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LIGO team recruits public to help with gravitational wave data analysis
June 29, 2016 | Rachel Gaal
In the wake of LIGO’s second black hole merger observation, scientists are hopeful of the future possibilities for gravitational wave detection. To ease the chore of sifting the data, the LIGO Scientific Collaboration (LSC) is turning to their followers to test out an upcoming project that will help the LIGO team improve their search for gravitational waves.
A project aimed at identifying glitches in LIGO data, Gravity Spy combines human collaboration and automated processing to improve the classification abilities of computers designed to filter out erroneous data. With help from volunteers, the Gravity Spy team hopes to increase public engagement with science and to provide training to both citizens and their machine learning algorithms.
The classification of glitches, which is done manually by volunteers and vetted by the Gravity Spy team, helps the algorithms preform the same cataloging on larger datasets and provides researchers the ability to define and discard sources of noise, increasing LIGO’s detection sensitivity.
The Gravity Spy team, representing multiple institutions and researchers, runs the project through Zooniverse—an online platform that hosts popular citizen-science projects in multiple disciplines. LIGO researchers within The Center for Interdisciplinary Exploration and Research in Astronomy (CIERA) at Northwestern University, LIGO Researchers at Caltech, machine learning researchers at Northwestern University, and crowd-sourced researchers at Syracuse make up the main team players.
Gravity Spy is now in beta testing and accepting open feedback from the public. Visit gravityspy.org to learn more and participate.