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We present a new open source python package, based on PyLightcurve andPyTorch, tailored for efficient computation and automatic differentiation ofexoplanetary transits. The classes and functions implemented are fullyvectorised, natively GPU-compatible and differentiable with respect to thestellar and planetary parameters. This makes PyLightcurve-torch suitable fortraditional forward computation of transits, but also extends the range ofpossible applications with inference and optimisation algorithms requiringaccess to the gradients of the physical model. This endeavour is aimed atfostering the use of deep learning in exoplanets research, motivated by an everincreasing amount of stellar light curves data and various incentives for theimprovement of detection and characterisation techniques.

PyLightcurve-torch: a transit modelling package for deep learning applications in PyTorch