We observe that present day disk galaxies have magnetic fields with a strength of several muG. They are roughly in equipartition with thermal and turbulent energy. Since seed fields are typically of the order of 1e-20G, the origin of the present day magnetic fields has been a long standing question of galaxy evolution. I present recent cosmological simulations that self-consistency evolve galaxies from the early universe to today. I show that they can reproduce present day magnetic fields in strength and structure for Milky Way-like galaxies. I discuss the physical mechanisms that efficiently amplify the magnetic fields and set their saturation strength. I then introduce new high resolution cosmological zoom simulations that generalise these results to a wide range halo masses from dwarf galaxies to groups of galaxies and quantify the numerical resolution needed to obtain converged results for our galaxy formation model. These results now enables us to use magnetic fields as diagnostics of the evolution of galaxies, and to faithfully include other physical processes like cosmic ray propagation or thermal conduction that depend on the structure and strength of magnetic fields.

It has often been assumed that magnetic fields reach equipartition too late to impact galaxy evolution. However, previous studies have tended to focus on isolated galaxies. Galaxy mergers, though, are a natural consequence of hierarchical structure formation, and bring with them several physical processes which could help amplify the magnetic field; strong tidal interactions inject turbulence, helping to promote a small-scale dynamo, whilst also leading to the compression and shearing of the gas, in which the field lines are flux-frozen. Given sufficient amplification, the magnetic field can then have a significant dynamical back-reaction. We have investigated this effect by running a series of high-resolution magnetohydrodynamic (MHD) ""zoom-in"" simulations of major mergers between disc galaxies using the Auriga model. In this talk, I will present some of the key results from these simulations, and will show how MHD simulations produce merger remnants with systematically different morphologies and sizes compared to their hydrodynamic analogues. I will demonstrate how this results from magnetic-field-driven angular momentum transfer, which typically acts to increase the baryonic concentration in the merger remnant. The impact of this is wide-reaching, resulting in altered feedback and generally increasing the black hole mass in MHD simulations. Our results show that magnetic fields are actually crucial for the correct modelling of disc galaxies.

Numerical simulations can substantially support the study of the origin of cosmic magnetism. Simulation projects that simultaneously consider a plurality of magnetic field seeding scenarios, resolve amplification processes, and reach cosmological scales are however still somewhat scarce. Leveraging on algorithmic advances at the heart of the novel cosmological code SWIFT, and developing concurrently a suite of Modern Lagrangian Magnetohydrodynamical (MHD) Solvers - each with a different formulation of Ideal and Resistive MHD - we seek to make theoretical predictions for the large-scale structure of magnetic fields in the late-time universe. We aim to make these forecasts for a variety of plausible magnetogenesis hypotheses, while identifying and correcting for biases introduced by the solver. I will discuss the progress that has been made in incorporating several flavours of MHD in SWIFT (two using direct induction of the magnetic field and one using vector potentials), how these yield competitive results on benchmark test cases, and how they perform on a first set of astrophysical and cosmological problems (for which the hydrodynamics and galaxy formation model have been kept fixed), emphasising where predictions converge and diverge and what can be learned from this comparison.

The non-thermal components of galaxies, magnetic fields (B) and cosmic rays (CRs), and their potential effects on galaxy formation are notoriously difficult to constrain observationally. Synchrotron emission is one of few observable tracers of these components, but several assumptions are required to make inferences about B or CRs. Towards exploring these assumptions, we use FIRE simulations which self consistently evolve CR proton, electron, and positron spectra from MeV to TeV energies and generate synthetic synchrotron predictions from simulated spiral galaxies with spectrally-resolved CR-MHD. Synchrotron emission can be dominated by relatively cool and dense gas, resulting in equipartition estimates of B with fiducial assumptions underestimating the ""true"" B by factors of 2-3 due to small volume filling factors. We also explore FIRE simulations which evolve a single bin of ~GeV CR protons with different transport models motivated by plasma physics theories. To first order, the synchrotron properties diverge between transport model families owing to a CR physics driven hysteresis. Models motivated by 'self-confinement' (SC) show a higher tendency to undergo `ejective' feedback events due to a runaway buildup of CR pressure in dense gas owing to the behavior of SC transport scalings at extremal CR energy densities. The corresponding CR wind-driven hysteresis results in markedly different synchrotron properties arising from different gas morphology and properties, indicating the potential for non-thermal radio continuum observations to constrain CR transport physics. Utilizing state-of-the-art CR-MHD simulations to generate synchrotron predictions holds promise to elucidate the role of B and CRs in galaxy formation and evolution.

Understanding the processes underlying galaxy formation is one of the most important challenges in astrophysics. Unresolved questions include the disconnect between the short time scale of gas collapse on small scales and the long time scale for galaxy evolution, as well as the mechanism responsible for ejecting mass, momentum, and energy out of galaxies (or preventing their infall) in a way that matches the observed scaling relations. Recent progress strongly suggests that cosmic rays may play a crucial role in controlling these processes in and around galaxies. However, the strength of cosmic ray feedback depends very sensitively on the dynamical coupling of cosmic rays to the plasma. I will present our recent efforts to model cosmic rays and magnetic fields in galaxy formation. After identifying the different stages of a gravitationally driven magnetic dynamo that grows the field to the observed strengths, I will explain how cosmic rays interact with and propagate through the magnetized plasma in the interstellar and circumgalactic media. This demonstrates that cosmic rays play a decisive role in the formation and evolution of galaxies by providing feedback that regulates star formation and drives gas out in galactic winds. Comparing cosmic ray spectra of electrons and protons to observational data and studying the correlation of the far-infrared emission with the gamma-ray and radio emission from galaxies enables us to test the cosmic-ray feedback and dynamo models for the growth of galactic magnetic fields. This argues that a complete understanding of galaxy formation necessarily includes these non-thermal components.

Modeling cosmic-ray (CR) transport on galactic scale is a challenging task primarily due to the complex physical processes coupling CRs to the thermal gas. As a result, in most interstellar-medium (ISM) studies involving CRs, the interaction between CRs and their scattering waves, that is unresolved on macroscopic scales, is treated via a constant scattering (or diffusion) coefficient, whose value is motivated by observational constraints. Considering the vastly varying conditions within the multiphase ISM, however, a constant scattering coefficient is unrealistic. To address this issue, we recently developed a detailed physical prescription for the transport of CRs, in which the scattering coefficient varies with the properties of the ambient gas. During my talk, I will first outline our method for CR transport and discuss the implications of adopting a more realistic formulation for the scattering rate. I will then present the application of our scheme in MHD simulations of galactic outflows. These simulations indicate that, under realistic scattering rates that are self-consistently determined, CRs efficiently accelerate extra-planar material if the latter is mostly warm gas, while they have very little effect on fast, hot outflows.

The evolution of a given galaxy is determined by the physical processes influencing its interstellar medium. Alongside supernova explosions, radiation pressure, and radiative heating, cosmic rays (CRs) have been identified as a vital feedback agent that is able to regulate star formation and shape the dynamics of the interstellar medium (ISM). Both CRs and the ISM are tightly connected. Next to providing an additional pressure component counteracting gravity, CRs (partly) ionize and heat neutral regions of the ISM even if other heating mechanisms or ionizing UV radiation are absent. On the other hand, the chemical composition and the magnetic field topology of the ISM directly influence how CRs are transported through a galaxy. In my talk, I introduce the CRISP (Cosmic Ray and InterStellar Physics) simulation framework - a new set of numerical tools for galaxy formation simulations that were designed to investigate these processes and to gain insight into their influence on galaxy evolution. One focus of CRISP is to provide an accurate description of CR transport which we model based on coarse-grained approximations of the relevant plasma physical processes. I present the first simulations of idealized Milky Way-type galaxies performed using the CRISP framework. I focus my presentation on two points: how CRs and supernovae are working in unison to drive highly structured and mass-loaded galactic winds, and how CRs are transported through these winds and the ISM by analyzing key parameters such as the CR streaming speed and the CR diffusion coefficient.

Cosmic rays (CRs) are ubiquitous in the interstellar medium (ISM) of the Milky Way and nearby galaxies and are thought to play an essential role in governing their evolution. However, many of their properties are not well-constrained. Since direct measurements of CRs are limited to our local environment, observations of radio and gamma-ray emission arising from CRs provide a powerful tool to constrain their transport properties and interactions with the ISM and magnetic fields in other galaxies. To help better understand the link between observational signatures and CR physics, we use a series of magneto-hydrodynamical AREPO simulations of isolated galaxies including self-consistent CR physics, with subsequent modelling of the CR spectra and their multi-frequency emission. I will show the underlying processes that are required to simultaneously match the observed correlations and spectra of star-forming galaxies like M82 and NGC 253 both in the radio and gamma-ray regime. Furthermore, I demonstrate the importance of modelling spectrally resolved CR transport for an accurate prediction of spatially resolved high-energy gamma-ray emission, as will be probed by the upcoming Cherenkov Telescope Array observatory. Lastly, I will give an outlook on applying our modelling of synthetic CR observables to cosmological zoom simulations within the Auriga galaxy formation model of dwarf to Milky Way sized galaxies and their satellites.

In large-scale simulations, which also include a spectrally resolved treatment of cosmic-ray injection and propagation, high-energy protons and electrons accelerated at the shocks of supernova remnants have to be described by a sub-grid model. Usually, the injected cosmic rays are represented by a simple power-law spectrum in momentum space. However, several models for more realistic cosmic-ray spectra produced by supernova remnants over their lifetime have been proposed in the recent past, enabling us to refine currently used sub-grid prescriptions in a physically-motivated way. We present an implementation of this approach in the cosmological SPH code OpenGadget3 and its application to galaxy simulations in isolated and in dense environments. We check if the more realistic cosmic-ray spectra from different types of supernovae lead to quantitative or qualitative differences compared to the ""minimalist approach"".

