Tensor Networks

Tensor networks are mathematical tools that help represent and analyze complex data structures by breaking them down into interconnected smaller parts called tensors. Think of them like a map of interconnected roads, where each intersection (tensor) holds information, and the roads (connections) show how data points relate. This structure simplifies calculations and makes handling large-scale, high-dimensional data more efficient, especially in fields like physics, machine learning, and data science. Essentially, tensor networks organize complex data into manageable, interconnected pieces, enabling better understanding and computation of vast, intricate systems.