A model demonstrates significant scale-dependent bias on BAO scales in biased tracers, indicating implications for surveys like DESI.
Key Points
Scale-dependent bias is crucial for understanding redshift-space clustering near the BAO scale, highlighting its significance in modeling.
Results show that incorporating scale-dependent bias improves the accuracy of 2-point clustering models for tracer samples at BAO scales.
Methodology involves a model-agnostic approach utilizing peaks theory and the Zel'dovich approximation to address bias and coupling effects.
Implications indicate that while scale-dependent bias is critical, the impact of mode coupling appears to be less significant in current observational surveys.