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Early and Late Cosmic Structure Formation
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
키워드  
Gravitational lensing
키워드  
Cosmic structure formation
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
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■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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