (ICL) and intracluster globular clusters (ICGCs) in the nearby Perseus galaxy cluster using Euclid's EROs. By modelling the isophotal and iso-density contours, we map the distributions and properties of the ICL and ICGCs out to a radius of 600 kpc (~1/3 of the virial radius) from the brightest cluster galaxy (BCG). We find that the central 500 kpc of the Perseus cluster hosts 70000$\pm$2800 GCs and $1.6\times10^{12}$ L$_\odot$ of diffuse light from the BCG+ICL in the near-infrared H$_E$. This accounts for 37$\pm$6% of the cluster's total stellar luminosity within this radius. The ICL and ICGCs share a coherent spatial distribution, suggesting a common origin or that a common potential governs their distribution. Their contours on the largest scales (>200 kpc) are offset from the BCG's core westwards by 60 kpc towards several luminous cluster galaxies. This offset is opposite to the displacement observed in the gaseous intracluster medium. The radial surface brightness profile of the BCG+ICL is best described by a double S\'ersic model, with 68$\pm$4% of the H$_E$ light in the extended, outer component. The transition between these components occurs at ~50 kpc, beyond which the isophotes become increasingly elliptical and off-centred. The radial ICGC number density profile closely follows the BCG+ICL profile only beyond this 50 kpc radius, where we find an average of 60 GCs per $10^9$ M$_\odot$ of diffuse stellar mass. The BCG+ICL colour becomes increasingly blue with radius, consistent with the stellar populations in the ICL having subsolar metallicities [Fe/H]~-0.6. The colour of the ICL, and the specific frequency and luminosity function of the ICGCs suggest that the ICL+ICGCs were tidally stripped from the outskirts of massive satellites with masses of a few $\times10^{10}$ M$_\odot$, with an increasing contribution from dwarf galaxies at large radii., Comment: Paper submitted as part of the A&A special issue `Euclid on Sky', which contains Euclid key reference papers and first results from the Euclid Early Release Observations. 24 pages, 17 figures, 5 tables. Submitted to A&A

We introduce Mixtral 8x7B, a Sparse Mixture of Experts (SMoE) language model. Mixtral has the same architecture as Mistral 7B, with the difference that each layer is composed of 8 feedforward blocks (i.e. experts). For every token, at each layer, a router network selects two experts to process the current state and combine their outputs. Even though each token only sees two experts, the selected experts can be different at each timestep. As a result, each token has access to 47B parameters, but only uses 13B active parameters during inference. Mixtral was trained with a context size of 32k tokens and it outperforms or matches Llama 2 70B and GPT-3.5 across all evaluated benchmarks. In particular, Mixtral vastly outperforms Llama 2 70B on mathematics, code generation, and multilingual benchmarks. We also provide a model fine-tuned to follow instructions, Mixtral 8x7B - Instruct, that surpasses GPT-3.5 Turbo, Claude-2.1, Gemini Pro, and Llama 2 70B - chat model on human benchmarks. Both the base and instruct models are released under the Apache 2.0 license., Comment: See more details at https://mistral.ai/news/mixtral-of-experts/

This study explores a VR-based intervention for Visuospatial neglect (VSN), a post-stroke condition. It aims to develop a VR task utilizing interactive visual-audio cues to improve sensory-motor training and assess its impact on VSN patients' engagement and performance. Collaboratively designed with physiotherapists, the VR task uses directional and auditory stimuli to alert and direct patients, tested over 12 sessions with two individuals. Results show a consistent decrease in task completion variability and positive patient feedback, highlighting the VR task's potential for enhancing engagement and suggesting its feasibility in rehabilitation. The study underlines the significance of collaborative design in healthcare technology and advocates for further research with a larger sample size to confirm the benefits of VR in VSN treatment, as well as its applicability to other multimodal disorders., Comment: 29 pages, 8 figures, 5 tables

We introduce Mistral 7B v0.1, a 7-billion-parameter language model engineered for superior performance and efficiency. Mistral 7B outperforms Llama 2 13B across all evaluated benchmarks, and Llama 1 34B in reasoning, mathematics, and code generation. Our model leverages grouped-query attention (GQA) for faster inference, coupled with sliding window attention (SWA) to effectively handle sequences of arbitrary length with a reduced inference cost. We also provide a model fine-tuned to follow instructions, Mistral 7B -- Instruct, that surpasses the Llama 2 13B -- Chat model both on human and automated benchmarks. Our models are released under the Apache 2.0 license., Comment: Models and code are available at https://mistral.ai/news/announcing-mistral-7b/

Financial firms commonly process and store billions of time-series data, generated continuously and at a high frequency. To support efficient data storage and retrieval, specialized time-series databases and systems have emerged. These databases support indexing and querying of time-series by a constrained Structured Query Language(SQL)-like format to enable queries like "Stocks with monthly price returns greater than 5%", and expressed in rigid formats. However, such queries do not capture the intrinsic complexity of high dimensional time-series data, which can often be better described by images or language (e.g., "A stock in low volatility regime"). Moreover, the required storage, computational time, and retrieval complexity to search in the time-series space are often non-trivial. In this paper, we propose and demonstrate a framework to store multi-modal data for financial time-series in a lower-dimensional latent space using deep encoders, such that the latent space projections capture not only the time series trends but also other desirable information or properties of the financial time-series data (such as price volatility). Moreover, our approach allows user-friendly query interfaces, enabling natural language text or sketches of time-series, for which we have developed intuitive interfaces. We demonstrate the advantages of our method in terms of computational efficiency and accuracy on real historical data as well as synthetic data, and highlight the utility of latent-space projections in the storage and retrieval of financial time-series data with intuitive query modalities., Comment: Accepted to ICAIF 2023

Time series imputation remains a significant challenge across many fields due to the potentially significant variability in the type of data being modelled. Whilst traditional imputation methods often impose strong assumptions on the underlying data generation process, limiting their applicability, researchers have recently begun to investigate the potential of deep learning for this task, inspired by the strong performance shown by these models in both classification and regression problems across a range of applications. In this work we propose MADS, a novel auto-decoding framework for time series imputation, built upon implicit neural representations. Our method leverages the capabilities of SIRENs for high fidelity reconstruction of signals and irregular data, and combines it with a hypernetwork architecture which allows us to generalise by learning a prior over the space of time series. We evaluate our model on two real-world datasets, and show that it outperforms state-of-the-art methods for time series imputation. On the human activity dataset, it improves imputation performance by at least 40%, while on the air quality dataset it is shown to be competitive across all metrics. When evaluated on synthetic data, our model results in the best average rank across different dataset configurations over all baselines., Comment: 8 pages (inc. refs), 1 figure

