//! # PolarQuant
//!
//! Walsh-Hadamard rotation + polar coordinate quantization for LLM weight and KV cache compression.
//!
//! ## Overview
//! PolarQuant compresses neural network weights and KV cache embeddings by:
//! 1. Block-wise L2 normalization to the unit hypersphere
//! 2. Walsh-Hadamard rotation to decorrelate values into approximately i.i.d. Gaussian
//! 3. Recursive polar coordinate transformation
//! 4. Lloyd-Max optimal codebook quantization of resulting angles
//!
//! Work in progress. Contributions welcome.