Galaxies, Active Galactic Nuclei and Cosmology
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Echo-mapping the extreme spacetime around black holes
William Alston, Dominic Walton
Accreting black holes are unique sources of some of the most extreme physics in the universe. They are a testbed for understanding general relativity and high-energy physics processes, having implications for all areas of science and space exploration. Key to solving many unanswered questions in contemporary astrophysics are precise measurements of the black hole mass, spin and detailed knowledge of the processes involved in the accretion and ejection of matter around the black hole. The accretion of matter is non-static, so the application of time series methods to the data provides important insight into the geometry and physical processes involved – something which spectral information cannot achieve alone.
The recent discovery of short time delays – or reverberation - between the intrinsic X-ray emission and the accretion disc reprocessing component around the black hole has made it possible to spatially map the close regions around black holes. This spatial information is measured by modelling the response of the disc to a flash of X-rays coming from the corona. This allows us to decode the geometry, relativistic effects and light bending in the extremely curved spacetime. Recently, we have modelled the reverberation signal in a nearby supermassive black hole as the system evolves over several months (Alston et al 2020). This revealed for the first time a dynamic picture of material around the event horizon, turning our previously static picture of the inner accretion flow into a movie. This powerful method means we are able to resolve structures to an accuracy of ~1 gravitational radii (Rg) - equivalent to measuring structures the size of the sun at a distance of over 1 billion light years.
This project involves the development and application of timing analysis methods, such as Fourier analysis and Gaussian Processes, as well as other data science and machine learning methods, to a wide variety of X-ray and optical data on accreting black holes. Together with the development and application of theoretical models, we will make the most accurate measurements of black hole mass and spin to date in a large sample of sources. The understanding we will gain from sources in the local universe will allow us to push this method to higher redshift and to test models of black hole growth over cosmic time.
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The Dusty Universe Unveiled: state-of-the-art (sub)millimetre surveys of galaxies across cosmic time
Kristen Coppin, Jim Geach
Over half of the star formation energy generation in the Universe is extincted at optical wavelengths and enshrouded by dust which absorbs and re-radiates the starlight in the far-infrared/submm; and the sub-mm and mm atmospheric windows allow us to access the redshifted far-infrared emission from this obscured or ``hidden’’ side of galaxy formation and evolution. The James Clerk Maxwell Telescope (JCMT) Cosmology Legacy Survey (S2CLS; Geach et al. 2017) and its extension via the SCUBA-2 COSMOS survey (S2COSMOS; Simpson et al. 2017) and now S2XLS (PI Geach) and STUDIES (Wang et al. 2017) are the largest and most sensitive and ambitious single-dish surveys at 850 and 450 micron (in the submm wavebands) ever conducted. In addition, the 50-m Large Millimeter Telescope in Mexico will be conducting unique and transformative imaging of the sky at millimeter wavelengths through a series of public Legacy Surveys (Ultra-Deep and Large Scale Structure surveys in particular) starting in late 2021 using the new TolTEC camera. These unprecedented legacy surveys have been yielding thousands of high-redshift galaxies selected in the sub-mm/mm wavebands - providing an order-of-magnitude improvement in the sample sizes of previous surveys at these wavelengths!
With so much data now in-hand there are several possible projects that could be carved out using a combination of these legacy (sub)mm surveys with existing ancillary multi-wavelength data to make progress on a key outstanding question in galaxy evolution: How are dust and metals built up in massive galaxies over cosmic time? Some key science that could be explored with these data sets by a keen student include (for example): 1) constraining the (sub)mm source counts beyond the confusion limit (using a statistical P(D) fluctuation analysis); 2) locating and probing the high-redshift tail of the distribution of (sub)mm galaxies (via new mm observations); and 3) exploring new parameter space on the dust content, obscuration fraction, and gas content in galaxies (via (sub)mm observations) as a function of mass out to much higher-redshift than has previously been explored. The project can be tailored to some degree to match the student’s interests and skill set.
We are also involved in ongoing efforts to perform detailed follow-up of these high-z submm-detected sources at higher resolution with the Atacama Large Millimetre Array (ALMA) situated at 5000m on the Chajnantor plateau in Chile. It is envisaged that the findings of this work will feed naturally into new ALMA and other telescope proposals, such as the James Webb Space Telescope (JWST).
