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Knowledge of the spectrograph's instrumental profile (IP) provides important information needed for wavelength calibration and for the use in scientific analyses. This work develops new methods for IP reconstruction in high resolution spectrographs equipped with Laser Frequency Comb calibration (LFC) systems and assesses the impact that assumptions on IP shape have on achieving accurate spectroscopic measurements. Astronomical LFCs produce \\(\\approx10000\\) bright, unresolved emission lines with known wavelengths, making them excellent probes of the IP. New methods based on Gaussian Process regression were developed to extract detailed information on the IP shape from this data. Applying them to HARPS, an extremely stable spectrograph installed on the ESO 3.6m telescope, we reconstructed its IP at 512 locations of the detector, covering 60% of the total detector area. We found that the HARPS IP is asymmetric and that it varies smoothly across the detector. Empirical IP models provide wavelength accuracy better than 10 ms\\(^{-1}\\) (5 ms\\(^{-1}\\)) with 92% (64%) probability. In comparison, reaching the same accuracy has a probability of only 29% (8%) when a Gaussian IP shape is assumed. Furthermore, the Gaussian assumption is associated with intra-order and inter-order distortions in the HARPS wavelength scale as large as 60ms\\(^{-1}\\). The spatial distribution of these distortions suggests they may be related to spectrograph optics and therefore may generally appear in cross-dispersed echelle spectrographs when Gaussian IPs are used. Methods presented here can be applied to other instruments equipped with LFCs, such as ESPRESSO, but also ANDES and G-CLEF in the future. The empirical IPs will be crucial for obtaining objective and unbiased measurements of fundamental constants from high resolution spectra, as well as measurements of the redshift drift, isotopic abundances, and other science cases.

Nuclear star clusters (NSCs) are among the densest stellar systems in the Universe and often coexist with supermassive black holes (SMBHs) at galaxy centres. While SMBH formation histories are essentially lost, NSCs preserve evolutionary imprints through their stellar populations and stellar kinematics, reflecting the cumulative effects of mergers, accretion, and internal dynamical evolution. We aim to investigate the orbital structure of the unusually large NSC in FCC 47 (NGC 1336) by decomposing its stellar orbits into dynamically distinct components. We extract stellar kinematics, and in particular the line-of-sight velocity distributions (LOSVDs), from VLT/MUSE integral-field spectroscopy using the non-parametric Bayes-LOSVD approach, and apply triaxial Schwarzschild orbit-superposition modelling with the DYNAMITE software. We decompose the orbit library into hot, warm, cold, and counter-rotating components. We detect triple-peaked LOSVDs in the nucleus, indicating a complex orbital structure. The NSC forms a counter-rotating, kinematically decoupled component. A hot pressure-supported component, a warm counter-rotating structure and a counter-rotating cold disk in the centre suggest hierarchical assembly via early star cluster accretion and later in situ star formation. Our orbital decomposition of FCC 47 supports a hybrid formation scenario for this NSC. Dynamically distinct substructures reflect the interplay of accretion and in situ star formation during galaxy evolution.

Full spectrum fitting is the prevailing method for extracting stellar kinematic and population measurements from 1D galaxy spectra. 3D methods refer to analysis of Integral Field Spectroscopy (IFS) data where spatial and spectral dimensions are modelled simultaneously. While several 3D methods exist for modelling gas structures there has been less investigation into the more computationally demanding problem of 3D full spectrum fitting for stellar recoveries. This work introduces and compares two algorithms for this task: the Projected Nesterov Kaczmarz Reconstruction method (PNKR) and a version of the Bayes-LOSVD software which has been modified to account for spatial correlations. We aim to understand strengths and weaknesses of both algorithms and assess the impact of 3D methods for stellar inferences. We apply both recovery algorithms to a mock IFS data over a signal-to-noise ratio (SNR) range from 20-200 and evaluate the quality of the recoveries compared to the known ground truth. Accounting for spatial correlations in Bayes-LOSVD significantly improved the accuracy and precision of kinematic recoveries. 3D modelling with PNKR did not provide any significant improvement over 1D fits however, for SNR>40, PNKR did recover the most accurate kinematics overall. Additionally, by modelling the joint distribution over kinematics and populations, PNKR could successfully infer trends between these quantities e.g. inferring local metallicity-velocity trends, albeit with a significant bias on the absolute metallicity. Having demonstrated advantages of (i) 3D modelling with Bayes-LOSVD, and (ii) joint kinematic-population analyses with PNKR, we conclude that both methodological advances will prove useful for detecting and characterising stellar structures from IFS data.

