title: Stellar feedback and the self-regulation of star formation in giant molecular clouds: a new semi-analytic approach
creator: Rahner, Daniel
subject: 520
subject: 520 Astronomy and allied sciences
subject: 530
subject: 530 Physics
description: Stars and the gas between them - the interstellar medium - are intrinsically coupled. Massive stars form in clouds of molecular gas and illuminate them with their radiation, thus creating regions of ionized hydrogen (HII regions) and photodissociation regions. Eventually these stars destroy their parent clouds via powerful feedback mechanisms: stellar winds, ionizing radiation, and supernova explosions. These feedback processes are a crucial self-regulation mechanism of star formation, since, as soon as the first massive stars have formed, further star formation is suppressed.    Stellar winds, radiation, and supernova feedback interact with each other in a highly non-linear manner. This complexity poses a problem not only for purely analytic approaches but also for three-dimensional hydrodynamical simulations due to the high computational cost.   Here, I present a novel, semi-analytic, one-dimensional model, called WARPFIELD, which allows the cost-efficient simulation of the effects of stellar feedback from a massive star cluster on its natal giant molecular cloud (GMC).  With WARPFIELD we can show that the strength of each feedback process depends strongly on time and environment. For a large range of GMC and star cluster properties we can also demonstrate that stellar feedback can naturally explain the observed inefficiency of star formation.
date: 2019
type: Dissertation
type: info:eu-repo/semantics/doctoralThesis
type: NonPeerReviewed
format: application/pdf
identifier: https://archiv.ub.uni-heidelberg.de/volltextserverhttps://archiv.ub.uni-heidelberg.de/volltextserver/26665/1/thesisPRINT.pdf
identifier: DOI:10.11588/heidok.00026665
identifier: urn:nbn:de:bsz:16-heidok-266655
identifier:   Rahner, Daniel  (2019) Stellar feedback and the self-regulation of star formation in giant molecular clouds: a new semi-analytic approach.  [Dissertation]     
relation: https://archiv.ub.uni-heidelberg.de/volltextserver/26665/
rights: info:eu-repo/semantics/openAccess
rights: http://archiv.ub.uni-heidelberg.de/volltextserver/help/license_urhg.html
language: eng