Seminars and Colloquia at ESO Santiago

SN 2023ixf and SN 2024ggi are among the best-observed Type II supernovae discovered to date, with multi-wavelength observations starting only hours after explosion. Their exceptional early coverage has provided new insight into the final stages of red supergiant evolution and the physical conditions immediately surrounding the progenitor stars. In this talk, I will summarize the main results obtained for both events and discuss their implications for pre-supernova mass loss and explosion properties. I will focus on the nebular phase of both events, where late-time spectra probe the inner ejecta and provide constraints on nucleosynthesis, explosion geometry, progenitor mass, and mass loss history. Finally, we place these results in the broader context of Type II supernova diversity and discuss how future high-cadence and multi-wavelength surveys will help clarify the role of circumstellar interaction in the final evolution of massive stars.

There has been growing evidence that Type Ia supernovae (SNe Ia) arise from various progenitor channels and explosion mechanisms. One such reason for this is the growing number of peculiar groups of SNe Ia that differ from cosmologically useful (normal) SNe Ia in photometric and spectroscopic properties. Here I look at 02es-like SNe Ia which are under-luminous at peak with a light curve width too broad for its luminosity. They show similarities to other under-luminous SNe Ia in their spectral features except a large range in their photospheric velocities. When observed early enough they have shown early UV flux excess, and [O I] in their late time nebular spectra. Considering these combined properties and more, literature suggests the violent merger of two white dwarfs is a strong contender for the progenitor for the 02es-like class. Using 1D radiative-transfer code TARDIS, we synthesise the spectra for this scenario for three violent merger models with differing initial white dwarf masses, with strong considerations made to line of sight effects that have shown to significantly impact observables in the model. TARDIS was used to investigate a large parameter space generating 36,000 synthetic spectra for which we developed methods to then compare to 02es-like SNe Ia observations. We found that the diversity within the sample arises from line of sight effects, and that the models explain the spectral evolution of the 02es-like observations particularly well.

In this lecture, I will discuss the physical properties of active galactic nuclei (AGN), focusing in particular on some of the most extreme objects recently discovered by the James Webb Space Telescope. I will describe how their main physical properties are measured, the challenges involved in interpreting these measurements, and the possible connection between highly accreting AGN in the early and local Universe. Finally, I will briefly discuss the role of ESO facilities, with particular emphasis on GRAVITY and its potential to probe the structure and dynamics of the broad-line region in these systems.

PyLongslit is a simple and transparent Python pipeline for processing astronomical long-slit spectroscopy data. The software is designed to prioritize manual execution, robustness, and pedagogical clarity, providing an accessible alternative to highly automated “black-box” reduction pipelines. The pipeline emphasizes visualization and quality assessment at each processing step, making it particularly well suited for teaching environments and for challenging datasets where automated methods may fail. Validation against established semi-automated reductions demonstrates good agreement in extracted spectra and noise estimates across multiple instruments. This presentation will highlight several difficult and edge-case reductions where manual control and transparency provide clear advantages, as well as provide an overview of the scientific research in which the pipeline has already been applied.

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Even though the gas around and between galaxies (the circumgalactic and intergalactic media, CGM and IGM) harbour about 90% of the baryons in the Universe, they remain significantly less understood than the matter associated with starlight from galaxies. In this talk, I will introduce the Baryon Cycle (ByCycle) project, a large high-resolution (R~20,000) 4MOST/VISTA spectroscopic survey that aims to bring these hidden baryons to light. By looking for MgII absorbers in the spectra of background quasars, we will trace cool (10^4 K) CGM gas found in the line of sight. With the help of a Variational Autoencoder that can reconstruct the pure quasar continua, we are able to effectively identify MgII absorbers via contextual anomaly detection without the need for any explicit spectral fitting. Thanks to a Random Forest, we are then able to reject a majority of false detections and achieve high purity (>~80%). Our framework makes it possible to process the hundreds of thousands of spectra our survey expects. I will present our machine learning methodology, its ongoing validation on real spectra, and an overview of the novel science that ByCycle will make possible.

