Events, Seminars, Talks

Abstract
Open clusters are one of the most useful places in the universe for studies of stellar and galactic evolution. Formed when stars collapse from the same molecular cloud into a gravitationally bound cluster, open clusters offer a unique way to study stars of a homogeneous age and chemical composition across a range of masses. This property means they are useful objects for many different areas of astronomy, and accurately cataloguing them is hence important. In this talk, I will present the work I conducted during my PhD, aiming to improve a number of aspects of the census of open clusters in the age  of Gaia. After an introduction to the field, I will start by discussing different unsupervised machine learning algorithms for detecting clusters in the billion-star dataset of Gaia. Next, I will present our recently published catalogue of over 7000 clusters, which represents the largest homogeneous unduplicated catalogue of open clusters to date, including cluster classifications and parameters calculated with approximate Bayesian neural networks. Finally, I will discuss upcoming work on better defining open clusters observationally, which will revolutionise how open clusters can be distinguished from unbound moving groups and associations.

Abstract
Open clusters are one of the most useful places in the universe for studies of stellar and galactic evolution. Formed when stars collapse from the same molecular cloud into a gravitationally bound cluster, open clusters offer a unique way to study stars of a homogeneous age and chemical composition across a range of masses. This property means they are useful objects for many different areas of astronomy, and accurately cataloguing them is hence important. In this talk, I will present the work I conducted during my PhD, aiming to improve a number of aspects of the census of open clusters in the age  of Gaia. After an introduction to the field, I will start by discussing different unsupervised machine learning algorithms for detecting clusters in the billion-star dataset of Gaia. Next, I will present our recently published catalogue of over 7000 clusters, which represents the largest homogeneous unduplicated catalogue of open clusters to date, including cluster classifications and parameters calculated with approximate Bayesian neural networks. Finally, I will discuss upcoming work on better defining open clusters observationally, which will revolutionise how open clusters can be distinguished from unbound moving groups and associations.

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MPIA signature speaker @ KoCo

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MPIA signature speaker @ KoCo

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Over 200 bright quasars have now been discovered in the first billion years of the Universe, with this number set to explode again with the now-online Euclid space mission. Observations of the first quasars, serving as "back-lights", have revolutionised our understanding of large-scale-structure at early times. In particular, our picture of hydrogen reionisation has been completely re-written. This process, during which intergalactic hydrogen becomes ionised by the light of the first stars, has broken every expectation: it ends much later (z~5.3), is far more inhomogeneous, and is far clumpier on small scales than all models had predicted. In this talk, I will present these surprising results obtained in the last 3 year by the XQR-30 Large Program. Along the way, we will need to worry about the origins of the first supermassive black holes, and the growing mystery of their unchanging properties across cosmic time.

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The Ultraviolet Imaging Telescope (UVIT) on AstroSat has been producing excellent images in the far-UV since it started operations in 2015. I lead two surveys using UVIT, to study open and globular clusters. We have completed 10 publications in the UVIT Open Cluster study (UOCS) series that cover blue stragglers, white dwarfs, sub-dwarfs and planetary nebulae. The Globular cluster UVIT Legacy Survey (GlobULeS) with 5 publications, has produced a far-UV catalog of several globular clusters, detection of a far-UV dim HB population in the most massive globular cluster Omega Centauri along with the binary blue straggler population of the core-collapsed cluster NGC 362. I plan to summarise the important results that we have obtained from these two surveys and the open questions arising out of these studies.

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With nearly one hundred gravitational-wave events observed by LIGO and Virgo, the mass spectrum of binary black holes starts revealing a number of features. While the most common primary black hole mass is about 8-10 Msun, the data reveal an excess at ~35 Msun and a long tail extending out to 90 Msun. Such features must encode the formation history of binary black holes, but their analysis has brought us more questions than answers to date. In my talk, I discuss several possible scenarios for the emergence of these features, based on novel semi-analytic models of binary evolution and star cluster dynamics.

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Mass loss plays a crucial role in the lives of massive stars, especially as the star leaves the main sequence and evolves all the way to the red supergiant (RSG) phase. Despite its importance, the physical processes that trigger mass loss events in RSGs are still not well understood. In this talk, I will introduce our new method to reproduce the atmospheric extensions of these cool evolved stars, where mass-loss events take place. I will also discuss the accuracy of our models when comparing the spectral energy distributions (SEDs) and interferometric visibilities with newly obtained VLTI/GRAVITY and MATISSE observations. This new methodology represents a step forward in modelling the winds of cool evolved stars.

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Euclid space mission of ESA is finally a reality, it is now out in space ready to observe the entire extra-galactic sky in the optical and in the infrared with exquisite resolution, depth and total observed area. The Euclid data set will be the deepest and widest source of extra-galactic information ever created and for such an amount of data ESA had to expand and improve the entire network of ground antennas to stand this unprecedented data transfer. With this unique tool, we will provide exquisite measures of weak-gravitational lensing, the 3D correlation function of galaxies, a huge sample of strong lenses for cosmography studies, the widest and broadest sample of galaxy clusters to probe cosmic structure formation and many other things. All with the goal of unveiling the nature of dark matter, dark energy and perhaps identify deviations from general relativity. I will describe the mission, the key scientific goals and the first tests performed on the first data. The first images we got are extremely promising!

