Collaborative Research: Optimized frequency-domain analysis for astronomical time series

合作研究:天文时间序列的优化频域分析

基本信息

  • 批准号:
    2307978
  • 负责人:
  • 金额:
    $ 58.74万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2023
  • 资助国家:
    美国
  • 起止时间:
    2023-08-15 至 2026-07-31
  • 项目状态:
    未结题

项目摘要

Earth-like planet searches are underway which can measure the motion of small planets around distant stars. However, investments in these instruments will not meet their full potential without advances in computer software. Through a three year award, a team led by the Universities of Delaware and Chicago will adapt a time domain data analysis tool previously used for health science and solar science for astronomy. Developing new analysis methods will save telescope time that costs tens of thousands of dollars per night by reducing the number of observations needed and increasing telescope efficiency. Students will be involved in the planet searches. The Team's goals are to involve physics and astronomy majors with all levels of academic preparation in planet searches and to create a supportive environment in which students can seek help from a faculty, scholars, and each other. While the Lomb-Scargle periodogram is foundational to astronomy, it has a significant short-coming: its variance does not decrease as more data are acquired. Statisticians have a 60-year history of developing variance-suppressing power spectrum estimators, but most are not used in astronomy because they are formulated for time series with uniform observing cadence and without seasonal or daily gaps. The team will mitigate the false-positive and bias problems of the Lomb-Scargle periodogram by adapting the multitaper power spectrum estimator for ground-based astronomical time series. They will present multitaper Magnitude-Squared Coherence (MSC) as a diagnostic of oscillations that manifest jointly in two or more observables. MSC between activity indicators and radial velocity is a powerful tool for identifying stellar rotation and harmonics, which have been responsible for many false positive planet detections. They will introduce a non-multitaper version of complex demodulation for ground-based time series. Complex demodulation, a local Fourier decomposition that reconstructs the long-period component of two coupled oscillations, can distinguish activity-modulated stellar signals from non-modulated planetary signals and recover full-phase rotation signals from observations of pulsating stars. This award funds development of the Oscillation Recognition and CAtegorization Software (ORCAS) package, which will contain python and Julia implementations of our frequency-domain methods. ORCAS will be sustainably hosted on bitbucket and registered with the Astrophysical Source Code Library. The methods developed can be applied to planet hunting, seismology, paleoclimatology, genetics, laser Doppler velocimetry, and the Rubin Observatory Legacy Survey of Space and Time.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
类似地球的行星搜索正在进行中,可以测量遥远恒星周围的小行星的运动。然而,如果计算机软件不取得进展,对这些工具的投资就无法充分发挥其潜力。通过为期三年的奖励,由特拉华州和芝加哥大学领导的一个团队将采用以前用于健康科学和天文学太阳科学的时域数据分析工具。开发新的分析方法将通过减少所需的观测次数和提高望远镜效率来节省望远镜的时间,这些时间每晚花费数万美元。学生将参与行星搜索。该团队的目标是让物理学和天文学专业的学生参与行星搜索的所有学术准备水平,并创造一个支持性的环境,让学生可以向教师,学者和彼此寻求帮助。虽然Lomb-Scargle周期图是天文学的基础,但它有一个显著的缺点:它的方差不会随着获得更多数据而减少。统计学家在开发方差抑制功率谱估计器方面有60年的历史,但大多数都没有用于天文学,因为它们是为具有统一观测节奏的时间序列制定的,没有季节或每日间隙。该小组将通过调整地面天文时间序列的多锥度功率谱估计器来减轻Lomb-Scargle周期图的假阳性和偏差问题。他们将提出多锥幅度平方相干(MSC)作为两个或多个观测量联合表现的振荡的诊断。活动指标和径向速度之间的MSC是一个强大的工具,用于识别恒星旋转和谐波,这是许多假阳性行星探测的原因。他们将介绍一种用于地面时间序列的非多锥度复解调法。复解调是一种局部傅里叶分解,它重建了两个耦合振荡的长周期分量,可以区分活动调制的恒星信号和非调制的行星信号,并从脉动恒星的观测中恢复全相位旋转信号。该奖项资助了振荡识别和分类软件(ORCAS)包的开发,该软件包将包含我们频域方法的python和Julia实现。ORCAS将可持续地托管在bitbucket上,并在天体物理源代码库中注册。所开发的方法可应用于行星搜寻、地震学、古气候学、遗传学、激光多普勒测速和鲁宾天文台时空遗产调查。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。

项目成果

期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

数据更新时间:{{ journalArticles.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ monograph.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ sciAawards.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ conferencePapers.updateTime }}

