N$ Qubit

N-qubit systems are the focus of intense research aimed at efficiently learning and characterizing their complex quantum states and processes. Current efforts concentrate on developing algorithms that leverage techniques like Pauli transfer matrix analysis, stabilizer bootstrapping, and physics-informed neural networks to overcome the exponential scaling challenges inherent in full quantum tomography. These advancements are crucial for benchmarking quantum hardware, optimizing quantum algorithms, and enabling efficient prediction of quantum dynamics, ultimately accelerating progress in quantum computing and related fields.