Systematic Bias from Eccentricity in Spin-Precessing Black Hole Binaries

As current gravitational-wave (GW) detectors improve their sensitivity and space-based detectors such as LISA are poised to launch in the next decade, the need for more comprehensive waveform models of coalescing black hole binaries has grown more urgent. Recent efforts have produced models of the inspiral phase incorporating both spin-precession and arbitrary eccentricity. In this work, we investigate the systematic bias due to not modeling these two effects simultaneously for simulated LISA binaries. We inject spin-precessing, eccentric GW signals and perform Bayesian parameter estimation with a non-eccentric model. By varying the eccentricity, spins, and masses, we quantify the biases in the inferred source parameters and identify the binaries that are susceptible to inaccurate characterization. Our findings delineate the parameter space where incomplete modeling can lead to misidentification of a binary's formation channel, a crucial step towards understanding the astrophysical origins of black holes.