Curve matching example, in which a single spline (in black) matches all curves simultaneously. Due to microlensing in particular, which adds independent lower-frequency variations to each curve, the curves could not be matched in this way with time and magnitude shifts only. Thus, an extra modulation is applied to each separately. These modulations are represented by lower order splines, displayed at the bottom. Physically, the black spline models the intrinsic variations of the source, while the coloured splines undo the effects of microlensing. Linking with the notation of Sect. 4, M_ext is here a cubic spline with a single internal knot of fixed position, and N_int = 9. To determine a time delay and its uncertainty, this matching was repeated thousands of times with artificially further-modulated curves (mimicking microlensing), other realisations of the noise, and different freedoms given to the splines. What this matching is like for the other targets can be found in a Jupyter notebook. This notebook is part of the repository containing the photometry extracted herein and the code to estimate the time delays.