Zhiyang He, Anand Natarajan, et al.
APS March Meeting 2023
We consider a two-dimensional quantum memory of qubits on a torus encoding an extended Fibonacci string-net model, and construct error correction strategies when those qubits are subjected to depolarizing noise. In the case of a fixed-rate sampling noise model, we find an error correcting threshold of 4.75% with a clustering decoder. Using the concept of tube algebras, we construct a set of measurements and of quantum gates which map arbitrary qubit errors to the Turaev-Viro subspace. Tensor network techniques then allow to quantitatively study the action of Pauli noise on that subspace. We perform Monte-Carlo simulations of the Fibonacci code, and compare the performance of several decoders. To the best of our knowledge, this is the first time that a threshold has been calculated for a two-dimensional error correcting code in which universal quantum computation can be performed in its code space.
Zhiyang He, Anand Natarajan, et al.
APS March Meeting 2023
Blake Johnson
APS March Meeting 2024
Ramis Movassagh, Yingkai Ouyang
QIP 2021
Alireza Seif, Haoran Liao, et al.
ISCA 2024