The NANOGrav 15 yr Data Set: Detector Characterization and Noise Budget

G. Agazie, A. Anumarlapudi, A. Archibald, Z. Arzoumanian, P. Baker, B. Bécsy, L. Blecha, A. Brazier, P. Brook, S. Burke-Spolaor, M. Charisi, S. Chatterjee, T. Cohen, J. Cordes, N. Cornish, F. Crawford, H. Cromartie, K. Crowter, M. DeCesar, P. Demorest, T. Dolch, B. Drachler, E. Ferrara, W. Fiore, E. Fonseca, G. Freedman, N. Garver-Daniels, P. Gentile, J. Glaser, D. Good, Lydia Guertin, K. Gültekin, J. Hazboun, R. Jennings, A. Johnson, Megan L. Jones, A. Kaiser, D. Kaplan, L. Kelley, M. Kerr, J. Key, N. Laal, M. Lam, W. Lamb, T. Joseph W. Lazio, N. Lewandowska, Tingting Liu, D. Lorimer, Jing Luo, R. Lynch, Chung-Pei Ma, D. Madison, A. McEwen, J. McKee, M. Mclaughlin, N. McMann, B. W. Meyers, C. Mingarelli, A. Mitridate, C. Ng, D. Nice, S. Ocker, K. Olum, T. Pennucci, B. Perera, N. Pol, H. Radovan, S. Ransom, P. Ray, J. Romano, S. C. Sardesai, A. Schmiedekamp, C. Schmiedekamp, K. Schmitz, B. Shapiro-Albert, X. Siemens, J. Simon, M. Siwek, I. Stairs, D. Stinebring, K. Stovall, A. Susobhanan, J. Swiggum, S. T
{"title":"The NANOGrav 15 yr Data Set: Detector Characterization and Noise Budget","authors":"G. Agazie, A. Anumarlapudi, A. Archibald, Z. Arzoumanian, P. Baker, B. Bécsy, L. Blecha, A. Brazier, P. Brook, S. Burke-Spolaor, M. Charisi, S. Chatterjee, T. Cohen, J. Cordes, N. Cornish, F. Crawford, H. Cromartie, K. Crowter, M. DeCesar, P. Demorest, T. Dolch, B. Drachler, E. Ferrara, W. Fiore, E. Fonseca, G. Freedman, N. Garver-Daniels, P. Gentile, J. Glaser, D. Good, Lydia Guertin, K. Gültekin, J. Hazboun, R. Jennings, A. Johnson, Megan L. Jones, A. Kaiser, D. Kaplan, L. Kelley, M. Kerr, J. Key, N. Laal, M. Lam, W. Lamb, T. Joseph W. Lazio, N. Lewandowska, Tingting Liu, D. Lorimer, Jing Luo, R. Lynch, Chung-Pei Ma, D. Madison, A. McEwen, J. McKee, M. Mclaughlin, N. McMann, B. W. Meyers, C. Mingarelli, A. Mitridate, C. Ng, D. Nice, S. Ocker, K. Olum, T. Pennucci, B. Perera, N. Pol, H. Radovan, S. Ransom, P. Ray, J. Romano, S. C. Sardesai, A. Schmiedekamp, C. Schmiedekamp, K. Schmitz, B. Shapiro-Albert, X. Siemens, J. Simon, M. Siwek, I. Stairs, D. Stinebring, K. Stovall, A. Susobhanan, J. Swiggum, S. T","doi":"10.3847/2041-8213/acda88","DOIUrl":null,"url":null,"abstract":"Pulsar timing arrays (PTAs) are galactic-scale gravitational wave (GW) detectors. Each individual arm, composed of a millisecond pulsar, a radio telescope, and a kiloparsecs-long path, differs in its properties but, in aggregate, can be used to extract low-frequency GW signals. We present a noise and sensitivity analysis to accompany the NANOGrav 15 yr data release and associated papers, along with an in-depth introduction to PTA noise models. As a first step in our analysis, we characterize each individual pulsar data set with three types of white-noise parameters and two red-noise parameters. These parameters, along with the timing model and, particularly, a piecewise-constant model for the time-variable dispersion measure, determine the sensitivity curve over the low-frequency GW band we are searching. We tabulate information for all of the pulsars in this data release and present some representative sensitivity curves. We then combine the individual pulsar sensitivities using a signal-to-noise ratio statistic to calculate the global sensitivity of the PTA to a stochastic background of GWs, obtaining a minimum noise characteristic strain of 7 × 10−15 at 5 nHz. A power-law-integrated analysis shows rough agreement with the amplitudes recovered in NANOGrav’s 15 yr GW background analysis. While our phenomenological noise model does not model all known physical effects explicitly, it provides an accurate characterization of the noise in the data while preserving sensitivity to multiple classes of GW signals.","PeriodicalId":179976,"journal":{"name":"The Astrophysical Journal Letters","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-06-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"29","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"The Astrophysical Journal Letters","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3847/2041-8213/acda88","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 29

