A long-standing problem in quantum information is: what are the resources that make quantum computers able to perform computational tasks in a way that outperforms any kind of classical Turing machine? The flip side of the same question is: what makes quantum mechanics so hard to simulate? These questions are at the core of the notion of quantum complexity. I am currently developing an approach to the rigorous treatment of quantum complexity through the interplay of two types of quantum entropies: Entanglement Entropy (EE) and Stabilizer Entropy (SE). 

The decoding algorithm in [Leo24b] features an efficient representation for quasi-chaotic circuits, but still requires exponential resources for the learning. I am looking for an efficient polynomial algorithm for this task, thereby making the decoding of quasi-chaotic quantum circuits an efficient task from scratch.