Models of gravitational lens candidates from Space Warps CFHTLS

We report modelling follow-up of recently-discovered gravitational-lens candidates in the Canada France Hawaii Telescope Legacy Survey. Lens modelling was done by a small group of specially-interested volunteers from the SpaceWarps citizen-science community who originally found the candidate lenses. Models are categorised according to seven diagnostics indicating (a) the image morphology and how clear or indistinct it is, (b) whether the mass map and synthetic lensed image appear to be plausible, and (c) how the lens-model mass compares with the stellar mass and the abundance-matched halo mass. The lensing masses range from ~10^11 Msun to >10^13 Msun. Preliminary estimates of the stellar masses show a smaller spread in stellar mass (except for two lenses): a factor of a few below or above ~10^11 Msun. Therefore, we expect the stellar-to-total mass fraction to decline sharply as lensing mass increases. The most massive system with a convincing model is J1434+522 (SW05). The two low-mass outliers are J0206-095 (SW19) and J2217+015 (SW42); if these two are indeed lenses, they probe an interesting regime of very low star-formation efficiency. Some improvements to the modelling software (SpaghettiLens), and discussion of strategies regarding scaling to future surveys with more and frequent discoveries, are included.Comment: 16 pages, 10 figures, 1 table, online supplement table_1.csv contains additional detailed numbers shown in table 1 and figure

Gravitational lens modelling in a citizen science context

We develop a method to enable collaborative modelling of gravitational lenses and lens candidates, that could be used by non-professional lens enthusiasts. It uses an existing free-form modelling program (glass), but enables the input to this code to be provided in a novel way, via a user-generated diagram that is essentially a sketch of an arrival-time surface. We report on an implementation of this method, SpaghettiLens, which has been tested in a modelling challenge using 29 simulated lenses drawn from a larger set created for the Space Warps citizen science strong lens search. We find that volunteers from this online community asserted the image parities and time ordering consistently in some lenses, but made errors in other lenses depending on the image morphology. While errors in image parity and time ordering lead to large errors in the mass distribution, the enclosed mass was found to be more robust: the model-derived Einstein radii found by the volunteers were consistent with those produced by one of the professional team, suggesting that given the appropriate tools, gravitational lens modelling is a data analysis activity that can be crowd-sourced to good effect. Ideas for improvement are discussed, these include (a) overcoming the tendency of the models to be shallower than the correct answer in test cases, leading to systematic overestimation of the Einstein radius by 10 per cent at present, and (b) detailed modelling of arcs.Comment: 10 pages, 12 figure

Mothers\u27 Experiences in the Nurse-Family Partnership Program: A Qualitative Case Study

BACKGROUND:Few studies have explored the experiences of low income mothers participating in nurse home visiting programs. Our study explores and describes mothers\u27 experiences participating in the Nurse-Family Partnership (NFP) Program, an intensive home visiting program with demonstrated effectiveness, from the time of program entry before 29 weeks gestation until their infant\u27s first birthday.METHODS:A qualitative case study approach was implemented. A purposeful sample of 18 low income, young first time mothers participating in a pilot study of the NFP program in Hamilton, Ontario, Canada partook in one to two face to face in-depth interviews exploring their experiences in the program. All interviews were digitally recorded and transcribed verbatim. Conventional content analysis procedures were used to analyze all interviews. Data collection and initial analysis were implemented concurrently.RESULTS:The mothers participating in the NFP program were very positive about their experiences in the program. Three overarching themes emerged from the data: 1. Getting into the NFP program; 2. The NFP nurse is an expert, but also like a friend providing support; and 3. Participating in the NFP program is making me a better parent.CONCLUSIONS:Our findings provide vital information to home visiting nurses and to planners of home visiting programs about mothers\u27 perspectives on what is important to them in their relationships with their nurses, how nurses and women are able to develop positive therapeutic relationships, and how nurses respond to mothers\u27 unique life situations while home visiting within the NFP Program. In addition our findings offer insights into why and under what circumstances low income mothers will engage in nurse home visiting and how they expect to benefit from their participation

Space Warps II. New Gravitational Lens Candidates from the CFHTLS Discovered through Citizen Science

We report the discovery of 29 promising (and 59 total) new lens candidates from the CFHT Legacy Survey (CFHTLS) based on about 11 million classifications performed by citizen scientists as part of the first Space Warps lens search. The goal of the blind lens search was to identify lens candidates missed by robots (the RingFinder on galaxy scales and ArcFinder on group/cluster scales) which had been previously used to mine the CFHTLS for lenses. We compare some properties of the samples detected by these algorithms to the Space Warps sample and find them to be broadly similar. The image separation distribution calculated from the Space Warps sample shows that previous constraints on the average density profile of lens galaxies are robust. SpaceWarps recovers about 65% of known lenses, while the new candidates show a richer variety compared to those found by the two robots. This detection rate could be increased to 80% by only using classifications performed by expert volunteers (albeit at the cost of a lower purity), indicating that the training and performance calibration of the citizen scientists is very important for the success of Space Warps. In this work we present the SIMCT pipeline, used for generating in situ a sample of realistic simulated lensed images. This training sample, along with the false positives identified during the search, has a legacy value for testing future lens finding algorithms. We make the pipeline and the training set publicly available.Comment: 23 pages, 12 figures, MNRAS accepted, minor to moderate changes in this versio

