日本語
 
Help Privacy Policy ポリシー/免責事項
  詳細検索ブラウズ

アイテム詳細


公開

学術論文

Detection and parameter estimation challenges of Type-II lensed binary black hole signals

MPS-Authors
/persons/resource/persons252872

Mehta,  Ajit Kumar
Astrophysical and Cosmological Relativity, AEI-Golm, MPI for Gravitational Physics, Max Planck Society;

External Resource
There are no locators available
Fulltext (restricted access)
There are currently no full texts shared for your IP range.
フルテキスト (公開)

2202.06334.pdf
(プレプリント), 6MB

付随資料 (公開)
There is no public supplementary material available
引用

Vijaykumar, A., Mehta, A. K., & Ganguly, A. (2023). Detection and parameter estimation challenges of Type-II lensed binary black hole signals. Physical Review D, 108(4):. doi:10.1103/PhysRevD.108.043036.


引用: https://hdl.handle.net/21.11116/0000-000D-D6D5-1
要旨
Strong lensing of {gravitational-wave signals} can produce three types of
images, denoted as Type-I, Type-II and Type-III, corresponding to the minima,
saddle and maxima of the lensing potential of the lensed images. Type-II
images, in particular, receive a non-trivial phase shift of $\pi/2$. This phase
shift can introduce additional distortions in the strains produced by the
Type-II image of the binary black hole signals depending on the morphology of
the signals, e.g., when they have contributions from higher harmonics,
precession, eccentricity, etc. {The probability of observing Type-II images is
nearly the same as that of strong lensing itself, and thus these signals are
likely to be observed in the near future.} In this work, we investigate the
potential applicability of these distortions in helping identify Type-II
signals from a single detection and the systematic biases that could arise in
the inference of parameters if they are recovered with gravitational-wave
templates that do not take the distortion into account. We show that the
lensing distortions will allow us to confidently identify the Type-II images
for highly inclined binaries: at network signal-to-noise ratio (SNR)
$\rho=20(50)$, individual Type-II images should be identifiable with ln Bayes
factor $\ln \mathcal{B} > 2$ for inclinations $ \iota > 5 \pi/12 (\pi/3) $.
Furthermore, based on the trends we observe in these results, we predict that,
at high SNRs ($\gtrsim 100$), individual Type-II images would be identifiable
even when the inclination angle is much lower ($\sim \pi/6$). We then show that
neglecting physical effects arising from these identifiable Type-II images can
significantly bias the estimates of source parameters. Thus, in the future,
using templates that take into account the lensing deformation would be
necessary to extract source parameters from Type-II lensed signals.