RUI: Expanding our View of the Gravitational-Wave Sky with Machine Learning and Numerical Relativity

RUI：通过机器学习和数值相对论扩展我们对引力波天空的看法

• 批准号: 2011975
• 负责人: Marissa Walker
• 金额: $ 14.99万
• 依托单位: Christopher Newport University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2023-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2011975&HistoricalAwards=false
• 关键词: RUI; Expanding; our; View; Gravitational

This award supports research in relativity and relativistic astrophysics and it addresses the priority areas of NSF's "Windows on the Universe" Big Idea. A century after Einstein predicted the existence of gravitational waves, the two Laser Interferometer Gravitational-wave Observatory (LIGO) detectors opened a new window on the universe by discovering gravitational waves passing through Earth, emanating from cataclysmic, distant events: colliding black holes and neutron stars. The phenomenal precision that LIGO needs to clearly observe these faint waves requires exquisitely isolated detectors. Capturing the physics of colliding black holes and neutron stars requires accurate waveform models. This award will establish a new research group at Christopher Newport University (CNU) to address both of these challenges, through characterizing LIGO detectors to better understand the origins of problematic noise in the detectors, and by improving the waveform models used to interpret the astrophysics of observed signals. Through these projects, the CNU group will play a crucial role in improving the quality of the LIGO detector data and the accuracy of the parameter estimation information that is shared with the astronomical community and the public. The students supported by this award will be trained in computer programming, data analysis, and machine learning. These important transferable skills will prepare the students for a wide range of successful and meaningful STEM careers in academia and industry. LIGO’s sensitivity to gravitational waves is limited by non-stationary noise, which fluctuates over time depending on various environmental influences. This work will extend a method developed by the PI with collaborators to correlate these variations in sensitivity with auxiliary instrumental sensors to determine the most possible causes, using lasso linear regression. This method has already been useful for identifying noise sources that change over the course of hours, but this work will target problematic persistent noise transients, which impede gravitational wave searches and have rates varying over the course of days and weeks. The PI and students will also contribute to data quality validation of gravitational wave candidate events, to ensure that the broader astronomical community has access to necessary data quality information. The expected improvements to LIGO in the coming years will enable the observation of many more black holes, doubtless some with interestingly different properties and some potentially having much higher signal-to-noise ratios. Accurately extracting the astrophysical parameters of these signals requires comparing to template waveforms that span the potential discovery space. The PI and her students will work on surrogate modeling (a way to efficiently interpolate between expensive but accurate numerical relativity waveforms), working with members of the Simulating eXtreme Spacetimes collaboration. This work will enhance our ability to interpret black hole observations, especially those with large spins.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.

该奖项支持相对论和相对论天体物理学的研究，并介绍了NSF“宇宙上的Windows”的优先领域。爱因斯坦（Einstein）预测引力波的存在一个世纪后，两个激光干涉仪引力波观测站（LIGO）探测器通过发现通过地球的引力波从灾难性的，遥远的事件中散发出来，从而打开了宇宙上的新窗口：碰撞黑洞和中子星星。 Ligo需要清楚地观察到这些微弱的波需要的现象精度需要完全孤立的检测器。捕获碰撞黑洞和中子星的物理学需要准确的波形模型。该奖项将在克里斯托弗·纽波特大学（CNU）建立一个新的研究小组，通过表征Ligo探测器来更好地了解检测器中问题噪声的起源，并通过改善用于解释观察到的信号的天体物理学的波形模型，以解决这两个挑战。通过这些项目，CNU集团将在提高LiGo探测器数据的质量以及与天文学界和公众共享的参数估计信息的准确性方面发挥关键作用。获得该奖项的学生将接受计算机编程，数据分析和机器学习的培训。这些重要的转移技能将使学生在学术界和行业中获得广泛而有意义的STEM职业。 Ligo对重力波的敏感性受到非平稳噪声的限制，非平稳噪声会随着时间的流逝而波动，具体取决于各种环境影响。这项工作将扩展PI与合作者开发的一种方法，以使用套索线性回归来确定这些变化的敏感性变化，以确定最大的原因。方法已经对确定在数小时的变化的噪声源很有用，但是这项工作将针对有问题的持续噪声瞬变，这会阻碍引力波搜索并在几天和几周的过程中速度变化。 PI和学生还将为引力候选事件的数据质量验证做出贡献，以确保更广泛的天文社区可以访问必要的数据质量信息。未来几年对Ligo的预期改善将使更多的黑洞观察到，怀疑一些有趣的特性，有些具有更高的信噪比。准确提取这些信号的天体物理参数需要与跨越潜在发现空间的模板波形进行比较。 PI和她的学生将与昂贵但准确的数值相对性波形之间有效插入替代建模（一种有效插值的方法），并与模拟极限合作的成员一起工作。这项工作将增强我们解释黑洞观察的能力，尤其是那些旋转大型的观测。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，被视为通过评估而被视为珍贵的支持。

