Enhancing Gravitational Wave Parameter Estimation with Non-Linear Memory: Breaking the Distance-Inclination Degeneracy
arxiv(2024)
摘要
In this study, we investigate the role of the non-linear memory effect in
gravitational wave (GW) parameter estimation, particularly we explore its
capability to break the degeneracy between luminosity distance and inclination
angle in binary coalescence events. Motivated by the rapid growth in GW
detections and the increasing sensitivity of GW observatories enhancing the
precision of cosmological and astrophysical measurements is crucial. We propose
leveraging the non-linear memory effect – a subtle, persistent feature in the
GW signal resulting from the cumulative impact of emitted gravitational waves
– as a novel approach to enhance parameter estimation accuracy. Through a
comprehensive series of injection studies, encompassing both reduced and full
parameter spaces, we evaluate the effectiveness of non-linear memory in various
scenarios for aligned-spin systems. Our findings demonstrate the significant
potential of non-linear memory in resolving the inclination-distance
degeneracy, particularly for events with high signal-to-noise ratios (SNR >
60) for the current generation of detectors and in the context of future
detector sensitivities such as the planned LIGO A^♯ upgrade. The results
also suggest that excluding non-linear memory from parameter estimation could
introduce significant systematics in future LIGO A^♯ detections. This
observation will hold even greater weight for next-generation detectors,
highlighting the importance of including non-linear memory in GW models for
achieving high-accuracy measurements for gravitational wave (GW) astronomy.
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