Context. Blob detection is a common problem in astronomy. One example is in stellar population modelling, where the distribution of stellar ages and metallicities in a galaxy is inferred from observations. In this context, blobs may correspond to stars born in-situ versus those accreted from satellites, and the task of blob detection is to disentangle these components. A difficulty arises when the distributions come with significant uncertainties, as is the case for stellar population recoveries inferred from modelling spectra of unresolved stellar systems. There is currently no satisfactory method for blob detection with uncertainties. Aims. We introduce a method for uncertainty-aware blob detection developed in the context of stellar population modelling of integrated-light spectra of stellar systems. Methods. We develop theory and computational tools for an uncertainty-aware version of the classic Laplacian-of-Gaussians method for blob detection, which we call ULoG. This identifies significant blobs considering a variety of scales. As a prerequisite to apply ULoG to stellar population modelling, we introduce a method for efficient computation of uncertainties for spectral modelling. This method is based on the truncated Singular Value Decomposition and Markov Chain Monte Carlo sampling (SVD-MCMC). Results. We apply the methods to data of the star cluster M54. We show that the SVD-MCMC inferences match those from standard MCMC, but are a factor 5-10 faster to compute. We apply ULoG to the inferred M54 age/metallicity distributions, identifying between 2 or 3 significant, distinct populations amongst its stars.

Supermassive black holes (SMBHs) and nuclear star clusters (NSCs) co-exist in many galaxies. While the formation history of the black hole is essentially lost, NSCs preserve their evolutionary history imprinted onto their stellar populations and kinematics. Studying SMBHs and NSCs in tandem might help us to ultimately reveal the build-up of galaxy centres. In this study, we combine large-scale VLT/MUSE and high-resolution adaptive-optics-assisted VLT/SINFONI observations of the early-type galaxy FCC 47 with the goal being to assess the effect of a spatially (non-)variable initial mass function (IMF) on the determination of the mass of the putative SMBH in this galaxy. We achieve this by performing DYNAMITE Schwarzschild orbit-superposition modelling of the galaxy and its NSC. In order to properly take account of the stellar mass contribution to the galaxy potential, we create mass maps using a varying stellar mass-to-light ratio derived from single stellar population models with fixed and with spatially varying IMFs. Using the two mass maps, we estimate black hole masses of \\((7.1^{+0.8}_{-1.1})\\times 10^7\\,M_{\\odot}\\) and \\((4.4^{+1.2}_{-2.1}) \\times 10^7\\,M_{\\odot}\\) at \\(3\\sigma\\) signifance, respectively. Compared to models with constant stellar-mass-to-light ratio, the black hole masses decrease by 15% and 48%, respectively. Therefore, a varying IMF, both in its functional form and spatially across the galaxy, has a non-negligible effect on the SMBH mass estimate. Furthermore, we find that the SMBH in FCC 47 has probably not grown over-massive compared to its very over-massive NSC.

We explore the connection between galaxies and dark matter halos in the Milky Way (MW) and quantify the implications on properties of the dark matter particle and the phenomenology of low-mass galaxy formation. This is done through a probabilistic comparison of the luminosity function of MW dwarf satellite galaxies to models based on two suites of zoom-in simulations. One suite is dark-matter-only while the other includes a disk component, therefore we can quantify the effect of the MW's baryonic disk on our results. We apply numerous Stellar-Mass-Halo-Mass (SMHM) relations allowing for multiple complexities: scatter, a characteristic break scale, and subhalos which host no galaxy. In contrast to previous works we push the model/data comparison to the faintest dwarfs by modeling observational incompleteness, allowing us to draw three new conclusions. Firstly, we constrain the SMHM relation for \\(10^22.4\\times10^8M_\\odot\\) (\\(1\\sigma\\)). Secondly, by translating to a Warm Dark Matter (WDM) cosmology, we bound the thermal relic mass \\(m_\\mathrm{WDM}>2.9\\) keV at 95\\% confidence, on a par with recent constraints from the Lyman-\\(\\alpha\\) forest. Lastly, we find that the observed number of ultra-faint MW dwarfs is in tension with the theoretical prediction that reionisation prevents galaxy formation in almost all \\(10^8M_\\odot\\) halos. This can be tested with the next generation of deep imaging surveys. To this end, we predict the likely number of detectable satellite galaxies in the Subaru/HSC survey and the LSST. Confronting these predictions with future observations will be amongst our strongest tests of WDM and the effect reionisation on low-mass systems.

