Optimization of tensor network codes with reinforcement learning
Tensor network codes enable structured construction and manipulation of stabilizer codes out of small seed codes. Here, we apply reinforcement learning (RL) to tensor network code geometries and demonstrate how optimal stabilizer codes can be found. Using the projective simulation framework, our RL...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IOP Publishing
2024-01-01
|
| Series: | New Journal of Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1088/1367-2630/ad23a6 |