SIMBAD references

2020MNRAS.498.4577B - Mon. Not. R. Astron. Soc., 498, 4577-4589 (2020/November-1)

Towards a polarization prediction for LISA via intensity interferometry.

BAUMGARTNER S., BERNARDINI M., CANIVETE CUISSA J.R., DE LAROUSSILHE H., MITCHELL A.M.W., NEUENSCHWANDER B.A., SAHA P., SCHAEFFER T., SOYUER D. and ZWICK L.

Abstract (from CDS):

Compact Galactic Binary Systems with orbital periods of a few hours are expected to be detected in gravitational waves (GW) by Laser Interferometer Space Antenna (LISA) or a similar mission. At present, these so-called verification binaries provide predictions for GW frequency and amplitude. A full polarization prediction would provide a new method to calibrate LISA and other GW observatories, but requires resolving the orientation of the binary on the sky, which is not currently possible. We suggest a method to determine the elusive binary orientation and hence predict the GW polarization, using km-scale optical intensity interferometry. The most promising candidate is CD-30° 11223, consisting of a hot helium subdwarf with mB = 12 and a much fainter white dwarf companion, in a nearly edge-on orbit with period 70.5 min. We estimate that the brighter star is tidally stretched by 6 per cent. Resolving the tidal stretching would provide the binary orientation. The resolution needed is far beyond any current instrument, but not beyond current technology. We consider scenarios where an array of telescopes with km-scale baselines and/or the Very Large Telescope (VLT) and Extremely Large Telescope (ELT) are equipped with recently developed kilopixel sub-ns single-photon counters and used for intensity interferometry. We estimate that a team-up of the VLT and ELT could measure the orientation to ±1° at 2σ confidence in 24 h of observation.

Abstract Copyright: © 2020 The Author(s) Published by Oxford University Press on behalf of the Royal Astronomical Society

Journal keyword(s): gravitational waves - techniques: interferometric - stars: individual: CD-30deg 11223

Simbad objects: 2

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