Space Warps: I. Crowd-sourcing the Discovery of Gravitational Lenses

We describe Space Warps, a novel gravitational lens discovery service that yields samples of high purity and completeness through crowd-sourced visual inspection. Carefully produced colour composite images are displayed to volunteers via a web- based classification interface, which records their estimates of the positions of candidate lensed features. Images of simulated lenses, as well as real images which lack lenses, are inserted into the image stream at random intervals; this training set is used to give the volunteers instantaneous feedback on their performance, as well as to calibrate a model of the system that provides dynamical updates to the probability that a classified image contains a lens. Low probability systems are retired from the site periodically, concentrating the sample towards a set of lens candidates. Having divided 160 square degrees of Canada-France-Hawaii Telescope Legacy Survey (CFHTLS) imaging into some 430,000 overlapping 82 by 82 arcsecond tiles and displaying them on the site, we were joined by around 37,000 volunteers who contributed 11 million image classifications over the course of 8 months. This Stage 1 search reduced the sample to 3381 images containing candidates; these were then refined in Stage 2 to yield a sample that we expect to be over 90% complete and 30% pure, based on our analysis of the volunteers performance on training images. We comment on the scalability of the SpaceWarps system to the wide field survey era, based on our projection that searches of 10$^5$ images could be performed by a crowd of 10$^5$ volunteers in 6 days.Comment: 21 pages, 13 figures, MNRAS accepted, minor to moderate changes in this versio

Gravitational lens modelling in a citizen science context

We develop a method to enable collaborative modelling of gravitational lenses and lens candidates, that could be used by non-professional lens enthusiasts. It uses an existing free-form modelling program (glass), but enables the input to this code to be provided in a novel way, via a user-generated diagram that is essentially a sketch of an arrival-time surface. We report on an implementation of this method, SpaghettiLens, which has been tested in a modelling challenge using 29 simulated lenses drawn from a larger set created for the Space Warps citizen science strong lens search. We find that volunteers from this online community asserted the image parities and time ordering consistently in some lenses, but made errors in other lenses depending on the image morphology. While errors in image parity and time ordering lead to large errors in the mass distribution, the enclosed mass was found to be more robust: the model-derived Einstein radii found by the volunteers were consistent with those produced by one of the professional team, suggesting that given the appropriate tools, gravitational lens modelling is a data analysis activity that can be crowd-sourced to good effect. Ideas for improvement are discussed; these include (a) overcoming the tendency of the models to be shallower than the correct answer in test cases, leading to systematic overestimation of the Einstein radius by 10 per cent at present, and (b) detailed modelling of arc

A qualitative study exploring feasibility and acceptability of acupuncture, yoga, and mindfulness meditation for managing weight after breast cancer

Introduction: Weight gain is common after breast cancer. Yoga, mindfulness meditation, and acupuncture may assist with managing weight. However, evidence on effectiveness is limited. This study assessed the feasibility and acceptability of recruiting for and implementing a randomized controlled trial (RCT) evaluating these interventions as adjuncts to lifestyle interventions (diet and exercise) for weight management in women with breast cancer. Methods: Qualitative study involving virtual focus groups or semi-structured interviews. Participants were recruited via email invitation from a breast cancer consumer organization and breast cancer center in Australia. Eligible participants had received treatment for breast cancer, and were fluent in English. A purposive sample of culturally and linguistically diverse (CALD) participants was also recruited. Focus groups and interviews were audio-recorded, transcribed verbatim and analyzed using thematic analysis with the constant comparison method. Results: Emails were sent to 1415 women of which 37 provided data in 5 focus groups and 1 semi-structured interview, including 1 focus group (n = 6) with only women from CALD backgrounds. Yoga and mindfulness meditation were perceived as feasible and acceptable for weight management, but acupuncture was seen to be too invasive to be acceptable. A focus on wellness rather than weight reduction, flexible program delivery, trusted advice, consideration of participant burden and benefit, and peer-support were key factors perceived to increase feasibility and acceptability. Conclusions: Yoga and mindfulness meditation are acceptable and useful adjuncts to lifestyle interventions for weight management after breast cancer. This research places end-users at the forefront of trial design, and will inform future trials using these interventions for weight management and improving health and wellbeing after breast cancer

The contribution of processing fluency to preference : a comparison with familiarity-based recognition

There is a great deal of evidence supporting the idea that, when a stimulus is processed fluently, it is more likely to be judged as pleasant. However, this influence of fluency on preference judgement seems to depend on several experimental conditions. So we tried to better understand these conditions via a comparison with recognition and by manipulating some aspects of the procedure (test format) and material (similarity and figure-ground contrast of the stimuli). Two experiments showed that some conditions maximally induce the use of processing fluency in a preference judgement, as in a recognition task. We discuss the implications of these findings for the well-documented discrepancy-attribution hypothesis (WhittleseaPeer reviewe

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

We present detailed morphology measurements for 8.67 million galaxies in the DESI Legacy Imaging Surveys (DECaLS, MzLS, and BASS, plus DES). These are automated measurements made by deep learning models trained on Galaxy Zoo volunteer votes. Our models typically predict the fraction of volunteers selecting each answer to within 5-10\% for every answer to every GZ question. The models are trained on newly-collected votes for DESI-LS DR8 images as well as historical votes from GZ DECaLS. We also release the newly-collected votes. Extending our morphology measurements outside of the previously-released DECaLS/SDSS intersection increases our sky coverage by a factor of 4 (5,000 to 19,000 deg$^2$) and allows for full overlap with complementary surveys including ALFALFA and MaNGA.Comment: 20 pages. Accepted at MNRAS. Catalog available via https://zenodo.org/record/7786416. Pretrained models available via https://github.com/mwalmsley/zoobot. Vizier and Astro Data Lab access not yet available. With thanks to the Galaxy Zoo volunteer