Understanding exactly how galaxies assemble their baryonic matter over cosmic time remains an open question in extragalactic astronomy. Multiple physical processes can influence the star formation history of a galaxy, including external processes such as minor mergers, gas accretion, dynamical heating of stellar populations, as well internal including massive wind outflows or feedback due to active galactic nuclei. In order to constrain the star formation history and explain the evolution of the baryonic content in galaxies we need accurate estimates of their physical parameters. In particular of critical importance is the stellar mass, star formation rate, and dust content together with measurements of the possible AGN contribution to the total galaxy luminosity at different epochs of the galaxy evolution.
The spectral energy distribution (SED) of a galaxy, typically estimated by collecting broad band photometry across all possible wavelengths, is a valuable source from which one can infer details about both the unresolved stellar population and an AGN, if present. Since the UV-optical emission absorbed by dust is re-emitted to infrared/submm wavelengths, the intrinsic stellar/AGN emission can be constrained by gathering observations from UV to far-IR after applying energy balance arguments.
In an effort to understand the nuclear and global emission of galaxies I have measured the physical properties of all the galaxies contained in the full Cornell Atlas of Spitzer/IRS Sources (CASSIS) catalogue, for which UV to 22μm photometry is available. I used state of the art SED models of CIGALE to fit broad-band photometric measurements in 14 wavelengths from all the public wide area/all-sky surveys. The sample consists of 1,146 galaxies in the redshift range 0 < z < 2.5. CIGALE is based on the energy balance between the absorbed stellar and the dust emission while taking into account the possible contribution due to the presence of an active galactic nucleus (AGN).
The provided catalogue contains the following integrated physical properties: stellar mass, star formation rate, stellar age, E(B-V) attenuation, FUV attenuation, dust luminosity, AGN luminosity as well as the contribution of the AGN component in the total infrared emission. Additionally, for two subsamples of galaxies with available structural parameters and optical spectral lines I provide two classifications. The first classification separates the galaxies to late-, blue & high- n, red & low- n, early-type, while the second to AGN, composite and star-forming galaxies.
I am currently contributing to the development of a new multi-wavelength technique for studying galaxy structure as part of the MegaMorph project.
As distinct gas and stellar units, galaxies exist in many shapes and sizes. Most galaxies are comprised of multiple structural components, primarily a bulge and a disk. Over the last decade we have undergone great advances in our ability to directly measure galaxy properties such as luminosity, size, and morphological type across multiple wavelengths. In order to understand the evolution of galaxies and the physical processes that occur over time, an accurate description of the galaxy structures and their properties is necessary at different epochs and wavelengths.
The main aim of this project is to develop software that can quickly and reliably decompose galaxies into their main structures and robustly measure the physical properties of these internal structures. We have developed a new method of study, providing a full wavelength-dependent model for an arbitrary set of multi-band data.
This new method focuses on improving our ability to extract structural information from galaxy images by expanding current single-band fitting routines to simultaneously using multiple images of the same galaxy. This technique makes more effective use of the wealth of multi-wavelength imaging available from modern surveys to robustly and consistently study the stellar populations of distinct galaxy structural components.
Our software has been implemented and tested to make full use of modern datasets by utilising multiple images of each galaxy at different wavelengths. The multi-band capability of our software has been evaluated for both real and simulated datasets, has been tested for large surveys (120,000 objects) and small samples of well-resolved nearby galaxies.
Today, we have evidence for the presence of supermassive black holes (SMBHs) in the centres of active galactic nuclei (AGN) and inactive galaxies. In the AGN case, SMBHs constitute the central engines of quasars and AGNs in general, while those in the inactive galaxies seem to be a relic of past quasar activity. Current observations lend further support to the theory that AGN galaxies are powered by mass accretion onto central black holes, which after the luminous phase of the host galaxies, when the nuclear gas has been swallowed or dispersed and the accretion process has stopped, the SMBHs continue to exist as relics having obtained their final mass. SMBHs are believed to represent an important ‘component’ in the galaxy structure throughout the galactic formation and evolution process.
It is still unclear how SMBHs are created, grown and co-evolve with their host galaxy. In order to improve the understanding of accretion of SMBHs and the important role it plays in the evolution of the host galaxy, researchers need large samples of inactive galaxies with determined Mbh, stellar velocity dispersion and galaxy structural properties, both nearby and at high redshift. Since the numbers of galaxies with 'direct' Mbh measurements are less than 100, the only other way to study SMBHs is to use the empirical relations to estimate 'indirect' Mbh for larger samples of galaxies that can then be used for constructing SMBH mass functions. Studying the mass function of SMBHs from the active era to the present day allows us to quantify the formation and growth of SMBHs. Most of my previous research, during my Ph.D, focused on quantifying the distribution of SMBHs in the nearby Universe.
Left: A summary of SMBH mass functions. The grey shaded region represent the Mbh–L GAMA SMBH best fit. The data points show the zero redshift SMBH mass function (blue points: Mbh–L GAMA; red circles: MGC; black circles connected with lines: Croton et al. (2006)). The curves are from Croton et al. (2006) and reveal the evolution of the SMBH mass functions (solid line: z=0.51; dashed line: z=0.99; dashed dotted line: z=2.07).