Improving astrophysical parameter estimation via offline noise subtraction for Advanced LIGO
J. C. Driggers, S. Vitale, A. P. Lundgren, M. Evans, K. Kawabe, S. E. Dwyer, K. Izumi, R. M. S. Schofield, A. Effler, D. Sigg, P. Fritschel, M. Drago, A. Nitz, … 展开作者
J. C. Driggers, S. Vitale, A. P. Lundgren, M. Evans, K. Kawabe, S. E. Dwyer, K. Izumi, R. M. S. Schofield, A. Effler, D. Sigg, P. Fritschel, M. Drago, A. Nitz, B. P. Abbott, R. Abbott, T. D. Abbott, C. Adams, R. X Adhikari, V. B. Adya, A. Ananyeva, S. Appert, K. Arai, S. M. Aston, C. Austin, S. W. Ballmer, D. Barker, B. Barr, L. Barsotti, J. Bartlett, I. Bartos, J. C. Batch, A. S. Bell, J. Betzwieser, G. Billingsley, J. Birch, S. Biscans, C. D. Blair, R. M. Blair, R. Bork, A. F. Brooks, H. Cao, G. Ciani, F. Clara, S. J. Cooper, P. Corban, S. T. Countryman, P. B. Covas, M. J. Cowart, D. C. Coyne, A. Cumming, L. Cunningham, K. Danzmann, C. F. Da Silva Costa, E. J. Daw, D. DeBra, R. DeSalvo, K. L. Dooley, S. Doravari, T. B. Edo, T. Etzel, T. M. Evans, H. Fair, A. Fernandez-Galiana, E. C. Ferreira, R. P. Fisher, H. Fong, R. Frey, V. V. Frolov, P. Fulda, M. Fyffe, B. Gateley, J. A. Giaime, K. D. Giardina, E. Goetz, R. Goetz, S. Gras, C. Gray, H. Grote, K. E. Gushwa, E. K. Gustafson, R. Gustafson, E. D. Hall, G. Hammond, J. Hanks, J. Hanson, T. Hardwick, G. M. Harry, M. C. Heintze, A. W. Heptonstall, J. Hough, R. Jones, S. Kandhasamy, S. Karki, M. Kasprzack, S. Kaufer, R. Kennedy, N. Kijbunchoo, W. Kim, E. J. King, P. J. King, J. S. Kissel, W. Z. Korth, G. Kuehn, M. Landry, B. Lantz, M. Laxen, J. Liu, N. A. Lockerbie, M. Lormand, M. MacInnis, D. M. Macleod, S. Marka, Z. Marka, A. S. Markosyan, E. Maros, P. Marsh, I. W. Martin, D. V. Martynov, K. Mason, T. J. Massinger, F. Matichard, N. Mavalvala, R. McCarthy, D. E. McClelland, S. McCormick, L. McCuller, J. McIver, D. J. McManus, T. McRae, G. Mendell, E. L. Merilh, P. M. Meyers, R. Mittleman, K. Mogushi, D. Moraru, G. Moreno, C. M. Mow-Lowry, G. Mueller, N. Mukund, A. Mullavey, J. Munch, T. J. N. Nelson, P. Nguyen, L. K. Nuttall, J. Oberling, M. Oliver, P. Oppermann, Richard J. Oram, B. O'Reilly, D. J. Ottaway, H. Overmier, J. R. Palamos, W. Parker, A. Pele, S. Penn, C. J. Perez, M. Phelps, V. Pierro, I. M. Pinto, M. Pirello, M. Principe, L. G. Prokhorov, O. Puncken, V. Quetschke, E. A. Quintero, H. Radkins, P. Raffai, K. E. Ramirez, S. Reid, D. H. Reitze, N. A. Robertson, J. G. Rollins, V. J. Roma, C. L. Romel, J. H. Romie, M. P. Ross, S. Rowan, K. Ryan, T. Sadecki, E. J. Sanchez, L. E. Sanchez, V. Sandberg, R. L. Savage, D. Sellers, D. A. Shaddock, T. J. Shaffer, B. Shapiro, D. H. Shoemaker, B. J. J. Slagmolen, B. Smith, J. R. Smith, B. Sorazu, A. P. Spencer, K. A. Strain, D. B. Tanner, R. Taylor, M. Thomas, P. Thomas, K. A. Thorne, E. Thrane, K. Toland, C. I. Torrie, G. Traylor, M. Tse, D. Tuyenbayev, G. Vajente, G. Valdes, A. A. van Veggel, S. Vass, A. Vecchio, P. J. Veitch, K. Venkateswara, G. Venugopalan, T. Vo, C. Vorvick, M. Walker, R. L. Ward, J. Warner, B. Weaver, R. Weiss, P. Wessels, B. Willke, C. C. Wipf, J. Worden, H. Yamamoto, C. C. Yancey, Hang Yu, Haocun Yu, L. Zhang, M. E. Zucker, J. Zweizig
The Advanced LIGO detectors have recently completed their second observation run successfully. The run lasted for approximately 10 months and lead to multiple new discoveries. The sensitivity to gravitational waves was partially limited by correlated noise. Here, we utilize auxiliary sensors that witness these correlated noise sources, and use them for noise subtraction in the time domain data. This noise and line removal is particularly significant for the LIGO Hanford Observatory, where the improvement in sensitivity is greater than 20%. Consequently, we were also able to improve the astrophysical estimation for the location, masses, spins and orbital parameters of the gravitational wave progenitors.
Assessing astrophysical foreground subtraction in DECIGO using compact binary populations inferred from the first part of the LIGO-Virgo-KAGRA's fourth observation run
Research Center for the Early Universe (RESCEU), Graduate School of Science, The University of Tokyo(东京大学理学研究科早期宇宙研究中心)
DeepSNR: A deep learning foundation for offline gravitational wave detection
Carnegie Mellon University(卡内基梅隆大学);Advanced Propulsion Laboratory at Applied Physics(应用物理高级推进实验室);Lund University(隆德大学);Technion - Israel Institute of Technology(以色列理工学院)
The Pennsylvania State University(宾夕法尼亚州立大学);Georgia Institute of Technology(佐治亚理工学院);University of Nevada, Las Vegas(内华达大学拉斯维加斯分校);NASA Marshall Space Flight Center(美国国家航空航天局马歇尔太空飞行中心)
The best of all worlds: gravitational-wave transient detection with multiple pipelines
Aristotle University of Thessaloniki(塞萨洛尼基亚里士多德大学);Institute for Accelerated AI Algorithms for Data-Driven Discovery (A3D3), MIT(麻省理工学院数据驱动发现加速AI算法研究所);University of Thessaly(色萨利大学)
DeepExtractor: Time-domain reconstruction of signals and glitches in gravitational wave data with deep learning
Faculty of Science, Open Universiteit(科学学院,开放大学);Institute for Gravitational and Subatomic Physics (GRASP), Utrecht University(引力与亚原子物理研究所(GRASP),乌得勒支大学);Nikhef(Nikhef研究所);Department of Physics, University of Massachusetts(物理系,马萨诸塞大学)
Unified matched-filter and excess-power pipeline for gravitational-wave detector characterization
Louisiana State University(路易斯安那州立大学);LIGO Laboratory, California Institute of Technology(加州理工学院 LIGO 实验室);The Pennsylvania State University(宾夕法尼亚州立大学);University of Rhode Island(罗德岛大学)