Researchers have developed an algorithmic framework called iterative tensor network transformations (ITNTs) to efficiently evaluate nonlinear operations on compressed data. ITNTs can operate on exponentially large datasets while maintaining a controlled computational cost. This method has been demonstrated in two areas: evaluating highly nonlinear functions on a 3D reactive flow field and finding extrema in complex optimization problems. --- Why it matters: This matters because it enables tensor network methods to be used for general-purpose data science and large-scale optimization, which could have significant impacts on fields like materials science, chemistry, and computer science. Source: https://arxiv.org/abs/2608.17135