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Early and Late Cosmic Structure Formation
Early and Late Cosmic Structure Formation
Detailed Information
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211150911
- ISBN
- 9798382775227
- DDC
- 530
- 저자명
- Liu, Xin.
- 서명/저자
- Early and Late Cosmic Structure Formation
- 발행사항
- [Sl] : The University of Chicago, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 143 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
- 주기사항
- Advisor: Habib, Salman.
- 학위논문주기
- Thesis (Ph.D.)--The University of Chicago, 2024.
- 초록/해제
- 요약In cosmological models of hierarchical structure formation, small primordial density fluctuations grow to eventually collapse under gravity and finally form halos dominated by dark matter. Cosmological simulations play a key role in studying structure formation especially on non-linear scales where analytical predictions are very challenging. This thesis presents three studies which focus on early and late stages of cosmic structure formation.We first use the density power spectrum as a probe to investigate non-collisional numerical discreteness errors in two-species cosmological N-body simulations. When initializing both species with the same total matter transfer function, biased power growth is measured on small scales if the solver force resolution is set to be finer than the mean interparticle separation. Significant large-scale power offsets are found from simulations with conventional offset grid initial conditions when individual transfer functions are applied to each species. These offsets still exist when the two species are designated with the same mass, implying the error does not come from the unequal particle mass but rather the discreteness in the total matter field. Two mitigation strategies are presented to address discreteness errors: the frozen potential method and softened inter-species short-range forces. Both mitigation strategies shows notable improvements in large-scale offsets by approaching the continuum limit.We then turn to dark matter halos in "Last Journey", a gravity-only cosmological simulation, with the aim of resolving questions regarding "too big to fail" substructure in group-scale halos, by studying the properties of fossil groups. Fossil groups are typically distinguished by high X-ray brightness and a large luminosity gap in the group between the brightest and second brightest galaxy. We exploit halo merger tree information to suggest two parameters: a luminous merger mass threshold and a last luminous merger redshift cut-off, in order to identify fossil group candidate halos. Our assumptions give rise to early formation, higher concentrations, and more relaxed fossil group candidates in contrast to other halos within the same mass range.The final project is a study of halo structure and how it can affect observations based on gravitational lensing. Current descriptions of dark matter halos often assume a specific form of the density profile and apply parametric fitting methods. We utilize Gaussian Processes, a non-parametric machine learning method to determine the spatial distribution of matter in halos and obtain a more robust understanding of halo profiles. Stable and smooth descriptions of halos are produced by this procedure which leads to more reliable results. We present a detailed study of halo profile fitting as well as classify halos into various sub-types based on the fitting results. This classification, which considers types of relaxed and unrelaxed halos, is useful to understand selection effects in surveys that use strong gravitational lensing to identify group and cluster scale halos.
- 일반주제명
- Physics
- 일반주제명
- Computational physics
- 일반주제명
- Astrophysics
- 키워드
- Cosmology
- 키워드
- Dark matter
- 키워드
- Halos
- 기타저자
- The University of Chicago Physics
- 기본자료저록
- Dissertations Abstracts International. 85-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
008250123s2024 us c eng d■001000017160115
■00520250211150911
■006m o d
■007cr#unu||||||||
■020 ▼a9798382775227
■035 ▼a(MiAaPQ)AAI30527674
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a530
■1001 ▼aLiu, Xin.
■24510▼aEarly and Late Cosmic Structure Formation
■260 ▼a[Sl]▼bThe University of Chicago▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a143 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-12, Section: B.
■500 ▼aAdvisor: Habib, Salman.
■5021 ▼aThesis (Ph.D.)--The University of Chicago, 2024.
■520 ▼aIn cosmological models of hierarchical structure formation, small primordial density fluctuations grow to eventually collapse under gravity and finally form halos dominated by dark matter. Cosmological simulations play a key role in studying structure formation especially on non-linear scales where analytical predictions are very challenging. This thesis presents three studies which focus on early and late stages of cosmic structure formation.We first use the density power spectrum as a probe to investigate non-collisional numerical discreteness errors in two-species cosmological N-body simulations. When initializing both species with the same total matter transfer function, biased power growth is measured on small scales if the solver force resolution is set to be finer than the mean interparticle separation. Significant large-scale power offsets are found from simulations with conventional offset grid initial conditions when individual transfer functions are applied to each species. These offsets still exist when the two species are designated with the same mass, implying the error does not come from the unequal particle mass but rather the discreteness in the total matter field. Two mitigation strategies are presented to address discreteness errors: the frozen potential method and softened inter-species short-range forces. Both mitigation strategies shows notable improvements in large-scale offsets by approaching the continuum limit.We then turn to dark matter halos in "Last Journey", a gravity-only cosmological simulation, with the aim of resolving questions regarding "too big to fail" substructure in group-scale halos, by studying the properties of fossil groups. Fossil groups are typically distinguished by high X-ray brightness and a large luminosity gap in the group between the brightest and second brightest galaxy. We exploit halo merger tree information to suggest two parameters: a luminous merger mass threshold and a last luminous merger redshift cut-off, in order to identify fossil group candidate halos. Our assumptions give rise to early formation, higher concentrations, and more relaxed fossil group candidates in contrast to other halos within the same mass range.The final project is a study of halo structure and how it can affect observations based on gravitational lensing. Current descriptions of dark matter halos often assume a specific form of the density profile and apply parametric fitting methods. We utilize Gaussian Processes, a non-parametric machine learning method to determine the spatial distribution of matter in halos and obtain a more robust understanding of halo profiles. Stable and smooth descriptions of halos are produced by this procedure which leads to more reliable results. We present a detailed study of halo profile fitting as well as classify halos into various sub-types based on the fitting results. This classification, which considers types of relaxed and unrelaxed halos, is useful to understand selection effects in surveys that use strong gravitational lensing to identify group and cluster scale halos.
■590 ▼aSchool code: 0330.
■650 4▼aPhysics
■650 4▼aComputational physics
■650 4▼aAstrophysics
■653 ▼aCosmology
■653 ▼aDark matter
■653 ▼aHalos
■653 ▼aGravitational lensing
■653 ▼aCosmic structure formation
■690 ▼a0605
■690 ▼a0216
■690 ▼a0596
■71020▼aThe University of Chicago▼bPhysics.
■7730 ▼tDissertations Abstracts International▼g85-12B.
■790 ▼a0330
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17160115▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
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