Stabilizer State

Stabilizer states, a class of easily-characterized quantum states, are central to quantum computation and error correction. Current research focuses on efficiently characterizing and learning these states, employing algorithms like agnostic tomography and quantum neural networks for tasks such as state reconstruction and decoding quantum information encoded in stabilizer codes. These efforts are crucial for advancing the development of fault-tolerant quantum computers, as the efficient manipulation and understanding of stabilizer states is fundamental to their operation and the mitigation of errors. Furthermore, the study of stabilizer states provides insights into the computational complexity of quantum algorithms and the nature of quantum pseudorandomness.