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The role of the Cosmic Web in the evolution of galaxies
Carolyn Devereux, Jim Geach, Rafael de Souza
The Cosmic Web is the large-scale structure of the universe and is dominated by dark matter. The aim of this project is to investigate the influence of the large scale structure on galaxy evolution. Using gravitational lensing of the CMB from Planck it is possible to reconstruct a map of the distribution of matter over the whole sky. This map can be correlated with the locations of galaxies to determine how galaxies map to the Cosmic Web giving us important information about the bias of galaxies within dark matter halos. The CMB lensing approach can be used to investigate how environment influences galaxy type (Devereux et al 2019, Geach et al 2013).
With significant numbers of galaxies being observed in current wide-area surveys it is an excellent time to use galaxy catalogues to investigate galaxy evolution using CMB lensing. The project will use radio survey data from LOFAR to explore the influence of environment on different galaxy types and how they evolve with redshift. The project will go on to identify cosmic filaments by analysis of galaxies using machine learning techniques and compare the approach with using CMB lensing correlation. The student will gain experience in analysing observational data, statistical analysis, coding and machine learning. The techniques and code can be applied to future data that will become available during the project such as LSST (Vera Rubin) and WEAVE. WEAVE will provide high quality redshift data that can improve the accuracy of these measurements particularly for looking back in time.
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The impact of supermassive black holes on their galaxies and environment
Gulay Gurkan, Martin Hardcastle
Supermassive black holes [SMBHs] in the centre of massive galaxies can produce powerful radio jets which affect their host galaxies as well as their surroundings. The link between SMBH jets, their host galaxies and the large-scale environment is key for understanding radio galaxy evolution. This PhD project will use excellent radio continuum and polarisation data (in hand) of GAMA23 field (Gürkan et al. 2022) collected using the Square Kilometer Array pathfinder ASKAP in conjunction with multi-wavelength data available. The student will select normal- and giant-size radio galaxies (which are amongst the largest single objects in the Universe, reaching to sizes 5 Mpc; e.g. Milky Way has a size of ~0.01 Mpc) in the GAMA23 field. The combination of radio intensity, polarimetry from ASKAP coupled with the excellent ancillary data will give a unique opportunity to investigate the relation between the impact of radio jets onto their host galaxies and their environments for statistically meaningful samples of radio sources, and compare these with simulations (e.g. Hardcastle & Krause 2014, Hardcastle 2018). More importantly, this will allow the student to establish methods for other fields with radio data, in preparation for the biggest radio astronomy project the SKA. With this project the student will have the opportunity to develop a set of crucial skills (in coding, data fitting and radio data analysis) easily transferable to other fields/subjects.
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The low-surface-brightness Universe: a new frontier in the study of galaxy evolution
Sugata Kaviraj, Aaron Watkins
Our current understanding of the Universe is dominated by bright objects (e.g. massive galaxies like the Milky Way), because such systems are brighter than the detection thresholds of past large observational surveys (e.g. the SDSS). However, the majority of stars in the Universe actually reside in the so-called ‘low-surface-brightness’ regime, i.e. in objects and structures that are much fainter than the detection limits of past surveys. This regime contains all dwarf (low-mass) galaxies which dominate the galaxy number density, making them critical to our understanding of galaxy evolution. It also includes faint tidal debris created by galaxy mergers, which are key to understanding how gravity, the predominant force in the Universe, shapes it over cosmic time. Put simply, a complete understanding of how the Universe evolves is not possible without a detailed comprehension of the low-surface-brightness regime.
Astrophysics is currently entering a revolutionary era of new surveys, which not only have large areas but are also incredibly deep. In particular, the Legacy Survey of Space and Time (LSST) and the Subaru Strategic Program from the Hyper Suprime-Cam telescope, are poised to transform our understanding of the Universe, by providing images that are more than 100 times deeper than those from previous surveys. These images will enable us to perform detailed studies of the low-surface-brightness Universe for the first time.
This project will combine state-of-the-art data from these surveys with in-house cosmological simulations (e.g. New Horizon) and advanced machine-learning techniques (e.g. Martin et al. 2020), to perform the first statistical studies of the low-surface-brightness Universe. The project will map the properties of dwarf galaxies in unprecedented detail, over at least half the lifetime of the Universe and quantify the role of key processes like galaxy merging in driving star-formation, black-hole growth and morphological transformation in galaxies over cosmic time.
The student will collaborate closely (through visits and conference trips) with colleagues in Paris, Oxford and a worldwide network of scientists within the international LSST project (in which our team members hold several leadership roles). The project will give the student an excellent skillset in astronomical observation, theory and machine-learning that is well-aligned with this new era of Big Data astronomy.
