The Bright Star in the globular cluster 47 Tucanae (NGC 104) is a post-asymptotic giant branch (post-AGB) star of spectral type B8 III. The ultraviolet spectra of late-B stars exhibit myriad absorption features, many due to species unobservable from the ground. The Bright Star thus represents a unique window into the chemistry of 47 Tuc. We have analyzed observations obtained with the Far Ultraviolet Spectroscopic Explorer, the Cosmic Origins Spectrograph aboard the Hubble Space Telescope, and the Magellan Inamori Kyocera Echelle Spectrograph on the Magellan Telescope. By fitting these data with synthetic spectra, we determine various stellar parameters (T eff = 10,850 ± 250 K, log g = 2.20 ± 0.13 ) and the photospheric abundances of 26 elements, including Ne, P, Cl, Ga, Pd, In, Sn, Hg, and Pb, which have not previously been published for this cluster. Abundances of intermediate-mass elements (Mg through Ga) generally scale with Fe, while the heaviest elements (Pd through Pb) have roughly solar abundances. Its low C/O ratio indicates that the star did not undergo third dredge-up and suggests that its heavy elements were made by a previous generation of stars. If so, this pattern should be present throughout the cluster, not just in this star. Stellar-evolution models suggest that the Bright Star is powered by a He-burning shell, having left the AGB during or immediately after a thermal pulse. Its mass (0.54 ± 0.16M ⊙) implies that single stars in 47 Tuc lose 0.1–0.2 M ⊙ on the AGB, only slightly less than they lose on the red giant branch.

We report here on the first results of a systematic monitoring of southern glitching pulsars at the Argentine Institute of Radioastronomy that started in the year 2019. We detected a major glitch in the Vela pulsar (PSR J0835−4510) and two small-glitches in PSR J1048−5832. For each glitch, we present the measurement of glitch parameters by fitting timing residuals. We then make an individual pulses study of Vela in observations before and after the glitch. We selected 6 days of observations around the major glitch on 2021 July 22 and study their statistical properties with machine learning techniques. We use Variational AutoEncoder (VAE) reconstruction of the pulses to separate them clearly from the noise. We perform a study with Self-Organizing Maps (SOM) clustering techniques to search for unusual behavior of the clusters during the days around the glitch not finding notable qualitative changes. We have also detected and confirm recent glitches in PSR J0742−2822 and PSR J1740−3015.