P. Couvares
California Institute of Technology
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Featured researches published by P. Couvares.
Physical Review D | 2017
B. Abbott; R. Abbott; M. R. Abernathy; R. Adhikari; S. Anderson; K. Arai; M. C. Araya; J. C. Barayoga; B. Barish; B. K. Berger; G. Billingsley; J. K. Blackburn; R. Bork; A. F. Brooks; C. Cahillane; T. Callister; C. Cepeda; R. Chakraborty; T. Chalermsongsak; P. Couvares; D. C. Coyne; V. Dergachev; R. W. P. Drever; P. Ehrens; T. Etzel; S. E. Gossan; K. E. Gushwa; E. K. Gustafson; E. D. Hall; A. W. Heptonstall
In Advanced LIGO, detection and astrophysical source parameter estimation of the binary black hole merger GW150914 requires a calibrated estimate of the gravitational-wave strain sensed by the detectors. Producing an estimate from each detector’s differential arm length control loop readout signals requires applying time domain filters, which are designed from a frequency domain model of the detector’s gravitational-wave response. The gravitational-wave response model is determined by the detector’s opto-mechanical response and the properties of its feedback control system. The measurements used to validate the model and characterize its uncertainty are derived primarily from a dedicated photon radiation pressure actuator, with cross-checks provided by optical and radio frequency references. We describe how the gravitational-wave readout signal is calibrated into equivalent gravitational-wave-induced strain and how the statistical uncertainties and systematic errors are assessed. Detector data collected over 38 calendar days, from September 12 to October 20, 2015, contain the event GW150914 and approximately 16 days of coincident data used to estimate the event false alarm probability. The calibration uncertainty is less than 10% in magnitude and 10° in phase across the relevant frequency band, 20 Hz to 1 kHz.
Proceedings of the Practice and Experience in Advanced Research Computing 2017 on Sustainability, Success and Impact | 2017
Derek Weitzel; Brian Bockelman; D. A. Brown; P. Couvares; F. Würthwein; Edgar Fajardo Hernandez
During 2015 and 2016, the Laser Interferometer Gravitational-Wave Observatory (LIGO) conducted a three-month observing campaign. These observations delivered the first direct detection of gravitational waves from binary black hole mergers. To search for these signals, the LIGO Scientific Collaboration uses the PyCBC search pipeline. To deliver science results in a timely manner, LIGO collaborated with the Open Science Grid (OSG) to distribute the required computation across a series of dedicated, opportunistic, and allocated resources. To deliver the petabytes necessary for such a large-scale computation, our team deployed a distributed data access infrastructure based on the XRootD server suite and the CernVM File System (CVMFS). This data access strategy grew from simply accessing remote storage to a POSIX-based interface underpinned by distributed, secure caches across the OSG.
international conference on e-science | 2017
Eliu Huerta; Roland Haas; Edgar Fajardo; Daniel S. Katz; Stuart B. Anderson; P. Couvares; Josh Willis; Timothy Bouvet; Jeremy Enos; William Kramer; Hon Wai Leong; D. J. Wheeler
We present a novel computational framework that connects Blue Waters, the NSF-supported, leadership-class supercomputer operated by NCSA, to the Laser Interferometer Gravitational-Wave Observatory (LIGO) Data Grid via Open Science Grid technology. To enable this computational infrastructure, we configured, for the first time, a LIGO Data Grid Tier-1 Center that can submit heterogeneous LIGO workflows using Open Science Grid facilities. In order to enable a seamless connection between the LIGO Data Grid and Blue Waters via Open Science Grid, we utilize Shifter to containerize LIGO’s workflow software. This work represents the first time Open Science Grid, Shifter, and Blue Waters are unified to tackle a scientific problem and, in particular, it is the first time a framework of this nature is used in the context of large scale gravitational wave data analysis. This new framework has been used in the last several weeks of LIGO’s second discovery campaign to run the most computationally demanding gravitational wave search workflows on Blue Waters, and accelerate discovery in the emergent field of gravitational wave astrophysics. We discuss the implications of this novel framework for a wider ecosystem of Higher Performance Computing users.
Bulletin of the American Physical Society | 2018
Roland Haas; Eliu Huerta; Edgar Fajardo; Daniel S. Katz; Stuart B. Anderson; P. Couvares; Josh Willis; Timothy Bouvet; Jeremy Enos; William Kramer; Hon Wai Leong; David R. Wheeler