Statistical mechanics of error exponents for error-correcting codes

Error exponents characterize the exponential decay, when increasing message length, of the probability of error of many error-correcting codes. To tackle the long standing problem of computing them exactly, we introduce a general, thermodynamic, formalism that we illustrate with maximum-likelihood decoding of low-density parity-check (LDPC) codes on the binary erasure channel (BEC) and the binary symmetric channel (BSC). In this formalism, we apply the cavity method for large deviations to derive expressions for both the average and typical error exponents, which differ by the procedure used to select the codes from specified ensembles. When decreasing the noise intensity, we find that two phase transitions take place, at two different levels: a glass to ferromagnetic transition in the space of codewords, and a paramagnetic to glass transition in the space of codes.Comment: 32 pages, 13 figure

The complexity of approximately counting in 2-spin systems on kk-uniform bounded-degree hypergraphs

One of the most important recent developments in the complexity of approximate counting is the classification of the complexity of approximating the partition functions of antiferromagnetic 2-spin systems on bounded-degree graphs. This classification is based on a beautiful connection to the so-called uniqueness phase transition from statistical physics on the infinite $\Delta$-regular tree. Our objective is to study the impact of this classification on unweighted 2-spin models on $k$-uniform hypergraphs. As has already been indicated by Yin and Zhao, the connection between the uniqueness phase transition and the complexity of approximate counting breaks down in the hypergraph setting. Nevertheless, we show that for every non-trivial symmetric $k$-ary Boolean function $f$ there exists a degree bound $\Delta_0$ so that for all $\Delta \geq \Delta_0$ the following problem is NP-hard: given a $k$-uniform hypergraph with maximum degree at most $\Delta$, approximate the partition function of the hypergraph 2-spin model associated with $f$. It is NP-hard to approximate this partition function even within an exponential factor. By contrast, if $f$ is a trivial symmetric Boolean function (e.g., any function $f$ that is excluded from our result), then the partition function of the corresponding hypergraph 2-spin model can be computed exactly in polynomial time