Galaxy morphologies provide valuable insights into their formation processes, tracing the spatial distribution of ongoing star formation and encoding signatures of dynamical interactions. While such information has been extensively investigated at low redshift, it is crucial to develop a robust system for characterising galaxy morphologies at earlier cosmic epochs. Relying solely on the nomenclature established for low-redshift galaxies risks introducing biases that hinder our understanding of this new regime. In this paper, we employ variational auto-encoders to perform feature extraction on galaxies at z $>$ 2 using JWST/NIRCam data. Our sample comprises 6869 galaxies at z $>$ 2, including 255 galaxies z $>$ 5, which have been detected in both the CANDELS/HST fields and CEERS/JWST, ensuring reliable measurements of redshift, mass, and star formation rates. To address potential biases, we eliminate galaxy orientation and background sources prior to encoding the galaxy features, thereby constructing a physically meaningful feature space. We identify 11 distinct morphological classes that exhibit clear separation in various structural parameters, such as CAS-$M_{20}$, S\'ersic indices, specific star formation rates, and axis ratios. We observe a decline in the presence of spheroidal-type galaxies with increasing redshift, indicating a dominance of disk-like galaxies in the early universe. We demonstrate that conventional visual classification systems are inadequate for high-redshift morphology classification and advocate the need for a more detailed and refined classification scheme. Leveraging machine-extracted features, we propose a solution to this challenge and illustrate how our extracted clusters align with measured parameters, offering greater physical relevance compared to traditional methods., Comment: 29 pages, 17 figures, accepted for publication in ApJ

The morphology of a galaxy has been shown to encode the evolutionary history and correlates strongly with physical properties such as stellar mass, star formation rates and past merger events. While the majority of galaxies in the local universe can be classified on the Hubble sequence, little is known about the different types of galaxies we observe at high redshift. The irregular morphology of these galaxies makes visual classifications difficult, and with the future of astronomy consisting of many "Big Data" surveys we need an efficient, and unbiased classification system in place. In this work we explore the use of unsupervised machine learning techniques to preform feature extraction from galaxy images to separate high redshift galaxies into different morphological types based on the machine learning clusters. We expand on previous work by addressing observation biases such as the orientation, apparent size of the galaxies and noise before extracting features, thus reducing the number of clusters and forcing the network to learn meaningful features. We then compare the extracted clusters' physical properties, to investigate the separation between the groups., Comment: 5 pages, accepted for publication in Memorie della SAIt

The Lunar Orbital Platform-Gateway (LOP-Gateway, or simply Gateway) is a crewed platform that will be assembled and operated in the vicinity of the Moon by NASA and international partner organizations, including ESA, starting from the mid-2020s. It will offer new opportunities for fundamental and applied scientific research. The Moon is a unique location to study the deep space plasma environment. Moreover, the lunar surface and the surface-bounded exosphere are interacting with this environment, constituting a complex multi-scale interacting system. This paper examines the opportunities provided by externally mounted payloads on the Gateway in the field of space plasma physics, heliophysics and space weather, but also examines the impact of the space environment on an inhabited platform in the vicinity of the Moon. It then presents the conceptual design of a model payload, required to perform these space plasma measurements and observations. It results that the Gateway is very well-suited for space plasma physics research. It allows a series of scientific objectives with a multidisciplinary dimension to be addressed.

Progress in reinforcement learning (RL) research is often driven by the design of new, challenging environments -- a costly undertaking requiring skills orthogonal to that of a typical machine learning researcher. The complexity of environment development has only increased with the rise of procedural-content generation (PCG) as the prevailing paradigm for producing varied environments capable of testing the robustness and generalization of RL agents. Moreover, existing environments often require complex build processes, making reproducing results difficult. To address these issues, we introduce GriddlyJS, a web-based Integrated Development Environment (IDE) based on the Griddly engine. GriddlyJS allows researchers to visually design and debug arbitrary, complex PCG grid-world environments using a convenient graphical interface, as well as visualize, evaluate, and record the performance of trained agent models. By connecting the RL workflow to the advanced functionality enabled by modern web standards, GriddlyJS allows publishing interactive agent-environment demos that reproduce experimental results directly to the web. To demonstrate the versatility of GriddlyJS, we use it to quickly develop a complex compositional puzzle-solving environment alongside arbitrary human-designed environment configurations and their solutions for use in automatic curriculum learning and offline RL. The GriddlyJS IDE is open source and freely available at https://griddly.ai.

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

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/

If humanity is ever to consider substantial, long-term colonization of Mars, the resources needed are going to be extensive. For a long-term human presence on Mars to be established, serious thought would need to be given to terraforming the planet. One major requirement for such terraforming is having the protection of a planetary magnetic field which Mars currently does not have. In this article we explore comprehensively for the first time, the practical and engineering challenges that affect the feasibility of creating an artificial magnetic field capable of encompassing Mars. This includes the concerns that define the design, where to locate the magnetic field generator and possible construction strategies. The rationale here is not to justify the need for a planetary magnetosphere but to put figures on the practicalities so as to be able to weigh the pros and cons of the different engineering approaches. The optimum solution proposed is completely novel, although inspired by natural situations and fusion plasma techniques. The solution with the lowest power, assembly and mass is to create an artificial charged particle ring (similar in form to a "radiation belt"), around the planet possibly formed by ejecting matter from one of the moons of Mars (in fashion similar to that that forms the Io-Jupiter plasma torus), but using electromagnetic and plasma waves to drive a net current in the ring(s) that results in an overall magnetic field. With a new era of space exploration underway, this is the time to start thinking about these new and bold future concepts and to begin filling strategic knowledge gaps. Furthermore, the principles explored here are also applicable to smaller scale objects like manned spacecraft, space stations or moon bases, which would benefit from the creation of protective mini-magnetospheres., Comment: Accepted for publication Acta Astronautica Sept 2021

We provide a model-independent reconstruction of dark energy from $z=0$ to $ \gtrsim 10^5$. We parameterise the model by a perfect fluid with a series of physically well-motivated bins in energy-density, such that the equation of state is always $-1 \le w \le 1$. Our method is capable of describing a range of theoretical models with smooth modifications to the expansion history. Combining the latest CMB, BAO, SN and local $H_0$ measurements, we obtain a large improvement of $\Delta \chi^2=41.3$ over LCDM, at the expense of 33 additional parameters in the fit, with dark energy contributing significantly between $z \sim 10^4 - 10^5$, and intriguingly with a sound speed $c_s^2 \sim 1/3$. A significant part of the $\Delta \chi^2$ improvement comes from \Planck\ + Atacama Cosmology Telescope (\textsc{Act}) data, alleviating tension between them within LCDM. We apply a correlation prior to penalise models with unnecessary degrees of freedom and find no preference for deviations from LCDM at late-times, but moderate Bayesian evidence of an early dark energy (EDE) component. Although the model has a large amount of freedom, it is unable to reduce $S_8 \equiv \sigma_8 (\Omega_\mathrm{c} / 0.3)^{0.5}$ below that of \lcdm, to bring about full concordance with large-scale structure data., Comment: 7 pages, 3 figures