To understand how our present-day Universe came into being, we have to look back to a few hundred thousand years after the Big Bang, when the first stars and galaxies formed. Thanks to numerical simulations, it is now established that supernova and active galactic nuclei (AGN) feedback are key processes to regulate galaxy growth. However, many recent works have suggested that other feedback mechanisms are also important, especially in low-mass galaxies. In particular, cosmic rays have been shown to contribute to regulate star formation and to carry dense gas, which is where radiation is preferentially absorbed. As such, are they an important source of feedback in the early Universe, and do they play a role in the reionisation of the Universe by affecting the escape of ionising radiation from galaxies? On the other hand, most massive galaxies host an actively accreting supermassive black holes, whose feedback can launch massive winds. Can those AGN-driven winds suppress star formation, and explain the growing number of observations of massive quenched galaxies at high-redshift commonly underestimated by all cosmological simulations to-date? To answer these questions, I will 1) present results from a suite of Sphinx simulations that include cosmic rays and radiation-magneto-hydrodynamics, dedicated to the study of the Epoch of Reionisation, and 2) show how improving the modelling of AGN feedback in the radiatively efficient regime (which dominates at early cosmic epochs) is necessary for better understanding the role of AGN feedback in quenching galaxies, from the cosmic dawn to present-day.

In recent years, cosmological hydrodynamical simulations have become a very popular interpretative tool in studies of galaxy formation and evolution. While many simulations of this class are, to some degree, calibrated to reproduce the local stellar mass function of galaxies, the evolution of the gaseous universe in these models retains genuine predictive power. Thus, such simulations can be used to self-consistently probe how the stellar mass of galaxies has been assembled at a statistical level, across several order of magnitude in mass. Using three modern cosmological simulations – EAGLE, IllustrisTNG, and SIMBA – I will present the results of a detailed, like-for-like comparison of how gas moves in and out of galaxies between these models. I will demonstrate that the varied implementations of stellar and AGN feedback in each simulation produce significant differences in the scale of gas ejection, and thus, the resulting preventative impact on cosmological gas accretion. This work lays the foundation for developing targeted observational tests that can favour certain methodologies, and move towards a more constrained understanding of the role of feedback processes in the baryon cycle.

We use FLAMINGO, the biggest full hydro cosmological simulation ever, to study the most massive objects in the universe and do a direct comparison with observations. FLAMINGO hosts many millions of galaxy groups and clusters, in their full cosmological environment, making it an ideal testing ground to do a statistically relevant comparison with observations. Using a new forward modeling pipeline for X-rays, including photo-ionization models from CLOUDY, we can accurately model the emission from clusters and their surroundings in a wide mass range. We construct X-ray scaling relations and study how they are impacted by halo- and stellar mass, cool-core fractions, relaxed-ness, projection effects, and redshift. Furthermore, because FLAMINGO has 9 observationally motivated feedback variations, we show the impact of AGN and stellar feedback on group and cluster profiles. For all FLAMINGO haloes, we also compute their density, entropy, temperature, and pressure profiles. In particular, we focus on the qualitatively different inner profiles obtained when using kinetic jet AGN feedback, and how this directly impacts the CC/NCC sample composition. We compare the thermodynamic profiles with observations, and fit them to estimate the hydrostatic bias, which we can now do for millions of galaxy groups and tens of thousands of massive clusters, and as a function of cluster properties. With the unprecedented size of the FLAMINGO simulations, we can do all these things for statistically relevant sample sizes, enabling a real comparison with observations at all masses.

In this talk, I will discuss the role of various physical processes (e.g. feedback and mergers), in altering the properties of galaxies and the distribution of baryons within and around dark matter halos. The talk will begin by focusing on galaxy clusters, introducing the initial results from the TNG-Cluster project, which comprises a collection of 352 detailed zoom simulations of galaxy clusters. I will delve into the dynamics of gas in relation to the properties of galaxies and halos, from the cluster cores to their outskirts. This will demonstrate how our results from the TNG-Cluster simulation broadly align with observations of the kinematics of multiphase gas across different scales in galaxy clusters, ranging from 1 kpc to Megaparsec scales.
Next, I will turn to galaxy groups and Milky Way-like halos, presenting the ongoing ""Beyond"" project. This project aims to develop a sophisticated AGN feedback model for the next generation of galaxy formation simulations. The preliminary results from the first runs of the ""Beyond"" simulations will be discussed, focusing on the effects of different AGN feedback implementations on the properties of galaxies, the circumgalactic medium (CGM), and the intergalactic medium (IGM) gas.

The high-performance computing world has reached a (symbolic) milestone in the last year with the arrival of the first exa-scale systems. Countries around the world are discussing what kind of ex-scale machine they will get and on what time-scale. How well are we doing with our large-scale structure and galaxy formation computations? By the commonly-adopted FLOPs metric, our largest calculations barely reach 1 peta-flop (very optimistically). There is thus a 1000-fold discrepancy between system capabilities and our usage. Will we be able to bridge that gap?
In this talk, I will discuss some of the problems the community faces (e.g. the need to transition towards accelerators) and suggest some possible paths forward based on our experience developing parts of the SWIFT cosmological code and trying to future-proof it.

One of the key questions in modelling the formation and evolution of galaxies is the impact and relative importance of the stellar and AGN feedback. We aim to constrain the varied prescriptions of stellar wind and AGN feedback using the statistical properties of highly ionized absorbers in cosmological simulations, implementing different feedback models. For each simulation, by considering a wide range of ultraviolet background (UVB), we show the statistical properties such as distribution functions of column density (N), b-parameter and velocity spread, the redshift space clustering and turbulence velocities are influenced by the feedback processes and the UVB used (arXiv:2301.10788). The difference in some of the predicted distributions between the varied feedback models is similar to the one obtained by varying the UVB for a given simulation. Most of the observed properties of O VI absorbers are roughly matched by simulations incorporating both stellar Wind and AGN feedback when using the softer UVB. We find the feedback processes affects the OVI-redshift-space-clustering for scales <2Mpc whereas the influence of UVB is restricted to <1Mpc length scales (arXiv:2311.03444). Both the turbulence due to various feedback processes and the spread in the kinetic temperature of the gas contributing to the absorption are manifested as non-thermal line broadening. We show the distribution of non-thermal broadening is also affected by both feedback processes and the ionizing UVB (arXiv:2309.05717). Therefore, in order to constrain different feedback processes and/or UVBs, using observed properties of HI and metal ions, it is important to perform simultaneous analysis of various observable parameters.

Active galactic nuclei (AGN) in the centres of their host galaxies release energy in the form of winds and jets that have different properties, efficiencies and launching mechanisms depending on the black hole (BH) accretion rate. Winds from quasars are implemented in all modern cosmological simulations of galaxy formation. Some such simulations also include the effects of AGN jets launched at low BH accretion rates, although usually in a simplistic manner. I will present efforts of modelling these jets in conjunction with BH spin evolution, which requires the inclusion of detailed accretion disc physics. I will present results from some initial tests of such a model in the context of idealized galaxy clusters with both single-episode AGN jet events, as well as self-consistent feeding and feedback with multiple episodes and self-regulated growth. These tests show that using AGN jets as a feedback mechanism can reduce the star formation rates and stellar masses of central galaxies in galaxy clusters, which helps alleviate a problem that plagues all hydrodynamical galaxy formation models. AGN jets also appear to lead to improved properties of the intracluster medium (as measured through the temperature and entropy profiles), as a result of less central energy deposition. I will also discuss some preliminary results of this model when used in large cosmological simulations. The jets appear to have little effect on the overall galaxy population (with the exception of massive central galaxies), but a massive effect on the intergalactic medium, which is much hotter than in the case without jets.

AGN feedback has an important role in shaping galaxy and Massive Black Hole (MBH) evolution, but many aspects are still unexplored. I’ll present a numerical model of AGN radiative feedback that (i) includes the generally neglected, but important, impact of spin and (ii) bridges from the accretion disc to nuclear scales, in an intermediate region which is generally overlooked, as GRHMDs simulations have smaller domain and galaxy/cosmological simulations cannot resolve these regions. Spin significantly modifies the amount and the anisotropy of the AGN emission, ultimately influencing the ability of radiation-driven AGN winds to couple to the surrounding material and affect the host galaxy out to large scales. In my model, accretion from resolved scales onto the unresolved AGN disc, spin evolution, the injection of AGN winds into resolved scales and their spin-induced anisotropy are all self-consistently evolved. I’ll discuss a suite of simulations aimed at investigating the role of AGN feedback anisotropy in shaping the structure of galactic outflows and their impact on the host galaxy gas reservoir and star formation out to kpc scales.

In theoretical models of galaxy evolution, black hole feedback is a necessary ingredient in order to explain the observed exponential decline in number density of massive galaxies. Most contemporary black hole feedback models in cosmological simulations rely on a constant radiative efficiency (usually __ _ 0.1) at all black hole accretion rates. I will present a synthesis model for the spin-dependent radiative efficiencies of three physical accretion rate regimes, i.e. __ = __(__), for use in large-volume cosmological simulations. The three regimes include: an advection dominated accretion flow, a quasar-like mode, and a slim disc mode. Additionally, there is a large-scale powerful Blandford-Znajek jet at low accretion rates. The black hole feedback model that I present is a kinetic model that prescribes mass loadings but could be used in thermal models directly using the radiative efficiency. In fact, the radiative efficiency curves could be implemented into any contemporary cosmological simulation. We implemented our model into the Simba galaxy evolution model to determine if it is possible to reproduce galaxy populations successfully, and provide a first calibration for further study. I will discuss the model and select impressive results from a billion particle simulation in a 150 cMpc cubed cosmological volume.