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As an interim between Gaia DR3 (2022) and DR4 (2026), ESA and the science consortium have published five new data sets derived from Gaia observations, including four entirely new data types, and one drastically improved data set. Contrary to the main releases, which address almost any area of astronomy, these data sets are more specialized. In the talk I will briefly describe them: Drastically improved minor-planet orbits, newly discovered gravitational lenses (multiple images of quasars), half a million additional Gaia stars in the core of omega Centauri, the three-dimensional distribution of diffuse interstellar bands in stellar spectra, the radial-velocity variations of long-period pulsating variables. Gaia DR4 will present a large number of new data types, and strong improvements in many of the already established ones. The present data sets are partly meant to enable follow-on work prior to DR4, and partly as "appetizers" for things to come in 2026.

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If you are looking for astronomical data – catalogues, images, spectra, time series, whatever –, consulting the Virtual Observatory Registry is an excellent idea. Using an interface the Heidelberg GAVO group have recently contributed to astropy-affiliated pyVO package, you now can do so from the comfort of your jupyter notebook. In this talk, I will show you how to build queries and how to use their results. This will also serve as a very hands-on introduction into the Registry’s data model and its remaining limitations, in particular as regards “blind discovery”: data collection discovery based on physical characteristics of what a researcher is looking for rather than on project or instrument names.

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Many areas of astrophysics rely on accurate results from stellar evolution models, in particular those of massive stars due to their importance as sources of ionizing flux and chemically enriched material. One of the biggest drivers in the evolution of massive stars is their mass loss rate, but alas this is also still one of their least well-constrained properties. In this talk, I will explore the impact of mass loss in stellar evolution models more deeply, comparing the effect of applying different mass loss rates during the main sequence of massive stars. Strikingly, the results show that the main sequence mass loss is able to affect the interior structure of a massive star down to its core, which has complex repercussions for its subsequent evolution and final fate. At the end of the talk, I will discuss the impact of these results for the applicability of stellar evolution models and address the problems and uncertainties that remain to be investigated.

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Albeit rare in absolute numbers, massive stars are shaping our cosmic history as they are connected to many astrophysical key processes. Commonly defined as stars with an initial mass of more than 8 times the mass of our Sun, massive stars are the progenitors of black holes and neutron stars, reaching all nuclear burning stages before eventually undergoing their inevitable core collapse. In their relative short, but wild life, these luminous objects have an enormous impact on their galactic environment, enriching the surrounding medium with momentum, matter and ionizing radiation. This so-called "feedback" of massive stars is a building block for the evolution of galaxies, initiating and inhibiting further star formation. In the "afterlives" of massive stars, black holes and neutron stars can merge with each other, giving rise a to Gravitational Wave events. Many details of massive stars as well as their impact and evolution are still poorly understood. In fact, the overall picture we draw in textbooks often does not hold once we actually try to bring all the observational and theoretical constraints together. We nowadays know that many massive stars have one or more companion and interactions between massive stars are common. While this gives rise to different evolutionary channels, many challenges remain. Further unconventional puzzle pieces and surprising constraints have arrived from observational frontiers such as the strong metal-enrichment in high-redshift galaxies discovered by JWST or the black hole statistics obtained from Gravitational Waves. Investigating the massive star puzzle with a combined approach of theory, observation and numerics is at the very heart of my research group at the ARI. Our central tool in this endeavour is the application and development of dedicated stellar atmosphere models. I will briefly introduce the techniques and challenges of atmosphere modelling for hot, massive stars and their winds as well as their empirical and theoretical applications. Afterwards, I will provide an overview about the multi-ranged research efforts in my group, ranging from the spectral analysis of individual stars and the identification of "hidden" companions over theoretical studies on radiation-driven winds up to the generation of synthetic stellar libraries and new predictions for stellar feedback.

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Supernova feedback injects energy and turbulence, influencing the star formation process, and is therefore essential to understanding the formation and evolution of galaxies. Supernova remnants exhibit distinctive emission line ratios and kinematic signatures, which are apparent in optical spectroscopy. Using optical integral field unit data from PHANGS-MUSE collaboration project, we are able to identify supernova remnants within 19 nearby galaxies. We use a combination of five different optical diagnostics to identify SNRs. We account for the influence of diffuse ionized gas, using the line ratio maps of [SII]/Halpha and [OI]/Halpha in comparison with the Halpha surface brightness to select out supernova remnants. In addition, the velocity dispersion map and line ratio diagnostic diagrams are also useful ancillaries to confirm their identification. We identify 2399 supernova remnants within 19 nearby galaxies. This paper catalogs optical SNRs from PHANGS-MUSE and characterizes them. ~ 33% of SNRs lie within HII regions. In the five criteria we use to identify SNRs, in comparison with the Halpha surface brightness works best that select out 1482 SNRs. We also define a clean sample of 1276 SNRs that have been detected in at least two diagnostics, giving us high confidence in our characterization of these as SNRs. Overall, our detection of ~ 130 SNRs per galaxy implies an SN rate of 1~2 per century in our sample.

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Intense star formation and rapid black hole accretion in the centers of galaxies produce energy that propels gas outward. These galactic winds affect the evolution of their host galaxies, self-regulate the future growth of stars and black holes, and populate the enormous reservoirs of gas surrounding them. In the past decade, optical and near-IR integral field spectroscopy (IFS) from the ground has revolutionized the study of galaxy-scale outflows that reach into the their surroundings. The unprecedented infrared sensitivity, spatial resolution, and spectral coverage of the JWST IFUs is also transformative for studying these outflows at new, mid-infrared wavelengths. I will discuss observations of galactic winds driven by star formation and black holes at redshifts z ~ 0.5 that probe their extent and properties and illuminate the connection between galaxies and their surroundings.