본문

서브메뉴

Astrophysical Inferences From Multimessenger Ensembles.
Astrophysical Inferences From Multimessenger Ensembles.

상세정보

자료유형  
 학위논문
Control Number  
0017163933
International Standard Book Number  
9798384098560
Dewey Decimal Classification Number  
523
Main Entry-Personal Name  
Criswell, Alexander W.
Publication, Distribution, etc. (Imprint  
[S.l.] : University of Minnesota., 2024
Publication, Distribution, etc. (Imprint  
Ann Arbor : ProQuest Dissertations & Theses, 2024
Physical Description  
218 p.
General Note  
Source: Dissertations Abstracts International, Volume: 86-03, Section: B.
General Note  
Advisor: Mandic, Vuk.
Dissertation Note  
Thesis (Ph.D.)--University of Minnesota, 2024.
Summary, Etc.  
요약Nearly a decade from the first detection of gravitational waves, the field of gravitational-wave astronomy is on the cusp of its population-driven era, wherein observations of a diverse ensemble of gravitational-wave and multimessenger sources promise to yield deep insights into the underlying astrophysical processes behind these dynamic phenomena. However, the very aspect of this population-driven era that gives rise to its incredible potential also carries with it a great challenge: the sheer scale and complexity of upcoming gravitational-wave and multimessenger datasets. Reckoning with this challenge will require a concerted, interdisciplinary effort to develop, implement, and execute new analyses that can realize the potential of these immense datasets. This thesis is an exploration of several such efforts, each establishing novel approaches and insights that have the potential to shape the future of the field. It is composed of three distinct parts. The first considers a novel analysis that seeks to constrain the dense nuclear equation of state through hierarchical Bayesian inference of an ensemble of subthreshold binary neutron star post-merger gravitational wave signals. The second presents detailed estimates of the prospects for multimessenger observations with upcoming space telescopes, and in doing so informs the strategy for electromagnetic follow-up to gravitational-wave events with the UltraViolet EXplorer, a major NASA mission of the 2030's. The final portion of the thesis develops a series of novel analyses for Bayesian inference of astrophysical stochastic gravitational wave backgrounds in the Laser Interferometer Space Antenna (LISA), a spaceborne gravitational-wave observatory launching in 2035. These analyses leverage several such signals' anisotropies to separate the distinct contributions of their component astrophysical source populations. In doing so, this work demonstrates for the first time 1) the existence of a previously unknown stochastic signal in LISA from white dwarf binaries in the Large Magellanic Cloud; 2) a prototype simultaneous inference infrastructure for LISA capable of characterizing isotropic and anisotropic stochastic background signals in the presence of the stochastic foreground contribution from white dwarf binaries in the Milky Way; and 3) the potential of LISA to simultaneously infer the distinct stochastic contributions of the white dwarf binary populations of the Milky Way and Large Magellanic Cloud.
Subject Added Entry-Topical Term  
Astrophysics.
Subject Added Entry-Topical Term  
Nuclear physics.
Subject Added Entry-Topical Term  
Electromagnetics.
Subject Added Entry-Topical Term  
Astronomy.
Subject Added Entry-Topical Term  
Theoretical physics.
Index Term-Uncontrolled  
Binary neutron star mergers
Index Term-Uncontrolled  
Gravitational waves
Index Term-Uncontrolled  
Multimessenger astronomy
Index Term-Uncontrolled  
Laser Interferometer Space Antenna
Index Term-Uncontrolled  
UltraViolet EXplorer
Added Entry-Corporate Name  
University of Minnesota Astrophysics
Host Item Entry  
Dissertations Abstracts International. 86-03B.
Electronic Location and Access  
로그인을 한후 보실 수 있는 자료입니다.
Control Number  
joongbu:656874