Abstract

Pulsar timing arrays (PTAs) are galactic-scale gravitational wave (GW) detectors. Each individual arm, composed of a millisecond pulsar, a radio telescope, and a kiloparsecs-long path, differs in its properties but, in aggregate, can be used to extract low-frequency GW signals. We present a noise and sensitivity analysis to accompany the NANOGrav 15 yr data release and associated papers, along with an in-depth introduction to PTA noise models. As a first step in our analysis, we characterize each individual pulsar data set with three types of white-noise parameters and two red-noise parameters. These parameters, along with the timing model and, particularly, a piecewise-constant model for the time-variable dispersion measure, determine the sensitivity curve over the low-frequency GW band we are searching. We tabulate information for all of the pulsars in this data release and present some representative sensitivity curves. We then combine the individual pulsar sensitivities using a signal-to-noise ratio statistic to calculate the global sensitivity of the PTA to a stochastic background of GWs, obtaining a minimum noise characteristic strain of 7 × 10−15 at 5 nHz. A power-law-integrated analysis shows rough agreement with the amplitudes recovered in NANOGrav’s 15 yr GW background analysis. While our phenomenological noise model does not model all known physical effects explicitly, it provides an accurate characterization of the noise in the data while preserving sensitivity to multiple classes of GW signals.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
nanogravity 15年数据集:检测器特性和噪声预算
脉冲星定时阵列(PTAs)是一种银河系尺度的引力波探测器。每一个单独的臂由一个毫秒脉冲星、一个射电望远镜和一个千秒差距长的路径组成,它们的特性不同,但总的来说,可以用来提取低频的GW信号。我们在NANOGrav 15年数据发布和相关论文中提供了噪声和敏感性分析,并深入介绍了PTA噪声模型。作为我们分析的第一步,我们用三种白噪声参数和两种红噪声参数来描述每个脉冲星数据集。这些参数,连同时序模型,特别是时变色散测量的分段常数模型,决定了我们正在寻找的低频GW波段的灵敏度曲线。我们将本次数据发布中所有脉冲星的信息制成表格,并给出一些具有代表性的灵敏度曲线。然后,我们使用信噪比统计结合单个脉冲星的灵敏度来计算PTA对GWs随机背景的全局灵敏度,得到5 nHz下的最小噪声特征应变为7 × 10−15。幂律综合分析显示,与NANOGrav的15年GW背景分析中恢复的振幅大致一致。虽然我们的现象学噪声模型不能明确地模拟所有已知的物理效应,但它提供了数据中噪声的准确表征,同时保持了对多类GW信号的灵敏度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Erratum: “Large Volcanic Event on Io Inferred from Jovian Sodium Nebula Brightening” (2019, ApJL, 871, L23) Voyager 1 Electron Densities in the Very Local Interstellar Medium to beyond 160 au Formation of Fan-spine Magnetic Topology through Flux Emergence and Subsequent Jet Production The First Robust Evidence Showing a Dark Matter Density Spike Around the Supermassive Black Hole in OJ 287 Evidence for a Redshifted Excess in the Intracluster Light Fractions of Merging Clusters at z ∼ 0.8
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1