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dc.contributor.advisorWilliams, Benjamin F
dc.contributor.authorGarofali, Kristen Elise
dc.date.accessioned2018-11-28T03:14:52Z
dc.date.available2018-11-28T03:14:52Z
dc.date.submitted2018
dc.identifier.otherGarofali_washington_0250E_19173.pdf
dc.identifier.urihttp://hdl.handle.net/1773/42954
dc.descriptionThesis (Ph.D.)--University of Washington, 2018
dc.description.abstractMassive stars are key drivers in the cycle of star formation and overall galactic chemical evolution, but many aspects of the evolution of high-mass stars, in particular the end stages of their lifetimes, are difficult to constrain observationally. High-mass X-ray binaries (HMXBs) and supernova remnants (SNRs) are observable at a broad range of wavelengths and are unique probes into how massive stars evolve, die and subsequently interact with and enrich their environments. Previous studies of HMXB and SNR populations, both galactic and extragalactic, have demonstrated the wealth of knowledge to be gleaned from X-ray observations of these objects. However, these studies have been limited in the range of galactic host environments (metallicities and star formation rates) probed, as well as suffering from distance, extinction and X-ray positional uncertainties. M33, a late-type Sc spiral, is ideal for X-ray studies of both HMXBs and SNRs. It's proximity to the Milky Way makes both HMXBs and SNRs resolvable for study, and its low foreground extinction and close to face-on inclination make it easier to study such objects as populations. Furthermore, it has deep, and wide coverage from Chandra, which affords high spatial resolution, and XMM-Newton, which offers high soft sensitivity, in conjunction with considerable archival Hubble Space Telescope (HST) coverage. In this thesis, I probe the X-ray source population of M33 with a particular emphasis on massive stars and their end products, which are well-characterized using the available multiwavelength coverage. I characterize the large X-ray point source population of M33 from deep XMM-Newton observations, from which I identify a sizable number of new soft sources, and produce a deep X-ray luminosity function indicative of a substantial population of HMXBs. The source population from this catalog forms the backbone for studying M33's massive star population from the X-ray perspective. From this source population, I also identify a large number of SNRs newly detected in X-rays in M33. With this large sample of SNRs I examine the effect of host galaxy properties, such as metallicity and star formation rate, on SNR characteristics and detectability. I further study the massive star population of M33 through identification and characterization of a new sample of candidate HMXBs in M33 found using archival HST and Chandra imaging. I use the HST photometric data to model the color-magnitude diagrams in the vicinity of each candidate HMXB to measure a resolved recent star formation history, and thus a formation time-scale, or age for each source. For a subset of these HMXBs, I present an in-depth source classification on the basis of available X-ray and optical spectra and colors. I discuss these results in the context of massive star, and massive binary evolution and their connection to host galaxy environment as seen through the lens of M33. Studying large samples of massive star end products in a nearby galaxy such as M33 paves the way towards understanding massive star and massive binary evolution, and the implications for formation of compact object binaries and gravitational wave sources.
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.relation.hasparttable4_full.txt; data; Full Table 4.4 from Chapter 4.
dc.relation.hasparttable2_3.txt; data; Full Table 2.3 from Chapter 2.
dc.rightsnone
dc.subjectmassive stars
dc.subjectsupernova remnants
dc.subjectX-ray binaries
dc.subjectAstronomy
dc.subjectAstrophysics
dc.subject.otherAstronomy
dc.titleX-ray Insights into Massive Star Evolution: the X-ray Source Population of M33 as seen by XMM-Newton, Chandra, and the Hubble Space Telescope
dc.typeThesis
dc.embargo.termsOpen Access


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