Black holes are believed to be crucial in regulating star formation in massive galaxies, which makes it essential to faithfully represent the physics of these objects in cosmological hydrodynamics simulations. Limited spatial and mass resolution makes following the dynamics of black holes particularly challenging. In particular, dynamical friction, which is responsible for driving massive black holes towards the centres of galaxies, cannot be accurately modelled with softened N-body interactions. A number of subgrid models have been proposed to mimic dynamical friction or directly include its full effects in simulations. Each of these methods has its individual benefits and shortcomings, while all suffer from a common issue of being unable to represent black holes with masses below the dark matter particle mass. In this talk, I will describe a model for unresolved dynamical friction, which has been calibrated on simulations run with the code KETJU, in which gravitational interactions of black holes are not softened. I will demonstrate that the model is able to sink black holes on correct timescales and is able to treat low-mass black holes in cosmological simulations.

We study the fueling mechanisms of supermassive black holes (SMBH) by examining the origin of gas accreted by 10^{9-9.5} M_sun SMBH at z=0. We trace the history of gas in 20 zoom-in cosmological simulations of massive galaxies with stellar masses of M_stel = 10^11-12 M_sun at $z=0 with rich major and minor merger histories. We trace the history of gas that central SMBH accretes and classify its origin depending on how it enters the primary halo. (1) Gas that ever belonged to a different galaxy before accretion is defined as external, and (2) all other smoothly accreted gas is labeled as smooth. Finally, (3) if the gas is produced by stellar evolution within the primary halo and then accreted to SMBH, we classify it as recycled. Our analysis reveals that the primary fuel source for SMBHs is the recycled gas from dying stars. The second most significant fuel source is external gas obtained through galaxy mergers. With this information we label all AGN activities in our simulation depending on their triggering mechanisms snapshot by snapshot. These simulation snapshots are post-processed with a radiative transfer code to generate JWST mock observations of redshift 0.5

Modern-day cosmological simulations have proven to be successful in reproducing realistic BH and AGN properties in low-redshift galaxies such as the observed BH scaling relations. However, towards high redshift, different simulations predict fundamentally different BH and AGN populations, likely related to different, often ad-hoc, sub-grid models for BH seeding, accretion and feedback. In particular, gas accretion onto BH is vital to be accurately modelled because it (among other parameters) determines the strength of AGN feedback. In this work, we therefore introduce a novel, physically motivated sub-grid model for BH accretion in the moving-mesh code AREPO. To accurately estimate the accretion rate, the model takes into account the dynamics (+ angular momentum) of nearby gas cells fulfilling a set of accretion criteria, as well as introduces both a free-fall and viscous timescale (where the latter is meant to represent the accretion disk), before estimating the final accretion rate onto the BH. In fact, the developed model is among the first which closely follows high-fidelity predictions of modern 3D GRMHD simulations of BH accretion disks. Utilising this new model, we perform high-resolution dwarf galaxy simulations and investigate how SMBHs grow in mass in a well-resolved ISM together with high-fidelity models for star formation and stellar feedback. We explore under what conditions stellar feedback can regulate SMBH growth, if it is possible to achieve (super-) Eddington accretion (and if so over what timescales), and if AGN feedback is a necessity to regulate SMBH growth.

Active Galactic Nuclei (AGN) feedback encompasses a vast range of scales, from the immediate vicinity of a supermassive black hole's (SMBH) event horizon to galactic halos, and occasionally extends to the intracluster medium. This range covers distances from a few astronomical units (AU) to megaparsecs (Mpc). Such extensive scale variation presents theoreticians with a formidable challenge, pressing the need for models that comprehensively capture the intricate details of this phenomenon.
In response to this challenge, our research integrates General Relativistic Magnetohydrodynamic (GRMHD) simulations of accretion flows around SMBHs with broader galactic simulations. Utilizing the GRMHD code H-AMR, we focus on hot accretion discs with rates below 0.01 of the Eddington rate, extracting key outflow properties such as mass, momentum, and energy fluxes. We then incorporate these properties as inner boundary conditions into a galactic simulation using the AREPO code. This ensures a continuous injection of mass, momentum, and energy into the simulated host galaxy, aligned with GRMHD simulation predictions.
Our integrative approach offers a more nuanced portrayal of AGN outflows – including winds and relativistic jets – and their interactions with the host galaxy's interstellar medium (ISM). Preliminary results from our simulations shed light on the effects on the galaxy's gas density and temperature. Additionally, we anticipate that our methodology will provide estimations of the potential impacts on star formation rates.

JWST has recently discovered new Active Galactic Nuclei (AGN) at redshifts 5 < z < 11 with masses generally within 10^6 - 10^7 Msun. We aim to understand accretion and feedback from these early black holes by developing and running cosmological zoom-in simulations using the latest version of the AREPO code. Specifically, we apply new models of black hole accretion physics to determine whether they accrete at super-Eddington to study black hole growth, including the formation of quasar black holes (~10^9 Msun) at z = 6 - 7.5, and the properties of their host galaxies. We base the accretion rate on a sub-grid alpha disc model where super-Eddington accretion is allowed. The resulting feedback from super-Eddington accretion is parametrized using the results of previous 2/3D (GR)RT-MHD simulations to characterize wind mass loading and kinetic energy as a function of the accretion rate. Our production runs are zoom-in simulations of cosmologically evolved galaxies with stellar masses that match the range of JWST observations, and are run at different resolutions to z = 6. We analyze simulations to examine how AGN feedback resulting from super-Eddington accretion constrains black hole and galactic (e.g. stellar mass) evolution with comparisons to observations.

Recent observations have established that dwarf galaxies can host black holes of intermediate mass (IMBH). With novel simulations including the detailed physics of the interstellar medium, accurate stellar dynamics and black hole feedback, we test the growth of IMBHs as well as their evolutionary impact on the host galaxy.
Our new subsolar-mass (0.8 solar mass) resolution simulations of dwarf galaxies have a resolved three-phase interstellar medium and account for non-equilibrium heating, cooling, and chemistry processes. The stellar initial mass function is fully sampled between 0.08 – 150 star masses while massive stars can form HII regions and explode as resolved supernovae. The stellar dynamics around the IMBH is integrated accurately with a regularization scheme. We present a viscous accretion disk model for the IMBH with momentum, energy, and mass-conserving wind feedback.
In my talk, I will discuss the interplay between AGN feedback, IMBH growth, star formation and stellar feedback. I will show how the presence of the IMBH and its feedback impacts the gas phase structure and the formation of a nuclear star cluster. Overall, the IMBH accretion rates are low and the growth times are long, in agreement with observational estimates from X-ray observations. I will discuss general implications for black hole growth and seeding.

Feedback from supernovae and radiation emitted by stars plays a pivotal role in shaping the early universe. These feedback processes have a direct influence on gas and stellar dynamics, leaving discernible traces in observational data. I introduce SPICE, a novel suite of radiation-hydrodynamical simulations targeting cosmic reionization. SPICE uses RAMSES-RT to track the propagation of radiation from stars and employs a state-of-the-art galaxy formation model with a focus on resolving the multiphase interstellar medium down to 20 pc scales. The goal of these simulations is to systematically probe a variety of stellar feedback models, including ""bursty"" and ""smooth"" modes of supernova energy injections. SPICE shows that subtle difference in the behavior of supernova feedback can drive profound difference in reionisation histories with burstier forms of feedback causing earlier reionisation. SPICE highlights that stellar feedback and its strength determine the morphological mix of galaxies emerging by z=5. While star-forming disks are prevalent if supernova feedback is smooth, bursty feedback generates dispersion dominated systems. I present a strong correlation between galaxy morphology and lyman continuum escape fractions of galaxies where dispersion supported galaxies show 20-50 times higher escape fractions as compared to their rotation dominated counterparts. Finally, I validate the observational signatures of different feedback models, as demonstrated by SPICE, against the latest data from JWST and ALMA observations.

We introduce a new set of cosmological radiation-hydrodynamical simulations of high-redshift galaxy formation, conducted using the AREPO-RT code. The objects were selected from the THESAN simulation and were re-simulated with the zoom-in technique for higher resolution, and employing a different galaxy formation model. We use a modified version of the SMUGGLE model for this purpose, which aims to resolve the different phases of the interstellar medium (ISM).
We discuss the modifications of the feedback modelling, examine various basic properties of the galaxies, such as the stellar mass-halo mass relation, as well as the morphology of the stellar populations and the interstellar medium. A key aspect of this project is investigating how ionizing radiation escapes from these galaxies, thereby contributing to cosmic reionization.
We also briefly touch upon the new zoomed initial conditions code used in this project, as well as on a new approach for the boundary conditions of the radiation fields at the edge of the high-resolution region of the zoom simulations, which allows for the external reionization of low mass objects.

In this talk, I will present GEAR-RT, a radiative transfer solver using the M1 closure in the open source code SWIFT. Some of its distinguishing features are that GEAR-RT employs particles as discretization elements and solves the equations using a Finite Volume Particle Method (FVPM). Secondly, GEAR-RT makes use of the task-based parallelization strategy of SWIFT, which allows for optimized load balancing, increased cache efficiency, asynchronous communications, and a domain decomposition based on work rather than on data. Furthermore, GEAR-RT is able to perform sub-cycles of radiative transfer steps w.r.t. a single hydrodynamics step. Radiation requires much smaller time step sizes than hydrodynamics, and sub-cycling permits calculations which are not strictly necessary to be skipped. Indeed, in a test case with gravity, hydrodynamics, and radiative transfer, the sub-cycling is able to reduce the runtime of a simulation by over 90%. While other state-of-the-art software permit for a fixed number of RT sub-cycles for any hydrodynamics step, GEAR-RT takes this method one step further and permits for the number of sub-cycles to be fully adaptive and to be determined dynamically by the local conditions: The sub-cycling follows a similar localised time-stepping approach in addition to the localised time-stepping approach we employ for all other physics.

