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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.

Dr Micah Bowles

Visitor

Research theme

  • Astronomy and astrophysics

Sub department

  • Astrophysics

Research groups

  • Zooniverse
  • Galaxy formation and evolution
  • MeerKAT
  • The Square Kilometre Array (SKA)
  • Breakthrough Listen
micah.bowles@physics.ox.ac.uk
Publications
Personal Website
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  • About
  • Research
  • Publications

Radio Galaxy Zoo: morphological classification by Fanaroff–Riley designation using self-supervised pre-training

Monthly Notices of the Royal Astronomical Society Oxford University Press 544:4 (2025) staf1942

Authors:

Nutthawara Buatthaisong, Inigo Val Slijepcevic, Anna MM Scaife, Micah Bowles, Andrew Hopkins, Devina Mohan, Stanislav S Shabala, O Ivy Wong

Abstract:

In this study, we examine over 14 000 radio galaxies finely selected from Radio Galaxy Zoo (RGZ) project and provide classifications for approximately 5900 FRIs and 8100 FRIIs. We present an analysis of these predicted radio galaxy morphologies for the RGZ catalogue, classified using a pre-trained radio galaxy foundation model that has been fine-tuned to predict Fanaroff–Riley (FR) morphology. As seen in previous studies, our results show overlap between morphologically classified FRI and FRII luminosity–size distributions and we find that the model’s confidence in its predictions is lowest in this overlap region, suggesting that source morphologies are more ambiguous. We identify the presence of low-luminosity FRII sources, the proportion of which, with respect to the total number of FRIIs, is consistent with previous studies. However, a comparison of the low-luminosity FRII sources found in this work with those identified by previous studies reveals differences that may indicate their selection is influenced by the choice of classification methodology. We investigate the impacts of both pre-training and fine-tuning data selection on model performance for the downstream classification task, and show that while different pre-training data choices affect model confidence they do not appear to cause systematic generalization biases for the range of physical and observational characteristics considered in this work; however, we note that the same is not necessarily true for fine-tuning. As automated approaches to astronomical source identification and classification become increasingly prevalent, we highlight training data choices that can affect the model outputs and propagate into downstream analyses.
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Radio Galaxy Zoo: Morphological classification by Fanaroff-Riley designation using self-supervised pre-training

ArXiv 2509.11988 (2025)

Authors:

Nutthawara Buatthaisong, Inigo Val Slijepcevic, Anna MM Scaife, Micah Bowles, Andrew Hopkins, Devina Mohan, Stanislav S Shabala, O Ivy Wong
Details from ArXiV

IRIS: A Bayesian Approach for Image Reconstruction in Radio Interferometry with expressive Score-Based priors

ArXiv 2501.02473 (2025)

Authors:

Noé Dia, MJ Yantovski-Barth, Alexandre Adam, Micah Bowles, Laurence Perreault-Levasseur, Yashar Hezaveh, Anna Scaife
Details from ArXiV

Scaling Laws for Galaxy Images

(2024)

Authors:

Mike Walmsley, Micah Bowles, Anna MM Scaife, Jason Shingirai Makechemu, Alexander J Gordon, Annette MN Ferguson, Robert G Mann, James Pearson, Jürgen J Popp, Jo Bovy, Josh Speagle, Hugh Dickinson, Lucy Fortson, Tobias Géron, Sandor Kruk, Chris J Lintott, Kameswara Mantha, Devina Mohan, David O'Ryan, Inigo V Slijepevic
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MIGHTEE polarization early science fields: the deep polarized sky

Monthly Notices of the Royal Astronomical Society Oxford University Press 528:2 (2024) 2511-2522

Authors:

Andrew R Taylor, Srikrishna Sekhar, Lennart Heino, Anna MM Scaife, Jeroen Stil, Micah Bowles, Matt Jarvis, Ian Heywood, Jordan D Collier

Abstract:

The MeerKAT International GigaHertz Tiered Extragalactic Exploration (MIGHTEE) is one of the MeerKAT large survey projects, designed to pathfind SKA key science. MIGHTEE is undertaking deep radio imaging of four well-observed fields (COSMOS, XMM-LSS, ELAIS S1, and CDFS) totaling 20 square degrees to μJy sensitivities. Broad-band imaging observations between 880 and1690 MHz yield total intensity continuum, spectro-polarimetry, and atomic hydrogen spectral imaging. Early science data from MIGHTEE are being released from initial observations of COSMOS and XMM–LSS. This paper describes the spectro-polarimetric observations, the polarization data processing of the MIGHTEE early science fields, and presents polarization data images and catalogues. The catalogues include radio spectral index, redshift information, and Faraday rotation measure synthesis results for 13 267 total intensity radio sources down to a polarized intensity detection limit of ∼20 μJy bm−1. Polarized signals were detected from 324 sources. For the polarized detections, we include a catalogue of Faraday Depth from both Faraday Synthesis and Q, U fitting, as well as total intensity and polarization spectral indices. The distribution of redshift of the total radio sources and detected polarized sources are the same, with median redshifts of 0.86 and 0.82, respectively. Depolarization of the emission at longer-wavelengths is seen to increase with decreasing total-intensity spectral index, implying that depolarization is intrinsic to the radio sources. No evidence is seen for a redshift dependence of the variance of Faraday depth.
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