Hintze Centre for Astrophysical Surveys

Abstract:

Type Ia supernovae (SNe Ia) are among the most precise cosmological distance indicators used to study the expansion history of the Universe. The vast increase in SN Ia data due to large-scale astrophysical surveys has led to the discovery of a wide variety of SN Ia sub-classes, such as transitional and fast-declining SNe Ia. However, their distinct photometric and spectroscopic properties differentiate them from the population of normal SNe Ia such that their use as cosmological tools remains challenged. Here, we present a high-cadenced photometric and spectroscopic dataset of two SNe Ia, SNe 2020ue and 2020nlb, which were discovered in the nearby Virgo cluster of galaxies. Our study shows that SN 2020nlb is a normal SN Ia whose unusually red colour is intrinsic, arising from a lower photospheric temperature rather than interstellar reddening, providing clear evidence that colour diversity among normal SNe Ia can have a physical origin. In contrast, SN 2020ue has photometric properties, such as colour evolution and light curve decay rate, similar to those of transitional SNe. It is hence more spectroscopically aligned with normal SNe Ia. This is evident from spectroscopic indicators such as the pseudo-equivalent width of lines. Thus, such SNe Ia, which lie photometrically at the edge of the standard normal SNe Ia range, may be missed in cosmological SNe Ia samples. Our results highlight that a spectroscopic analysis of SNe Ia around peak brightness is crucial for identifying intrinsic colour variations and constructing a more complete and physically homogeneous SN Ia sample for precision cosmology. Si II

Abstract:

Kilonovae are the scientifically rich—but observationally elusive—optical transient phenomena associated with compact binary mergers. Only a handful of events have been discovered to date, all through multiwavelength (gamma-ray) and multimessenger (gravitational-wave) signals. Given their scarcity, it is important to maximise the discovery possibility of new kilonova events. To this end, we present our follow-up observations of the gravitational-wave signal S250818k—a plausible binary neutron star merger at a distance of 237 ± 62 Mpc. Pan-STARRS tiled 286 and 318 deg2 (32% and 34% of the 90% sky localisation region) within 3 and 7 days of the GW signal, respectively. ATLAS covered 65% of the sky map within 3 days, but with lower sensitivity. These observations uncovered 47 new transients; however, none were deemed to be linked to S250818k. We undertook an expansive follow-up campaign of AT2025ulz, the purported counterpart to S250818k. The griz-band light curve, combined with our redshift measurement (z = 0.0849 ± 0.0003), all indicate that SN2025ulz is a type IIb supernova and thus not the counterpart to S250818k. We rule out the presence of an AT2017gfo-like kilonova within ≈27% of the distance posterior sampled by our Pan-STARRS pointings (≈9.1% across the total 90% 3D sky localisation). We demonstrate that early observations are optimal for probing the distance posterior of the 3D gravitational-wave sky map, and that SN2025ulz was a plausible kilonova candidate for ≲5 days, before ultimately being ruled out.

Abstract:

Context. The H I mass function (HIMF) is a crucial tool for understanding the evolution of the H I content in galaxies over cosmic time and, hence, to constraining both the baryon cycle in galaxy evolution and the reionization history of the Universe. Aims. We aim to derive semiempirical constraints at z  ∼ 0.37 by combining literature results on the stellar mass function from optical surveys with recent findings on the M HI  −  M ⋆ scaling relation derived via spectral stacking analysis applied to 21 cm line interferometric data from the MIGHTEE and CHILES surveys, conducted with the MeerKAT and VLA radio telescopes, respectively. Methods. We drew synthetic stellar mass samples directly from the publicly available results underlying the analysis of the COSMOS2020 galaxy photometric sample. We then converted M ⋆ into M HI using analytical fitting functions to the data points from H I stacking. We next fit a Schechter function to the median HIMF from all the samples via Monte Carlo Markov chains. We finally derived the posterior distribution for Ω HI by integrating the models for the HIMF built from the posteriors samples of the Schechter parameters. Results. We find a deviation of the HIMF at z  ∼ 0.37 from the results at z  ∼ 0 from the ALFALFA survey and at z  ∼ 1 from uGMRT data. Our results for Ω HI are in broad agreement with other literature results and follow the overall trend on Ω HI as a function of redshift. The derived value Ω HI = (7.02 +0.59 −0.52 ) × 10 −4 at z  ∼ 0.37 from the combined analysis deviates by ∼2.9 σ from the ALFALFA result at z  ∼ 0. Conclusions. Our findings regarding the HIMF and Ω HI derived from deep, state-of-the-art interferometric surveys differ from previous literature results at z  ∼ 0 and z  ∼ 1. We are unable to confirm at this stage whether these differences are due to cosmic evolution consistent with a smooth transition of the H I content of galaxies over the last 8 Gyr or due to selection biases and systematics.

Abstract:

Drawing on four well‐established theoretical perspectives, this paper proposes an intersectional, emotionally grounded framework for understanding how gender and age jointly shape entrepreneurial perceptions across psychological, social, and cultural domains. Using 2024 Italian Global Entrepreneurship Monitor data and ordinal logistic regression, we find that women are approximately 30% more likely to report fear of failure and 20% less likely to feel self‐efficacious, despite perceiving high social respect for entrepreneurs. These emotional constraints persist across age, suggesting that gendered affective barriers are stable over time. We also demonstrate that composite indices, commonly used in entrepreneurial research, partially obscure gendered nuances that are better revealed through disaggregated analysis. This study contributes to entrepreneurship theory by integrating emotional risk into socially embedded models of entrepreneurial cognition. By addressing gendered emotional barriers, we contribute to building more socially sustainable and resilient entrepreneurial ecosystems, in line with the UN Sustainable Development Goals (SDGs). We further frame these barriers as strategic obstacles to environmentally responsible entrepreneurship, underscoring their relevance to SDGs 5, 8, 9, and 12. Finally, we highlight managerial implications: Incubators, accelerators, and firms should design gender‐sensitive interventions, such as inclusive training, mentorship, and financial instruments, to foster innovation, responsible production, and the resilience of entrepreneurial ecosystems.