Browsing by Author "An, Fangxia"

Now showing 1 - 4 of 4
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    Machine-learning approaches for classifying star-forming galaxies and active galactic nuclei from MIGHTEE-detected radio sources in the COSMOS field
    (Oxford University Press, 2025) Silima, Walter; An, Fangxia; Vaccari, Mattia; Hussein, Eslam
    Radio synchrotron emission originates from both massive star formation and black hole accretion, two processes that drive galaxy evolution. Efficient classification of sources dominated by either process is therefore essential for fully exploiting deep, wide-field extragalactic radio continuum surveys. In this study, we implement, optimize, and compare five widely used supervised machine-learning (ML) algorithms to classify radio sources detected in the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE)-COSMOS survey as star-forming galaxies (SFGs) and active galactic nuclei (AGNs). Training and test sets are constructed from conventionally classified MIGHTEE-COSMOS sources, and 18 physical parameters of the MIGHTEE-detected sources are evaluated as input features. As anticipated, our feature analyses rank the five parameters used in conventional classification as the most effective: the infrared–radio correlation parameter ($q_\mathrm{IR}$), the optical compactness morphology parameter (class_star), stellar mass, and two combined mid-infrared colours. By optimizing the ML models with these selected features and testing classifiers across various feature combinations, we find that model performance generally improves as additional features are incorporated. Overall, all five algorithms yield an F1-score (the harmonic mean of precision and recall) >90 per cent even when trained on only 20 per cent of the data set. Among them, the distance-based k-nearest neighbours classifier demonstrates the highest accuracy and stability, establishing it as a robust and effective method for classifying SFGs and AGNs in upcoming large radio continuum surveys.
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    Mightee: Multi-wavelength counterparts in the Comos field
    (Oxford University Press, 2024) Imogen H. Whittam; Prescott Matthew; Jarvis M.J; An, Fangxia; Glowacki M.; Adams N.J.
    In this paper, we combine the early science radio continuum data from the MeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) Survey, with optical and near-infrared data and release the cross-matched catalogues. The radio data used in this work covers 0.86 deg2 of the COSMOS field, reaches a thermal noise of 1.7 μJy beam-1 and contains 6102 radio components. We visually inspect and cross-match the radio sample with optical and near-infrared data from the hyper suprime-cam (HSC) and UltraVISTA surveys. This allows the properties of active galactic nuclei and star-forming populations of galaxies to be probed out to z ≈ 5. Additionally, we use the likelihood ratio method to automatically cross-match the radio and optical catalogues and compare this to the visually cross-matched catalogue. We find that 94 per cent of our radio source catalogue can be matched with this method, with a reliability of 95 per cent. We proceed to show that visual classification will still remain an essential process for the cross-matching of complex and extended radio sources. In the near future, the MIGHTEE survey will be expanded in area to cover a total of ∼20 deg2; thus the combination of automated and visual identification will be critical. We compare the redshift distribution of SFG and AGN to the SKADS and T-RECS simulations and find more AGN than predicted at z ∼1.
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    The physical properties of star-forming galaxies with strong [oiii]lines at z=3.25
    (IOP Publishing, 2022) Wen, Run; An, Fangxia; Zheng, Xian Zhong
    We present an analysis of physical properties of 34 [O III] emission-line galaxies (ELGs) at z = 3.254 ± 0.029 in the Extended Chandra Deep Field South (ECDFS). These ELGs are selected from deep narrow H2S(1) and broad Ks imaging of 383 arcmin2 obtained with CFHT/WIRCam. We construct spectral energy distributions (SEDs) from U to Ks to derive the physical properties of ELGs. These [O III] ELGs are identified as starburst galaxies with strong [O III] lines of LOIII ∼ 1042.6–1044.2 erg s−1 and have stellar masses of M* ∼ 109.0–1010.6 Me and star formation rates of ∼10–210 Me yr−1 . Our results show that 24% of our sample galaxies are dusty with AV > 1 mag and EW([O III])rest ∼ 70–500 Å, which are often missed in optically selected [O III] ELG samples.
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    Radio spectral properties of star-forming galaxies in the MIGHTEE-COSMOS field and their impact on the far-infrared-radio correlation
    (Oxford University Press, 2021) Vacaari, M; An, Fangxia; Smail, Ian
    We study the radio spectral properties of 2094 star-forming galaxies (SFGs) by combining our early science data from theMeerKAT International GHz Tiered Extragalactic Exploration (MIGHTEE) survey with VLA, GMRT radio data, and richancillary data in the COSMOS field. These SFGs are selected at VLA 3 GHz, and their flux densities from MeerKAT 1.3 GHzand GMRT 325 MHz imaging data are extracted using the ‘superdeblending’ technique. The median radio spectral index isα3 GHz1.3 GHz=−0.80±0.01 without significant variation across the rest-frame frequencies∼1.3–10 GHz, indicating radio spectradominated by synchrotron radiation. On average, the radio spectrum at observer-frame 1.3–3 GHz slightly steepens withincreasing stellar mass with a linear fitted slope ofβ=−0.08±0.01, which could be explained by age-related synchrotronlosses. Due to the sensitivity of GMRT 325 MHz data, we apply a further flux density cut at 3 GHz (S3 GHz≥50μJy) and obtaina sample of 166 SFGs with measured flux densities at 325 MHz, 1.3 GHz, and 3 GHz. On average, the radio spectrum of SFGsflattens at low frequency with the median spectral indices ofα1.3 GHz325 MHz=−0.59+0.02−0.03andα3.0 GHz1.3 GHz=−0.74+0.01−0.02. At low frequency,our stacking analyses show that the radio spectrum also slightly steepens with increasing stellar mass. By comparing the far-infrared-radio correlations of SFGs based on different radio spectral indices, we find that adoptingα3 GHz1.3 GHzfork-corrections willsignificantly underestimate the infrared-to-radio luminosity ratio (qIR)for>17 per cent of the SFGs with measured flux densityat the three radio frequencies in our sample, because their radio spectra are significantly flatter at low frequency (0.33–1.3 GHz)