{{ item.title }}
  • 作者:
    {{ item.author }}

数据更新时间:{{ patent.updateTime }}

Sarah Dodson-Robinson其他文献

Sarah Dodson-Robinson的其他文献

{{ item.title }}
{{ item.translation_title }}
  • DOI:
    {{ item.doi }}
  • 发表时间:
    {{ item.publish_year }}
  • 期刊:
  • 影响因子:
    {{ item.factor }}
  • 作者:
    {{ item.authors }}
  • 通讯作者:
    {{ item.author }}

{{ truncateString('Sarah Dodson-Robinson', 18)}}的其他基金

CAREER: Giant Planets in Dusty Disks
职业:尘埃盘中的巨行星
  • 批准号:
    1520101
  • 财政年份:
    2014
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Continuing Grant
CAREER: Giant Planets in Dusty Disks
职业:尘埃盘中的巨行星
  • 批准号:
    1055910
  • 财政年份:
    2011
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Continuing Grant

相似国自然基金

Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 批准年份:
    2024
  • 资助金额:
    0.0 万元
  • 项目类别:
    省市级项目
Cell Research
  • 批准号:
    31224802
  • 批准年份:
    2012
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research
  • 批准号:
    31024804
  • 批准年份:
    2010
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Cell Research (细胞研究)
  • 批准号:
    30824808
  • 批准年份:
    2008
  • 资助金额:
    24.0 万元
  • 项目类别:
    专项基金项目
Research on the Rapid Growth Mechanism of KDP Crystal
  • 批准号:
    10774081
  • 批准年份:
    2007
  • 资助金额:
    45.0 万元
  • 项目类别:
    面上项目

相似海外基金

Collaborative Research: Optimized frequency-domain analysis for astronomical time series
合作研究:天文时间序列的优化频域分析
  • 批准号:
    2307979
  • 财政年份:
    2023
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Standard Grant
Collaborative Research: MoDL: Graph-Optimized Cellular Connectionism via Artificial Neural Networks for Data-Driven Modeling and Optimization of Complex Systems
合作研究:MoDL:通过人工神经网络进行图优化的细胞连接,用于复杂系统的数据驱动建模和优化
  • 批准号:
    2234032
  • 财政年份:
    2023
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Standard Grant
Collaborative Research: MoDL: Graph-Optimized Cellular Connectionism via Artificial Neural Networks for Data-Driven Modeling and Optimization of Complex Systems
合作研究:MoDL:通过人工神经网络进行图优化的细胞连接,用于复杂系统的数据驱动建模和优化
  • 批准号:
    2234031
  • 财政年份:
    2023
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Standard Grant
Collaborative Research: CNS Core: Medium: Rethinking Multi-User VR - Jointly Optimized Representation, Caching and Transport
合作研究:CNS 核心:媒介:重新思考多用户 VR - 联合优化表示、缓存和传输
  • 批准号:
    2212200
  • 财政年份:
    2022
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Continuing Grant
Collaborative Research: CNS Core: Medium: Rethinking Multi-User VR - Jointly Optimized Representation, Caching and Transport
合作研究:CNS 核心:媒介:重新思考多用户 VR - 联合优化表示、缓存和传输
  • 批准号:
    2212201
  • 财政年份:
    2022
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Continuing Grant
Collaborative Research: CNS Core: Medium: Rethinking Multi-User VR - Jointly Optimized Representation, Caching and Transport
合作研究:CNS 核心:媒介:重新思考多用户 VR - 联合优化表示、缓存和传输
  • 批准号:
    2212202
  • 财政年份:
    2022
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Continuing Grant
Collaborative Research: Optimized Testing Strategies for Fighting Pandemics: Fundamental Limits and Efficient Algorithms
合作研究:抗击流行病的优化测试策略:基本限制和高效算法
  • 批准号:
    2133170
  • 财政年份:
    2022
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Standard Grant
Collaborative Research: Optimized Testing Strategies for Fighting Pandemics: Fundamental Limits and Efficient Algorithms
合作研究:抗击流行病的优化测试策略:基本限制和高效算法
  • 批准号:
    2133205
  • 财政年份:
    2022
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Standard Grant
Collaborative Research: CIF: Medium: QODED: Quantum codes Optimized for the Dynamics between Encoded Computation and Decoding using Classical Coding Techniques
协作研究:CIF:中:QODED:针对使用经典编码技术的编码计算和解码之间的动态进行优化的量子代码
  • 批准号:
    2106213
  • 财政年份:
    2021
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Continuing Grant
RUI: Collaborative Research: Optimized design principles inspired by compliant natural propulsors
RUI:协作研究:受顺应自然推进器启发的优化设计原则
  • 批准号:
    2100209
  • 财政年份:
    2021
  • 资助金额:
    $ 58.74万
  • 项目类别:
    Standard Grant
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了