torch-harmonics implements differentiable spherical harmonic transforms and related signal processing operations within the PyTorch framework. The library provides GPU-accelerated primitives for computing spherical Fourier transforms, convolution operations, and other harmonic analysis tools that maintain gradient flow during backpropagation. These components serve as building blocks for neural networks operating on spherical data such as global climate data, molecular structures, or 3D point clouds.