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On the Statistics of the Universe: An Effective Field Theory Approach to Large Scale Structures
On the Statistics of the Universe: An Effective Field Theory Approach to Large Scale Structures
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20260202105612
- ISBN
- 9798265427083
- DDC
- 523.80223
- 저자명
- Zheng, Henry.
- 서명/저자
- On the Statistics of the Universe: An Effective Field Theory Approach to Large Scale Structures
- 발행사항
- [Sl] : Stanford University, 2025
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2025
- 형태사항
- 291 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 87-05, Section: B.
- 주기사항
- Advisor: Senatore, Leonardo;Silverstein, Eva.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2025.
- 초록/해제
- 요약The cosmic microwave background (CMB) has been exhaustively measured and analyzed, solidify- ing its role in shaping our understanding of the early universe. As a result, large-scale structure (LSS) now stands as the leading frontier for extracting new, high-precision cosmological information. The Effective Field Theory of Large-Scale Structure (EFTofLSS), after many stages of theoretical development, is now poised for application to observational data. In this work, we compute next- to-leading order (NLO) corrections to both the power spectrum and bispectrum of biased tracers within the EFTofLSS framework. We further introduce a fast and accurate algorithm for evaluating these corrections to sub-percent precision in a cosmology-independent manner, significantly reduc- ing computational cost during inference. We demonstrate how the one-loop bispectrum predictions tighten constraints on early universe physics and enhance the sensitivity of upcoming galaxy surveys. In addition, we highlight the role of NLO corrections in enhancing the robustness of neutrino mass measurements under various beyond the standard model [lambda]-CDM extensions. Lastly, we introduce a new optimization algorithm, ECD q = 1, adapted from a similar algorithm used in Bayesian inference, the MicroCanonical Hamiltonian Monte Carlo (MCHMC) algorithm.
- 일반주제명
- Stars & galaxies
- 일반주제명
- Neutrinos
- 일반주제명
- Injection molding
- 일반주제명
- Integrals
- 일반주제명
- Astronomy
- 일반주제명
- Astrophysics
- 일반주제명
- Atomic physics
- 일반주제명
- Industrial engineering
- 일반주제명
- Materials science
- 일반주제명
- Mathematics
- 일반주제명
- Particle physics
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 87-05B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798265427083
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■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a523.80223
■1001 ▼aZheng, Henry.
■24510▼aOn the Statistics of the Universe: An Effective Field Theory Approach to Large Scale Structures
■260 ▼a[Sl]▼bStanford University▼c2025
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2025
■300 ▼a291 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 87-05, Section: B.
■500 ▼aAdvisor: Senatore, Leonardo;Silverstein, Eva.
■5021 ▼aThesis (Ph.D.)--Stanford University, 2025.
■520 ▼aThe cosmic microwave background (CMB) has been exhaustively measured and analyzed, solidify- ing its role in shaping our understanding of the early universe. As a result, large-scale structure (LSS) now stands as the leading frontier for extracting new, high-precision cosmological information. The Effective Field Theory of Large-Scale Structure (EFTofLSS), after many stages of theoretical development, is now poised for application to observational data. In this work, we compute next- to-leading order (NLO) corrections to both the power spectrum and bispectrum of biased tracers within the EFTofLSS framework. We further introduce a fast and accurate algorithm for evaluating these corrections to sub-percent precision in a cosmology-independent manner, significantly reduc- ing computational cost during inference. We demonstrate how the one-loop bispectrum predictions tighten constraints on early universe physics and enhance the sensitivity of upcoming galaxy surveys. In addition, we highlight the role of NLO corrections in enhancing the robustness of neutrino mass measurements under various beyond the standard model [lambda]-CDM extensions. Lastly, we introduce a new optimization algorithm, ECD q = 1, adapted from a similar algorithm used in Bayesian inference, the MicroCanonical Hamiltonian Monte Carlo (MCHMC) algorithm.
■590 ▼aSchool code: 0212.
■650 4▼aStars & galaxies
■650 4▼aNeutrinos
■650 4▼aInjection molding
■650 4▼aIntegrals
■650 4▼aAstronomy
■650 4▼aAstrophysics
■650 4▼aAtomic physics
■650 4▼aIndustrial engineering
■650 4▼aMaterials science
■650 4▼aMathematics
■650 4▼aParticle physics
■690 ▼a0606
■690 ▼a0596
■690 ▼a0748
■690 ▼a0546
■690 ▼a0794
■690 ▼a0405
■690 ▼a0798
■71020▼aStanford University.
■7730 ▼tDissertations Abstracts International▼g87-05B.
■790 ▼a0212
■791 ▼aPh.D.
■792 ▼a2025
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17360735▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
