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Unified $\chi^2$ discriminators for gravitational wave searches from compact coalescing binaries

Sanjeev Dhurandhar
(
- IUCAA, Pune
)

Feb 25, 2025

14 pages

e-Print:

2502.18051 [gr-qc]

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Abstract: (arXiv)

Gravitational wave (GW) signals of astrophysical origin are typically weak. This is because gravity is a weak force, the weakest among the four forces we know of. In order to detect GW signals, one must make differential measurements of effective lengths less than a thousandth of the size of a proton. In spite of the detectors achieving extraordinary sensitivity, the detector noise typically overwhelms the signal, so that GW signals are deeply buried in the data. The challenge to the data analyst is of extracting the GW signal from the noise, that is, first deciding whether a signal is present or not then if present, measuring its parameters. However, in the search for coalescing compact binary (CBC) signals, short-duration non-Gaussian noise transients (glitches) in the detector data significantly affect the search sensitivity.

\chi^2

discriminators are therefore employed to mitigate their effect. We show that the underlying mathematical structure of any

\chi^2

is a vector bundle over the signal manifold

\mathcal{P}

, that is, the manifold traced out by the signal waveforms in the Hilbert space of data segments

\mathcal{D}

. The

\chi^2

is then defined as the square of the

L_2

norm of the data vector projected onto a finite-dimensional subspace

\mathcal{S}

(fibre) of

\mathcal{D}

chosen orthogonal to the triggered template waveform. Any such fibre leads to a

\chi^2

discriminator and the full vector bundle comprising the subspaces

\mathcal{S}

and the base manifold

\mathcal{P}

contitute the discriminator. We show that this structure paves the way for constructing effective discriminators against different morphologies of glitches. Here we specifically demonstrate our method on blip glitches, which can be modelled as sine-Gausians, which then generates an optimal

\chi^2

statistic for blip glitches.

Note:

14 pages, 6 figures

References(29)

Figures(8)

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