The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model

We present a novel Bayesian method, referred to as BLOBBY3D, to infer gas kinematics that mitigates the effects of beam smearing for observations using integral field spectroscopy. The method is robust for regularly rotating galaxies despite substructure in the gas distribution. Modelling the gas su...

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Published in:Monthly Notices of the Royal Astronomical Society
Main Authors: Varidel, Mathew R., Croom, Scott M., Lewis, Geraint F., Brewer, Brendon J., Di Teodoro, Enrico M., Bland-Hawthorn, Joss, Bryant, Julia J., Federrath, Christoph, Foster, Caroline, Glazebrook, Karl, Goodwin, Michael, Groves, Brent, Hopkins, Andrew M., Lawrence, Jon S., López-Sánchez, Ángel R., Medling, Anne M., Owers, Matt S., Richards, Samuel N., Scalzo, Richard, Scott, Nicholas, Sweet, Sarah M., Taranu, Dan S., van de Sande, Jesse
Format: Article in Journal/Newspaper
Language:English
Published: 2019
Subjects:
Online Access:https://researchers.mq.edu.au/en/publications/38109794-51ca-49fc-812d-936c08f22341
https://doi.org/10.1093/mnras/stz670
https://research-management.mq.edu.au/ws/files/103655817/103515427.pdf
http://www.scopus.com/inward/record.url?scp=85067020233&partnerID=8YFLogxK
http://purl.org/au-research/grants/arc/FT140100255
http://purl.org/au-research/grants/arc/CE170100013
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spelling ftmacquarieunicr:oai:https://researchers.mq.edu.au:publications/38109794-51ca-49fc-812d-936c08f22341 2024-09-15T18:33:20+00:00 The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model Varidel, Mathew R. Croom, Scott M. Lewis, Geraint F. Brewer, Brendon J. Di Teodoro, Enrico M. Bland-Hawthorn, Joss Bryant, Julia J. Federrath, Christoph Foster, Caroline Glazebrook, Karl Goodwin, Michael Groves, Brent Hopkins, Andrew M. Lawrence, Jon S. López-Sánchez, Ángel R. Medling, Anne M. Owers, Matt S. Richards, Samuel N. Scalzo, Richard Scott, Nicholas Sweet, Sarah M. Taranu, Dan S. van de Sande, Jesse 2019-05-01 application/pdf https://researchers.mq.edu.au/en/publications/38109794-51ca-49fc-812d-936c08f22341 https://doi.org/10.1093/mnras/stz670 https://research-management.mq.edu.au/ws/files/103655817/103515427.pdf http://www.scopus.com/inward/record.url?scp=85067020233&partnerID=8YFLogxK http://purl.org/au-research/grants/arc/FT140100255 http://purl.org/au-research/grants/arc/CE170100013 eng eng info:eu-repo/semantics/openAccess Varidel , M R , Croom , S M , Lewis , G F , Brewer , B J , Di Teodoro , E M , Bland-Hawthorn , J , Bryant , J J , Federrath , C , Foster , C , Glazebrook , K , Goodwin , M , Groves , B , Hopkins , A M , Lawrence , J S , López-Sánchez , Á R , Medling , A M , Owers , M S , Richards , S N , Scalzo , R , Scott , N , Sweet , S M , Taranu , D S & van de Sande , J 2019 , ' The SAMI Galaxy Survey : Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model ' , Monthly Notices of the Royal Astronomical Society , vol. 485 , no. 3 , pp. 4024-4044 . https://doi.org/10.1093/mnras/stz670 methods: data analysis methods: statistical techniques: imaging spectroscopy galaxies: kinematics and dynamics article 2019 ftmacquarieunicr https://doi.org/10.1093/mnras/stz670 2024-08-28T23:47:19Z We present a novel Bayesian method, referred to as BLOBBY3D, to infer gas kinematics that mitigates the effects of beam smearing for observations using integral field spectroscopy. The method is robust for regularly rotating galaxies despite substructure in the gas distribution. Modelling the gas substructure within the disc is achieved by using a hierarchical Gaussian mixture model. To account for beam smearing effects, we construct a modelled cube that is then convolved per wavelength slice by the seeing, before calculating the likelihood function. We show that our method can model complex gas substructure including clumps and spiral arms. We also show that kinematic asymmetries can be observed after beam smearing for regularly rotating galaxies with asymmetries only introduced in the spatial distribution of the gas. We present findings for our method applied to a sample of 20 star-forming galaxies from the SAMI Galaxy Survey. We estimate the global H α gas velocity dispersion for our sample to be in the range σ¯ v ∼[7, 30] km s −1 . The relative difference between our approach and estimates using the single Gaussian component fits per spaxel is σ¯ v /σ¯ v = −0.29 ± 0.18 for the Hα flux-weighted mean velocity dispersion. Article in Journal/Newspaper sami Macquarie University Research Portal Monthly Notices of the Royal Astronomical Society 485 3 4024 4044
institution Open Polar
collection Macquarie University Research Portal
op_collection_id ftmacquarieunicr
language English
topic methods: data analysis
methods: statistical
techniques: imaging spectroscopy
galaxies: kinematics and dynamics
spellingShingle methods: data analysis
methods: statistical
techniques: imaging spectroscopy
galaxies: kinematics and dynamics
Varidel, Mathew R.