Dwarf galaxies are particularly susceptible to the stellar feedback from ionizing radiation, winds, and supernova explosions, making them a unique platform for probing the detailed feedback physics. Recent numerical models have endeavoured to resolve the multiphase interstellar medium with a very high resolution of several solar masses, while many opt to approximate methods when modelling radiation feedback rather than an explicit radiative transfer calculation due to the computational challenge. We present the RIGEL model, a novel framework to self-consistently model the effects of stellar feedback in the interstellar medium (ISM) of dwarf galaxies with individual massive stars. The model combines a state-of-the-art radiation hydrodynamics module (Arepo-RT) with a library of metallicity dependent radiation and wind feedback intensity from individual massive stars. The radiation from infra-red to He ionizing bands is tracked with seven bins and a practical method is designed to correct the resolution issues in the unresolved compact HII region. We track the non-equilibrium H, He chemistry and equilibrium abundance of C/O species to capture the thermodynamics of all ISM phases from hot ionized gas to cold molecular gas. We test this model on very high-resolution (1Msun) isolated dwarf galaxy simulations with gas (stellar) mass of 4(2)*10^7 Sun. We found that the star formation rate (SFR) is reduced by an order of magnitude due to the radiation feedback. Radiation feedback occurs immediately after a massive star is formed and disperses the molecular clouds rapidly in dwarf galaxies. Thus, the time spread of low-mass star clusters is tightly related to the timing of the onset of radiation feedback. The efficient early feedback prohibits the formation of massive star clusters, shapes the cluster initial mass function sheep at the high-mass end and shortens the age spread of star clusters to less than 2 Myr.

Many unresolved questions remain in our understanding of galaxy formation and evolution from cosmic dawn to the epoch of reionization. Recent JWST observations have uncovered this epoch and raised unique challenges to the existing galaxy formation model. In this talk, I will briefly summarize the big questions brought by JWST, including the surprisingly large abundance of UV-bright galaxies at cosmic dawn, ultra-compact galaxies, and the ubiquitous AGN activities. Despite potential observational uncertainties, they may suggest that our current galaxy formation theories are incomplete or need adjustments to account for different behaviors at the cosmic frontier. I will introduce our recent studies of these questions using empirical models and cosmological simulations (THESAN and FIRE-2) and discuss the implications for advancing galaxy formation physics in light of JWST observations.

The formation of stars in galaxies are largely controlled by its competition with feedback from massive stars, with pre-supernova feedback playing a crucial role in this context. There has been significant progress in quantifying this competition in conditions resembling weakly star-forming galaxies such as the Milky Way. However, the nature of star formation and feedback in highly dust-obscured environments -- such as encountered in IR-bright galaxies in the local, and more commonly higher redshift, Universe -- and its implications are yet to be fully explored. This regime result in starbursts that form massive, compact, super-star clusters, the feedback from which could have important dynamical consequences on their host galaxies. In this talk, I will present insights obtained from state-of-the-art radiation-hydrodynamic numerical simulations of star cluster formation in this regime. I will specifically highlight the aspects of star formation and feedback unique to this regime: the high star formation efficiencies achieved, the crucial role of radiation pressure on dust grains, high gas/dust temperatures achieved due to the obscured conditions, and a relatively high degree of Lyman Continuum photon leakage from the star clusters. These insights could be utilised to build more appropriate, physically-motivated subgrid prescriptions for galaxy formation models in this regime, to tackle the issue of relative underabundance of highly infrared-bright galaxies obtained in the literature.

Massive stars form in dense gas cores of giant molecular clouds, where they influence their natal clouds through radiation and other feedback processes. Recent advancements in instrumentation now enable investigating star-forming regions across entire nearby galaxies with unprecedented spatial resolution. To facilitate a detailed comparison between theoretical models and observations, we simulate HII regions using our new moment-based, multiple-frequency radiative transfer scheme in the SWIFT code. For the first time, we couple these models to the non-equilibrium CHIMES photochemistry network which includes the photochemistry of metal species that are commonly needed for the emission line diagnostics such as the BPT diagram. To obtain mock optical emission lines, we employ RADMC-3D and Cloudy for post-processing. We will show the emission line diagnostics of the spatially resolved H II region on the BPT diagram and compare it with unresolved ones. Our simulated HII regions lie well within the star-forming regions of widely used emission line ratio diagnostics (e.g., BPT diagram). We will also compare the predicted intensities of optical recombination lines with those derived from several analytical methods, which demonstrates the potential of our novel approach to yield more realistic simulations that align with observations.

Observations with the James Webb Space Telescope have revealed an abundance of bright z>10 galaxy candidates that are increasingly difficult to reconcile with the predictions of most theoretical models towards higher redshifts. Various explanations for this potential discrepancy have been proposed, such as feedback-free starbursts, radiation-driven outflows clearing the of dust from star-forming regions, a top-heavy stellar initial mass function (IMF), or only detecting galaxies going through periods of intense star formation due to their faster growth in mass.
To investigate how an IMF, which, as suggested by the simulations of star-forming clouds in Chon et al. 2022, becomes increasingly top-heavy towards higher redshifts and lower gas metallicities, affects the properties of these early galaxies and reionisation, we have built the first model that follows early galaxy evolution and reionisation accounting for such an evolving IMF. To this end, we have adjusted the descriptions for supernovae feedback, metal enrichment, and ionising and ultraviolet radiation emissions in the Astraeus framework that couples an N-body simulation with a semi-analytical model for galaxy evolution and a semi-numerical model for reionisation.
In this talk, I will show how our parameterisation of an evolving IMF changes the ultraviolet luminosity functions, the relations between different galactic properties and the topology of the ionised regions growing around the galaxies in the intergalactic medium during reionisation compared to a constant Salpeter IMF.

In this talk, I will present the main results of the recently accepted for publication of the last three papers in the AGORA collaboration. In these papers, we analyze many properties of a single Milky Way mass galaxy simulated using many of the most used numerical codes in the community and also using different stellar feedback strategies. We have found good convergence on global parameters like the merger history or the stellar mass assembly, but significant differences in the stellar disk morphology, the CGM properties, and the satellites' star formation history. I will also present the new ongoing projects within the AGORA collaboration. Finally, I will announce a future collaboration between the Euclid-Arrakihs community and the AGORA project, including the generation of new AGORA CosmoRun models using different dark matter flavours.

Galactic winds are observed to be of multiphase nature and consist out of cold, warm and hot gas that can well be traced by HI and CO in the cold, H-alpha in the warm and at the highest gas temperatures via photo-ionized metal species such as MgII or OIII or X-rays. While this presents a strong challenge for outflow observations due to the fact that we need to invest in different techniques and instruments, the challenge with respect to the numerical modeling is equally hard due to the small-scale physics involved and the high resolution needed to resolve the launching and subsequent mixing of the gas further out in the CGM. I will present a set of high-resolution simulations (solar mass and sub-parsec) of isolated dwarf galaxies, that are targeted to understand the nature of galactic winds and their surrounding ambient medium. My simulations include single stars, non-equilibrium cooling and chemistry and resolved feedback from photo-ionizing radiation as well as supernovae. Consistent with a number of different outflow simulations we find that the warm wind (T ~1e4 K) is transporting most of the mass while the hot wind is responsible for the bulk of the energy budget in the wind (T~5e5 K). Our simulations are able to successfully reproduce the observed low mass loading factors observed in local dwarf galaxies and can recover their multiphase nature. The energy loading appears lower than predicted by theoretical models, posing a joint challenge for analytic wind theory and direct numerical simulation.

The exact nature of the star formation (SF) and feedback (FB) physics driving galaxy evolution remains uncertain. While cosmological simulations now manage to reproduce global properties and scaling relations of the z=0 galaxy population, the SF and FB physics models of these simulations differ significantly. They are often simplistic and highly degenerate, thereby limiting what we can learn from them. To break these degeneracies, it is crucial to identify promising observables that can distinguish between different physics models.
I will present detailed analysis of a sample of 60 Milky Way halo-mass galaxies from cosmological simulations. This set of simulations comprises galaxies evolved self-consistently across cosmic time with different baryonic sub-grid physics: three different SF models (including a turbulence-dependent one) and two different stellar FB (SFB) prescriptions (one with early SFB).
I show that despite broadly similar stellar masses at z=0, other galaxy properties, particularly those of the cold and neutral interstellar medium (ISM; e.g. mass, density, morphology) differ significantly between the different physics samples. This is a direct consequence of the different models leading to SF in different ISM conditions, thus affecting the impact of the subsequent SFB and further evolution of the galaxy. Finally, focussing on the neutral gas, I will demonstrate that the ISM morphology is a particularly promising observable to disentangle the effects of SF and SFB.
Comparing these predictions with the wealth of observations expected from current and upcoming facilities (e.g. the SKA) will significantly advance our understanding of the baryonic physics driving galaxy evolution.

Stellar feedback plays a pivotal role in shaping the structure and energetics of the ISM. Various channels of stellar feedback exist, including SNe, stellar winds, and radiation, but their relative significance remains the subject of debate. I will present the SATIN simulations that study the evolution of the star forming multi-phase ISM of entire disc galaxies, and the interaction with various feedback channels. The whole SATIN model, integrated into the RAMSES-RT code, allows for the self-consistent development of a star-forming, multi-phase ISM within entire MW like disc simulations. The model integrates the formation of massive star clusters with individual stellar mass distributions. These massive stars follow individual stellar evolution models to calculate the stellar radiation and the specific delay time until undergoing a supernova explosion. I will show, that that with radiation from massive stars, SN feedback, cooling and gravity, the galactic ISM develops a realistic three phase structure. The coupling between the stellar radiation and the gas leads to a self-consistent launching of a stellar wind. Radiation reduces the amount of cold gas and increases the amount of warm gas within the galaxy and influences the turbulent structure of the multi phase gas. It also helps the star formation rates to naturally follow observed scaling relations for local Milky Way gas surface densities. The completed simulations collectively provide a robust baseline for future studies including additional feedback channels (such as AGN feedback) and contribute to our nuanced understanding of stellar feedback processes in galaxy-scale simulations.

