Publication

Physical drivers of the cosmic star formation history

Pearson, W. J., 2019, Groningen: University of Groningen. 228 p.

Research output: ThesisThesis fully internal (DIV)Academic

APA

Pearson, W. J. (2019). Physical drivers of the cosmic star formation history. Groningen: University of Groningen. https://doi.org/10.33612/diss.101445849

Author

Pearson, William James. / Physical drivers of the cosmic star formation history. Groningen : University of Groningen, 2019. 228 p.

Harvard

Pearson, WJ 2019, 'Physical drivers of the cosmic star formation history', Doctor of Philosophy, University of Groningen, Groningen. https://doi.org/10.33612/diss.101445849

Standard

Physical drivers of the cosmic star formation history. / Pearson, William James.

Groningen : University of Groningen, 2019. 228 p.

Research output: ThesisThesis fully internal (DIV)Academic

Vancouver

Pearson WJ. Physical drivers of the cosmic star formation history. Groningen: University of Groningen, 2019. 228 p. https://doi.org/10.33612/diss.101445849


BibTeX

@phdthesis{26660f58ff8143da8a4f7d2a43c8e9e5,
title = "Physical drivers of the cosmic star formation history",
abstract = "The build up of stars over the history of the universe is important for understanding why our universe looks the way it does today: it is the stars that create the energy that lights up the night sky. This thesis looks into some of the drivers of this star formation over the history of the universe.The connection between star formation rate and the mass of stars in galaxies is studied along with the connection between star formation and galaxy mergers. To do this, new techniques and tools are required for generating accurate star formation rate estimates and detecting galaxy mergers. A key component of star formation rate estimates, emission in the far-infrared, suffers from relatively low resolution which causes galaxies to blend with one another.In this thesis, existing de-blending tools have been improved, allowing better extraction of far-infrared luminosities and hence better estimates of star formation rates. This thesis also employs the latest deep learning techniques to identify merging galaxies in both simulations and observations of our universe.Studying the relation between the star formation rate and the existing mass of stars in galaxies found that in the early universe, high mass and low mass galaxies formed stars at similar rates. As the universe aged, high mass galaxies become less able to form new stars. For the influence of galaxy mergers on star formation rates, this thesis found that on average, galaxy mergers do not notably influence star formation rates but can trigger starbursts.",
author = "Pearson, {William James}",
year = "2019",
doi = "10.33612/diss.101445849",
language = "English",
isbn = "978-94-034-2128-5",
publisher = "University of Groningen",
school = "University of Groningen",

}

RIS

TY - THES

T1 - Physical drivers of the cosmic star formation history

AU - Pearson, William James

PY - 2019

Y1 - 2019

N2 - The build up of stars over the history of the universe is important for understanding why our universe looks the way it does today: it is the stars that create the energy that lights up the night sky. This thesis looks into some of the drivers of this star formation over the history of the universe.The connection between star formation rate and the mass of stars in galaxies is studied along with the connection between star formation and galaxy mergers. To do this, new techniques and tools are required for generating accurate star formation rate estimates and detecting galaxy mergers. A key component of star formation rate estimates, emission in the far-infrared, suffers from relatively low resolution which causes galaxies to blend with one another.In this thesis, existing de-blending tools have been improved, allowing better extraction of far-infrared luminosities and hence better estimates of star formation rates. This thesis also employs the latest deep learning techniques to identify merging galaxies in both simulations and observations of our universe.Studying the relation between the star formation rate and the existing mass of stars in galaxies found that in the early universe, high mass and low mass galaxies formed stars at similar rates. As the universe aged, high mass galaxies become less able to form new stars. For the influence of galaxy mergers on star formation rates, this thesis found that on average, galaxy mergers do not notably influence star formation rates but can trigger starbursts.

AB - The build up of stars over the history of the universe is important for understanding why our universe looks the way it does today: it is the stars that create the energy that lights up the night sky. This thesis looks into some of the drivers of this star formation over the history of the universe.The connection between star formation rate and the mass of stars in galaxies is studied along with the connection between star formation and galaxy mergers. To do this, new techniques and tools are required for generating accurate star formation rate estimates and detecting galaxy mergers. A key component of star formation rate estimates, emission in the far-infrared, suffers from relatively low resolution which causes galaxies to blend with one another.In this thesis, existing de-blending tools have been improved, allowing better extraction of far-infrared luminosities and hence better estimates of star formation rates. This thesis also employs the latest deep learning techniques to identify merging galaxies in both simulations and observations of our universe.Studying the relation between the star formation rate and the existing mass of stars in galaxies found that in the early universe, high mass and low mass galaxies formed stars at similar rates. As the universe aged, high mass galaxies become less able to form new stars. For the influence of galaxy mergers on star formation rates, this thesis found that on average, galaxy mergers do not notably influence star formation rates but can trigger starbursts.

U2 - 10.33612/diss.101445849

DO - 10.33612/diss.101445849

M3 - Thesis fully internal (DIV)

SN - 978-94-034-2128-5

PB - University of Groningen

CY - Groningen

ER -

ID: 101445849