GalaHAD: Galaxy Formation With High Accuracy Dynamics

Lead Research Organisation: Liverpool John Moores University
Department Name: Astrophysics Research Institute

Abstract

Large star-forming disc galaxies like the Milky Way are some of the most striking and beautiful objects in the Universe, often characterised by their breathtaking spiral arms. Understanding how these fascinating systems arranged themselves into their present state is one of the central aims of modern astrophysics. In my proposed research I will create and analyse simulations with unprecedented resolution within the larger cosmological environment in order to understand how the formation of our Galaxy unfolded.

Our home, the Milky Way galaxy, contains about 100 billion stars. The majority of these stars are in the middle of a large "halo" of dark matter, the crucibles in which galaxies are forged. These haloes are connected to the large-scale filamentary structure of the Universe, dubbed the Cosmic Web, from which haloes acquire gas and smaller galaxies known as satellites. Galaxies grow by accreting this material from their haloes over more than 13 billion years, transforming gas into stars which then move around in response to many complex, highly dynamical processes like gas accretion, mergers and spiral arms. We cannot observe this evolution directly, but astronomers are now able to measure the locations, chemical composition, motions, and ages for a large number of stars to a high degree of accuracy. This "fossil record" information provides vital clues to the birth conditions of stars, which can be very different depending on their origin and age, and how they evolved over Cosmic time. By mapping out this information for many stars, astronomers can piece together how galaxies like the Milky Way formed like a cosmic jigsaw.

The complexity of this great challenge demands sophisticated theoretical models to interpret these observations - the final snapshot in our Cosmic story. However, it is now an enormous challenge for simulations to model both the larger cosmological environment and the central spiral galaxy at the high level of detail necessary to resolve the intricate Galactic structure and its stellar populations that telescopes are now seeing. To get around this roadblock, I will employ new modelling techniques to dramatically enhance the resolution of the stellar and dark matter components of the galaxy to unprecedented levels. These simulations will resolve detailed, highly dynamical structures that were previously inaccessible, and will allow us to follow the many complex physical processes that have occurred since the Big Bang in more detail than ever before. In particular, we will learn how our beautiful spiral arms formed, how they shuffled stars around our Galaxy over Cosmic time, and how epic galaxy collisions that occurred in the ancient Milky Way shaped how it looks today. Additionally, these simulations will open a new window into the formation of very small, low-mass galaxies that lurk in the surroundings of the Milky Way, pushing our current knowledge to new horizons.

Observations require these simulations for their interpretation. Because we currently live in a golden era of large observational surveys which will provide increasing amounts of information, it is essential to carry out this project now in order to maximise our return from these observations. By making mock observations from my simulations, we can compare the simulations directly to observations to provide a holistic view of how the Milky Way formed. We will also learn how the motions of stars can inform us about the nature of the dark matter particle. Answers to these profound questions will greatly benefit mankind's curiosity of the Universe and its mysteries, and inspire future generations of scientists within society. These simulations will be made publicly available and will become a valuable resource for other astronomers, and produce the most detailed images and movies currently available of the origin and formation of our cosmic home.

Publications

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Barrientos Acevedo D (2023) Spatially resolved mock observations of stellar kinematics: full radiative transfer treatment of simulated galaxies in Monthly Notices of the Royal Astronomical Society

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Ciuca I (2024) Chasing the impact of the Gaia -Sausage-Enceladus merger on the formation of the Milky Way thick disc in Monthly Notices of the Royal Astronomical Society: Letters

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Deason A (2023) Unravelling the mass spectrum of destroyed dwarf galaxies with the metallicity distribution function in Monthly Notices of the Royal Astronomical Society

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García-Bethencourt G (2023) A high fidelity Milky Way simulation with Kraken, Gaia-Enceladus, and Sequoia analogues: clues to their accretion histories in Monthly Notices of the Royal Astronomical Society

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Grand R (2023) An ever-present Gaia snail shell triggered by a dark matter wake in Monthly Notices of the Royal Astronomical Society

 
Description XXXIV Canary Islands Winter School of Astrophysics
Geographic Reach Multiple continents/international 
Policy Influence Type Influenced training of practitioners or researchers
 
Title Auriga Superstars 
Description This model builds on the successful Auriga physics model developed for computational simulations of galaxy formation in a cosmological context. This uses a modified version of the massively parallel N-body & magneto-hydrodynamics (MHD) code AREPO. The Auriga superstars model comprises a new method to model star formation in these simulations. In this model, a total of 64 star particles are formed per star-formation event rather than the traditional single star particle. The 64 star particles are 1/64th of the mass of the gas cell from which they are spawned, are placed at the centre of mass of the cell (identical positions), and their velocities sampled from a narrow Gaussian distribution of width given by the local sound speed and centred on the velocity vector of their parent gas cell. The advantage is a 64 times gain in stellar resolution for a relatively low computational cost. A high-cadence (5 Myr) output for star particles only. This is done by a linear extrapolation of the positions and velocities of star particles between global timesteps, and circumvents the need to reduce the maximum global timestep which would slow-down the simulation significantly. 
Type Of Material Computer model/algorithm 
Year Produced 2023 
Provided To Others? Yes  
Impact Cutting-edge observations of the positions and velocities of billions of stars throughout the Milky Way galaxy (in particular from the astrometric survey Gaia) have revealed very detailed, highly perturbed distribution of stars. The phase space structures observed are likely caused by a range of phenomena spanning a wide range of physical scales, from the large scale distribution of dark matter surrounding the galaxy, to small dark matter subhalos and internal galactic dynamics from a central bar and spiral arms. The Auriga superstars method allows us to resolve all of these processes for the first time: previously, only highly simplified N-body simulations could follow the evolution of spiral arms and other finely detailed substructures. The high-cadence output allows for deep scrutiny of the dynamical evolution of the stellar component of galaxies, which has not traditionally been possible in cosmological simulations. I have already demonstrated the power of this technique in a published paper in MNRAS: I performed an initial pilot simulation which I used to shed light on the origin of the so-called "Gaia Snail Shell": a feature that we now think indicates the Milky Way was significantly perturbed by its misshapen dark matter halo in the recent past. The method is crucial to obtain this result, because without them the Snail Shell is simply not resolved. This leads to high scientific impact in the fields of astrophysics and cosmology. It also enables the production of high resolution images and movies of galaxy evolution that is of interest to the general public and STEM students. 
 
