Galaxy And Mass Assembly: Accurate panchromatic photometry from optical priors using LAMBDAR

Angus Wright, Aaron Robotham, N. Bourne, Simon Driver, L. Dunne, S.J. Maddox, M. Alpaslan, Stephen Andrews, A.E. Bauer, J. Bland-Hawthorn, S. Brough, M.J.I. Brown, C. Clarke, M. Cluver, Luke Davies, M.W. Grootes, B.W. Holwerda, A.M. Hopkins, T.H. Jarrett, Prajwal Kafle & 11 others Rebecca Lange, J. Liske, J. Loveday, Amanda Moffett, P. Norberg, C.C. Popescu, M. Smith, E.N. Taylor, R.J. Tuffs, L. Wang, S.M. Wilkins

    Research output: Contribution to journalArticle

    50 Citations (Scopus)

    Abstract

    © 2016 The Authors. Published by Oxford University Press on behalf of The Royal Astronomical Society.We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (LAMBDAR), a novel code for calculating matched aperture photometry across images that are neither pixel- nor PSF-matched, using prior aperture definitions derived from high-resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalization, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric data set from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR; Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from LAMBDAR with that presented in Driver et al. (2016), finding broad agreement between the data sets. None the less, we demonstrate that the photometry from LAMBDAR is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the LAMBDAR data set. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using LAMBDAR photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour-colour parameter-space able to be explored.
    Original languageEnglish
    Pages (from-to)765-801
    JournalMonthly Notices of the Royal Astronomical Society
    Volume460
    Issue number1
    DOIs
    Publication statusPublished - 2016

    Fingerprint

    photometry
    assembly
    galaxies
    apertures
    outlier
    confusion
    color
    high resolution
    propagation
    star formation rate
    spectral energy distribution
    stellar mass
    pixel
    pixels
    programme
    energy
    rate

    Cite this

    Wright, Angus ; Robotham, Aaron ; Bourne, N. ; Driver, Simon ; Dunne, L. ; Maddox, S.J. ; Alpaslan, M. ; Andrews, Stephen ; Bauer, A.E. ; Bland-Hawthorn, J. ; Brough, S. ; Brown, M.J.I. ; Clarke, C. ; Cluver, M. ; Davies, Luke ; Grootes, M.W. ; Holwerda, B.W. ; Hopkins, A.M. ; Jarrett, T.H. ; Kafle, Prajwal ; Lange, Rebecca ; Liske, J. ; Loveday, J. ; Moffett, Amanda ; Norberg, P. ; Popescu, C.C. ; Smith, M. ; Taylor, E.N. ; Tuffs, R.J. ; Wang, L. ; Wilkins, S.M. / Galaxy And Mass Assembly: Accurate panchromatic photometry from optical priors using LAMBDAR. In: Monthly Notices of the Royal Astronomical Society. 2016 ; Vol. 460, No. 1. pp. 765-801.
    @article{566927ccb03048468e57b59c6c84f3c4,
    title = "Galaxy And Mass Assembly: Accurate panchromatic photometry from optical priors using LAMBDAR",
    abstract = "{\circledC} 2016 The Authors. Published by Oxford University Press on behalf of The Royal Astronomical Society.We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (LAMBDAR), a novel code for calculating matched aperture photometry across images that are neither pixel- nor PSF-matched, using prior aperture definitions derived from high-resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalization, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric data set from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR; Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from LAMBDAR with that presented in Driver et al. (2016), finding broad agreement between the data sets. None the less, we demonstrate that the photometry from LAMBDAR is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the LAMBDAR data set. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using LAMBDAR photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour-colour parameter-space able to be explored.",
    author = "Angus Wright and Aaron Robotham and N. Bourne and Simon Driver and L. Dunne and S.J. Maddox and M. Alpaslan and Stephen Andrews and A.E. Bauer and J. Bland-Hawthorn and S. Brough and M.J.I. Brown and C. Clarke and M. Cluver and Luke Davies and M.W. Grootes and B.W. Holwerda and A.M. Hopkins and T.H. Jarrett and Prajwal Kafle and Rebecca Lange and J. Liske and J. Loveday and Amanda Moffett and P. Norberg and C.C. Popescu and M. Smith and E.N. Taylor and R.J. Tuffs and L. Wang and S.M. Wilkins",
    year = "2016",
    doi = "10.1093/mnras/stw832",
    language = "English",
    volume = "460",
    pages = "765--801",
    journal = "Monthly Notices of the Royal Astronomical Society",
    issn = "0035-8711",
    publisher = "OXFORD UNIV PRESS UNITED KINGDOM",
    number = "1",

    }

    Wright, A, Robotham, A, Bourne, N, Driver, S, Dunne, L, Maddox, SJ, Alpaslan, M, Andrews, S, Bauer, AE, Bland-Hawthorn, J, Brough, S, Brown, MJI, Clarke, C, Cluver, M, Davies, L, Grootes, MW, Holwerda, BW, Hopkins, AM, Jarrett, TH, Kafle, P, Lange, R, Liske, J, Loveday, J, Moffett, A, Norberg, P, Popescu, CC, Smith, M, Taylor, EN, Tuffs, RJ, Wang, L & Wilkins, SM 2016, 'Galaxy And Mass Assembly: Accurate panchromatic photometry from optical priors using LAMBDAR' Monthly Notices of the Royal Astronomical Society, vol. 460, no. 1, pp. 765-801. https://doi.org/10.1093/mnras/stw832

