  We present TORAX, a new, open-source, differentiable tokamak core transport
simulator implemented in Python using the JAX framework. TORAX solves the
coupled equations for ion heat transport, electron heat transport, particle
transport, and current diffusion, incorporating modular physics-based and ML
models. JAX's just-in-time compilation ensures fast runtimes, while its
automatic differentiation capability enables gradient-based optimization
workflows and simplifies the use of Jacobian-based PDE solvers. Coupling to
ML-surrogates of physics models is greatly facilitated by JAX's intrinsic
support for neural network development and inference. TORAX is verified against
the established RAPTOR code, demonstrating agreement in simulated plasma
profiles. TORAX provides a powerful and versatile tool for accelerating
research in tokamak scenario modeling, pulse design, and control.
