Skip to main content
Home
Department Of Physics text logo
  • Research
    • Our research
    • Our research groups
    • Our research in action
    • Research funding support
    • Summer internships for undergraduates
  • Study
    • Undergraduates
    • Postgraduates
  • Engage
    • For alumni
    • For business
    • For schools
    • For the public
Menu
Black Hole

Lensing of space time around a black hole. At Oxford we study black holes observationally and theoretically on all size and time scales - it is some of our core work.

Credit: ALAIN RIAZUELO, IAP/UPMC/CNRS. CLICK HERE TO VIEW MORE IMAGES.

Prof. Matt Jarvis

Professor of Astrophysics

Research theme

  • Astronomy and astrophysics

Sub department

  • Astrophysics

Research groups

  • Cosmology
  • Galaxy formation and evolution
  • Hintze Centre for Astrophysical Surveys
  • MeerKAT
  • Rubin-LSST
  • The Square Kilometre Array (SKA)
Matt.Jarvis@physics.ox.ac.uk
Telephone: 01865 (2)83654
Denys Wilkinson Building, room 703
  • About
  • Publications

The VISTA Deep Extragalactic Observations (VIDEO) Survey

Monthly Notices of the Royal Astronomical Society 428 (2012)

Authors:

MJ Jarvis, DG Bonfield, VA Bruce, JE Geach, K McAlpine, RJ McLure, E Gonzalez-Solares, M Irwin, J Lewis, A Kupcu Yoldas, S Andreon, NJG Cross, JP Emerson, G Dalton, JS Dunlop, ST Hodgkin, O Le Fevre, M Karouzos, K Meisenheimer, S Oliver, S Rawlings, C Simpson, I Smail, DJB Smith, M Sullivan, W Sutherland, SV White, JTL Zwart
More details from the publisher
More details
Details from ArXiV

The MeerKAT International GHz tiered Extragalactic Exploration (MIGHTEE) survey

Proceedings of Science Proceedings of Science (2016)

Authors:

Matthew Jarvis, AR Taylor, I Agudo, RP Deane, B Frank, N Gupta, Ian Heywood, N Maddox, K McAlpine, AMM Scaife, M Vaccari, JTL Zwart, E Adams, DJ Bacon, AJ Baker, BA Bassett, PN Best, R Beswick, S Blyth, ML Brown, M Bruggen, M Cluver, S Colafranceso, Grant Cotter, C Cress, R Dave, C Ferrari, MJ Hardcastle, Catherine Hale, I Harrison, PW Hatfield, H-R Klockner, S Kolwa, E Malefahlo, T Marubini, T Mauch, K Moodley, R Morganti, R Norris, Josephine Peters, I Prandoni, M Prescott, S Oliver, N Oozeer, HJA Rottgering, N Seymour, C Simpson, O Smirnov

Abstract:

The MIGHTEE large survey project will survey four of the most well-studied extragalactic deep fields, totalling 20 square degrees to $\mu$Jy sensitivity at Giga-Hertz frequencies, as well as an ultra-deep image of a single ~1 square degree MeerKAT pointing. The observations will provide radio continuum, spectral line and polarisation information. As such, MIGHTEE, along with the excellent multi-wavelength data already available in these deep fields, will allow a range of science to be achieved. Specifically, MIGHTEE is designed to significantly enhance our understanding of, (i) the evolution of AGN and star-formation activity over cosmic time, as a function of stellar mass and environment, free of dust obscuration; (ii) the evolution of neutral hydrogen in the Universe and how this neutral gas eventually turns into stars after moving through the molecular phase, and how efficiently this can fuel AGN activity; (iii) the properties of cosmic magnetic fields and how they evolve in clusters, filaments and galaxies. MIGHTEE will reach similar depth to the planned SKA all-sky survey, and thus will provide a pilot to the cosmology experiments that will be carried out by the SKA over a much larger survey volume.
Details from ORA
Details from ArXiV

Environmental quenching and galactic conformity in the galaxy cross-correlation signal

Monthly Notices of the Royal Astronomical Society Oxford University Press (2017)