There have been a number of corner detection methods proposed for event cameras in the last years, since event-driven computer vision has become more accessible. Current state-of-the-art have either unsatisfactory accuracy or real-time performance when considered for practical use, for example when a camera is randomly moved in an unconstrained environment. In this paper, we present yet another method to perform corner detection, dubbed look-up event-Harris (luvHarris), that employs the Harris algorithm for high accuracy but manages an improved event throughput. Our method has two major contributions, 1. a novel "threshold ordinal event-surface" that removes certain tuning parameters and is well suited for Harris operations, and 2. an implementation of the Harris algorithm such that the computational load per event is minimised and computational heavy convolutions are performed only "as-fast-as-possible", i.e. only as computational resources are available. The result is a practical, real-time, and robust corner detector that runs more than 2.6x the speed of current state-of-the-art; a necessity when using high-resolution event-camera in real-time. We explain the considerations taken for the approach, compare the algorithm to current state-of-the-art in terms of computational performance and detection accuracy, and discuss the validity of the proposed approach for event cameras.

In recent years, researchers have achieved great success in applying Deep Reinforcement Learning (DRL) algorithms to Real-time Strategy (RTS) games, creating strong autonomous agents that could defeat professional players in StarCraft~II. However, existing approaches to tackle full games have high computational costs, usually requiring the use of thousands of GPUs and CPUs for weeks. This paper has two main contributions to address this issue: 1) We introduce Gym-$\mu$RTS (pronounced "gym-micro-RTS") as a fast-to-run RL environment for full-game RTS research and 2) we present a collection of techniques to scale DRL to play full-game $\mu$RTS as well as ablation studies to demonstrate their empirical importance. Our best-trained bot can defeat every $\mu$RTS bot we tested from the past $\mu$RTS competitions when working in a single-map setting, resulting in a state-of-the-art DRL agent while only taking about 60 hours of training using a single machine (one GPU, three vCPU, 16GB RAM). See the blog post at https://wandb.ai/vwxyzjn/gym-microrts-paper/reports/Gym-RTS-Toward-Affordable-Deep-Reinforcement-Learning-Research-in-Real-Time-Strategy-Games--Vmlldzo2MDIzMTg and the source code at https://github.com/vwxyzjn/gym-microrts-paper, Comment: Accepted to IEEE Conference of Games (COG) 2021. See the blog post at https://wandb.ai/vwxyzjn/gym-microrts-paper/reports/Gym-RTS-Toward-Affordable-Deep-Reinforcement-Learning-Research-in-Real-Time-Strategy-Games--Vmlldzo2MDIzMTg and the source code at https://github.com/vwxyzjn/gym-microrts-paper

There are relatively few conventions followed in reinforcement learning (RL) environments to structure the action spaces. As a consequence the application of RL algorithms to tasks with large action spaces with multiple components require additional effort to adjust to different formats. In this paper we introduce {\em Conditional Action Trees} with two main objectives: (1) as a method of structuring action spaces in RL to generalise across several action space specifications, and (2) to formalise a process to significantly reduce the action space by decomposing it into multiple sub-spaces, favoring a multi-staged decision making approach. We show several proof-of-concept experiments validating our scheme, ranging from environments with basic discrete action spaces to those with large combinatorial action spaces commonly found in RTS-style games.

A detailed study of the morphology of lenticular galaxies is an important way to understand how this type of galaxy formed and evolves over time. Decomposing a galaxy into its components (disc, bulge, bar, ...) allows recovering the colour gradients present in each system, its star formation history, and its assembly history. We use GALFITM to perform a multi-wavelength structural decomposition of the closest lenticular galaxy, NGC 3115, resulting in the description of its stellar light into several main components: a bulge, a thin disc, a thick disc and also evidence of a bar. We report the finding of central bluer stellar populations in the bulge, as compared to the colour of the galaxy outskirts, indicating either the presence of an Active Galactic Nucleus (AGN) and/or recent star formation activity. From the spectral energy distribution results, we show that the galaxy has a low luminosity AGN component, but even excluding the effect of the nuclear activity, the bulge is still bluer than the outer-regions of the galaxy, revealing a recent episode of star formation. Based on all of the derived properties, we propose a scenario for the formation of NGC 3115 consisting of an initial gas-rich merger, followed by accretions and feedback that quench the galaxy, until a recent encounter with the companion KK084 that reignited the star formation in the bulge, provoked a core displacement in NGC 3115 and generated spiral-like features. This result is consistent with the two-phase formation scenario, proposed in previous studies of this galaxy., Comment: Accepted for publication in MNRAS: 22 pages, 15 figures, 7 tables, 1 appendix

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

At high redshift, due to both observational limitations and the variety of galaxy morphologies in the early universe, measuring galaxy structure can be challenging. Non-parametric measurements such as the CAS system have thus become an important tool due to both their model-independent nature and their utility as a straightforward computational process. Recently, convolutional neural networks (CNNs) have been shown to be adept at image analysis, and are beginning to supersede traditional measurements of visual morphology and model-based structural parameters. In this work, we take a further step by extending CNNs to measure well known non-parametric structural quantities: concentration ($C$) and asymmetry ($A$). We train CNNs to predict $C$ and $A$ from individual images of $\sim 150,000$ galaxies at $0 < z < 7$ in the CANDELS fields, using Bayesian hyperparameter optimisation to select suitable network architectures. Our resulting networks accurately reproduce measurements compared with standard algorithms. Furthermore, using simulated images, we show that our networks are more stable than the standard algorithms at low signal-to-noise. While both approaches suffer from similar systematic biases with redshift, these remain small out to $z \sim 7$. Once trained, measurements with our networks are $> 10^3$ times faster than previous methods. Our approach is thus able to reproduce standard measures of non-parametric morphologies and shows the potential of employing neural networks to provide superior results in substantially less time. This will be vital for making best use of the large and complex datasets provided by upcoming galaxy surveys, such as Euclid and Rubin-LSST., Comment: 18 pages, 13 figures, accepted for publication in ApJ

In recent years, there have been immense breakthroughs in Game AI research, particularly with Reinforcement Learning (RL). Despite their success, the underlying games are usually implemented with their own preset environments and game mechanics, thus making it difficult for researchers to prototype different game environments. However, testing the RL agents against a variety of game environments is critical for recent effort to study generalization in RL and avoid the problem of overfitting that may otherwise occur. In this paper, we present Griddly as a new platform for Game AI research that provides a unique combination of highly configurable games, different observer types and an efficient C++ core engine. Additionally, we present a series of baseline experiments to study the effect of different observation configurations and generalization ability of RL agents.

