Publication in Physical Review Research: “Quantum convolutional neural network for phase recognition in two dimensions”
On November 7th, Physical Review Research has published our work which had appeared earlier as a pre-print. This project was jointly realized by Leon C. Sander, Nathan A. McMahon, Petr Zapletal, and Michael J. Hartmann.
In this work, we construct a QCNN that can perform phase recognition in two dimensions and correctly identify the phase transition from a toric code phase with ℤ2 topological order to the paramagnetic phase. The network also exhibits a noise threshold up to which the topological order is recognized. Furthermore, it captures correlations between all stabilizer elements of the toric code, which cannot be accessed by direct measurements. This increases the threshold for errors leading to such correlations and allows for correctly identifying the topological phase in the presence of strong correlated errors. Our work generalizes phase recognition with QCNNs to higher spatial dimensions and intrinsic topological order, where exploration and characterization via classical numerics become challenging.