Citation
Lippuner, Jonas (2018) r-Process Nucleosynthesis in Neutron Star Mergers with the New Nuclear Reaction Network SkyNet. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/Z9V40SCS. https://resolver.caltech.edu/CaltechTHESIS:06072017-212011532
Abstract
At the Big Bang, only the lightest elements, mainly hydrogen and helium, were produced. Stars synthesize heavier elements, such as helium, carbon, and oxygen, from lighter ones through nuclear fusion. Iron-group elements are created in supernovae (both type Ia and core-collapse). It has been known for 60 years that the slow and rapid neutron capture processes (s- and r-process) are each responsible for creating about half of the elements beyond the iron group. The s-process is known to occur in asymptotic giant branch stars, but the astrophysical site of the r-process is still a mystery. Based on observations of heavy elements in old stars, it was theorized that r-process nucleosynthesis takes place in core-collapse supernovae (CCSNe). However, recent CCSN simulations indicate that the conditions required for the r-process are not obtained in CCSN. The focus has thus shifted to neutron star mergers (both binary neutron star and black hole-neutron star mergers), where the r-process easily synthesizes all the known heavy elements. Neutron star mergers are expected to be detected by the Laser Interferometer Gravitational Wave Observatory (LIGO) in the near future, which should either confirm or rule out their proposed association with radioactively powered transients called kilonovae or macronovae that are the observational signatures of r-process nucleosynthesis. To understand how the r-process operates in different astrophysical scenarios and what relative abundance patterns it produces, detailed nuclear reaction network calculations are needed that track thousands of isotopes and tens of thousands of nuclear reactions. In this thesis, I present SkyNet, a new general-purpose nuclear reaction network that can evolve an arbitrary list of nuclear species with an arbitrary set of nuclear reactions. I describe in detail the different physics that is implemented in SkyNet and I perform code tests and comparisons to other nuclear reaction networks. Then I use SkyNet to systematically investigate r-process nucleosynthesis as a function of the initial electron fraction, initial entropy, and expansion timescale of the fluid. Further, I present r-process nucleosynthesis calculations with SkyNet in the dynamical ejecta of a black hole–neutron star merger with varying levels of neutrino irradiation. Finally, I study the r-process in the outflow of a neutron star merger remnant disk as a function of the lifetime of the central hypermassive neutron star (HMNS). SkyNet is easy to use and flexible and it is publicly available as open-source software. Multiple researchers are already using SkyNet for their work, and I hope that SkyNet will be a useful tool for the broader nuclear astrophysics community.
Item Type: | Thesis (Dissertation (Ph.D.)) | ||||||||||||||
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Subject Keywords: | nucleosynthesis; nuclear reaction network | ||||||||||||||
Degree Grantor: | California Institute of Technology | ||||||||||||||
Division: | Physics, Mathematics and Astronomy | ||||||||||||||
Major Option: | Physics | ||||||||||||||
Thesis Availability: | Public (worldwide access) | ||||||||||||||
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Group: | TAPIR | ||||||||||||||
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Defense Date: | 22 June 2017 | ||||||||||||||
Non-Caltech Author Email: | jonas (AT) lippuner.ca | ||||||||||||||
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Record Number: | CaltechTHESIS:06072017-212011532 | ||||||||||||||
Persistent URL: | https://resolver.caltech.edu/CaltechTHESIS:06072017-212011532 | ||||||||||||||
DOI: | 10.7907/Z9V40SCS | ||||||||||||||
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Default Usage Policy: | No commercial reproduction, distribution, display or performance rights in this work are provided. | ||||||||||||||
ID Code: | 10312 | ||||||||||||||
Collection: | CaltechTHESIS | ||||||||||||||
Deposited By: | Jonas Lippuner | ||||||||||||||
Deposited On: | 13 Jul 2017 15:44 | ||||||||||||||
Last Modified: | 04 Oct 2019 00:16 |
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