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A Cryogenic Silicon Interferometer for Gravitational-wave Detection

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arxiv 2001.11173 v2 pith:LDW4THJZ submitted 2020-01-30 astro-ph.IM gr-qcphysics.ins-det

Rana X Adhikari , Odylio Aguiar , Koji Arai , Bryan Barr , Riccardo Bassiri , Garilynn Billingsley , Ross Birney , David Blair
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classification astro-ph.IMgr-qcphysics.ins-det
keywords detectioninstrumentligobinarygravitationaltimesuniversewill
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The detection of gravitational waves from compact binary mergers by LIGO has opened the era of gravitational wave astronomy, revealing a previously hidden side of the cosmos. To maximize the reach of the existing LIGO observatory facilities, we have designed a new instrument that will have 5 times the range of Advanced LIGO, or greater than 100 times the event rate. Observations with this new instrument will make possible dramatic steps toward understanding the physics of the nearby universe, as well as observing the universe out to cosmological distances by the detection of binary black hole coalescences. This article presents the instrument design and a quantitative analysis of the anticipated noise floor.

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Forward citations

Cited by 3 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Remnant properties of binary neutron star mergers undergoing prompt collapse

    gr-qc 2025-07 conditional novelty 6.0 of 10

    Prompt-collapse neutron star merger remnants occupy a narrow, high-spin region of the mass-spin plane, and Cosmic Explorer could use tidal deformability to classify most such mergers as neutron star events out to 100-250 Mpc.

  2. Inspiral tests of general relativity and waveform geometry

    gr-qc 2026-02 conditional novelty 5.0 of 10

    The power of ppE-style GR tests comes from waveform geometry: GR parameter biases absorb most of any smooth phase deviation, and SVD finds the few orthogonal directions that remain.

  3. Robustness of Sensitivity Evaluations for Gravitational Wave Detection Algorithms

    gr-qc 2025-09 conditional novelty 5.0 of 10

    AresGW model 1's injection detection count at a false-alarm rate of 1/month varies with noise dataset by up to 39% coefficient of variation, while sensitive distance varies by only a few percent.

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