MARC

 008250224s2024        us  ||||||||||||||c||eng  d
■001000017163933
■00520250211152811
■006m          o    d                
■007cr#unu||||||||
■020    ▼a9798384098560
■035    ▼a(MiAaPQ)AAI31557914
■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a523
■1001  ▼aCriswell,  Alexander  W.
■24510▼aAstrophysical  Inferences  From  Multimessenger  Ensembles.
■260    ▼a[S.l.]▼bUniversity  of  Minnesota.  ▼c2024
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2024
■300    ▼a218  p.
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-03,  Section:  B.
■500    ▼aAdvisor:  Mandic,  Vuk.
■5021  ▼aThesis  (Ph.D.)--University  of  Minnesota,  2024.
■520    ▼aNearly  a  decade  from  the  first  detection  of  gravitational  waves,  the  field  of  gravitational-wave  astronomy  is  on  the  cusp  of  its  population-driven  era,  wherein  observations  of  a  diverse  ensemble  of  gravitational-wave  and  multimessenger  sources  promise  to  yield  deep  insights  into  the  underlying  astrophysical  processes  behind  these  dynamic  phenomena.  However,  the  very  aspect  of  this  population-driven  era  that  gives  rise  to  its  incredible  potential  also  carries  with  it  a  great  challenge:  the  sheer  scale  and  complexity  of  upcoming  gravitational-wave  and  multimessenger  datasets.  Reckoning  with  this  challenge  will  require  a  concerted,  interdisciplinary  effort  to  develop,  implement,  and  execute  new  analyses  that  can  realize  the  potential  of  these  immense  datasets.  This  thesis  is  an  exploration  of  several  such  efforts,  each  establishing  novel  approaches  and  insights  that  have  the  potential  to  shape  the  future  of  the  field.  It  is  composed  of  three  distinct  parts.  The  first  considers  a  novel  analysis  that  seeks  to  constrain  the  dense  nuclear  equation  of  state  through  hierarchical  Bayesian  inference  of  an  ensemble  of  subthreshold  binary  neutron  star  post-merger  gravitational  wave  signals.  The  second  presents  detailed  estimates  of  the  prospects  for  multimessenger  observations  with  upcoming  space  telescopes,  and  in  doing  so  informs  the  strategy  for  electromagnetic  follow-up  to  gravitational-wave  events  with  the  UltraViolet  EXplorer,  a  major  NASA  mission  of  the  2030's.  The  final  portion  of  the  thesis  develops  a  series  of  novel  analyses  for  Bayesian  inference  of  astrophysical  stochastic  gravitational  wave  backgrounds  in  the  Laser  Interferometer  Space  Antenna  (LISA),  a  spaceborne  gravitational-wave  observatory  launching  in  2035.  These  analyses  leverage  several  such  signals'  anisotropies  to  separate  the  distinct  contributions  of  their  component  astrophysical  source  populations.  In  doing  so,  this  work  demonstrates  for  the  first  time  1)  the  existence  of  a  previously  unknown  stochastic  signal  in  LISA  from  white  dwarf  binaries  in  the  Large  Magellanic  Cloud;  2)  a  prototype  simultaneous  inference  infrastructure  for  LISA  capable  of  characterizing  isotropic  and  anisotropic  stochastic  background  signals  in  the  presence  of  the  stochastic  foreground  contribution  from  white  dwarf  binaries  in  the  Milky  Way;  and  3)  the  potential  of  LISA  to  simultaneously  infer  the  distinct  stochastic  contributions  of  the  white  dwarf  binary  populations  of  the  Milky  Way  and  Large  Magellanic  Cloud.
■590    ▼aSchool  code:  0130.
■650  4▼aAstrophysics.
■650  4▼aNuclear  physics.
■650  4▼aElectromagnetics.
■650  4▼aAstronomy.
■650  4▼aTheoretical  physics.
■653    ▼aBinary  neutron  star  mergers
■653    ▼aGravitational  waves
■653    ▼aMultimessenger  astronomy
■653    ▼aLaser  Interferometer  Space  Antenna
■653    ▼aUltraViolet  EXplorer
■690    ▼a0596
■690    ▼a0753
■690    ▼a0756
■690    ▼a0606
■690    ▼a0607
■71020▼aUniversity  of  Minnesota▼bAstrophysics.
■7730  ▼tDissertations  Abstracts  International▼g86-03B.
■790    ▼a0130
■791    ▼aPh.D.
■792    ▼a2024
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17163933▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

미리보기

내보내기

chatGPT토론

Ai 추천 관련 도서


    New Books MORE
    Related books MORE
    최근 3년간 통계입니다.

    高级搜索信息

    • 预订
    • 캠퍼스간 도서대출
    • 서가에 없는 책 신고
    • 我的文件夹
    材料
    注册编号 呼叫号码. 收藏 状态 借信息.
    TQ0032979 T   원문자료 열람가능/출력가능 열람가능/출력가능
    마이폴더 부재도서신고

    *保留在借用的书可用。预订,请点击预订按钮

    해당 도서를 다른 이용자가 함께 대출한 도서

    Related books

    Related Popular Books

    도서위치