Authors:

Peter Hatfield, Matthew Jarvis

Abstract:

It has long been known that environment has a large effect on star formation in galaxies. There are several known plausible mechanisms to remove the cool gas needed for star formation, such as strangulation, harassment and ram-pressure stripping. It is unclear which process is dominant, and over what range of stellar mass. In this paper, we find evidence for suppression of the cross-correlation function between massive galaxies and less massive star-forming galaxies, giving a measure of how less likely a galaxy is to be star-forming in the vicinity of a more massive galaxy. We develop a formalism for modelling environmental quenching mechanisms within the Halo Occupation Distribution formalism. We find that at $z \sim 2$ environment is not a significant factor in determining quenching of star-forming galaxies, and that galaxies are quenched with similar probabilities in group environments as they are globally. However, by $z \sim 0.5$ galaxies are much less likely to be star forming when in a group environment than when not. This increased probability of being quenched does not appear to have significant radial dependence within the halo, supportive of the quenching being caused by the halting of fresh inflows of pristine gas, as opposed to by tidal stripping. Furthermore, by separating the massive sample into passive and star-forming, we see that this effect is further enhanced when the central galaxy is passive. This effect is present only in the 1-halo term (within a halo) at high redshifts ($z>1$), but is apparent in the 2-halo term at lower redshifts ($z<1$), a manifestation of galactic conformity.

More details from the publisher
Details from ORA
More details
Details from ArXiV
More details

Augmenting machine learning photometric redshifts with Gaussian mixture models

Monthly Notices of the Royal Astronomical Society Oxford University Press 498:4 (2020) 5498-5510

Authors:

PW Hatfield, IA Almosallam, MJ Jarvis, N Adams, RAA Bowler, Z Gomes, SJ Roberts, C Schreiber

Abstract:

Wide-area imaging surveys are one of the key ways of advancing our understanding of cosmology, galaxy formation physics, and the large-scale structure of the Universe in the coming years. These surveys typically require calculating redshifts for huge numbers (hundreds of millions to billions) of galaxies – almost all of which must be derived from photometry rather than spectroscopy. In this paper, we investigate how using statistical models to understand the populations that make up the colour–magnitude distribution of galaxies can be combined with machine learning photometric redshift codes to improve redshift estimates. In particular, we combine the use of Gaussian mixture models with the high-performing machine-learning photo-z algorithm GPz and show that modelling and accounting for the different colour–magnitude distributions of training and test data separately can give improved redshift estimates, reduce the bias on estimates by up to a half, and speed up the run-time of the algorithm. These methods are illustrated using data from deep optical and near-infrared data in two separate deep fields, where training and test data of different colour–magnitude distributions are constructed from the galaxies with known spectroscopic redshifts, derived from several heterogeneous surveys.
More details from the publisher
Details from ORA
More details
More details
Details from ArXiV

On the relationship between the cosmic web and the alignment of galaxies and AGN jets

Monthly Notices of the Royal Astronomical Society Oxford University Press (OUP) (2025) staf613

Authors:

S Lyla Jung, IH Whittam, MJ Jarvis, CL Hale, MN Tudorache, T Yasin
More details from the publisher
More details

Pagination

  • Current page 1
  • Page 2
  • Page 3
  • Page 4
  • Page 5
  • Page 6
  • Page 7
  • Page 8
  • Page 9
  • …
  • Next page Next
  • Last page Last

Footer Menu

  • Contact us
  • Giving to the Dept of Physics
  • Work with us
  • Media

User account menu

  • Log in

Follow us

FIND US

Clarendon Laboratory,

Parks Road,

Oxford,

OX1 3PU

CONTACT US

Tel: +44(0)1865272200

University of Oxfrod logo Department Of Physics text logo
IOP Juno Champion logo Athena Swan Silver Award logo

© University of Oxford - Department of Physics

Cookies | Privacy policy | Accessibility statement

Built by: Versantus

  • Home
  • Research
  • Study
  • Engage
  • Our people
  • News & Comment
  • Events
  • Our facilities & services
  • About us
  • Current students
  • Staff intranet