Population III stars were born in halos of pristine gas composition. In such a halo, once the gas density reaches n_H~1cm**-3, molecular cooling leads to the collapse of the gas and the birth of pop III stars. Halo properties, such as chemical abundances, mass, angular momentum can affect the collapse of the gas and thus the pop III initial mass function.
We study the properties of primordial halos and how the halos hosting first star formation differ from other halos. The aim of this study is to obtain a representative population of halos at a given redshift that host a cold and massive gas clouds and thus host the birth of the first stars. We have submitted this to A&A.
We investigate the growth of primordial halos in a large cosmological simulation. We use the code RAMSES and the chemical solver KROME to study halo formation with non-equilibrium thermochemistry. We then identify structures in the dark and baryonic matter fields thus linking the presence or absence of dense gas clouds to the mass and the physical properties of the hosting halos.
In our simulations, the mass threshold for a halo to host a cold dense gas cloud is 7e5 M_sun and the threshold in H2 mass-fraction is ~ 2e-4. The halo history and accretion rate play a minor role. We found halos with higher HD abundance. These halos are colder as the temperature in the range 10^2 - 10^4 cm**-3 depends a lot on the HD abundance.

The Milky Way, with its distinctive observational features, is a unique laboratory to constrain physical parameters and test various theories ranging from star formation on all dynamical scales, to the formation of gaseous structures and ultimately to galaxy evolution in general. In particular the spiral structure, its connection to star formation and galactic outflows, make it highly relevant for our understanding of galactic dynamics.
We use the moving-mesh code Arepo to perform high-resolution magnetohydrodynamical simulations of the Milky Way. We include stellar feedback following individual massive stars, a detailed galactic potential, which is adjusted to fit Milky Way conditions, as well as dynamically coupled cosmic rays. In addition, we determine the thermal state of the gas via a non-equilibrium chemical network. In our analysis we focus specifically on the star formation and feedback process and its effect on the spiral and vertical structure of the galaxy. We show how star formation and stellar migration correlate with the evolution of spiral arms. Furthermore, we connect gas dynamics resulting from feedback-driven turbulence to magnetically supported thickening of the disk and cosmic ray-driven outflows.

Modern galaxy simulation routinely reaches parsec resolution, thereby unlocking a self-consistent treatment of the internal structure of GMCs while accounting for the galactic-scale gas flows. With these models, we have seen significant theoretical progress, particularly concerning star formation, feedback, and the multi-phase ISM. Nonetheless, many models are still limited to treating stars as mono-age stellar populations, with feedback quantities averaged over a perfectly sampled IMF, missing important details of when and where stars inject feedback. Many state-of-the-art galaxy models no longer need this restriction and should apply a star-by-star approach, particularly for massive stars.
I will present my star-by-star model INFERNO, incorporating stellar feedback, chemical enrichment, and the natal velocities of individual stars in hydrodynamical simulations of entire galaxies. My model alleviates many of the restrictions imposed by the traditional approach, e.g., when and where stars inject feedback. Furthermore, INFERNO incorporates a state-of-the-art chemical yield model with on-the-fly enrichment calculations for 80 elements in the periodic table.
In my talk, I will present results from my model to highlight why models with individual stars are needed, for example, to include the effect of runaway stars. Furthermore, I will present new results from simulations of dwarf galaxies in cosmological environments, including all observable stars as individual particles throughout a Hubble time. I will focus on predictions for faint galaxies in the Local Universe, highlighting challenges arising when observations are limited to the brightest stars and why star-by-star simulations are needed to guide the next generation of telescopes.

In our understanding of galaxy evolution, dwarf galaxies represent a key ingredient, as these act as the building blocks of larger galaxies, and they can help us understand the early stages of the first galaxies in the Universe. In the context of simulations, the dwarf galaxy mass scale represents a challenge itself just to be able to resolve them within a cosmological box. State-of-the-art zoom-in simulations solve this issue but still rely on the chosen sub-grid physics model to account for the processes involved. For instance, SN feedback is a fundamental process regulating the evolution of dwarf galaxies and, therefore, sensitive to the chosen model. LYRA is a new set of zoom-in cosmological hydrodynamical simulations designed to resolve with great detail the formation and evolution of dwarf galaxies. Having a baryonic mass of 4 Msun resolves individual stars above that mass, as well as supernovae shocks self-consistently, removing the need for sub-grid physics implementation of this process, including new recipes for the chemical enrichment from Pop III stars. These simulations offer a promising avenue for advancing our understanding of the formation and assembly of dwarf galaxies, their stellar populations, and the influence of baryon physics in their assembly history. I will present some results from these simulations, particularly about the build-up of the stellar mass and the causes of the differences in their growth histories. I will show that the fact that some of these galaxies continue star formation post-reionization leads to distinct present-day metallicity distributions.

With newer surveys and telescopes coming online and pushing to lower surface brightness, we are uncovering new populations of both dwarf galaxies and star clusters that blur the boundaries between the two. Combined with computing power becoming exponentially better, the resolution and accuracies of cosmological simulation suites can probe down to ever increasing detail. In my PhD project, I use the state-of-the art EDGE simulations (mass resolution ~1e2 Msun; spatial resolution ~3pc; LCDM cosmology) that form both dwarf galaxies and star clusters naturally to study the formation of the very smallest stellar systems. I focus on how these systems form and how we can observationally separate star clusters that do not form with any bound dark matter from dwarf galaxies which do. This will give new insight into the different stellar systems which may be currently miscategorised, ie a dwarf galaxy that has been stripped of its dark matter halo, or a star cluster that has accreted dark matter. I compare my results from the EDGE simulations to observations of dwarf galaxies and globular clusters, showing that EDGE is able to simultaneously form dense star clusters and low density dwarf galaxies in their cosmological context, for the first time.

Despite its marginal contribution to the baryonic mass in galaxies, dust weighs heavy in galaxy formation physics. In one aspect, dust plays an important role mediating key physical processes; shielding gas from radiation, providing a substrate for molecule formation and capturing key elements from the diffuse medium. In another, dust affects our understanding of galaxies through our recovery of intrinsic galaxy properties; dust contributes UV-optical attenuation, and re-emission at thermal wavelengths, used to infer things like stellar mass and star formation rate. Still, the dust properties of galaxies remain poorly understood in many respects; dust formation requires understanding the densest ISM and the decryption of dust observations requiring an understanding of the complex star-dust geometries that emerge. Considering dust in hydrodynamical simulations gives us a means to explore these influences. I will discuss what we can learn from dust-inclusive virtual observations of the EAGLE simulations (e.g. Trayford et al 2017, Trayford et al 2020), but also how this may be caveated by simulation limitations, and the lack of an explicit dust model. I will then discuss the model of dust evolution we have developed for an upcoming suite of cosmological simulations. In particular, I will discuss how actively coupling dust properties to heating and cooling physics in the ISM gives us a self consistent model for dust and influences galaxy formation. Finally I will discuss how combining post processing and active dust modelling gives us new leverage to decode physics from galaxy observations.

In my talk I will discuss results from a suite of simulations I have run varying facets of the FIRE-2 feedback and star formation prescription models. These runs take one of our cosmologically evolved Milky Way mass spirals very near z = 0, alter the physics, and then evolve the disk for an additional 265 Myr (~2 galactic dynamical times). Doing so allows me to see the new equilibrium ISM and star formation rate conditions that arise, and explore how choices in the feedback and star formation prescriptions affect gas turbulence, the dynamical state of the gas, and the phase structure of the ISM. Broadly I will show how choices that affect the global energetics affect the greatest changes to the ISM, whereas altering the delay time distribution of core-collapse SNe (equivalently, mildly altering their spatial distribution) do not greatly affect the thin gas disk in the FIRE model. None of these changes greatly affect the equilibrium velocity dispersions, as other physical processes change in response to changes in the feedback model. Lastly, I will tie these changes to observables and point out avenues for constraining feedback and star formation models in zoom-in simulations.

Dwarf galaxies are typically old and dark matter dominated, and their shallow gravitational potential wells make them a sensitive barometer of both internal and external astrophysical processes. They are hence a powerful means of stress-testing galaxy formation models, and the underlying cosmological model. We present a suite of high-resolution _-CDM cosmological zoom-in simulations capable of resolving populations of dwarf galaxies in diverse cosmic environments. We use this suite to study environmental effects on the number density of dwarf galaxies, scatter in the low mass regime of the stellar mass – halo mass relation, and key internal properties such as star formation histories, morphology and gas content. In particular we find that the luminous fraction of low mass haloes, at a given halo mass, has a dependence on the halo concentration, shedding light on the formation times and mechanisms of dwarf galaxies in varied environments.

Ultra Faint Dwarf (UFDs) galaxies are the faintest among the faintest galaxies known in our Universe. Being so small, they represent a unique tool to constrain cosmological models down to the smallest scales out of reach by direct observations.
I will show how current simulations of UFDs fail to reproduce some properties of UFDs like their metallicity and size. As those issues are directly interconnected to the complex build-up history imposed by the LCDM they either question its validity at the smallest scales
or reveal the limitation of current state-of-the-art-numerical models.

A number of hydrodynamical simulations have now succeeded in generating populations of galaxies and black holes that strongly resemble those in the real universe. However, to learn why such successes have been achieved we need to complement these efforts with more targeted simulations which reveal the causal effects that link a galaxy's history to its observable traits such as star formation rate, black hole mass, and gas masses and ionisation states in the interstellar and circumgalactic medium. I will introduce the GMGalaxies programme which, over the last few years, has constructed controlled tests of cosmological galaxy formation, resimulating galaxies in a cosmological context with tightly controlled changes to their history and environment. As an example I will focus on a conundrum: statistically speaking, the formation time of a galaxy can be a good predictor for whether it will be star-forming or quenched. But the actual physical mechanism establishing this link is hard to tease out from a population. By careful experimentation, independently varying the collapse time and the merging history, one may reveal this statistical correlation is an acausal effect arising from the effects of major mergers (Davies, Pontzen & Crain 2023, MNRAS accepted, arxiv 2301.04145). I will more broadly argue for complementary large volumes and zoom simulations as a means for understanding galaxy formation.

