Peter Shor

Random classical linear codes are widely believed to be hard to decode, exponentially so at constant coding rate. If the rate vanishes asymptotically sufficiently rapidly, slightly sub-exponential decoding algorithms are known. By contrast, the complexity of decoding a random quantum stabilizer code has remained an open question for quite some time. This work closes the gap in our understanding of the algorithmic hardness of decoding random quantum versus random classical codes. We prove that decoding a random stabilizer code with even a single logical qubit is at least as hard as decoding a random classical code at constant rate—the maximally hard regime. This result suggests that the easiest random quantum decoding problem is at least as hard as the hardest random classical decoding problem, and shows that any sub-exponential algorithm decoding a typical stabilizer code, at any coding rate, would immediately imply a breakthrough in cryptography. More generally, we also characterize many other complexity-theoretic properties of stabilizer codes. While classical decoding admits a random self-reduction, we prove significant barriers for the existence of random self-reductions in the quantum case. This result follows from new bounds on Clifford entropies and Pauli mixing times, which may be of independent interest. As a complementary result, we demonstrate various other self-reductions which are in fact achievable, such as between search and decision. Our work also demonstrates several ways in which quantum phenomena, such as quantum degeneracy, force several reasonable definitions of stabilizer decoding—all of which are classically identical—to have distinct or non-trivially equivalent complexity.

There are a number of interesting, open additivity questions in quantum information theory. Recently, I have been able to show that some of these are equivalent. I will discuss open additivity questions in general and this proof of equivalence in particular.

I will explain how quantum error correcting codes work, using a few simple examples, and introduce some of the general theory of quantum error correction.