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

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., Comment: 25 pages, 16 figures, 2 tables. ApJ accepted

Access to a fast and easily copied forward model of a game is essential for model-based reinforcement learning and for algorithms such as Monte Carlo tree search, and is also beneficial as a source of unlimited experience data for model-free algorithms. Learning forward models is an interesting and important challenge in order to address problems where a model is not available. Building upon previous work on the Neural GPU, this paper introduces the Neural Game Engine, as a way to learn models directly from pixels. The learned models are able to generalise to different size game levels to the ones they were trained on without loss of accuracy. Results on 10 deterministic General Video Game AI games demonstrate competitive performance, with many of the games models being learned perfectly both in terms of pixel predictions and reward predictions. The pre-trained models are available through the OpenAI Gym interface and are available publicly for future research here: \url{https://github.com/Bam4d/Neural-Game-Engine}

Dust lanes bisect the plane of a typical edge-on spiral galaxy as a dark optical absorption feature. Their appearance is linked to the gravitational stability of spiral disks; the fraction of edge-on galaxies that displays a dust lane is a direct indicator of the typical vertical balance between gravity and turbulence; a balance struck between the energy input from star-formation and the gravitational pull into the plane of the disk. Based on morphological classifications by the Galaxy~Zoo project on the Kilo-Degree Survey (KiDS) imaging data in the Galaxy and Mass Assembly (GAMA) fields, we explore the relation of dust lanes to the galaxy characteristics, most of which were determined using the {\sc magphys} spectral energy distribution fitting tool: stellar mass, total and specific star-formation rates, and several parameters describing the cold dust component. We find that the fraction of dust lanes does depend on the stellar mass of the galaxy; they start to appear at $M^* \sim 10^9 M_\odot$. A dust lane also implies strongly a dust mass of at least $10^5 M_\odot$, but otherwise does not correlate with cold dust mass parameters of the {\sc magphys} spectral energy distribution analysis, nor is there a link with star-formation rate, specific or total. Dust lane identification does not depend on disk ellipticity (disk thickness) or Sersic profile but correlates with bulge morphology; a round bulge favors dust lane votes. The central component along the line of sight that produces the dust lane is not associated with either one of the components fit by {\sc magphys}, the cold diffuse component or the localized, heated component in HII regions, but a mix of these two., Comment: Accepted for publication in the Astronomical Journal

We present a multi-wavelength analysis of the galaxies in nine clusters selected from the WINGS dataset, examining how galaxy structure varies as a function of wavelength and environment using the state of the art software GALAPAGOSII. We simultaneously fit single S\'ersic functions on three optical (u, B and V) and two near-infrared (J and K) bands thus creating a wavelength-dependent model of each galaxy. We measure the magnitudes, effective radius ($R_{e}$) the S\'ersic index ($n$), axis ratio and position angle in each band. The sample contains 790 cluster members (located close to the cluster center < 0.64 R$_{200}$ and 254 non-member galaxies that we further separate based on their morphology into ellipticals, lenticulars and spirals. We find that the S\'ersic index of all galaxies inside clusters remains nearly constant with wavelength while $R_{e}$ decreases as wavelength increases for all morphological types. We do not observe a significant variation on n and $R_{e}$ as a function of projected local density and distance from the clusters center. Comparing the n and $R_{e}$ of bright cluster galaxies with a subsample of non-member galaxies we find that bright cluster galaxies are more concentrated (display high $n$ values) and are more compact (low $R_{e}$). Moreover, the light profile ($\mathcal{N}$) and size ($\mathcal{R}$) of bright cluster galaxies does not change as a function of wavelength in the same manner as non-member galaxies., Comment: 16 pages, 17 figures and 5 tables

We use Bayesian convolutional neural networks and a novel generative model of Galaxy Zoo volunteer responses to infer posteriors for the visual morphology of galaxies. Bayesian CNN can learn from galaxy images with uncertain labels and then, for previously unlabelled galaxies, predict the probability of each possible label. Our posteriors are well-calibrated (e.g. for predicting bars, we achieve coverage errors of 11.8% within a vote fraction deviation of 0.2) and hence are reliable for practical use. Further, using our posteriors, we apply the active learning strategy BALD to request volunteer responses for the subset of galaxies which, if labelled, would be most informative for training our network. We show that training our Bayesian CNNs using active learning requires up to 35-60% fewer labelled galaxies, depending on the morphological feature being classified. By combining human and machine intelligence, Galaxy Zoo will be able to classify surveys of any conceivable scale on a timescale of weeks, providing massive and detailed morphology catalogues to support research into galaxy evolution., Comment: Accepted by MNRAS. 21 pages, including appendices

This paper investigates the effect of learning a forward model on the performance of a statistical forward planning agent. We transform Conway's Game of Life simulation into a single-player game where the objective can be either to preserve as much life as possible or to extinguish all life as quickly as possible. In order to learn the forward model of the game, we formulate the problem in a novel way that learns the local cell transition function by creating a set of supervised training data and predicting the next state of each cell in the grid based on its current state and immediate neighbours. Using this method we are able to harvest sufficient data to learn perfect forward models by observing only a few complete state transitions, using either a look-up table, a decision tree or a neural network. In contrast, learning the complete state transition function is a much harder task and our initial efforts to do this using deep convolutional auto-encoders were less successful. We also investigate the effects of imperfect learned models on prediction errors and game-playing performance, and show that even models with significant errors can provide good performance., Comment: Submitted to IEEE Conference on Games 2019