The rotational lines of CO are routinely used to detect molecular gas in galaxies. The variation of the CO(J=1 _ 0)-to-H2 conversion factor _CO with physical conditions has been extensively investigated in the Milky Way and nearby galaxies. At higher redshifts, however, the limited number of galaxies observed in CO and the need to rely on J>1 transitions pose a challenge to studying the dependence of _CO on other galaxy properties. In recent years, the [CII] fine-structure line has proved extremely useful for probing molecular gas, especially in metal-poor galaxies harbouring CO-dark gas. The nature and origin of this line are highly debated as it can arise from multiple ISM phases and not all [CII] emission of a galaxy is associated with the molecular gas phase. In my talk, I will present a new sub-grid model for computing the non-equilibrium abundances of H2 and its carbon-based tracers, namely CO, CI, and C+, in cosmological simulations of galaxy formation. The model accounts for the unresolved density structure in simulations using a variable probability distribution function (PDF) of sub-grid densities and a simplified network for hydrogen and carbon chemistry. We obtain L_CO(1-0) and L_[CII] for our simulated galaxies in post-processing to assess the reliability of CO and C+ as molecular gas tracers under different ISM conditions and galactic environments. Based on our findings, we discuss the implications of using CO and [CII] lines for estimating the molecular gas mass for the entire population of galaxies at high redshifts.

Robust modeling of star formation and feedback remains among the key challenges for galaxy formation simulations as these processes strongly depend on the small-scale turbulent structure of the ISM that cannot be resolved in state-of-the-art galaxy simulations. I will overview our recent work on galaxy simulations where we use an explicit model for unresolved turbulence (following the Large-Eddy Simulation (LES) methodology) to model dynamically variable local star formation efficiency (SFE) instead of assuming a fixed tunable value. Such turbulence-based star formation strongly affects the amount and lifetime of dense gas and its spatial de-correlation with the sites of recent star formation on sub-kiloparsec scales, providing a way to constrain such models observationally. Forward-modeling of SFE allows one to avoid extrapolation of tunable subgrid models to the regimes where they were not calibrated, such as low-metallicity environments typical for the early universe and dwarf galaxies. To facilitate the usage of such models in other codes, I will also present a simple approach alternative to LES, where the explicitly modeled subgrid turbulence is sourced implicitly by the local numerical dissipation. Despite its simplicity, the model captures many non-trivial features of high-resolution ""direct"" simulations of decaying supersonic turbulence and galaxy simulations with more complex explicit LES models, while also being straightforward to implement.

Lagrangian simulations have at least three values that describe the resolution of a simulation: the gravitational force softening length, the hydrodynamical smoothing length, and the mass resolution. For typical particle masses in cosmological simulations of order 100,000 Msun, self-gravitating structures in a multi-phase interstellar medium (ISM), which includes cold gas with T < 100 K, are formally unresolved. This has in the past motivated the use of an entropy (or pressure) floor, sometimes referred to as an equation of state, which models the ISM in a single, warm phase with a temperature of > 10,000 K. Modelling the cold phase of the ISM requires a thorough analysis of (numerical) instabilities that form in gas that is formally unresolved, yet plays a critical role in the gas dynamic within galaxies. We introduce the ""softened Jeans criteria"", valid in softened gravity, and use them to characterise the formation of numerical instabilities at and below the formal resolution limit in simulations with a multi-phase ISM. In this analysis, we highlight the key differences between simulations with constant and adaptive softening lengths, on how perturbations in formally only marginally resolved or unresolved gas grow or decay. Finally, we demonstrate how even simulations with moderate mass resolution can model the multi-phase ISM without artificial numerical instabilities.

Stellar clusters are critical constituents within galaxies: they are the results of extreme modes of star formation, and through their correlated stellar feedback they regulate their host galaxy evolution. Including the effect of clustered supernovae in the baryonic lifecycle of their host galaxies is a major step missing in current modern simulations of galaxy formation. In this talk, I will present a novel method to model individual star clusters and their critical influence on their host galaxy evolution. By using a sink prescription that allows clusters to form via gas accretion and mergers, I will demonstrate the interplay between clustered feedback and the properties of the ISM on galactic scales. Lastly, I will discuss how the formation of star cluster populations is affected in this scenario.

Substantial observed variations in the efficiency of star formation between main sequence galaxies and quenched, bulge-dominated galaxies raise the question of whether star formation in quenched and main sequence galactic environments can be treated with the same model in cosmological simulations.
Using a suite of six high-resolution multi-phase chemo-dynamical Arepo simulations spanning observed galactic environments from the main sequence to quenched, bulge-dominated galaxies, I will show that five out of six galaxies display excellent agreement with pressure-regulated models for star formation on kpc scales, despite large variations in disk stability. This relationship between the star formation rate and mid-plane pressure holds great promise as the basis for improved sub-grid models for star formation within cosmological simulations. In the sixth galaxy, morphological quenching occurs due to the external gravitational potential at the scales of star-forming giant molecular clouds, introducing a deviation from the pressure-regulated trend that is proportional to the galactic angular velocity. I will use this example to discuss how morphologically-quenched environments can be treated by introducing flexibility to a pressure-regulated model for star formation.

The circumgalactic medium (CGM) plays a vital role in the formation and evolution of galaxies. It acts as the intermediary boundary between the interstellar medium (ISM) and the intergalactic medium (IGM) and is a reservoir for baryonic matter, subsequently accreting onto the ISM, further fuelling star formation. It is a notoriously difficult region to probe observationally due to its complex, multiphase structure. We study the physical properties and column density of CGM as a function of halo mass. This research was conducted as an extension of the Auriga project which uses the magneto-hydrodynamical cosmological simulation code AREPO. We analyse zoom-in simulations of haloes with a mass range between 10^10-10^13 solar masses with stellar masses ranging from 10^7-10^12 solar masses. We analysed the temperature, density, metallicity and radial velocity, additionally post-processing column density of HI, CIV, OVI, MgII and SiII, of these haloes with one study focusing on the halo mass dependence of these properties and a second investigating these properties in the presence and absence of a magnetic field. We conclude that the multiphase nature of the CGM is affected by the halo mass. Furthermore, magnetic fields play a major role in affecting the physical properties of the CGM with a halo mass range of 10^11 and 10^12 solar masses.

Observations of the CGM are matured enough to allow observers find intrinsic differences in the CGM depending on the large scale environment a galaxy is embedded in. In order to study the physical processes that drive these environmental dependencies of the CGM, large cosmological simulations are necessary. However, there is no guarantee that current simulations can reproduce the observed CGM, because the CGM properties are highly sensitive to different feedback implementations. Based on a theoretical study of the CGM in a cosmological context, I will argue that cosmological simulations of galaxy formation should consider observations of the CGM in their calibration strategies. First I will introduce the problem we wanted to solve and the original plan to tackle it. Then I will show step by step why the original plan to use ionization states from postprocessing failed and why we had to resort to a different approach. This will then serve as a starting point for a discussion of the processes necessary to include in the calibration of simulations of galaxy formation such that studies of the CGM in a cosmological context give reliable results.

I will discuss new simulation efforts aiming to better understand the physics of the baryon and circumgalactic medium, and their role in shaping galaxies. (i) First, how ""Project GIBLE"" and super-Lagrangian refinement techniques may finally resolve the small-scale structure of the CGM. These new simulations have the promise to reveal the physics of the 'cold phase' -- the formation of cool, overdense clouds of gas, their physical evolution and morphologies, the role of magnetic fields, boundary layers, and impact (or lack thereof) on the galaxy itself. (ii) Second, how the new ""TNG-Cluster"" simulation probes the structure and properties of the hot intracluster medium of galaxy clusters, including the kinematics, turbulence, thermodynamical properties, and the role of AGN feedback on the ICM. Through both topics I will describe outcomes and perspectives offered by the TNG physical model on the gaseous atmospheres of galaxies, from the Milky Way scale to the most massive dark matter halos that exist.

Gas around galaxies aka the Circum-galactic medium (CGM) strongly influences the overall baryon budget of a galaxy and is responsible, in a subtle yet definitive way, in governing many galactic observables. I will present some results from the Hestia constrained simulations as well as the IllustrisTNG simulations that shed light on the properties of the Local Group (LG) CGM as well as probe the correlation between satellite galaxies and cold CGM. Via a controlled experiment within the Hestia setup, I will demonstrate the possibility of an observational bias in LG CGM arising due to our own Milky Way's (MW) CGM. The realism of this possibility could, at least, partially account for the discrepancy between simulated and observed LG CGM ion column densities. I will also talk about the satellites-cold CGM connection in TNG50 simulations, delving deeper into which of the satellite properties correlates the most with halo cold gas. This will, ultimately, support the argument that the cold gas contribution from satellites towards the host CGM needs to be better constrained in order to get a complete baryon census for any galaxy.