Croom, Scott M.
Lewis, Geraint F.
Brewer, Brendon J.
Di Teodoro, Enrico M.
Bland-Hawthorn, Joss
Bryant, Julia J.
Federrath, Christoph
Foster, Caroline
Glazebrook, Karl
Goodwin, Michael
Groves, Brent
Hopkins, Andrew M.
Lawrence, Jon S.
López-Sánchez, Ángel R.
Medling, Anne M.
Owers, Matt S.
Richards, Samuel N.
Scalzo, Richard
Scott, Nicholas
Sweet, Sarah M.
Taranu, Dan S.
van de Sande, Jesse
The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model
topic_facet methods: data analysis
methods: statistical
techniques: imaging spectroscopy
galaxies: kinematics and dynamics
description We present a novel Bayesian method, referred to as BLOBBY3D, to infer gas kinematics that mitigates the effects of beam smearing for observations using integral field spectroscopy. The method is robust for regularly rotating galaxies despite substructure in the gas distribution. Modelling the gas substructure within the disc is achieved by using a hierarchical Gaussian mixture model. To account for beam smearing effects, we construct a modelled cube that is then convolved per wavelength slice by the seeing, before calculating the likelihood function. We show that our method can model complex gas substructure including clumps and spiral arms. We also show that kinematic asymmetries can be observed after beam smearing for regularly rotating galaxies with asymmetries only introduced in the spatial distribution of the gas. We present findings for our method applied to a sample of 20 star-forming galaxies from the SAMI Galaxy Survey. We estimate the global H α gas velocity dispersion for our sample to be in the range σ¯ v ∼[7, 30] km s −1 . The relative difference between our approach and estimates using the single Gaussian component fits per spaxel is σ¯ v /σ¯ v = −0.29 ± 0.18 for the Hα flux-weighted mean velocity dispersion.
format Article in Journal/Newspaper
author Varidel, Mathew R.
Croom, Scott M.
Lewis, Geraint F.
Brewer, Brendon J.
Di Teodoro, Enrico M.
Bland-Hawthorn, Joss
Bryant, Julia J.
Federrath, Christoph
Foster, Caroline
Glazebrook, Karl
Goodwin, Michael
Groves, Brent
Hopkins, Andrew M.
Lawrence, Jon S.
López-Sánchez, Ángel R.
Medling, Anne M.
Owers, Matt S.
Richards, Samuel N.
Scalzo, Richard
Scott, Nicholas
Sweet, Sarah M.
Taranu, Dan S.
van de Sande, Jesse
author_facet Varidel, Mathew R.
Croom, Scott M.
Lewis, Geraint F.
Brewer, Brendon J.
Di Teodoro, Enrico M.
Bland-Hawthorn, Joss
Bryant, Julia J.
Federrath, Christoph
Foster, Caroline
Glazebrook, Karl
Goodwin, Michael
Groves, Brent
Hopkins, Andrew M.
Lawrence, Jon S.
López-Sánchez, Ángel R.
Medling, Anne M.
Owers, Matt S.
Richards, Samuel N.
Scalzo, Richard
Scott, Nicholas
Sweet, Sarah M.
Taranu, Dan S.
van de Sande, Jesse
author_sort Varidel, Mathew R.
title The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model
title_short The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model
title_full The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model
title_fullStr The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model
title_full_unstemmed The SAMI Galaxy Survey:Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model
title_sort sami galaxy survey:bayesian inference for gas disc kinematics using a hierarchical gaussian mixture model
publishDate 2019
url https://researchers.mq.edu.au/en/publications/38109794-51ca-49fc-812d-936c08f22341
https://doi.org/10.1093/mnras/stz670
https://research-management.mq.edu.au/ws/files/103655817/103515427.pdf
http://www.scopus.com/inward/record.url?scp=85067020233&partnerID=8YFLogxK
http://purl.org/au-research/grants/arc/FT140100255
http://purl.org/au-research/grants/arc/CE170100013
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genre_facet sami
op_source Varidel , M R , Croom , S M , Lewis , G F , Brewer , B J , Di Teodoro , E M , Bland-Hawthorn , J , Bryant , J J , Federrath , C , Foster , C , Glazebrook , K , Goodwin , M , Groves , B , Hopkins , A M , Lawrence , J S , López-Sánchez , Á R , Medling , A M , Owers , M S , Richards , S N , Scalzo , R , Scott , N , Sweet , S M , Taranu , D S & van de Sande , J 2019 , ' The SAMI Galaxy Survey : Bayesian inference for gas disc kinematics using a hierarchical Gaussian mixture model ' , Monthly Notices of the Royal Astronomical Society , vol. 485 , no. 3 , pp. 4024-4044 . https://doi.org/10.1093/mnras/stz670
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container_title Monthly Notices of the Royal Astronomical Society
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container_start_page 4024
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