  We introduce JAX FDM, a differentiable solver to design mechanically
efficient shapes for 3D structures conditioned on target architectural,
fabrication and structural properties. Examples of such structures are domes,
cable nets and towers. JAX FDM solves these inverse form-finding problems by
combining the force density method, differentiable sparsity and gradient-based
optimization. Our solver can be paired with other libraries in the JAX
ecosystem to facilitate the integration of form-finding simulations with neural
networks. We showcase the features of JAX FDM with two design examples. JAX FDM
is available as an open-source library at
https://github.com/arpastrana/jax_fdm.