    Galaxy And Mass Assembly: Accurate panchromatic photometry from optical priors using LAMBDAR. / Wright, Angus; Robotham, Aaron; Bourne, N.; Driver, Simon; Dunne, L.; Maddox, S.J.; Alpaslan, M.; Andrews, Stephen; Bauer, A.E.; Bland-Hawthorn, J.; Brough, S.; Brown, M.J.I.; Clarke, C.; Cluver, M.; Davies, Luke; Grootes, M.W.; Holwerda, B.W.; Hopkins, A.M.; Jarrett, T.H.; Kafle, Prajwal; Lange, Rebecca; Liske, J.; Loveday, J.; Moffett, Amanda; Norberg, P.; Popescu, C.C.; Smith, M.; Taylor, E.N.; Tuffs, R.J.; Wang, L.; Wilkins, S.M.

    In: Monthly Notices of the Royal Astronomical Society, Vol. 460, No. 1, 2016, p. 765-801.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Galaxy And Mass Assembly: Accurate panchromatic photometry from optical priors using LAMBDAR

    AU - Wright, Angus

    AU - Robotham, Aaron

    AU - Bourne, N.

    AU - Driver, Simon

    AU - Dunne, L.

    AU - Maddox, S.J.

    AU - Alpaslan, M.

    AU - Andrews, Stephen

    AU - Bauer, A.E.

    AU - Bland-Hawthorn, J.

    AU - Brough, S.

    AU - Brown, M.J.I.

    AU - Clarke, C.

    AU - Cluver, M.

    AU - Davies, Luke

    AU - Grootes, M.W.

    AU - Holwerda, B.W.

    AU - Hopkins, A.M.

    AU - Jarrett, T.H.

    AU - Kafle, Prajwal

    AU - Lange, Rebecca

    AU - Liske, J.

    AU - Loveday, J.

    AU - Moffett, Amanda

    AU - Norberg, P.

    AU - Popescu, C.C.

    AU - Smith, M.

    AU - Taylor, E.N.

    AU - Tuffs, R.J.

    AU - Wang, L.

    AU - Wilkins, S.M.

    PY - 2016

    Y1 - 2016

    N2 - © 2016 The Authors. Published by Oxford University Press on behalf of The Royal Astronomical Society.We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (LAMBDAR), a novel code for calculating matched aperture photometry across images that are neither pixel- nor PSF-matched, using prior aperture definitions derived from high-resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalization, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric data set from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR; Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from LAMBDAR with that presented in Driver et al. (2016), finding broad agreement between the data sets. None the less, we demonstrate that the photometry from LAMBDAR is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the LAMBDAR data set. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using LAMBDAR photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour-colour parameter-space able to be explored.

    AB - © 2016 The Authors. Published by Oxford University Press on behalf of The Royal Astronomical Society.We present the Lambda Adaptive Multi-Band Deblending Algorithm in R (LAMBDAR), a novel code for calculating matched aperture photometry across images that are neither pixel- nor PSF-matched, using prior aperture definitions derived from high-resolution optical imaging. The development of this program is motivated by the desire for consistent photometry and uncertainties across large ranges of photometric imaging, for use in calculating spectral energy distributions. We describe the program, specifically key features required for robust determination of panchromatic photometry: propagation of apertures to images with arbitrary resolution, local background estimation, aperture normalization, uncertainty determination and propagation, and object deblending. Using simulated images, we demonstrate that the program is able to recover accurate photometric measurements in both high-resolution, low-confusion, and low-resolution, high-confusion, regimes. We apply the program to the 21-band photometric data set from the Galaxy And Mass Assembly (GAMA) Panchromatic Data Release (PDR; Driver et al. 2016), which contains imaging spanning the far-UV to the far-IR. We compare photometry derived from LAMBDAR with that presented in Driver et al. (2016), finding broad agreement between the data sets. None the less, we demonstrate that the photometry from LAMBDAR is superior to that from the GAMA PDR, as determined by a reduction in the outlier rate and intrinsic scatter of colours in the LAMBDAR data set. We similarly find a decrease in the outlier rate of stellar masses and star formation rates using LAMBDAR photometry. Finally, we note an exceptional increase in the number of UV and mid-IR sources able to be constrained, which is accompanied by a significant increase in the mid-IR colour-colour parameter-space able to be explored.

    U2 - 10.1093/mnras/stw832

    DO - 10.1093/mnras/stw832

    M3 - Article

    VL - 460

    SP - 765

    EP - 801

    JO - Monthly Notices of the Royal Astronomical Society

    JF - Monthly Notices of the Royal Astronomical Society

    SN - 0035-8711

    IS - 1

    ER -