Optimal Inapproximability with Universal Factor Graphs

by Per Austrin, Jonah Brown-Cohen, and Johan Hastad

Oded's comments

This natural notion of a universal factor graph was suggested by Feige and Jozeph, who showed non-optimal inapproximation results for Max-3SAT and other CSPs. (I am not sure I like the term `factor' and would prefer use `instance-graph'; also, I regret that I forgot to call attention to their work at the time.) Anyhow, this work shows that many of the most popular optimal inapproximability results for CSPs, extend to the case of universal factor graphs.

The original abstract

The factor graph of an instance of a constraint satisfaction problem (CSP) is the bipartite graph indicating which variables appear in each constraint. An instance of the CSP is given by the factor graph together with a list of which predicate is applied for each constraint. We establish that many Max-CSPs remains as hard to approximate as in the general case even when the factor graph is fixed (depending only on the size of the instance) and known in advance.
Examples of results obtained for this restricted setting are:

The main technical tool used to establish these results is a new way of folding the long code which we call ``functional folding''.

See ECCC TR19-151.

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