Adaptive multi-line fitting for stable line-core intensity and Doppler velocity

Next-generation solar spectrographs increasingly record dense wavelength windows in which tens to hundreds of spectral lines are sampled at each spatial location and time step. This expands the scope for multi-line, multi-height diagnostics of magnetohydrodynamic (MHD) motions, but also raises a practical challenge: deriving stable line-core intensity and line-of-sight (LOS) velocity time series when profiles evolve rapidly, become asymmetric, blend, or develop multi-lobed cores. Common fast estimators (e.g., parabolic minima, centre-of-gravity measures, Fourier-phase proxies, and fixed-window symmetric fits) can perform well for simple, isolated absorption lines, yet can intermittently misidentify the core in crowded or morphologically complex cases. Even infrequent mis-tracking can leave step-like artefacts that redistribute power and bias spectral, phase, and coherence measures used in wave and dynamics analyses. We introduce LineFit , a fully reproducible adaptive multi-line fitting approach tailored to dense-window spectroscopy from facilities such as DKIST, Sunrise III, and integral-field instruments. LineFit models each line locally with bounded non-linear least-squares fits to a Voigt-family profile, including an asymmetric-Voigt option to accommodate unequal wing broadening, and incorporates close-pair ownership control together with conservative, per-line window adaptation and split-core-aware handling. Using a synthetic near-UV time series with unambiguous ground truth, we benchmark LineFit against four widely used fast baselines and assess both instantaneous centre errors and downstream time-series diagnostics. Several fast methods remain competitive for many lines, whereas LineFit is most robust in key stress cases involving intermittently split-core profiles and correspondingly yields power spectra that agree most closely with the truth. We also demonstrate a proof-of-principle that benchmarks hybrid acceleration of the LineFit software via supervised emulation, offering at least three orders-of-magnitude improvement in processing time, with 87% of validation samples agreeing with LineFit to within 0.1 pm in recovered line-centre position. All code and notebooks required to reproduce the testbed, figures, and results are publicly available, providing a portable benchmark and a practical basis for stable multi-line time-series extraction, with a clear route towards hybrid acceleration via supervised emulation.