We present the results of a systematic search and characterisation of jellyfish galaxy candidates in the multi-cluster system A901/2, at z ~ 0.165, as part of the OMEGA survey. By visual inspecting ACS/HST F606W images looking for morphological signatures of ram-pressure stripping events in Halpha-emitting galaxies, we identify a total of 70 candidates. Out of these, 53 are clearly star-forming galaxies and 5 are highly probable AGN hosts, the classification of the remaining galaxies is more uncertain. They have late-type and irregular morphologies and most of them are part of the blue cloud with only 4 being previously classified as dusty reds. The AGN activity is not prominent in the sample and, of the few cases of galaxies hosting AGN, such activity does not seem to be correlated to the gas stripping phenomenon. Our jellyfish galaxy candidates do not have a preferential pattern of motion within the multi-cluster system, although the most compelling cases appear to inhabit the inner regions of the most massive sub-cluster centres. The sSFR of these galaxies indicates that their star formation activity is enhanced, in contrast with what is observed for the rest of the star-forming galaxy population in the system. Half of the sample is forming stars at a higher rate than the main-sequence for field galaxies and this behaviour is more evident for the most compelling candidates. For some galaxies, the spatially resolved Halpha emission appears to be as disturbed and extended as their continuum counterparts. Our findings point towards a scenario where the ram pressure stripping is triggering a period of intense and extended star formation throughout the galaxy while it is also disturbing the morphology. This is the largest sample of jellyfish galaxy candidates found in a single system suggesting that cluster mergers might be the ideal environment for studying ram pressure stripping effects., Comment: 15 pages, 9 figures, MNRAS accepted

In this paper we study the reconfinement of initially freely-expanding unmagnetised relativistic jets by the pressure of non-uniform external gas using numerical approach. The results are compared with the simple semi-analytic model proposed by Komissarov & Falle (1997). In particular, we explore the reconfinement in power-law atmospheres and in the King atmosphere, which describes the X-ray coronas of giant elliptic galaxies. The results show significant deviations from the KF model, which systematically underestimates the reconfinement scale. For the power-law atmospheres the disagreement increases with the power index k, exceeding two orders of magnitude for k=1.5. For the King model, strong deviations are found on the outskirts of the atmosphere, where the distribution approaches a power law. However for jets reconfined inside the core, the reconfinement scale is increased only by the factor of two. When the King model is modified by adding a central cusp, this has little impact on the jets which are reconfined outside of the cusp region but inside the cusp the reconfinement scale significantly reduces., Comment: Submitted to Computational Astrophysics and Cosmology

We study the effect of inclination on the apparent brightness of star-forming galaxies in spectral passbands that are commonly used as star-formation indicators. As diagnostics we use mass-to-light ratios in three passbands: the UV continuum at 280 nm, the H$\alpha$ emission line, and the FIR 24$\mu$-band. We include a study of inclination trends in the IR/UV ratio ("IRX") and the IR/H$\alpha$ ratio. Our sample comprises a few hundred galaxies from the region around the clusters Abell 901/902 with deep data and inclinations measured from outer disks in Hubble Space Telescope images. As a novelty, the H$\alpha$- and separately the NII-emission are measured by tunable-filter imaging and encompass galaxies in their entirety. At galaxy stellar masses above log $M_*/M_\odot > 10$ we find trends in the UV and H$\alpha$ mass-to-light ratio that suggest an inclination-induced attenuation from face-on to edge-on of $\sim 1$ mag and $\sim 0.7$ mag in UV and H$\alpha$, respectively, implying that star-formation rates of edge-on galaxies would be underestimated by $\sim 2.5\times$ in UV and $\sim 2\times$ in H$\alpha$. We find the luminosities in UV and H$\alpha$ to be well correlated, but the optical depth of diffuse dust that causes inclination dependence appears to be lower for stars emitting at 280 nm than for gas clouds emitting Balmer lines. For galaxies with log $M_*/M_\odot < 9.7$, we find no measurable effect at $>0.1$ mag. The absence of an inclination dependence at 24$\mu$ confirms that the average galaxy is optically thin in the FIR., Comment: 12 pages, accepted for publication in MNRAS

The primary difficulty in measuring dynamical masses of galaxy clusters from galaxy data lies in the separation between true cluster members from interloping galaxies along the line of sight. We study the impact of membership contamination and incompleteness on cluster mass estimates obtained with 25 commonly used techniques applied to nearly 1000 mock clusters. We show that all methods overestimate or underestimate cluster masses when applied to contaminated or incomplete galaxy samples respectively. This appears to be the main source of the intrinsic scatter in the mass scaling relation. Applying corrections based on a prior knowledge of contamination and incompleteness can reduce the scatter to the level of shot noise expected for poorly sampled clusters. We establish an empirical model quantifying the effect of imperfect membership on cluster mass estimation and discuss its universal and method-dependent features. We find that both imperfect membership and the response of the mass estimators depend on cluster mass, effectively causing a flattening of the estimated - true mass relation. Imperfect membership thus alters cluster counts determined from spectroscopic surveys, hence the cosmological parameters that depend on such counts., Comment: 18 pages, 11 figures, 3tables; accepted for publication in MNRAS

Since the discovery that the majority of low-redshift galaxies exhibit some level of spiral structure, a number of theories have been proposed as to why these patterns exist. A popular explanation is a process known as swing amplification, yet there is no observational evidence to prove that such a mechanism is at play. By using a number of measured properties of galaxies, and scaling relations where there are no direct measurements, we model samples of SDSS and S$^4$G spiral galaxies in terms of their relative halo, bulge and disc mass and size. Using these models, we test predictions of swing amplification theory with respect to directly measured spiral arm numbers from Galaxy Zoo 2. We find that neither a universal cored or cuspy inner dark matter profile can correctly predict observed numbers of arms in galaxies. However, by invoking a halo contraction/expansion model, a clear bimodality in the spiral galaxy population emerges. Approximately 40 per cent of unbarred spiral galaxies at $z \lesssim 0.1$ and $\mathrm{M_*} \gtrsim 10^{10} \mathrm{M_\odot}$ have spiral arms that can be modelled by swing amplification. This population display a significant correlation between predicted and observed spiral arm numbers, evidence that they are swing amplified modes. The remainder are dominated by two-arm systems for which the model predicts significantly higher arm numbers. These are likely driven by tidal interactions or other mechanisms., Comment: 19 pages, 13 figures, accepted for publication in MNRAS

Modern cosmological simulations model the universe with increasing sophistication and at higher spatial and temporal resolutions. These enhancements permit detailed comparisons between the simulation outputs and real observational data. Recent projects such as Illustris are capable of producing simulated images that are comparable to those obtained from local surveys. This paper tests how well Illustris achieves this goal across a diverse population of galaxies using visual morphologies derived from Galaxy Zoo citizen scientists. Morphological classifications provided by volunteers for simulated galaxies are compared with similar data for a compatible sample of images drawn from the SDSS Legacy Survey. This paper investigates how simple morphological characterization by human volunteers asked to distinguish smooth from featured systems differs between simulated and real galaxy images. Differences are identified, which are likely due to the limited resolution of the simulation, but which could be revealing real differences in the dynamical evolution of populations of galaxies in the real and model universes. Specifically, for stellar masses $M_{\star}\lesssim10^{11}M_{\odot}$, a larger proportion of Illustris galaxies that exhibit disk-like morphology or visible substructure, relative to their SDSS counterparts. Toward higher masses, simulated and observed galaxies converge and exhibit similar morphology distributions. The stellar mass threshold indicated by this divergent behavior confirms recent works using parametric measures of morphology from Illustris simulated images. When $M_{\star}\gtrsim10^{11}M_{\odot}$, the Illustris dataset contains fewer galaxies that classifiers regard as unambiguously featured. These results suggest that comparison between the detailed properties of observed and simulated galaxies, even when limited to reasonably massive systems, may be misleading., Comment: 12 pages, 7 figures, to be published in The Astrophysical Journal

