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YNOGK, written in Fortran, calculates the null geodesics in the Kerr spacetime. It uses Weierstrass' and Jacobi's elliptic functions to express all coordinates and affine parameters as analytical and numerical functions of a parameter $p$, which is an integral value along the geodesic. The information about the turning points do not need to be specified in advance by the user, allowing applications such as imaging, the calculation of line profiles or the observer-emitter problem to become root finding problems. Elliptic integrations are computed by Carlson's elliptic integral method, which allows fast computation.
YNOGKM (Yun-Nan observatories geodesic in a Kerr-Newman spacetime for massive particles) performs fast calculation of time-like geodesics in the Kerr-Newman (K-N) spacetime; it is a direct extension of YNOGK (Yun-Nan observatories geodesic Kerr) calculating null geodesics in a Kerr spacetime. The four Boyer-Lindquis coordinates and proper time are expressed as functions of a parameter p semi-analytically by using the Weierstrass' and Jacobi's elliptic functions and integrals. The elliptic integrals are computed by Carlson's elliptic integral method, which guarantees the fast speed of the code. The source Fortran file ynogkm.f90 contains three modules: constants, rootfind, ellfunction, and blcoordinates.
Lemon solves the radiative transfer (RT) processes that contain scattering. These processes are described by differentio-integral equations with given initial or boundary conditions; Lemon solves these differentio-integral equations, which can be converted into the second kind integral equations of Fredholm. The code then obtains the Neumman solution (a series that consists of infinite terms of multiple integrals) from the Fredholm integral equation, and uses the Monte Carlo (MC) method to evaluate these integrals. Lemon is written in Fortran; IDL programs are included for plotting the results.
kpic_pipeline reduces data taken with the Keck Planet Imager and Characterizer (KPIC). Written in Python, the code processes high resolution spectroscopy data taken with KPIC to study exoplanet atmospheres; it processes and calibrate the data to enable spectroscopic model fitting. kpic_pipeline can reduce the observed data into 1D spectra for one given science target or can be used to reduce the full nightly data.