Research paper proposing Low-Rank Quantile Surfaces (LRQS), a bivariate causal model for efficient causal discovery in complex systems. This model subsumes existing noise models and allows for multiple quantile bases to represent changes beyond location-scale effects. The research provides a simple-yet-powerful causal score for identifying causal relationships in data.