Periodic Reporting for period 3 - GMGalaxies (Understanding the diversity of galaxy morphology in the era of large spectroscopic surveys)
Reporting period: 2022-10-01 to 2024-03-31
GMGalaxies is a research programme investigating the relationship between the history of cosmic structures and their properties which can be measured from images in telescopes.The ultimate goal is to move beyond our current phenomenological understanding of the universe towards a precision account of galaxy formation, and how it is driven by dark matter and dark energy; this is essential for reaching an improved overall account of physics and the nature of our existence, which is at the core of the relevance to society.
Our more specific objectives are to answer questions such as:
* How does the appearance of galaxies today, as observed with a variety of state-of-the-art instruments (including photometric, spectroscopic and radio) inform us about their past?
* What happened in the history of some galaxies to transform them into passive ellipticals while others, seemingly of the same mass and in the same environment, are star-forming spirals?
* Can we understand extreme galaxies such as those with very low or high surface brightnesses?
Answering these questions about the link between morphology and star formation is crucial in an era where understanding the way galaxies trace the underlying dark universe is essential for progress in precision cosmology. Weak lensing studies, for example, require the link between a galaxy’s history, environment and shape to be pinpointed; similarly, galaxy rotation curves are used by many astronomers as a laboratory to determine the nature of dark matter, but this requires an understanding of these links between history, physics and today’s observational properties.
Current research in this area rightly gives significant attention to the crucial problem of how feedback — energy input from supernovae, active galactic nuclei, and more — affect observable properties. But as well as investigating this avenue, the GMGalaxies team have pioneered and now continue to develop and apply a new technique (“genetic modification”) to investigate systematically the role of a galaxy’s merging and accretion history at high resolution, and to enhance our understanding of large scale structure in the Universe.
Our more specific objectives are to answer questions such as:
* How does the appearance of galaxies today, as observed with a variety of state-of-the-art instruments (including photometric, spectroscopic and radio) inform us about their past?
* What happened in the history of some galaxies to transform them into passive ellipticals while others, seemingly of the same mass and in the same environment, are star-forming spirals?
* Can we understand extreme galaxies such as those with very low or high surface brightnesses?
Answering these questions about the link between morphology and star formation is crucial in an era where understanding the way galaxies trace the underlying dark universe is essential for progress in precision cosmology. Weak lensing studies, for example, require the link between a galaxy’s history, environment and shape to be pinpointed; similarly, galaxy rotation curves are used by many astronomers as a laboratory to determine the nature of dark matter, but this requires an understanding of these links between history, physics and today’s observational properties.
Current research in this area rightly gives significant attention to the crucial problem of how feedback — energy input from supernovae, active galactic nuclei, and more — affect observable properties. But as well as investigating this avenue, the GMGalaxies team have pioneered and now continue to develop and apply a new technique (“genetic modification”) to investigate systematically the role of a galaxy’s merging and accretion history at high resolution, and to enhance our understanding of large scale structure in the Universe.
We have been applying our genetic modification technique which involves generating multiple, slightly different sets of early-Universe conditions from which a given galaxy, halo, or void will emerge. As each version of the Universe is evolved in its own computer simulation, the initial differences lead to contrasting evolutions – for instance, the galaxy might be formed earlier or later in the Universe's history, or undergo a different number of mergers with other galaxies. All this takes place in a fully cosmological setting, replicating the accretion of gas and dark matter along filaments.
As such, we provide a highly complementary account of galaxy formation, making clear what the causal relationships are between the history of particular galaxies and their observable properties. Our main results so far systematically probe how galaxy mergers can lead to ‘quenching’, i.e. galaxies that experience a sufficiently major merger cease forming stars and subsequently change their appearance over time. We have connected these mechanisms to the way in which gas gathers around galaxies in the so-called ‘circumgalactic medium’, and proposed novel observational tests which will shed further light on how galaxies of different masses interact with these surroundings.
We have also been developing the genetic modification technique to enable the construction of further tests. We have shown that we can alter not just the mass ratio of mergers, but also the angular momentum of material that falls into our galaxies. At the end of this reporting period, we obtained results showing how angular momentum causally determines the extent of the disk of galaxies, results which will be published shortly and which we will continue to develop. We have created a proof in principle to show that we can re-simulate single galaxies placed into different cosmological environments to see how environments affect galactic evolution.
Finally, we have developed new interpretable machine learning techniques to study the connection between dark matter halos around galaxies, their environment, and the early universe initial conditions.
As such, we provide a highly complementary account of galaxy formation, making clear what the causal relationships are between the history of particular galaxies and their observable properties. Our main results so far systematically probe how galaxy mergers can lead to ‘quenching’, i.e. galaxies that experience a sufficiently major merger cease forming stars and subsequently change their appearance over time. We have connected these mechanisms to the way in which gas gathers around galaxies in the so-called ‘circumgalactic medium’, and proposed novel observational tests which will shed further light on how galaxies of different masses interact with these surroundings.
We have also been developing the genetic modification technique to enable the construction of further tests. We have shown that we can alter not just the mass ratio of mergers, but also the angular momentum of material that falls into our galaxies. At the end of this reporting period, we obtained results showing how angular momentum causally determines the extent of the disk of galaxies, results which will be published shortly and which we will continue to develop. We have created a proof in principle to show that we can re-simulate single galaxies placed into different cosmological environments to see how environments affect galactic evolution.
Finally, we have developed new interpretable machine learning techniques to study the connection between dark matter halos around galaxies, their environment, and the early universe initial conditions.
Our work, in which galaxy simulations are used as “laboratories”, is unlike any other numerical cosmology project globally, and has made use of a completely new technique. During the project, we have massively extended the ability of this technique to construct controlled experiments and shed light on the causal processes determining the shapes, sizes and colours of galaxies. In terms of results, by showing the connection between the circumgalactic medium and morphology of galaxies, we have made predictions for forthcoming observations in X-ray, quasar absorption line, and radio telescope studies. These are all avenues that we will continue to develop over the rest of the project. We are also showing how novel ‘interpretable machine learning’ techniques can form a complementary part of our analysis, where artificial intelligences trained to predict the results of simulations can in turn shed light on the physical mechanisms at play.