A central topic in extragalactic astronomy is understanding the formation and evolutionary histories of galaxies. These systems often comprise multiple structural components with distinct physical and dynamical properties, making it challenging to disentangle their individual contributions. Aiming at investigating the true structure of the inner stellar disk, we have developed a comprehensive pipeline for the chronochemical and dynamical analysis of galaxies (Glance: Galactic archaeoLogy via chronochemicAl & dyNamiCal modElling). The presented pipeline employs several state-of-the-art techniques by integrating them into a single, automated pipeline, enabling streamlined analysis of integral-field spectroscopy data, by allowing users to easily and directly extract valuable information on stellar populations, kinematics, dynamics, and gas properties. It automates multiple analysis techniques, including stellar population synthesis (Fado, Starlight, post-processing with RemoveYoung, kinematic extraction (pPXF, Bayes-LOSVD), and dynamical modelling (Dynamite). It handles tasks such as Galactic extinction correction, de-redshifting, Voronoi binning, and nebular continuum correction, while offering extensive customization options. Parallel processing significantly reduces computational time. When applied to MUSE data sampling the central region of NGC 1566, this methodology reveals that its stellar disk significantly deviates from the conventional exponential model, challenging the assumption of universality in disk morphology. In summary, this work presents a powerful, publicly available pipeline for conducting galactic archaeology, designed to advance our understanding of the formation and evolution of galaxies.

We establish the connection between the Magellanic Clouds (MCs) and the dwarf galaxy candidates discovered in the Dark Energy Survey (DES) by building a dynamical model of the MC satellite populations, based on an extensive suite of tailor-made numerical simulations. Our model takes into account the response of the Galaxy to the MCs infall, the dynamical friction experienced by the MCs and the disruption of the MC satellites by their hosts. The simulation suite samples over the uncertainties in the MC's proper motions, the masses of the MW and the Clouds themselves and allows for flexibility in the intrinsic volume density distribution of the MC satellites. As a result, we can accurately reproduce the DES satellites' observed positions and kinematics. Assuming that Milky Way (MW) dwarfs follow the distribution of subhaloes in \\(\\Lambda\\)CDM, we further demonstrate that, of 14 observed satellites, the MW halo contributes fewer than 4 (8) of these with 68% (95%) confidence and that 7 (12) DES dwarfs have probabilities greater than 0.7 (0.5) of belonging to the LMC. Marginalising over the entire suite, we constrain the total number of the Magellanic satellites at ~70, the mass of the LMC around \\(10^{11}M_\\odot\\) and show that the Clouds have likely endured only one Galactic pericentric passage so far. Finally, we give predictions for the line-of-sight velocities and the proper motions of the satellites discovered in the vicinity of the LMC.

Triaxial dynamical models of massive galaxies observed in the ATLAS3D project can provide new insights into the complex evolutionary processes that shape galaxies. The ATLAS3D survey is ideal as the sample comprises a good mix of fast and slow rotators with vastly different mass assembly histories. We present a detailed dynamical study with our triaxial modelling code DYNAMITE, which models galaxies as a superposition of their stellar orbits. The models allow us to constrain the intrinsic shape of the stellar component, the distributions of the visible and invisible matter and the orbit distribution in these nearby early-type galaxies and to relate it with different evolutionary scenarios. Triaxial modelling is essential for these galaxies to understand their complex kinematical features.

The goal of this work is to probe the total mass distribution of early-type galaxies with globular clusters (GCs) as kinematic tracers, by constraining the parameters of the profile with a flexible modelling approach. To that end, we leverage the extended spatial distribution of GCs from the SLUGGS survey (\\(\\langle R_{\\rm GC,\\ max} \\rangle \\sim 8R_{\\rm e}\\)) in combination with discrete dynamical modelling. We use discrete Jeans anisotropic modelling in cylindrical coordinates to determine the velocity moments at the location of the GCs in our sample. We use a Bayesian framework to determine the best-fit parameters of the total mass density profile and orbital properties of the GC systems. We find that the orbital properties (anisotropy and rotation of the dispersion-dominated GC systems) minimally impact the measurements of the inner slope and enclosed mass, while a strong presence of dynamically-distinct subpopulations or low numbers of kinematic tracers can bias the results. Owing to the large spatial extent of the tracers our method is sensitive to the intrinsic inner slope of the total mass profile and we find \\(\\overline{\\alpha} = -1.88\\pm 0.01\\) for 12 galaxies with robust measurements. To compare our results with literature values we fit a single power-law profile to the resulting total mass density. In the radial range 0.1-4~\\(R_{\\rm e}\\) our measured slope has a value of \\(\\langle \\gamma_{\\rm tot}\\rangle = -2.22\\pm0.14\\) and is in good agreement with the literature.