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Planets and Their Hidden Companions: Expanding Detection Methods With Machine Learning
Planets and Their Hidden Companions: Expanding Detection Methods With Machine Learning
Planets and Their Hidden Companions: Expanding Detection Methods With Machine Learning

상세정보

자료유형  
 학위논문 서양
최종처리일시  
20260202103632
ISBN  
9798315791867
DDC  
523
저자명  
Angelo, Isabel Nora.
서명/저자  
Planets and Their Hidden Companions: Expanding Detection Methods With Machine Learning
발행사항  
[Sl] : University of California, Los Angeles, 2025
발행사항  
Ann Arbor : ProQuest Dissertations & Theses, 2025
형태사항  
193 p
주기사항  
Source: Dissertations Abstracts International, Volume: 86-12, Section: B.
주기사항  
Advisor: Petigura, Erik A.
학위논문주기  
Thesis (Ph.D.)--University of California, Los Angeles, 2025.
초록/해제  
요약In this thesis, I expand on existing methodologies for identifying distant planetary and stellar companions to known planet hosts. First, I outline my discovery of a distant planetary companion to Kepler-1656b, a highly eccentric sub-Saturn. To make this discovery, I used a combination of traditional radial velocity detection methods and dynamical modeling of the system to resolve the properties of an outer planetary companion. In doing so, I characterized the dynamical environment of the Kepler-1656 system and found that, surprisingly, the outer planet is exciting the inner planet eccentricity in situ, i.e. without inducing inward migration of the inner planet. I also identified signatures of similar companions, which I call "gentle giants", in the broader sub-Saturn and giant planet populations.The second portion of my thesis explores more experimental methods of detecting stellar companions to known planet hosts using data-driven spectroscopy. Recent advances in data-driven spectroscopy have enabled more modeling of stellar spectra, which may in turn allow us to detect signatures of stellar companions to planet hosts that are missed by more traditional binary detection methods. I trained data-driven models on spectra from the Gaia mission and Keck-I telescope, and in doing so, developed a novel wavelet-based method for removing non-astrophysical contamination in stellar spectra. I found that while our models are excellent at label transfer- a standard application of data-driven spectroscopy- they are limited in their ability to accurately model stellar spectra and identify hidden stellar companions. I also comment on the state of the field of data-driven spectroscopy and outline possible paths towards more accurate spectroscopic models and surveys for planet-hosting binaries.
일반주제명  
Astrophysics
일반주제명  
Astronomy
일반주제명  
Planetology
일반주제명  
Analytical chemistry
키워드  
Planet hosts
키워드  
Planetary companion
키워드  
Kepler-1656 system
키워드  
Gaia mission
키워드  
Planet-hosting binaries
기타저자  
University of California, Los Angeles Astronomy and Astrophysics 00EB
기본자료저록  
Dissertations Abstracts International. 86-12B.
전자적 위치 및 접속  
로그인 후 원문을 볼 수 있습니다.

MARC

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■020    ▼a9798315791867
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■040    ▼aMiAaPQ▼cMiAaPQ
■0820  ▼a523
■1001  ▼aAngelo,  Isabel  Nora.
■24510▼aPlanets  and  Their  Hidden  Companions:  Expanding  Detection  Methods  With  Machine  Learning
■260    ▼a[Sl]▼bUniversity  of  California,  Los  Angeles▼c2025
■260  1▼aAnn  Arbor▼bProQuest  Dissertations  &  Theses▼c2025
■300    ▼a193  p
■500    ▼aSource:  Dissertations  Abstracts  International,  Volume:  86-12,  Section:  B.
■500    ▼aAdvisor:  Petigura,  Erik  A.
■5021  ▼aThesis  (Ph.D.)--University  of  California,  Los  Angeles,  2025.
■520    ▼aIn  this  thesis,  I  expand  on  existing  methodologies  for  identifying  distant  planetary  and  stellar  companions  to  known  planet  hosts.  First,  I  outline  my  discovery  of  a  distant  planetary  companion  to  Kepler-1656b,  a  highly  eccentric  sub-Saturn.  To  make  this  discovery,  I  used  a  combination  of  traditional  radial  velocity  detection  methods  and  dynamical  modeling  of  the  system  to  resolve  the  properties  of  an  outer  planetary  companion.  In  doing  so,  I  characterized  the  dynamical  environment  of  the  Kepler-1656  system  and  found  that,  surprisingly,  the  outer  planet  is  exciting  the  inner  planet  eccentricity  in  situ,  i.e.  without  inducing  inward  migration  of  the  inner  planet.  I  also  identified  signatures  of  similar  companions,  which  I  call  "gentle  giants",  in  the  broader  sub-Saturn  and  giant  planet  populations.The  second  portion  of  my  thesis  explores  more  experimental  methods  of  detecting  stellar  companions  to  known  planet  hosts  using  data-driven  spectroscopy.  Recent  advances  in  data-driven  spectroscopy  have  enabled  more  modeling  of  stellar  spectra,  which  may  in  turn  allow  us  to  detect  signatures  of  stellar  companions  to  planet  hosts  that  are  missed  by  more  traditional  binary  detection  methods.  I  trained  data-driven  models  on  spectra  from  the  Gaia  mission  and  Keck-I  telescope,  and  in  doing  so,  developed  a  novel  wavelet-based  method  for  removing  non-astrophysical  contamination  in  stellar  spectra.  I  found  that  while  our  models are  excellent  at  label  transfer-  a  standard  application  of  data-driven  spectroscopy-  they  are  limited  in  their  ability  to  accurately  model  stellar  spectra  and  identify  hidden  stellar  companions.  I  also  comment  on  the  state  of  the  field  of  data-driven  spectroscopy  and  outline  possible  paths  towards  more  accurate  spectroscopic  models  and  surveys  for  planet-hosting  binaries.
■590    ▼aSchool  code:  0031.
■650  4▼aAstrophysics
■650  4▼aAstronomy
■650  4▼aPlanetology
■650  4▼aAnalytical  chemistry
■653    ▼aPlanet  hosts
■653    ▼aPlanetary  companion
■653    ▼aKepler-1656  system
■653    ▼aGaia  mission
■653    ▼aPlanet-hosting  binaries
■690    ▼a0596
■690    ▼a0606
■690    ▼a0486
■690    ▼a0590
■71020▼aUniversity  of  California,  Los  Angeles▼bAstronomy  and  Astrophysics  00EB.
■7730  ▼tDissertations  Abstracts  International▼g86-12B.
■790    ▼a0031
■791    ▼aPh.D.
■792    ▼a2025
■793    ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17358025▼nKERIS▼z이  자료의  원문은  한국교육학술정보원에서  제공합니다.

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