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Abstract We present coordinated observations of GRB 170202A carried out by the Zadko and the Virgin Island Robotic Telescopes. The observations started 59 s after the event trigger, and provided nearly continuous coverage for two days, due to the unique locations of these telescopes. We clearly detected an early rise in optical emission, followed by late optical flares. By complementing these data with archival observations, we show that GRB 170202A is well described by the standard fireball model if multiple reverse shocks are taken into account. Its fireball is evidenced as expanding within a constant-density interstellar medium, with most burst parameters being consistent with the usual ranges found in the literature. The electron and magnetic energy parameters ( ϵ e , ϵ B ) are orders of magnitude smaller than the commonly assumed values. We argue that the global fit of the fireball model achieved by our study should be possible for any burst, pending the availability of a sufficiently comprehensive data set. This conclusion emphasizes the crucial importance of coordinated observation campaigns of gamma-ray bursts, such as the one central to this work, to answer outstanding questions about the underlying physics driving these phenomena. 

The overarching goal of this research project is to provide a novel contribution to perceived bias research by testing the hypothesis that mere exposure to instances of subtle gender bias in STEM settings can have important effects on observers, depending on whether they recognize such events as gender bias or do not see it as bias. The goal of the first of five experiments was to assess how witnessing subtle gender bias events influences explicit stereotype activation among people who recognize the events as gender stereotyping as well as those who do not. We utilized video materials that were developed and tested in our previous NSF research that show a group of four engineering students, 2 women and 2 men, working together on an engineering design task. There are two versions of the video: one in which the students engaged in subtle gender bias (bias version), and one in which the students engaged in neutral interactions (control version). Over 400 participants were recruited from a large midwestern research university from computer science and engineering majors in which 30% or fewer majors are women. The survey included assessments of perceptions of gender stereotyping in the video, general stereotype endorsement and STEM stereotype endorsement, and three individual difference measures (gender-based rejection sensitivity, sexism sensitivity and negative emotionality) used as covariates in analyses. We found that participants who saw the bias video reported greater explicit stereotyping when they failed to recognize gender bias in the video. When they did recognize bias, they reported explicit stereotyping at levels similar to those in the control condition. This pattern suggests that exposure to subtle gender bias events may have activated gender stereotypes, but when participants recognized the events as gender bias, they tempered their explicit stereotyping. 

The overarching goal of this research project is to provide a novel contribution to perceived bias research by testing the hypothesis that mere exposure to instances of subtle gender bias in STEM settings can have important effects on observers, depending on whether they recognize such events as gender bias or do not see it as bias. The goal of the first of five experiments was to assess how witnessing subtle gender bias events influences explicit stereotype activation among people who recognize the events as gender stereotyping as well as those who do not. We utilized video materials that were developed and tested in our previous NSF research that show a group of four engineering students, 2 women and 2 men, working together on an engineering design task. There are two versions of the video: one in which the students engaged in subtle gender bias (bias version), and one in which the students engaged in neutral interactions (control version). Over 400 participants were recruited from a large midwestern research university from computer science and engineering majors in which 30% or fewer majors are women. The survey included assessments of perceptions of gender stereotyping in the video, general stereotype endorsement and STEM stereotype endorsement, and three individual difference measures (gender-based rejection sensitivity, sexism sensitivity and negative emotionality) used as covariates in analyses. We found that participants who saw the bias video reported greater explicit stereotyping when they failed to recognize gender bias in the video. When they did recognize bias, they reported explicit stereotyping at levels similar to those in the control condition. This pattern suggests that exposure to subtle gender bias events may have activated gender stereotypes, but when participants recognized the events as gender bias, they tempered their explicit stereotyping. 

