SNR-ξ² Optimization to Improve Detection of Precessing Binary Black Holes

Current gravitational-wave searches for compact binaries are not optimally sensitive to signals from binary black holes (BBHs) with precessing spins. This is largely due to the computational cost associated with generating and filtering against fully precessing template banks, which require a significantly larger parameter space than aligned-spin models. In this study, we investigate an alternative strategy that utilizes triggers from existing aligned-spin searches. Precessing BBH signals can still appear as high signal-to-noise (SNR) ratio events in such searches. However, due to waveform mismatches with the aligned-spin templates, they often result in high values from traditional signal-consistency tests, indicating a poor fit. This typically leads to these signals being down-ranked or misclassified as noise. To address this, we present a novel method that rapidly re-evaluates and optimizes the SNR and signal-consistency test values of potentially precessing candidate events. This method can efficiently recover precessing signals without requiring the overhead of a full precessing search.