Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Examples of minimal-memory, non-catastrophic quantum convolutional
  encoders   One of the most important open questions in the theory of quantum
convolutional coding is to determine a minimal-memory, non-catastrophic,
polynomial-depth convolutional encoder for an arbitrary quantum convolutional
code. Here, we present a technique that finds quantum convolutional encoders
with such desirable properties for several example quantum convolutional codes
(an exposition of our technique in full generality will appear elsewhere). We
first show how to encode the well-studied Forney-Grassl-Guha (FGG) code with an
encoder that exploits just one memory qubit (the former Grassl-Roetteler
encoder requires 15 memory qubits). We then show how our technique can find an
online decoder corresponding to this encoder, and we also detail the operation
of our technique on a different example of a quantum convolutional code.
Finally, the reduction in memory for the FGG encoder makes it feasible to
simulate the performance of a quantum turbo code employing it, and we present
the results of such simulations.

25
The categories of this paper are: patt-sol
30
The categories of this paper are: q-alg
35
The categories of this paper are: mtrl-th
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
24
The categories of this paper are: dg-ga
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph