Unveiling Uncertainty and Speed Limits in Krylov Space

This research explores fundamental limits in Krylov space, a concept important for understanding and optimizing numerical algorithms used in machine learning and scientific computing. The study's focus on uncertainty and speed limits could potentially lead to more efficient and accurate computational methods.

• •Investigates the interplay between uncertainty and geometric constraints within Krylov space.
• •Could have implications for developing faster and more reliable numerical algorithms.
• •Potentially relevant to fields like quantum computing and optimization problems.