Bayesian Analysis of Instrument Noise and Gravitational Wave Signals

仪器噪声和引力波信号的贝叶斯分析

• 批准号: 1912053
• 负责人: Neil Cornish
• 金额: $ 30万
• 依托单位: Montana State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-08-15 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1912053&HistoricalAwards=false
• 关键词: Bayesian; Analysis; Instrument; Noise; Gravitational

This award supports research in gravitational wave detector and data analysis, and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. The discovery of gravitational waves from multiple black hole mergers and the spectacular joint observation of electromagnetic and gravitational wave signals from a neutron star merger have firmly established gravitational wave astronomy as an important new field. The goal of this project is to improve on our capability to detect and characterize gravitational signals of all kinds, including those from unexpected and hitherto un-modeled sources. This will be done by improving the signal-agnostic waveform reconstruction techniques developed under predecessor awards, and by developing new techniques to model and mitigate the effects of non-stationary and non-Gaussian instrument noise.Gravitational wave astronomy is producing revolutionary discoveries that are yielding unique insights into some of the Universe's most exotic phenomena. These discoveries have generated tremendous interest from the public, astronomers and physicists in other fields, and with students of all ages. The research projects supported by this award offer tremendous opportunities for graduate and undergraduate students; the blend of creative activities associated with the development of sophisticated and innovative data analysis techniques, combined with hands on exposure in applying these techniques to complex data sets, will provide excellent training for the next generation of scientists. These skills are transferable and highly sought after in other fields.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.

该奖项支持引力波探测器和数据分析的研究，并解决了NSF“宇宙之窗”大创意的优先领域。多个黑洞合并产生的引力波的发现和中子星星合并产生的电磁波和引力波信号的壮观联合观测，坚定地确立了引力波天文学作为一个重要的新领域的地位。该项目的目标是提高我们探测和表征各种引力信号的能力，包括那些来自意想不到和迄今未建模来源的信号。这将通过改进在先前奖项下开发的信号不可知波形重建技术，以及开发新技术来建模和减轻非平稳和非高斯仪器噪声的影响来实现。引力波天文学正在产生革命性的发现，这些发现正在产生对宇宙中一些最奇特现象的独特见解。这些发现引起了公众、其他领域的天文学家和物理学家以及各个年龄段的学生的极大兴趣。该奖项支持的研究项目为研究生和本科生提供了巨大的机会;与复杂和创新的数据分析技术的开发相关的创造性活动的融合，结合将这些技术应用于复杂数据集的实践，将为下一代科学家提供出色的培训。该奖项反映了NSF的法定使命，并通过使用基金会的知识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

Comparison of maximum-likelihood mapping methods for gravitational-wave backgrounds

引力波背景最大似然映射方法的比较

• DOI: 10.1103/physrevd.105.023519
• 发表时间: 2022
• 期刊: Physical Review D
• 影响因子: 5
• 作者: Renzini, Arianna I.;Romano, Joseph D.;Contaldi, Carlo R.;Cornish, Neil J.
• 通讯作者: Cornish, Neil J.

Modeling compact binary signals and instrumental glitches in gravitational wave data

对引力波数据中的紧凑二进制信号和仪器故障进行建模

• DOI: 10.1103/physrevd.103.044013
• 发表时间: 2021
• 期刊: Physical Review D
• 影响因子: 5
• 作者: Chatziioannou, Katerina;Cornish, Neil;Wijngaarden, Marcella;Littenberg, Tyson B.
• 通讯作者: Littenberg, Tyson B.

Noise spectral estimation methods and their impact on gravitational wave measurement of compact binary mergers

• DOI: 10.1103/physrevd.100.104004
• 发表时间: 2019-07
• 期刊: Physical Review D
• 影响因子: 5
• 作者: K. Chatziioannou;C. Haster;T. Littenberg;W. Farr;S. Ghonge;M. Millhouse;J. Clark;N. Cornish

Rapid and robust parameter inference for binary mergers

• DOI: 10.1103/physrevd.103.104057
• 发表时间: 2021-01
• 作者: N. Cornish

Accurate modeling and mitigation of overlapping signals and glitches in gravitational-wave data

• DOI: 10.1103/physrevd.106.042006
• 发表时间: 2022-05
• 期刊: Physical Review D
• 影响因子: 5
• 作者: S. Hourihane;K. Chatziioannou;M. Wijngaarden;D. Davis;T. Littenberg;N. Cornish