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Maximiliano Isi

Researcher at Massachusetts Institute of Technology

Publications -  239
Citations -  68019

Maximiliano Isi is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: LIGO & Gravitational wave. The author has an hindex of 80, co-authored 220 publications receiving 53588 citations. Previous affiliations of Maximiliano Isi include York University & California Institute of Technology.

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All-sky search for continuous gravitational waves from isolated neutron stars using Advanced LIGO O2 data

B. P. Abbott, +1225 more
- 08 Jul 2019 - 
TL;DR: In this article, the results of an all-sky search for continuous gravitational waves (CWs), which can be produced by fast spinning neutron stars with an asymmetry around their rotation axis, were presented.
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Search for High-energy Neutrinos from Binary Neutron Star Merger GW170817 with ANTARES, IceCube, and the Pierre Auger Observatory

Arnauld Albert, +1932 more
TL;DR: In this article, the authors search for high-energy neutrinos from the binary neutron star merger in the GeV-EeV energy range using the ANTARES, IceCube, and Pierre Auger Observatories.
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Effects of data quality vetoes on a search for compact binary coalescences in Advanced LIGO's first observing run

B. P. Abbott, +983 more
TL;DR: The systematic removal of noisy data from analysis time is shown to improve the sensitivity of searches for compact binary coalescences, and the output of the PyCBC pipeline is used as a metric for improvement.
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Search for Tensor, Vector, and Scalar Polarizations in the Stochastic Gravitational-Wave Background

B. P. Abbott, +1143 more
TL;DR: Using data recorded by Advanced LIGO during its first observing run, no evidence for a background of any polarization is found, and the first direct bounds on the contributions of vector and scalar polarizations to the stochastic background are placed.
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Effects of waveform model systematics on the interpretation of GW150914

B. P. Abbott, +1033 more
TL;DR: In this paper, the effects of possible systematic errors in the waveform models on estimates of its source parameters were investigated and no evidence for a systematic bias relative to the statistical error of the original parameter recovery of GW150914 due to modeling approximations or modeling inaccuracies was found.