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Searching for codes credited to 'Rescigno, Federica'

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Found 2 codes.

[ascl:2310.006] MAGPy-RV: Gaussian Process regression pipeline with MCMC parameter searching
Rescigno, Federica; Dixon, Bryce; Haywood, Raphaëlle D.
MAGPy-RV (Modelling stellar Activity with Gaussian Processes in Radial Velocity) models data with Gaussian Process regression and affine invariant Monte Carlo Markov Chain parameter searching. Developed to model intrinsic, quasi-periodic variations induced by the host star in radial velocity (RV) surveys for the detection of exoplanets and the accurate measurements of their orbital parameters and masses, it now includes a variety of kernels and models and can be applied to any timeseries analysis. MAGPy-RV includes publication level plotting, efficient posterior extraction, and export-ready LaTeX results tables. It also handles multiple datasets at once and can model offsets and systematics from multiple instruments. MAGPy-RV requires no external dependencies besides basic python libraries and corner (ascl:1702.002).
[ascl:2207.009] SolAster: 'Sun-as-a-star' radial velocity variations
Ervin, Tamar; Halverson, Samuel; Burrows, Abigail; Murphy, Nei; Roy, Arpita; Haywood, Raphaelle D.; Rescigno, Federica; Bender, Chad F.; Lin, Andrea S. J.; Burt, Jennifer; Mahadevan, Suvrath
SolAster provides querying, analysis, and calculation methods to independently derive 'sun-as-a-star' RV variations using SDO/HMI data for any time span since SDO has begun observing. Scaling factors are provided in order to calculate RVs comparable to magnitudes measured by ground-based spectrographs (HARPS-N and NEID). In addition, there are routines to calculate magnetic observables to compare with RV variations and determine what is driving Solar activity.