Title Auriga public python analysis repository 
Description This is a python-based software package for the analysis of cosmological simulation data products. It comes with a jupyter notebook tutorial. 
Type Of Material Data analysis technique 
Year Produced 2023 
Provided To Others? Yes  
Impact Scientific & academic impact: this user-friendly software is a useful tool and training resource for undergraduate projects (BSc, MSc etc) and University undergraduate classes (such as computer labs etc) to get to grips with reading, manipulating, and analysing large simulation datasets. It has already been used as such in the prestigious Canary Islands Winter School of Astrophysics XXXIV: The Local Group as a benchmark for Galaxy Evolution (La Laguna, Tenerife, Spain - 8-15 November 2023), which comprised about 60 undergraduate and graduate PhD students and young postdocs. 
URL https://bitbucket.org/grandrt/auriga_public/src/master/
 
Title Dwarf refinement 
Description Normally, cosmological hydrodynamical simulations of galaxy formation employ a constant mass resolution for the baryonic matter constituents (stars and gas). At current state of the art resolution levels, it is not possible to resolve low-mass galaxies. This algorithm uses a specialised technique to increase the resolution of the gas cells around low-mass dark matter halos only. At each time step, dark matter halos with less than 1.5e10 Solar masses are identified and gas cells within an effective radius of each subhalo are tagged for refinement using a passive scalar tracer approach. Cells tagged for refinement are then split into 8 child cells, thereby granting almost an order of magnitude higher gas resolution around subhalos with the potential to host dwarf galaxies. This is potentially important to resolve the formation of faint galaxies, and is a far more cost-effective method compared to traditional brute-force increases of the baseline gas resolution. The method is flexible enough to increase the resolution of targeted cells by in principal an arbitrary factor. 
Type Of Material Computer model/algorithm 
Year Produced 2024 
Provided To Others? No  
Impact Probe deeper into the low-mass end of the galaxy stellar mass function, where many predictions for the nature of dark matter become distinguishable. 
 
Title Overview and public data release of the Auriga Project: cosmological simulations of dwarf and Milky Way-mass galaxies 
Description We present an extended suite of the Auriga cosmological gravo-magnetohydrodynamical ``zoom-in'' simulations of 40 Milky Way-mass halos and 26 dwarf galaxy-mass halos run with the moving-mesh code Arepo. Auriga adopts the $?$ Cold Dark Matter ($?$CDM) cosmogony and includes a comprehensive galaxy formation physics model following the coupled cosmic evolution of dark matter, gas, stars, and supermassive black holes which has been shown to produce numerically well-converged galaxy properties for Milky Way-mass systems. We describe the first public data release of this augmented suite of Auriga simulations, which includes raw snapshots, group catalogues, merger trees, initial conditions, and supplementary data, as well as public analysis tools with worked examples of how to use the data. To demonstrate the value and robustness of the simulation predictions, we analyse a series of low-redshift global properties that compare well with many observed scaling relations, such as the Tully-Fisher relation, the star-forming main sequence, and HI gas fraction/disc thickness. Finally, we show that star-forming gas discs appear to build rotation and velocity dispersion rapidly for $z\gtrsim 3$ before they ``settle'' into ever-increasing rotation-dispersion ratios ($V/s$). This evolution appears to be in rough agreement with some kinematic measurements from H$a$ observations, and demonstrates an application of how to utilise the released data. 
Type Of Material Database/Collection of data 
Year Produced 2024 
Provided To Others? Yes  
Impact Scientific impact: this is only the second public data release of cosmological hydrodynamical zoom-in simulations of galaxy formation in the world, and the only European-led such data release. Furthermore, it is the largest dataset of their simulation type ever to be made public. As such, it provides a valuable resource for the scientific community to use the simulation data products (which include raw and post-processed high-level data) for studies on a variety of astrophysical and cosmological subjects. The initial conditions released will enable others to perform simulations with different codes and models for a clean understanding how theoretical predictions depend on different codes/models, which is a major source of uncertainty in the field. Academic impact: the data are easily accessible via the Globus platform and can be used for undergraduate projects (BSc, MSc etc) and as a training resource in University undergraduate classes (such as computer labs etc). They have already been used as such in the prestigious Canary Islands Winter School of Astrophysics XXXIV: The Local Group as a benchmark for Galaxy Evolution (La Laguna, Tenerife, Spain - 8-15 November 2023), which comprised about 60 undergraduate and graduate PhD students and young postdocs. 
URL https://arxiv.org/abs/2401.08750
 
Description interview with science journalist 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Public/other audiences
Results and Impact My PhD student Alex Merrow gave interviews to two science journalists who wrote online science articles about their science result obtained with simulations produced during the course of the award.
Year(s) Of Engagement Activity 2023
URL https://www.popsci.com/science/how-do-you-make-cosmic-sausage/