项目成果

LIGO detector characterization in the second and third observing runs

• DOI: 10.1088/1361-6382/abfd85
• 发表时间: 2021-01
• 期刊: Classical and Quantum Gravity
• 影响因子: 3.5
• 作者: D. Davis;J. Areeda;B. Berger;R. Bruntz;A. Effler;R. Essick;R. Fisher;P. Godwin;E. Goetz;A. Helmling-Cornell;B. Hughey;E. Katsavounidis;A. Lundgren;D. Macleod;Z. Márka;T. Massinger;A. Matas;J. McIver;G. Mo;K. Mogushi;P. Nguyen;L. Nuttall;R. Schofield;D. Shoemaker;S. Soni;A. Stuver;A. Urban;G. Valdes;M. Walker;R. Abbott;C. Adams;R. Adhikari;A. Ananyeva;S. Appert;K. Arai;Y. Asali;S. Aston;C. Austin;A. Baer;M. Ball;S. Ballmer;S. Banagiri;D. Barker;C. Barschaw;L. Barsotti;J. Bartlett;J. Betzwieser;R. Beda;D. Bhattacharjee;J. Bidler;G. Billingsley;S. Biscans;C. Blair;R. Blair;N. Bode;P. Booker;R. Bork;A. Bramley;A. Brooks;D. Brown;A. Buikema;C. Cahillane;T. Callister;G. Caneva Santoro;K. Cannon;J. Carlin;K. Chandra;X. Chen;N. Christensen;A. Ciobanu;F. Clara;C. Compton;S. Cooper;K. Corley;M. Coughlin;S. Countryman;P. Covas;D. Coyne;S. Crowder;T. Dal Canton;B. Danila;L. Datrier;G. Davies;T. Dent;N. Didio;C. Di Fronzo;K. Dooley;J. Driggers;P. Dupej;S. Dwyer;T. Etzel;M. Evans;T. Evans;S. Fairhurst;J. Feicht;Á. Fernández-Galiana;R. Frey;P. Fritschel;V. Frolov;P. Fulda;M. Fyffe;B. Gadre;J. Giaime;K. Giardina;G. González;S. Gras;C. Gray;R. Gray;A. Green;A. Gupta;E. Gustafson;R. Gustafson;J. Hanks;J. Hanson;T. Hardwick;I. Harry;R. Hasskew;M. Heintze;J. Heinzel;N. Holland;I. J. Hollows;C. Hoy;S. Hughey;S. Jadhav;K. Janssens;G. Johns;J. Jones;S. Kandhasamy;S. Karki;M. Kasprzack;K. Kawabe;D. Keitel;N. Kijbunchoo;Y. M. Kim;P. King;J. Kissel;S. Kulkarni;Rahul Kumar;M. Landry;B. Lane;B. Lantz;M. Laxen;Y. Lecoeuche;J. Leviton;J. Liu;M. Lormand;R. Macas;A. Macedo;M. Macinnis;V. Mandic;G. Mansell;S. Márka;B. Martinez;K. Martinovic;D. Martynov;K. Mason;F. Matichard;N. Mavalvala;R McCarthy-;D. McClelland;S. Mccormick;L. McCuller;C. McIsaac;T. McRae;G. Mendell;K. Merfeld;E. Merilh;P. Meyers;F. Meylahn;I. Michaloliakos;H. Middleton;J. Mills;T. Mistry;R. Mittleman;G. Moreno;C. Mow-Lowry;S. Mozzon;L. Mueller;N. Mukund;A. Mullavey;J. Muth;T. Nelson;A. Neunzert;S. Nichols;E. Nitoglia;J. Oberling;J. Oh;S. Oh;R. Oram;R. Ormiston;N. Ormsby;C. Osthelder;D. Ottaway;H. Overmier;A. Pai;J. R. Palamos;F. Pannarale;W. Parker;O. Patane;M. Patel;E. Payne;A. Pele;R. Penhorwood;C. Perez;K. S. Phukon;M. Pillas;M. Pirello;H. Radkins;K. Ramirez;J. Richardson;K. Riles;K. Rink;N. Robertson;J. Rollins;C. Romel;J. Romie;M. Ross;K. Ryan;T. Sadecki;M. Sakellariadou;E. Sanchez;L. Sanchez;L. Sandles;T. R. Saravanan;R. Savage;D. Schaetzl;R. Schnabel;E. Schwartz;D. Sellers;T. Shaffer;D. Sigg;A. Sintes;B. Slagmolen;J. R. Smith;K. Soni;B. Sorazu;A. Spencer;K. Strain;D. Strom;L. Sun;M. Szczepańczyk;J. Tasson;R. Tenorio;M. Thomas;P. Thomas;K. Thorne;K. Toland;C. Torrie;A. Tran;G. Traylor;M. Trevor;M. Tse;G. Vajente;N. van Remortel;D. Vander-Hyde;A. Vargas;J. Veitch;P. Veitch;K. Venkateswara;Gautam Venugopalan;A. Viets;V. Villa-Ortega;T. Vo;C. Vorvick;M. Wade;G. Wallace;R. Ward;J. Warner;B. Weaver;A. Weinstein;R. Weiss;K. Wette;D. White;L. White;C. Whittle;A. Williamson;B. Willke;C. Wipf;L. Xiao;R. Xu;H. Yamamoto;Hang Yu;Haocun Yu;L. Zhang;Y. Zheng;M. Zucker;J. Zweizig

GWTC-2: Compact Binary Coalescences Observed by LIGO and Virgo during the First Half of the Third Observing Run

• DOI: 10.1103/physrevx.11.021053
• 发表时间: 2021-06-09
• 期刊: PHYSICAL REVIEW X
• 影响因子: 12.5
• 作者: Abbott, R.;Abbott, T. D.;Zweizig, J.
• 通讯作者: Zweizig, J.