Please use this identifier to cite or link to this item:
Title: Parameter estimation of coalescing supermassive black hole binaries with LISA
Authors: Arun, K.G.
Issue Date: 27-Jul-2006
Publisher: The American Physical Society
Citation: Physical Review D, 2006, Vol.74, p024025
Abstract: Laser Interferometer Space Antenna (LISA) will routinely observe coalescences of supermassive black hole (BH) binaries up to very high redshifts. LISA can measure mass parameters of such coalescences to a relative accuracy of 10-4–10-6, for sources at a distance of 3 Gpc. The problem of parameter estimation of massive nonspinning binary black holes using post-Newtonian (PN) phasing formula is studied in the context of LISA. Specifically, the performance of the 3.5PN templates is contrasted against its 2PN counterpart using a waveform which is averaged over the LISA pattern functions. The improvement due to the higher order corrections to the phasing formula is examined by calculating the errors in the estimation of mass parameters at each order. The estimation of the mass parameters [script M] and eta is significantly enhanced by using the 3.5PN waveform instead of the 2PN one. For an equal mass binary of 2×106M[sun] at a luminosity distance of 3 Gpc, the improvement in chirp mass is ~11% and that of eta is ~39%. Estimation of coalescence time tc worsens by 43%. The improvement is larger for the unequal mass binary mergers. These results are compared to the ones obtained using a nonpattern averaged waveform. The errors depend very much on the location and orientation of the source and general conclusions cannot be drawn without performing Monte Carlo simulations. Finally the effect of the choice of the lower frequency cutoff for LISA on the parameter estimation is studied.
ISSN: 1550-7998
1550-2368 (online)
Alternative Location:
Copyright: (2006) by the American Physical Society
Appears in Collections:Research Papers (TP)

Files in This Item:
File Description SizeFormat 
2006 PRD V74 p024025.pdf10p.308.3 kBAdobe PDFView/Open

Items in RRI Digital Repository are protected by copyright, with all rights reserved, unless otherwise indicated.