We explore constraints on the joint photometric and morphological evolution of typical low redshift galaxies as they move from the blue cloud through the green valley and onto the red sequence. We select GAMA survey galaxies with $10.25<{\rm log}(M_*/M_\odot)<10.75$ and $z<0.2$ classified according to their intrinsic $u^*-r^*$ colour. From single component S\'ersic fits, we find that the stellar mass-sensitive $K-$band profiles of red and green galaxy populations are very similar, while $g-$band profiles indicate more disk-like morphologies for the green galaxies: apparent (optical) morphological differences arise primarily from radial mass-to-light ratio variations. Two-component fits show that most green galaxies have significant bulge and disk components and that the blue to red evolution is driven by colour change in the disk. Together, these strongly suggest that galaxies evolve from blue to red through secular disk fading and that a strong bulge is present prior to any decline in star formation. The relative abundance of the green population implies a typical timescale for traversing the green valley $\sim 1-2$~Gyr and is independent of environment, unlike that of the red and blue populations. While environment likely plays a r\^ole in triggering the passage across the green valley, it appears to have little effect on time taken. These results are consistent with a green valley population dominated by (early type) disk galaxies that are insufficiently supplied with gas to maintain previous levels of disk star formation, eventually attaining passive colours. No single event is needed quench their star formation., Comment: MNRAS, in press

The Astropy project supports and fosters the development of open-source and openly-developed Python packages that provide commonly-needed functionality to the astronomical community. A key element of the Astropy project is the core package Astropy, which serves as the foundation for more specialized projects and packages. In this article, we provide an overview of the organization of the Astropy project and summarize key features in the core package as of the recent major release, version 2.0. We then describe the project infrastructure designed to facilitate and support development for a broader ecosystem of inter-operable packages. We conclude with a future outlook of planned new features and directions for the broader Astropy project., Comment: Minor changes to author list and title. Comments and feedback welcome through the paper source repository: https://github.com/astropy/astropy-v2.0-paper For more information about Astropy, see http://www.astropy.org/

We describe data release 3 (DR3) of the Galaxy And Mass Assembly (GAMA) survey. The GAMA survey is a spectroscopic redshift and multi-wavelength photometric survey in three equatorial regions each of 60.0 deg^2 (G09, G12, G15), and two southern regions of 55.7 deg^2 (G02) and 50.6 deg^2 (G23). DR3 consists of: the first release of data covering the G02 region and of data on H-ATLAS sources in the equatorial regions; and updates to data on sources released in DR2. DR3 includes 154809 sources with secure redshifts across four regions. A subset of the G02 region is 95.5% redshift complete to r<19.8 over an area of 19.5 deg^2, with 20086 galaxy redshifts, that overlaps substantially with the XXL survey (X-ray) and VIPERS (redshift survey). In the equatorial regions, the main survey has even higher completeness (98.5%), and spectra for about 75% of H-ATLAS filler targets were also obtained. This filler sample extends spectroscopic redshifts, for probable optical counterparts to H-ATLAS sub-mm sources, to 0.8 mag deeper (r<20.6) than the GAMA main survey. There are 25814 galaxy redshifts for H-ATLAS sources from the GAMA main or filler surveys. GAMA DR3 is available at the survey website (www.gama-survey.org/dr3/)., Comment: 14 pages, 15 figures, accepted by MNRAS. GAMA DR3 is available at http://www.gama-survey.org/dr3/

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

With the advent of wide-field cosmological surveys, we are approaching samples of hundreds of thousands of galaxy clusters. While such large numbers will help reduce statistical uncertainties, the control of systematics in cluster masses becomes ever more crucial. Here we examine the effects of an important source of systematic uncertainty in galaxy-based cluster mass estimation techniques: the presence of significant dynamical substructure. Dynamical substructure manifests as dynamically distinct subgroups in phase-space, indicating an 'unrelaxed' state. This issue affects around a quarter of clusters in a generally selected sample. We employ a set of mock clusters whose masses have been measured homogeneously with commonly-used galaxy-based mass estimation techniques (kinematic, richness, caustic, radial methods). We use these to study how the relation between observationally estimated and true cluster mass depends on the presence of substructure, as identified by various popular diagnostics. We find that the scatter for an ensemble of clusters does not increase dramatically for clusters with dynamical substructure. However, we find a systematic bias for all methods, such that clusters with significant substructure have higher measured masses than their relaxed counterparts. This bias depends on cluster mass: the most massive clusters are largely unaffected by the presence of significant substructure, but masses are significantly overestimated for lower mass clusters, by $\sim10\%$ at $10^{14}$ and $\geq20\%$ for $\leq10^{13.5}$. The use of cluster samples with different levels of substructure can, therefore, bias certain cosmological parameters up to a level comparable to the typical uncertainties in current cosmological studies., Comment: 14 pages, 8 figures, 3 tables. Submitted to MNRAS

In recent years, Unmanned Aerial Vehicle (UAV) technology has been introduced into the mining industry to conduct terrain surveying. This work investigates the application of UAVs with artificial lighting for measurement of rock fragmentation under poor lighting conditions, representing night shifts in surface mines or working conditions in underground mines. The study relies on indoor and outdoor experiments for rock fragmentation analysis using a quadrotor UAV. Comparison of the rock size distributions in both cases show that adequate artificial lighting enables similar accuracy to ideal lighting conditions., Comment: 8 pages, 6 figures, 2 tables, Application of Computers and Operations Research in the Mining Industry (APCOM)