We present our follow-up observations with GRANDMA of transient sources revealed by the Zwicky Transient Facility (ZTF). Over a period of six months, all ZTF alerts were examined in real time by a dedicated science module implemented in the Fink broker, which will be used in filtering of transients discovered by the Vera C. Rubin Observatory. In this article, we present three selection methods to identify kilonova candidates. Out of more than 35 million alerts, a hundred sources have passed our selection criteria. Six were then followed-up by GRANDMA (by both professional and amateur astronomers). The majority were finally classified either as asteroids or as supernovae events. We mobilized 37 telescopes, bringing together a large sample of images, taken under various conditions and quality. To complement the orphan kilonova candidates, we included three additional supernovae alerts to conduct further observations during summer 2021. We demonstrate the importance of the amateur astronomer community that contributed images for scientific analyses of new sources discovered in a magnitude range r′ = 17 − 19 mag. We based our rapid kilonova classification on the decay rate of the optical source that should exceed 0.3 mag d−1. GRANDMA’s follow-up determined the fading rate within 1.5 ± 1.2 d post-discovery, without waiting for further observations from ZTF. No confirmed kilonovae were discovered during our observing campaign. This work will be continued in the coming months in the view of preparing for kilonova searches in the next gravitational-wave observing run O4.

 

ABSTRACT GRANDMA (Global Rapid Advanced Network Devoted to the Multi-messenger Addicts) is a network of 25 telescopes of different sizes, including both photometric and spectroscopic facilities. The network aims to coordinate follow-up observations of gravitational-wave (GW) candidate alerts, especially those with large localization uncertainties, to reduce the delay between the initial detection and the optical confirmation. In this paper, we detail GRANDMA’s observational performance during Advanced LIGO/Advanced Virgo Observing Run 3 (O3), focusing on the second part of O3; this includes summary statistics pertaining to coverage and possible astrophysical origin of the candidates. To do so, we quantify our observation efficiency in terms of delay between GW candidate trigger time, observations, and the total coverage. Using an optimized and robust coordination system, GRANDMA followed-up about 90 per cent of the GW candidate alerts, that is 49 out of 56 candidates. This led to coverage of over 9000 deg2 during O3. The delay between the GW candidate trigger and the first observation was below 1.5 h for 50 per cent of the alerts. We did not detect any electromagnetic counterparts to the GW candidates during O3, likely due to the very large localization areas (on average thousands of degrees squares) and relatively large distance of the candidates (above 200 Mpc for 60 per cent of binary neutron star, BNS candidates). We derive constraints on potential kilonova properties for two potential BNS coalescences (GW190425 and S200213t), assuming that the events’ locations were imaged. 

Context. The ESA Gaia mission provides a unique time-domain survey for more than 1.6 billion sources with G ≲ 21 mag. Aims. We showcase stellar variability in the Galactic colour-absolute magnitude diagram (CaMD). We focus on pulsating, eruptive, and cataclysmic variables, as well as on stars that exhibit variability that is due to rotation and eclipses. Methods. We describe the locations of variable star classes, variable object fractions, and typical variability amplitudes throughout the CaMD and show how variability-related changes in colour and brightness induce “motions”. To do this, we use 22 months of calibrated photometric, spectro-photometric, and astrometric Gaia data of stars with a significant parallax. To ensure that a large variety of variable star classes populate the CaMD, we crossmatched Gaia sources with known variable stars. We also used the statistics and variability detection modules of the Gaia variability pipeline. Corrections for interstellar extinction are not implemented in this article. Results. Gaia enables the first investigation of Galactic variable star populations in the CaMD on a similar, if not larger, scale as was previously done in the Magellanic Clouds. Although the observed colours are not corrected for reddening, distinct regions are visible in which variable stars occur. We determine variable star fractions to within the current detection thresholds of Gaia . Finally, we report the most complete description of variability-induced motion within the CaMD to date. Conclusions. Gaia enables novel insights into variability phenomena for an unprecedented number of stars, which will benefit the understanding of stellar astrophysics. The CaMD of Galactic variable stars provides crucial information on physical origins of variability in a way that has previously only been accessible for Galactic star clusters or external galaxies. Future Gaia data releases will enable significant improvements over this preview by providing longer time series, more accurate astrometry, and additional data types (time series BP and RP spectra, RVS spectra, and radial velocities), all for much larger samples of stars.