Enhanced detection of high frequency gravitational waves using optically diluted optomechanical filters

Michael Page, Jiayi Qin, James La Fontaine, Chunnong Zhao, Li Ju, David Blair

    Research output: Contribution to journalArticlepeer-review

    12 Citations (Scopus)

    Abstract

    Detections of gravitational waves (GW) in the frequency band 35 to 500 Hz have led to the birth of GW astronomy. Expected signals above 500 Hz, such as the quasinormal modes of lower mass black holes and neutron star merger signatures, are currently not detectable due to increasing quantum shot noise at high frequencies. Squeezed vacuum injection has been shown to allow broadband sensitivity improvement, but this technique does not change the slope of the noise at high frequency. It has been shown that white light signal recycling using negative dispersion optomechanical filter cavities with strong optical dilution for thermal noise suppression can in principle allow broadband high frequency sensitivity improvement. Here we present detailed modeling of AlGaAs/GaAs optomechanical filters to identify the available parameter space in which such filters can achieve the low thermal noise required to allow useful sensitivity improvement at high frequency. Material losses, the resolved sideband condition and internal acoustic modes dictate the need for resonators substantially smaller than previously suggested. We identify suitable resonator dimensions and show that a 30 μm scale cat-flap resonator combined with optical squeezing allows 8 fold improvement of strain sensitivity at 2 kHz compared with Advanced LIGO. This corresponds to a detection volume increase of a factor of 500 for sources in this frequency range.

    Original languageEnglish
    Article number124060
    JournalPhysical Review D
    Volume97
    Issue number12
    DOIs
    Publication statusPublished - 15 Jun 2018

    Fingerprint

    Dive into the research topics of 'Enhanced detection of high frequency gravitational waves using optically diluted optomechanical filters'. Together they form a unique fingerprint.

    Cite this