In this paper we study the morphological properties of spiral galaxies, including measurements of spiral arm number and pitch angle. Using Galaxy Zoo 2, a stellar mass-complete sample of 6,222 SDSS spiral galaxies is selected. We use the machine vision algorithm SpArcFiRe to identify spiral arm features and measure their associated geometries. A support vector machine classifier is employed to identify reliable spiral features, with which we are able to estimate pitch angles for half of our sample. We use these machine measurements to calibrate visual estimates of arm tightness, and hence estimate pitch angles for our entire sample. The properties of spiral arms are compared with respect to various galaxy properties. The star formation properties of galaxies vary significantly with arm number, but not pitch angle. We find that galaxies hosting strong bars have spiral arms substantially ($4-6^\mathrm{o}$) looser than unbarred galaxies. Accounting for this, spiral arms associated with many-arm structures are looser (by 2$^\mathrm{o}$) than those in two-arm galaxies. In contrast to this average trend, galaxies with greater bulge-to-total stellar mass ratios display both fewer and looser spiral arms. This effect is primarily driven by the galaxy disc, such that galaxies with more massive discs contain more spiral arms with tighter pitch angles. This implies that galaxy central mass concentration is not the dominant cause of pitch angle and arm number variations between galaxies, which in turn suggests that not all spiral arms are governed by classical density waves or modal theories., Comment: 18 pages, 13 figures, accepted for publication in MNRAS

We conduct a comprehensive projected phase-space analysis of the A901/2 multi-cluster system at $z\sim0.165$. Aggregating redshifts from spectroscopy, tunable-filter imaging, and prism techniques, we assemble a sample of 856 cluster galaxies reaching $10^{8.5}M_\odot$ in stellar mass. We look for variations in cluster galaxy properties between virialised and non-virialised regions of projected phase-space (PPS). Our main conclusions point to relatively gentle environmental effects, expressed mainly on galaxy gas reservoirs. (1) Stacking the four subclusters in A901/2, we find galaxies in the virialised region are more massive, redder, and have marginally higher S\`ersic indices, but their half-light radii and Hubble types are not significantly different. (2) After accounting for trends in stellar mass, there is a remaining change in rest-frame colour across PPS. Primarily, the colour difference is due to an absence in the virialised region of galaxies with rest-frame $B-V<0.7$ and moderate-to-high ($M_\star>10^{9.85}M_\odot$) stellar mass. (3) There is an infalling population of lower-mass ($M_\star\leq10^{9.85}M_\odot$), relatively blue ($B-V<0.7$) elliptical or spheroidal galaxies that is strikingly absent in the virialised region. (4) The number of bona-fide star-forming and AGN galaxies in the PPS regions is strongly dictated by stellar mass. However, there remains a reduced fraction of star-forming galaxies in the centres of the clusters at fixed stellar mass, consistent with the star-formation-density relation in galaxy clusters. (5) There is no change in specific H$\alpha$-derived star-formation rates of star-forming galaxies at fixed mass across the cluster environment. This suggests that preprocessing of galaxies during infall plays a prominent role in quenching star formation., Comment: Accepted for publication in MNRAS

The dense environment of galaxy clusters strongly influences the nature of galaxies. Here, we study the cause of the size distribution of a sample of 560 spectroscopic members spanning a wide dynamical range down to 10^8.5 M_sol (log(M)-2) in the massive CLASH cluster MACSJ 1206.2-0847 at z~0.44. We use Subaru SuprimeCam imaging covering the highest-density core out to the infall regions (3 virial radii) to look for cluster-specific effects. We also compare our measurements to a compatible large field study in order to span extreme environmental densities. This paper presents the trends we identified for cluster galaxies divided by their colors into star-forming and quiescent galaxies and into distinct morphological types (using S\'ersic index and bulge/disk decompositions). We observed larger sizes for early type and smaller sizes for massive late type galaxies in clusters in comparison to the field. We attribute this to longer quenching timescales of more massive galaxies in the cluster. Our analysis further revealed an increasing importance of recently quenched transition objects ("red disks"). This is a virialized population found at higher cluster-centric radii with sizes similar to the quiescent, spheroid-dominated population of the cluster center, but with disks still in-tact. The mass-size relation of cluster galaxies may therefore be understood as the consequence of a mix of progenitors formed at different quenching epochs. We also find that galaxy sizes smoothly decreasing as a function of bulge fraction. At same bulge-to-total ratio and same stellar mass, quiescent galaxies are smaller than star-forming galaxies. This is likely because of a fading of the outskirts of the disk, which we saw in comparing sizes of their disk-components. Ram-pressure stripping of the cold gas and other forms of more gradual gas starvation are likely responsible for this observation., Comment: 20 Pages, 16 Figures; ; Accepted for publication in A&A on 2017 May 11

Deep observations of nearby galaxy clusters with Chandra have revealed concave 'bay' structures in a number of systems (Perseus, Centaurus and Abell 1795), which have similar X-ray and radio properties. These bays have all the properties of cold fronts, where the temperature rises and density falls sharply, but are concave rather than convex. By comparing to simulations of gas sloshing, we find that the bay in the Perseus cluster bears a striking resemblance in its size, location and thermal structure, to a giant ($\approx$50 kpc) roll resulting from Kelvin-Helmholtz instabilities. If true, the morphology of this structure can be compared to simulations to put constraints on the initial average ratio of the thermal and magnetic pressure, $\beta= p_{\rm th} / p_{\rm B}$, throughout the overall cluster before the sloshing occurs, for which we find $\beta=200$ to best match the observations. Simulations with a stronger magnetic field ($\beta=100$) are disfavoured, as in these the large Kelvin-Helmholtz rolls do not form, while in simulations with a lower magnetic field ($\beta=500$) the level of instabilities is much larger than is observed. We find that the bay structures in Centaurus and Abell 1795 may also be explained by such features of gas sloshing., Comment: 12 pages, 10 figures, accepted for publication in MNRAS

We use multi-wavelength SDSS images and Galaxy Zoo morphologies to identify a sample of $\sim$$270$ late-type galaxies with an off-centre bar. We measure offsets in the range 0.2-2.5 kpc between the photometric centres of the stellar disc and stellar bar. The measured offsets correlate with global asymmetries of the galaxies, with those with largest offsets showing higher lopsidedness. These findings are in good agreement with predictions from simulations of dwarf-dwarf tidal interactions producing off-centre bars. We find that the majority of galaxies with off-centre bars are of Magellanic type, with a median mass of $10^{9.6} M_{\odot}$, and 91% of them having $M_{\star}<3\times10^{10} M_{\odot}$, the characteristic mass at which galaxies start having higher central concentrations attributed to the presence of bulges. We conduct a search for companions to test the hypothesis of tidal interactions, but find that a similar fraction of galaxies with offset bars have companions within 100 kpc as galaxies with centred bars. Although this may be due to the incompleteness of the SDSS spectroscopic survey at the faint end, alternative scenarios that give rise to offset bars such as interactions with dark companions or the effect of lopsided halo potentials should be considered. Future observations are needed to confirm possible low mass companion candidates and to determine the shape of the dark matter halo, in order to find the explanation for the off-centre bars in these galaxies., Comment: 12 pages, 9 figures, accepted for publication in MNRAS

