20 April 2020
Intuition tells us that it should be easier to scramble a solved Rubik’s cube than to solve a scrambled one. Computer scientists recently discovered tantalizing evidence that, for a broad and important class of puzzles with continuous symmetries, that intuition may well be mistaken! In this project, we will develop novel algorithms for solving such puzzles much more efficiently than was previously thought possible. This has important applications for ‘tensors’ (large arrays of high-dimensional data that are ubiquitous in machine learning and quantum computing, but which are notoriously difficult to work with), and promises to shed new light on fundamental questions about the speed limits of computation.
KLEIN grants are intended for realising curiosity-driven, fundamental research of high quality and/or scientific urgency. The KLEIN grant offers researchers the possibility to elaborate creative and risky ideas and to realise scientific innovations that can form the basis for the research themes of the future.