We introduce tensor-network stabilizer codes which come with a natural tensor-network
decoder. These codes can correspond to any geometry, but, as a special case, we …

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 …

We consider tensor-network stabilizer codes and show that their tensor-network decoder
has the property that independent logical qubits can be decoded in parallel. As long as the …

Tensor-network codes enable the construction of large stabilizer codes out of tensors
describing smaller stabilizer codes. An application of tensor-network codes was an efficient …

Arikan's Polar codes attracted much attention as the first efficiently decodable and capacity
achieving codes. Furthermore, Polar codes exhibit an exponentially decreasing block error …

Most modern communication systems, such as those intended for deployment in IoT
applications or 5G and beyond networks, utilize multiple domains for transmission and …

We propose in this paper a new coding scheme called twisted-pair superposition
transmission (TPST). The encoding is to “mix together” a pair of basic codes by …

“Bounds on information combining” are entropic inequalities that determine how the
information (entropy) of a set of random variables can change when these are combined in …

BMERA or convolutional polar codes are an extension of polar codes with a provably better
error exponent than polar codes. A successive cancellation (SC) decoding algorithm for …

The continuous multiscale entanglement renormalization ansatz (cMERA) is a variational
class of states for quantum fields. As originally formulated, the cMERA applies to infinite …