Does the environment of a galaxy directly influence the quenching history of a galaxy? Here we investigate the detailed morphological structures and star formation histories of a sample of SDSS group galaxies with both classifications from Galaxy Zoo 2 and NUV detections in GALEX. We use the optical and NUV colours to infer the quenching time and rate describing a simple exponentially declining SFH for each galaxy, along with a control sample of field galaxies. We find that the time since quenching and the rate of quenching do not correlate with the relative velocity of a satellite but are correlated with the group potential. This quenching occurs within an average quenching timescale of $\sim2.5~\rm{Gyr}$ from star forming to complete quiescence, during an average infall time (from $\sim 10R_{200}$ to $0.01R_{200}$) of $\sim 2.6~\rm{Gyr}$. Our results suggest that the environment does play a direct role in galaxy quenching through quenching mechanisms which are correlated with the group potential, such as harassment, interactions or starvation. Environmental quenching mechanisms which are correlated with satellite velocity, such as ram pressure stripping, are not the main cause of quenching in the group environment. We find that no single mechanism dominates over another, except in the most extreme environments or masses. Instead an interplay of mergers, mass & morphological quenching and environment driven quenching mechanisms dependent on the group potential drive galaxy evolution in groups., Comment: 20 pages, 11 figures

Spiral arms are common features in low-redshift disc galaxies, and are prominent sites of star-formation and dust obscuration. However, spiral structure can take many forms: from galaxies displaying two strong `grand design' arms, to those with many `flocculent' arms. We investigate how these different arm types are related to a galaxy's star-formation and gas properties by making use of visual spiral arm number measurements from Galaxy Zoo 2. We combine UV and mid-IR photometry from GALEX and WISE to measure the rates and relative fractions of obscured and unobscured star formation in a sample of low-redshift SDSS spirals. Total star formation rate has little dependence on spiral arm multiplicity, but two-armed spirals convert their gas to stars more efficiently. We find significant differences in the fraction of obscured star-formation: an additional $\sim 10$ per cent of star-formation in two-armed galaxies is identified via mid-IR dust emission, compared to that in many-armed galaxies. The latter are also significantly offset below the IRX-$\beta$ relation for low-redshift star-forming galaxies. We present several explanations for these differences versus arm number: variations in the spatial distribution, sizes or clearing timescales of star-forming regions (i.e., molecular clouds), or contrasting recent star-formation histories., Comment: 15 pages, 13 figures, accepted for publication in MNRAS

This work investigates the application of Unmanned Aerial Vehicle (UAV) technology for measurement of rock fragmentation without placement of scale objects in the scene to determine image scale. Commonly practiced image-based rock fragmentation analysis requires a technician to walk to a rock pile, place a scale object of known size in the area of interest, and capture individual 2D images. Our previous work has used UAV technology for the first time to acquire real-time rock fragmentation data and has shown comparable quality of results; however, it still required the (potentially dangerous) placement of scale objects, and continued to make the assumption that the rock pile surface is planar and that the scale objects lie on the surface plane. This work improves our UAV-based approach to enable rock fragmentation measurement without placement of scale objects and without the assumption of planarity. This is achieved by first generating a point cloud of the rock pile from 2D images, taking into account intrinsic and extrinsic camera parameters, and then taking 2D images for fragmentation analysis. This work represents an important step towards automating post-blast rock fragmentation analysis. In experiments, a rock pile with known size distribution was photographed by the UAV with and without using scale objects. For fragmentation analysis without scale objects, a point cloud of the rock pile was generated and used to compute image scale. Comparison of the rock size distributions show that this point-cloud-based method enables producing measurements with better or comparable accuracy (within 10% of the ground truth) to the manual method with scale objects., Comment: 8 pages, 9 figures

On the morning of the August 11th 1999, a total eclipse of the sun plunged Cornwall and parts of Devon into darkness. The event of the eclipse was bound to attract a great deal of scientific and media attention. Realizing that the differences in day-time/night-time propagation of VLF/LF/MF to HF bands would also apply during the darkness of the eclipse, the eclipse offered a rare PR opportunity to promote radio to the general public. At the same time the specific nature of the disturbance to the upper atmosphere and the effect on radio propagation could be examined in detail using scientific instruments at minimum cost since most instruments would not have to be moved. This would allow prediction models to be tested in a controlled fashion. Contained within this report are the details and results of the radio and ionospheric experiments conducted by the Rutherford Appleton Laboratory during the 1999 total solar eclipse. The promoting of the radio experiments with the general public produced nearly 60 appearances on local and national TV, newspapers and periodicals. Close to 1700 people responded to the general public medium wave experiment and 16 million people looked in on the general eclipse web site (part funded by RA) that included the details of the radio experiments. A large database of systematic observations across VLF to HF was collected from radio amateurs and from the RA Regional Offices allowing comparisons to be made with ITU estimates. There is a brief look at the scientific results and a forward look as to how the analysis of this disturbance might have impact on the use of ionospheric models for Space Weather tools in the future., Comment: 41 pages, 33 Figures, government funded research final report, unclassified

We present a study of the star formation and AGN activity for galaxies in the Abell 901/2 multi-cluster system at z~0.167 as part of the OMEGA survey. Using Tuneable Filter data obtained with the OSIRIS instrument at the GTC we produce spectra covering the Halpha and [N II] spectral lines for more than 400 galaxies. Using optical emission-line diagnostics, we identify a significant number of galaxies hosting AGN, which tend to have high masses and a broad range of morphologies. Moreover, within the environmental densities probed by our study, we find no environmental dependence on the fraction of galaxies hosting AGN. The analysis of the integrated Halpha emission shows that the specific star formation rates (SSFRs) of a majority of the cluster galaxies are below the field values for a given stellar mass. We interpret this result as evidence for a slow decrease in the star formation activity of star-forming galaxies as they fall into higher-density regions, contrary to some previous studies which suggested a rapid truncation of star formation. We find that most of the intermediate- and high-mass spiral galaxies go through a phase in which their star formation is suppressed but still retain significant star-formation activity. During this phase, these galaxies tend to retain their spiral morphology while their colours become redder. The presence of this type of galaxies in high density regions indicates that the physical mechanism responsible for suppressing star-formation affects mainly the gas component of the galaxies, suggesting that ram-pressure stripping or starvation are potentially responsible., Comment: 20 pages, 16 figures. Accepted for publication in MNRAS