Enhancing Gravitational Wave Parameter Estimation with Non-Linear Memory: Breaking the Distance-Inclination Degeneracy

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 $>$ 90) for the current generation of detectors or closer than 1 Gpc in the context of future detector sensitivities such as the planned LIGO A$^\sharp$ upgrade. The results also suggest that excluding non-linear memory from parameter estimation could introduce significant systematics in future LIGO A$^\sharp$ 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.