Ly$\alpha$ emission is a powerful tracer of the life cycle of galaxy evolution and escape of ionising photons. However, the findings from the previous theoretical studies are limited by poor numerical resolution, limited physical models, and poor LOS statistics. Here we resort to a large simulation suite of dwarf galaxies that includes different physical models and postprocess the simulations with radiative transfer code to generate mock Ly$\alpha$ observables. For our fiducial simulation with the most complete set of physics, our results show that Ly$\alpha$ haloes are more extended than the intrinsic ones while Ly$\alpha$ spectral shapes manifest the strength of feedback. In particular, spatially resolved Ly$\alpha$ parameter maps are highly sensitive to the underlying gas distribution and motion. Ly$\alpha$ and LyC show completely different signatures along different LOS based on how the LOS pierces through the low-density channels generated by feedback. Comparing simulation runs with different physics, we find their Ly$\alpha$ signatures show systematic offsets due to different levels of the feedback strength and clumpiness of neutral gas. Nonetheless, a universal correlation between Ly$\alpha$ observables and LyC escape fraction is found, regardless of the simulated physics, showing the robust connection between Ly$\alpha$ and LyC emission.

I present results from a new generation of numerical simulations significantly advancing our abilities to interpret observational signatures of galactic outflows and the circumgalactic medium (Rey et al. 2023b).
How gas flows in and out of galaxies is fundamental to the regulation of their star formation. Observations of this baryon cycle typically target emission and absorption lines from metallic ions, from which we infer the metallicity, kinematic and thermodynamics of gas surrounding galaxies and in turn constrain our models of galaxy formation. This inference is highly challenging, requiring a detailed account of the ionization and chemical structure of the gas, while resolving the cooling and condensation length-scales that sets its multi-phase structure.
I present a new generation of numerical models tackling this challenge head-on, solving for the first time the coupled equations of hydrodynamics, radiative transfer, and non-equilibrium chemistry from over 60 metal ions in galaxy formation simulations. This allows me to make direct observational predictions of a galaxy’s emission and absorption lines, without post-processing or equilibrium assumptions.
Complementing this setup with a new scheme aiming to actively resolve the local gas cooling length in diffuse gas, I will show how better resolving the micro-physics of galactic outflows systematically boost their energetics and affects their multi-phase structure. Analyzing the spectral line predictions “as an observer would”, I further highlight how these new models enable the first calibrations of biases when inferring outflow properties (e.g. metallicity) from emission lines.

Conventional cosmological simulations evolve a randomly generated realization of a specified power spectrum. This approach allows to statistically compare the properties of galaxies and diffuse gas in large volumes, but cannot replicate specific observed large-scale structures. To overcome this shortcoming, we use constrained cosmological simulations, which utilize tailored initial conditions to match the large-scale structure of an observed patch of the sky. Here, we reconstruct the initial conditions with data from the COSMOS Lyman-Alpha Mapping And Tomography Observations (CLAMATO) survey at z ≈ 2.0 _ 2.5. In the “cosmosTNG” simulation suite, we run a range of cosmological galaxy formation simulations with these initial conditions and the TNG galaxy formation model. With this approach, we offer a novel avenue to evaluate our galaxy formation models at the peak of cosmic star formation – “cosmic noon” – and their alignment with existing and forthcoming surveys in the COSMOS field. This presentation will detail the methodology used to generate these initial conditions and discuss preliminary results.

The angular momentum of galaxies controls the kinematics of their stars, which in turn drives observable quantities such as the apparent radius, the bulge fraction, and the alignment with other nearby structures, yet its origin remains poorly understood. To reveal its origin, I will present high-resolution (35pc) numerical experiments in which we systematically modify the gravitational tides in the initial conditions of the simulations. This provides us for the first time with control over the angular momentum accretion history within a full cosmological environment.
I will focus on three galaxies, simulated from z=200 to z=2 with five distinct angular momentum accretion histories. Our results reveal that modifying early-universe tides alters the timing and parameters of mergers, predictably influencing the total stellar angular momentum within a galaxy's virial radius.
Notably, one of the simulated galaxies has no large satellite at z=2, which results in the specific angular momentum being concentrated in the central galaxy. I demonstrate we can control its stellar angular momentum over 0.7dex and show that this causes its effective radius to grow by 40%, its v/_ parameter to grow by a factor _2.6 and its bulge fraction to decrease from 0.72 to 0.57.
The ability to control angular momentum provides opportunities for future investigations into the causal origins of scaling relations between galaxy mass, angular momentum, and morphology. This work advances the current state of cosmological simulations, providing insights crucial for disentangling the intricate processes at play in galaxy formation.

Future surveys of cosmic shear, the weak lensing distortion of galaxies, will be used to constrain cosmological parameters to unprecedented levels of accuracy. Euclid, one such survey, will quantify cosmic shear through its observations of distant galaxies. However, estimates of the amplitude of the shear are biased by Intrinsic alignment (IA), a non-linear effect that results in low-mass halos being preferentially aligned to the closest filament while large-mass halos are preferentially perpendicular. We therefore need to understand the inner workings of IA onto halos, in order to disentangle it from the weak lensing statistics. In this talk, I will present the non-linear acquisition of dark matter halo spins in N-body simulations thanks to “genetic modifications” of the initial conditions. Using a novel implementation of the splicing technique, we fix the expected linear part of the spin by fixing the potential field in the region where a given halo will form. Doing so allows us to resample the large-scale cosmological environment, thus capturing the non-linear effect cosmic filaments have on spin acquisition. While intrinsic alignment has been probed on a population scale in large cosmological volumes, the novelty of our work relies on our use of controlled numerical experiments, allowing us to unravel the origin of the spin of individual halos as opposed to the population statistics.

In recent years the size and depth of observational surveys have necessitated increases in both the resolution and volume of simulations. These increases drastically increase the computational cost of simulations. As a result, we must often sacrifice resolution to achieve a larger volume, or vice versa. Zoom simulations alleviate this computational cost with a targetted approach enabling high-resolution resimulations of regions covering the full dynamic range of the Universe, such as those done in the FLARES simulations. As such, they are a promising method to not only enable high-resolution simulations over a large dynamic range, but are also a promising avenue for reducing the computational cost, and thus carbon footprint, of cosmological simulation research.
In this talk, I will introduce the approach implemented in the SWIFT simulation code to enable the efficient running of zoom simulations across a wide range of scales. I will demonstrate its performance in contrast to last-generation and contemporary zoom simulation codes and briefly present results from a study using the code to study the optimal selection method when emulating an entire parent volume with a subset of regions.

Cosmological hydrodynamic simulations aim to self consistently evolve gravity, hydrodynamics and astrophysical processes in a fully cosmological context, offering some of the most realistic descriptions of the formation and evolution of galaxies currently available. However, many key astrophysical processes (such as star formation as well as stellar and AGN feedback) happen below the resolution limit of the simulations, requiring them to be implemented using numerical ‘subgrid’ routines. Due to the high computational expense of these simulations the available parameter space cannot be fully explored directly, meaning that the predictive power of these simulations is often not well understood. A key limitation when trying to use these simulations to constrain both galaxy formation and cosmological parameters. To begin to address this problem I present a new extension to the ARTEMIS suite of high resolution (~10^4 M_sun particle mass) cosmological zoom-in simulations of Milky Way mass haloes where the key subgrid parameters are systematically varied alongside the assumed warm dark matter particle mass (in total running 126 simulations). From this new simulation suite, machine learning emulators are built that allow for a wide range of statistics (currently 271) to be predicted in ~1ms. The significant increase in computational speed offered by the emulator fundamentally changes the type of analysis that can be performed, allowing for a much better understanding of the role of the (subgrid) models used in these simulations.

In the next fews years Euclid and LSST will push our understanding of the matter distribution of the Universe to galactic scales. In order to interpret the results obtained by these surveys we will have to gain a deeper understanding of the effect of baryons on our cosmological inference. For the FLAMINGO project we have used a new method that uses machine learning to carefully calibrate the subgrid physics models for supernova and AGN feedback. Our method uses emulators to fit subgrid physics model parameters to observations. I will present how we apply this methodology to calibrate the FLAMINGO model. The FLAMINGO project consist of a 2.8Gpc volume at 1e9 Msun resolution, a 1Gpc at 1e8 Msun resolution and many variations of feedback and cosmology at 1e9 Msun resolution in 1Gpc volumes. I will show that by making use of emulators build using 32 smaller-volume simulations we are able to fit the free parameters of the subgrid model to observations, taking into account potential biases. Additionally we use the emulators to constrain models that skirt the observational errorbars. We also calibrate an alternative AGN feedback model that uses kinetic jets instead of thermal dumps. By explicitly fitting the subgrid models to observations we gain a deeper understanding of the cosmological impact from baryons, and how their impact can be predicted from independent observations. I use these results to show that baryonic feedback doesn't solve the sigma8 tension and how different feedback models impact the cosmological inference from cluster counts.

Calibrating cosmological simulations of galaxy formation involves a large number of assumptions. Which observational data should the simulation be fit to? Which parameters of the model should be tuned? Does the model itself require changes? To tackle these questions, we use a new model of galaxy formation: COLIBRE. The COLIBRE simulations improve on the EAGLE simulations by, among others, using a new code (SWIFT), including a multiphase interstellar medium, incorporating a model for the evolution of dust, calculating the radiative cooling of primordial elements in non-equilibrium, and using more sophisticated prescriptions for stellar and AGN feedback. We run simulations with different feedback models and for various model parameters and use them to train Gaussian-process emulators to predict the z=0 galaxy stellar mass function (GSMF) and size-stellar mass relation (SSM) as functions of the model parameters. We fit the trained emulators to observations and show that it is largely the prescription for supernova (SN) feedback that determines the goodness of the fit for low- and intermediate-mass galaxies. Specifically, we demonstrate that (i) the z=0 observed GSMF can be matched with a relatively simple SN feedback model; (ii) reproducing the z=0 SSM relation in addition to the GSMF necessitates more sophisticated SN feedback; and (iii) matching high-redshift data as a third constraint requires even more complex feedback models. We show that the models with more complex SN feedback not only reproduce the calibration observables, but also match a rich variety of other galaxy properties to which the models have not been calibrated.

