Hintze Centre for Astrophysical Surveys

Abstract:

Supernovae (SNe) IIn are terminal explosions of massive stars that are surrounded by a dense circumstellar medium (CSM). Among SNe IIn, a notable subset is the SN 2009ip-like, which exhibits an initial, fainter peak attributed to stellar variability in the late evolutionary stages, followed by a brighter peak, interpreted as the SN explosion itself. In this context, we analysed the spectrophotometric evolution of SN 2024hpj, an object with a triple-peaked light curve and spectra typical of a SN IIn but with a complex line profile composed of broad P-Cygni features topped by narrow emissions. Comparing it with other SN 2009ip-like events in the literature, as well as with other unpublished objects (SNe 2019mry, 2022ytx, 2024uzf, and 2025csc), we identify star-forming regions as their preferred formation environment. On the other hand, the diversity of spectrophotometric features within the sample suggests that variations in CSM mass and distribution may influence the observed characteristics. We identify four sub-classes based on the luminosity and rapidity of the light curve evolution, which provides insights into possible differences in the progenitors, while a statistical analysis of their observed rate indicates progenitor masses around 25 − 31 M ⊙ or lower.

Abstract:

We present the third data release of the LOFAR Two-metre Sky Survey (LoTSS-DR3). The survey images cover 88% of the northern sky and were created from 12 950 h of data (18.6 PB) accumulated over 10.5 years. Producing the images took 20 million core hours of processing through direction-independent and direction-dependent calibration pipelines that correct for instrumental effects as well as spatially and temporally varying ionospheric distortions. In our 120–168 MHz continuum mosaic images with an angular resolution of 6″ (9″ below declination 10°) we catalogue 13 667 877 sources, formed from 16 943 656 Gaussian components. The scatter in the astrometric precision approximately follows the expected noise-like behaviour but with an additional systematic component of at least 0.24″ that is likely due to calibration imperfections. The random flux density scale error is 6%, while the systematic offset was previously shown to be within 2%. The median sensitivity of our mosaics is 92 μJy beam −1 , improving to 68 μJy beam −1 at high observing elevations, but degrading to 183 μJy beam −1 at the celestial equator due to station area projection effects. Completeness simulations, accounting for realistic source models, time- and bandwidth-smearing effects, and astrometric errors, indicate that we detect more than 95% of compact sources with integrated flux densities exceeding 9 times the local root mean square (RMS) noise. However, the recovered source counts in a particular integrated flux density bin do not match the injected counts until flux densities exceed 45 times the local RMS noise. The Euclidean-normalised differential source counts derived from the survey constrain the radio source population over five orders of magnitude and are in good agreement with previous deep and wide-area surveys. All data products are publicly available, including catalogues, individual-field Stokes I , Q , U , and V images, mosaicked Stokes I images, and uv data with associated direction-dependent calibration solutions.

Abstract:

Untargeted neutral hydrogen ( > 1.5 kpc) to be ultra-diffuse galaxies (UDGs). Furthermore, we extracted surveys are well suited to identifying low surface brightness galaxies (LSBGs) that are gas rich, and they offer a complementary view to optically selected populations. We examined the LSBG population as identified via stellar and gaseous content using the MIGHTEE XMM-LSS early science data and the publicly available catalogs of optically identified LSBGs. There is currently little overlap between these datasets, with only three galaxies commonly detected. We performed surface brightness photometry of selected MIGHTEE detections to find 29 LSBGs, and 26 of these meet the size requirement (R_ eff spectra at the location of all optically identified galaxies, placing upper limits on the mass ratio in these systems. While the population overall tends toward bluer colors, the and the optically selected samples mostly overlap in mean effective surface brightness, effective radii, and color. Although it is not straightforward to discern why the LSBGs were missed in optical searches, this work highlights the utility of surveys in finding these faint systems. The LSBGs are gas rich compared to the general population. Furthermore, three out of four UDGs with available kinematics show no systematic offset from the baryonic Tully-Fisher relation, although we are biased away from sources with low rotational velocities due to the low spectral resolution of the data. This work demonstrates the utility of observations for finding and characterizing the low surface brightness Universe.

Abstract:

As radio emission from normal galaxies is a dust-free tracer of star formation, tracing the star formation history of the Universe is a key goal of the Square Kilometre Array and the Next-Generation Very Large Array. In order to investigate how well radio luminosity traces star formation rate (SFR) in the early Universe, we have examined the radio properties of a JWST Paα sample of galaxies at 1.0 ≲ z ≲ 1.8. In the GOODS-S field, we cross-matched a sample of 506 FRESCO Paα emitters with the 1.23 GHz radio continuum data from the MeerKAT MIGHTEE survey, finding 47 detections. After filtering for active galactic nuclei (via X-ray detections, hot mid-infrared dust, and extended radio emission), as well as blended sources, we obtained a sample of star-forming galaxies comprising 11 cataloged radio detections, 18 noncataloged detections (at ≈3σ–5σ), and 298 undetected sources. Stacking the 298 undetected sources, we obtain a 3.3σ detection in the radio. This sample, along with a local sample of Paα emitters, lies along previous radio luminosity/SFR relations from local (<0.2) to high redshift (z ∼ 1). Fitting the FRESCO data at 1.0 ≲ z ≲ 1.8, we find log(L1.4GHz)= (1.31 ± 0.17) × log(SFRPaα)+ (21.36 ± 0.17), which is consistent with other literature relations. We can explain some of the observed scatter in the L1.4GHz/SFRPaα correlation by a toy model in which the synchrotron emission is a delayed/averaged tracer of the instantaneous Paα SFR by ∼10/75 Myr.