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Galactic Archaeology -- the origin of elements and gravitational wave events
Chiaki Kobayashi, Sean Ryan
Just after the Big Bang, only very light elements (H, He, Li, Be, and B) can be produced, and heavier elements are all formed in stars and ejected by supernovae. Many elements (from carbon to uranium) have been observed in millions of stars in the Milky Way with spectroscopic ‘galactic archaeology' surveys, and some of the production sites are also observed as gravitational wave events such as the neutron star merger in 2017. The student will study the origin of elements in the Universe by comparing computational simulations of galaxies to these observational data, then predict the gravitational wave events for future missions in space (LISA) and on Moon. Our hydrodynamical simulation code already includes basic physics such as star formation and supernova feedback, and thus it is possible to compare with the observed elemental abundances in the Milky Way and its satellite galaxies. The student will update the code (written in c) to include the detailed effects from binary stars (for the first time in the world), and use local LINUX cluster and national supercomputer facility (DiRAC).
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Jet feedback in star-forming galaxies
Martin Krause, Martin Hardcastle
The evolution of galaxies and their central supermassive black holes is closely linked and evidence is accumulating that the mutual interaction is different for different galaxies and in different epochs of the Universe. The black holes produce powerful radio jets that may affect star formation in galaxies, in particular, via preventing cooling gas around the galaxies from arriving in the galaxy in the first place and also by triggering star formation by compressing dense gas already inside the galaxies. Our group has contributed to this progress with simulations in the past. This PhD project would use existing simulation software to study jets in galaxies with a star-forming disc, similar to the Milky Way. The jets are expected to form radio lobes, affect outflow properties of the gas and the rate of star formation. Such results will then be compared to observations available within the group and from the literature. This will result in a better understanding which observations may be explained by jets and how important this jet feedback really is in star-forming galaxies. The project is well-suited for somebody who enjoys coding and gaining physical insight from an analysis of simulations of the interplay of the laws of physics and careful comparison to observations.
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Simulating the Radioactive Milky Way
Martin Krause, Rob Yates
The buildup of the chemical elements in the chart of nuclei is a fascinating story that involves a number of different factors: Most of the elements heavier than helium have been formed in stars and during different kinds of stellar explosions. Direct evidence for this process comes from the measurements of radioactive decay lines shortly after an explosion and also from radioactive decay of elements with longer half lives that accumulate in the interstellar medium. 26Al, ejected from a variety of sources, and 60Fe, ejected from supernovae, only, both have half lives of the order of a million years and have been found in the Milky Way with gamma ray observations. The observations can, however, only be interpreted with the help of computer simulations that predict sky distributions for different assumptions about how the stars shed the radioactive nuclei and how the ejecta evolve in the dynamic interstellar medium. Our group is active in such simulations. The project consists in running new simulations with the existing code, and in particular, explore the differences between the expected sky distributions for 26Al and 60Fe.
The project is particularly timely since NASA's COSI mission (recently confirmed for launch in ≈ 2027) is expected to measure for the first time the distribution of radioactive 60Fe in the Milky Way. Knowledge of hydrodynamics and some prior experience with simulation codes are beneficial, but can also be acquired at the beginning of the project.
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Structural Decomposition of Galaxy Images for Big-data Astronomy
Rafael S. de Souza, Ashley Spindler
Accurately characterising galaxy structures, such as bulges, discs, bars and additional complex components, is imperative to build a comprehensive picture of cosmic evolution. In modern Astronomy, large samples of galaxies have been decomposed in their structural components. Such studies enable us to improve galaxy formation models. Several insights about galaxy evolution can benefit from this analysis, such as the relationship between galaxy mass and size, the luminosity-surface brightness relation for different galaxy classes, and their relation with the cosmic web.
Many codes are available to fit two-dimensional galaxy profiles, including BUDDA, GALFIT, GALMORPH, GIM2D, IMFIT, and ProFit. Most of them differ in details, such as the likelihood definition and sampling or optimisation schemes. Despite their extensive usability, they still need to fully exploit the capabilities of modern and scalable languages such as Torch to enable fast analysis of vast amounts of data using modern GPU capabilities.