As more and more data from recent and upcoming large cosmological surveys become available, the need for equally detailed theoretical models of galaxy formation, including large-volume cosmological simulations emerges. Despite the success of modern hydrodynamical simulations nowadays, they must always compromise in either resolution or size, due to the complexity and computational expense of running such simulations.
As an aid, we perform supervised learning to map baryonic matter to dark matter in high-resolution hydrodynamical simulations. We use the merger trees from TNG100 of the IllustrisTNG simulation suite, that entail the formation history of DM subhalos in the form of graphs, along with Graph Neural Networks (GNNs), which excel in handling datasets that carry such a distinct intrinsic structure. We train a GNN to infer galaxy baryonic properties, namely stellar and gas mass, given the subhalo host’s DM properties across the merger tree. We obtain a potent model that is capable of reproducing galaxy populations that are statistically consistent with simulated ones. This powerful tool can generate entire galaxy populations for cosmological volumes: one can run computationally inexpensive, simple DM-only (N-body) simulations and subsequently augment them, by ”painting” baryons on top of the Dark Matter, enabling the construction of Gpc-scale boxes with baryonic physics. Additionally, we use the trained GNN to study the galaxy-halo connection, i.e. which subhalo DM properties and merger tree features (e.g., accretion versus mergers) arise as the most influential training inputs when determining galaxy baryonic properties.

Galaxy mergers play a crucial role in galaxy evolution. However, understanding the causal relationships between mergers and galaxy properties from simulations poses two significant challenges: the large stochastic differences between merger histories that must be simulated, and the inherent uncertainty in the subgrid prescriptions implemented in the codes. We report on our project to tackle both these factors, using `genetic modifications' of the initial conditions (ICs) to generate controlled alterations to a galaxy's merger history in a systematic way, while also using different simulation codes to understand the uncertainty introduced by subgrid implementations. We make use of the VINTERGATAN-GM suite of zoom-in cosmological hydrodynamical simulations, which simulates five realizations of a MW-mass halo while `genetically' modifying the strength of a $z \sim 2$ merger with the GenetIC code, constrained to reproduce a halo of the same mass at $z=0$, using the VINTERGATAN model. We also compare the results to a complementary suite of simulations which evolve the same ICs with the IllustrisTNG model. We explore different properties of the galaxy and their dependence on the mass ratio of the target merger, such as galaxy sizes and mass profiles, star-formation histories, galaxy morphology and dynamics, and also how robust any potential trends are to the physics model employed. Thus, we aim to understand whether such simulation codes, which in principle are expected to produce significantly different galaxies, may still respond in similar ways to targeted changes to merger histories, and what combination of physical processes may conspire to do so.

Recent large-box cosmological hydrodynamical simulations produce a realistic bi-modal galaxy population and other gaseous and stellar properties making them an inevitable tool not only for theorists but also for observers. However, even with the advance in their numerical resolution and implementation of various astrophysical processes, star formation and feedback have to be implemented in a subgrid fashion. Because these subgrid models are fine-tuned to a few key observables, the true test of their validity lies in the comparison to galaxy scaling relation relations that did not enter this calibration. I will focus on the mass-age and mass-metallicity relation of the IllustrisTNG simulations revealing that especially the metallicities are incompatible with observations. My main goal is to bridge the gap between observers and simulators by presenting millions of SDSS-like mock spectra for all three volumes of TNG. I will walk through each step of the mock creation process to show how stellar population scaling relations change from purely simulational quantities to observationally derived ones. Being aware of these biases and complexities introduced by transforming between observations and simulations is crucial. I will discuss that they should be accounted for when calibrating subgrid models and how they help to improve future simulations and observations. Only with resolving any disagreements we can accurately interpret our results and reconcile observed galaxy properties with physical, often not directly observable, processes that shape them. Lastly, I point out that all mock spectra will be publicly available to help with science needs for observers and simulators alike.

The GigaEris simulation is a cosmological, N-body hydrodynamical ""zoom-in"" simulation of the formation of a Milky Way-sized galaxy with the unprecedented resolution of better than a thousand solar masses, encompassing of order a billion particles within the refined region. In this talk, we will delve into the intricate processes that led to the creation of the early thin disc component at z > 6 , its implications in the context of the new JWST observations, and its relationship with the low-redshift disc and pseudobulge components commonly found in spiral galaxies. Finally, by exploiting our ability to resolve high-z star clusters, we show some of them have properties consistent with those of progenitors of Globular Clusters and Nuclear Star Clusters of massive present-day spiral galaxies. For nuclear star clusters, we describe a new hybrid in-situ + ex-situ formation scenario based on the rich dynamical information from our simulations. We will broaden our perspective to high-redshift galaxies, exploring the broader context of our research.

Galaxy centers are extreme environments and can host among the most powerful events in the universe when gas is efficiently accreted onto the central supermassive black hole. Galactic bars can be the catalyst of this process, driving gas from the disc towards the central region. This results in an accumulation of copious amounts of molecular gas which leads to particularly interesting conditions for gas dynamics and star formation. Here, the ISM evolves in much more extreme conditions compared to a solar-neighborhood environment, and resolving this complexity in numerical simulations is crucial to properly follow the regulation of gas accretion onto the central SMBH which in turn can affect the evolution of the entire galaxy.
I perform idealized high-resolution MHD simulations of barred galaxies analyzing the gas dynamics in the center. Our models are designed to resolve the molecular phase down to sub-parsec scales employing high-physical-fidelity numerical prescriptions. I describe the impact of different physical agents on the evolution of the gas in the region and their ability in regulating star formation, ISM properties and gas inflow. Magnetic fields, for instance, can reach peaks of a few mG and are dynamically relevant in the central few hundred parsecs of the galaxy. Magnetic instabilities can drive turbulence, provide pressure support and drive inflow towards the innermost few pc, complementing the action of the galactic bar in removing angular momentum for regions where the latter is ineffective in doing so.

The first galaxies formed 200-300 million years after the Big Bang._The smallest of these early galaxies, the ultra-faint dwarfs (UFDs), were quenched by reionization, so those that survived until now are composed of ancient stars from 13 billion years ago. Stars from these tiny galaxies_thus are relics from the era of the first stars and galaxies, preserving clean signatures of early chemical enrichment. Currently, though, simulations are unable to explain observed stellar chemical abundances in these galaxies. To fully utilize the available chemical abundance data on stars from UFDs, we are running cosmological simulations of early dwarf galaxy formation_with individual stars, detailed chemical_yields, and highly-resolved metal mixing. This allows us to explore complex galaxy formation processes including source-dependent metal mixing, hierarchical galaxy merging, bursty star formation, and variations across different galaxies to learn how early galaxies evolved.

The existence of dynamically cold disks, characterized by significant rotation support, in high redshift galaxies remains a subject of intense debate. I will address the intriguing question of whether dynamically cold disks are indeed prevalent during the early cosmic epochs or if they represent exceptional cases. Leveraging the power of zoom-in cosmological simulations, I will present predictions from the SERRA suite, specifically tailored for the anticipated synergy between the JWST and ALMA, to investigate these elusive structures at z>4. The JWST-ALMA synergy holds great promise for studying dynamically cold disks. JWST's high-resolution near-infrared imaging and spectroscopic capabilities enable the exploration of stellar populations and the kinematics of ionized gas within these disks, particularly through the observation of the H-alpha emission line. On the other hand, ALMA's exceptional sensitivity and resolution enable tracing cold gas content and the investigation of the kinematics of high redshift galaxies through CO and [CII] emission lines. During the talk, I will present the latest predictions from the SERRA suite (Pallottini+22, Kohandel+19,20,23a,b), addressing the existence of dynamically cold disks both during the EoR (z>6) and at cosmic high noon (4

Identifying bound substructures in simulations, as well as robustly measuring their properties and how they evolve, is a crucial step in making accurate predictions concerning large and small cosmological scales. A variety of algorithms exist for this purpose, which commonly rely on identifying spatial over-densities or coherent structures in phase-space.
These metrics can fail spectacularly, such as when the density contrast is insufficient or large physical distortions are present, resulting in biased predictions and disjoint evolutionary histories that require careful post-processing to fix. Additionally, they employ free parameters whose values have only been tested in N-body simulations, where the dynamics and spatial distribution of structures is substantially different from simulations that include galaxy formation physics. Beyond this, choices concerning how to measure their properties can result in disparate data products, even if the same sets of structures are found.
In this talk, I will compare how four different halo finders perform on cosmological simulations, highlighting the difficulty of identifying structures and how the method of particle tracking offers a more robust alternative to traditional algorithms. Finally, I will also discuss the need “re-calibrate” halo finders for their appropriate use in hydrodynamical simulations, as well as the need for a common framework to compute structure properties.

Bose–Einstein-condensed dark matter, also called scalar field dark matter (SFDM) or fuzzy dark matter, has become a popular alternative to cold dark matter (CDM), because it predicts galactic cores, in contrast to the cusps of CDM halos (‘cusp-core problem’), though the core size depends upon dark matter particle parameters. We investigated for the first time the impact of baryons onto realistic galactic halo profiles of SFDM endowed with a repulsive particle self-interaction. This regime is very difficult to investigate for computational reasons, and simulations are not yet available in the literature. However, by analysing the quantum Hamilton-Jacobi framework of the SFDM model, we were able to study adiabatic contraction (AC) in such halos to derive quantitative results. We calculated the impact of AC onto SFDM halos of mass ~10^(11) Msun, with various baryon fractions and core radii _(0.1–4) kpc, and compared our predictions with observational velocity data of dwarf galaxies. As I will report in this talk, we find that AC-modified SFDM halos with kpc-size core radii reproduce the data very well, suggesting stellar feedback is not necessary. On the other hand, halos with sub-kpc core radii face the same issue than CDM, in that they are not in accordance with galaxy data in the central halo parts. I will emphasize the observational and modelling aspects, which will be required in the future, in order to distinguish CDM from dark matter models with small cores.