The spectral energy distribution (SED) of a galaxy encodes vital information about its chemical composition, stellar populations, and dust content. To model the infrared emission, many modern SED-fitting codes rely on dust energy balance, which assumes that all energy absorbed by dust in the UV-optical is equal to the energy emitted in the infrared regime. However, few studies have been carried out to test the validity of this assumption at high redshift, where direct infrared observations are sparse. In this work, we perform aperture photometry in 111 galaxies from the Blue Jay survey (1.7 < z < 3.5) using public JWST/MIRI observations from the PRIMER, COSMOS-Web and COSMOS-3D surveys. By comparing measurements from MIRI to Prospector SED models derived using HST and NIRCam photometry, we find that mid-infrared fluxes are systematically overpredicted by about 10% at 7.7µm up to a factor of ~3 at 21µm. The discrepancy increases with inferred dust attenuation, indicating that dust energy balance suffers from line-of-sight effects in systems with complex dust geometries. Adding NIRSpec spectroscopy to the fits breaks parameter degeneracies and reduces the overpredictions by a factor of ~2. The bias is completely removed when fitting the measured MIRI photometry with the HST and NIRCam data. In the latter case, the resulting best-fit model spectra of dusty galaxies (Av>1) show significantly lower infrared luminosities (-30%) compared to spectra obtained without MIRI, strongly suggesting that the total energy budget drives the overpredictions. Our study highlights the limitations of dust energy balance at high redshift and underlines the importance of direct observations for accurately recovering the ISM and dust properties of Cosmic Noon galaxies.

Mapping cold molecular gas and dust at sub-kiloparsec (kpc) scales in galaxies is essential for understanding the physical processes driving star formation in the ISM, particularly during the peak epoch of cosmic star formation (z~2-3; cosmic noon). At these redshifts, near-IR IFU and rest-frame UV/optical observations with JWST and HST reveal turbulent rotating disks, dominated by compact and bright stellar clumps. However, the origin and role of these stellar clumps in galaxy assembly remain debated. Addressing this requires resolving their parent giant molecular clouds (GMCs) with sub-kpc CO observations tracing the cold molecular gas. Detecting GMCs at z>1, however, is extremely challenging due to the required sensitivity and resolution. Strong gravitational lensing can overcome these limits when combined with the high capabilities of ALMA. I will present high-resolution ALMA Band-3 and JWST/NIRCam observations of J0658, a 20x-magnified main-sequence star-forming galaxy at z=2.78. Using a new JWST-based strong lensing model, we performed a detailed characterization of the star-forming clumps and tested the Kennicutt--Schmidt (KS) relation at sub-kpc scales. We found a breakdown of the KS relation driven by the resolution of individual evolutionary stages of the star formation cycle in J0658, as well as evidence for a lensed galaxy pair at z~2.78 thanks to new ALMA Band-4 observations. Finally, I will highlight ongoing and upcoming projects targeting various highly magnified sources, aimed at extending these analyses to a broader population of high-z galaxies.

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Star formation proceeds in magnetized clouds, in which a combination of gas dynamics, dust evolution and angular momentum transport results in new stellar objects and their protoplanetary disks. In this talk, I will show how one can use facilities such as ALMA and NOEMA to get an all-around view on dust, gas, and magnetism evolution during the collapse phase. I study two protostars in the Perseus region, B1b-North and B1b-South. About 5,000 au apart from each other, these objects show both similarities and differences in the aspects mentioned above. Did these new stars form in the same way? Is their future bound to be the same? Or are they non-identical twins?

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Accurately balancing gas reservoirs, star formation, and feedback across cosmic time remains a central challenge for galaxy formation models. In this talk, I will present a comparison of three state-of-the-art cosmological simulations: Magneticum, IllustrisTNG, and SIMBA, with recent observational constraints from MaNGA, eROSITA, and Sunyaev-Zel'dovich measurements. While reproducing the observed hot gas content of dark matter halos requires strong AGN feedback, such models often overquench star formation in galaxies. Conversely, weaker feedback better reproduces galaxy populations but systematically overpredicts the hot gas content of massive halos. I will discuss how these results reveal fundamental shortcomings in current AGN feedback prescriptions, suggesting that the challenge lies not only in the amount of energy injected but also in its timing, location, and coupling to the surrounding gas. These findings provide important guidance for the development of the next generation of galaxy formation models.

Core-collapse supernovae are very energetic explosions that have a significant impact in the interstellar medium within galaxies. However, it is not well understood how progenitors of core-collapse supernovae form, evolve, and explode. In this talk, I plan to constrain the core-collapse supernova progenitor properties studying their star formation efficiency (or molecular gas depletion time) environments. In summary, it is found that interacting massive binaries occur in regions of intense, efficient star formation rather than simply higher gas content.

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