This project will combine state-of-the-art statistical and deep-learning analysis to create a modern, open-source, and collaborative code to extract galactic structural properties optimally. This project will be particularly timely in preparation to exploit the data provided by the Legacy Survey of Space and Time (LSST). The project aims to create the fastest profile-fitting code available to date; once the preliminary part is done, the student will further generalise the code to decompose integral field spectroscopy data (similar to hyperspectral images), for which no scalable code exists to date.
The student will have the opportunity to collaborate with an international team of scientists, including the members of the Cosmostatistics Initiative.
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Probing Galaxy Evolution Through Time with Deep Learning
Ashley Spindler, Jim Geach
The shapes and dynamics of galaxies throughout the Universe provide a powerful lens through which we can understand the processes that shape them. Accurately labelling the morphologies of galaxies is a vital task in the study of galaxy evolution, and is a task that until recently was best completed by humans. Citizen science projects, such as Galaxy Zoo, have provided astronomers with hundreds of thousands of labelled galaxy images, revealing the intricate structures and histories held within. But, in the coming era of Big Data Astronomy, machine learning and AI are becoming a popular alternative to handle the vast scale of next-generation sky surveys.
AI powered astronomy is a rapidly growing field, with many models and codes now available and producing downstream datasets. This PhD project will aim to further develop advanced image recognition and object detection technologies. Working with cutting-edge deep imaging, such as the Legacy Survey of Space and Time, and the Subaru Strategic Program on the Hyper-Supreme Cam, the student will produce machine labelled morphological catalogues of millions of galaxies, and uncover the changing nature of galaxy structure through cosmic time.
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The Extremes of Accretion: Observational X-ray Frontiers
Dominic Walton, Will Alston
Accretion onto compact objects powers some of the most luminous and extreme phenomena in the universe. Accreting supermassive black holes ultimately power all of the different populations of active galactic nuclei (AGN), while stellar remnant black holes and neutron stars power luminous X-ray binary systems (XRBs) that are scattered throughout all major galaxies. This accretion process also drives powerful outflows (winds, jets) that allow these compact sources to impact their surroundings, and are responsible for driving the 'feedback' processes that dictate the observed co-evolution of supermassive black holes and their host galaxies. Understanding this accretion process (and its by-products) is therefore of critical importance. In particular, there are still major questions to be answered regarding how supermassive black holes came to be as massive as they are today (and, in the most extreme cases, how they were able to rapidly do so while the universe was still in its relative infancy).
Projects are available in two potential areas: black hole spin and ultraluminous X-ray sources. Both will primarily involve analysis of new and archival X-ray observations from e.g. the XMM-Newton, Swift, Chandra and NuSTAR observatories, including spectroscopic and time-domain analyses. In addition to the more immediate scientific progress, both areas will also serve as key preparation for the Athena X-ray observatory (ESA’s next flagship-class space telescope) as well as the Probe-class X-ray mission concepts being developed by NASA (e.g. HEX-P), and will also offer connections with the gravitational wave community.
Black Hole Spin: in astrophysics black holes are expected to be fully defined by just two numbers, their mass and their spin (or angular momentum). Information on the growth history of SMBHs is imprinted on their spin distribution, and so SMBH spin measurements are of particular importance for understanding this process, and in turn galaxy evolution (which is inextricably linked to SMBH growth). Similarly, spin measurements in black hole XRBs tells us information about the formation of the black holes in these systems, as well as offering a key point of comparison between the XRB population and the black holes seen merging via gravitational waves. Finally, spin measurements in both classes of source may be important for understanding relativistic jets. Such measurements are possible via detailed X-ray spectral/timing analyses of accreting black holes, and the same techniques can be used to measure spin in both AGN and black hole XRBs, providing an opportunity to probe the connection between these different black hole populations. The primary goal here is to further understand this connection, and further our efforts to undertake measurements of black hole spin.
Ultraluminous X-ray Sources: these are the most extreme XRBs and are now understood to be the best local examples of accretion above the Eddington limit, which may be required to grow the SMBHs now being seen in the early universe. ULXs were themselves assumed to be black holes for a long time, but remarkably we now know that some ULXs are powered by wildly super-Eddington neutron stars! Only a handful of these neutron star ULXs are currently known, but there is speculation they may make a significant contribution to the broader ULX population. In fact, we are still hunting for the first confirmed black hole ULX, although there is again speculation that such systems exist as evolutionary pre-cursors to the gravitational wave black hole mergers. The primary goal here is to further our understanding of the ULX population, studying the known ULX pulsars to understand how they are able to accrete at such extreme rates, searching for new ULX pulsars, and also for the first black hole ULX.