Parameterized Intractability of Even Set and Shortest Vector Problem

TL;DR

This paper proves that two important parameterized problems, the $k$-Even Set and the $k$-Shortest Vector Problem, are W[1]-hard, indicating their fixed-parameter intractability under randomized reductions, resolving longstanding open questions.

Contribution

It establishes the W[1]-hardness of the $k$-Even Set and $k$-SVP problems, showing they are unlikely to be fixed-parameter tractable.

Findings

$k$-Even Set is W[1]-hard under randomized reductions.

$k$-SVP is W[1]-hard to approximate for any $p > 1$.

Addresses long-standing open questions in parameterized complexity.

Abstract

The $k$-Even Set problem is a parameterized variant of the Minimum Distance Problem of linear codes over $\mathbb F_2$, which can be stated as follows: given a generator matrix $\mathbf A$ and an integer $k$, determine whether the code generated by $\mathbf A$ has distance at most $k$, or in other words, whether there is a nonzero vector $\mathbf{x}$ such that $\mathbf A \mathbf{x}$ has at most $k$ nonzero coordinates. The question of whether $k$-Even Set is fixed parameter tractable (FPT) parameterized by the distance $k$ has been repeatedly raised in literature; in fact, it is one of the few remaining open questions from the seminal book of Downey and Fellows (1999). In this work, we show that $k$-Even Set is W[1]-hard under randomized reductions. We also consider the parameterized $k$-Shortest Vector Problem (SVP), in which we are given a lattice whose basis vectors are integral and an integer $k$, and the goal is to determine whether the norm of the shortest vector (in the $\ell_p$ norm for some fixed $p$) is at most $k$. Similar to $k$-Even Set, understanding the complexity of this problem is also a long-standing open question in the field of Parameterized Complexity. We show that, for any $p > 1$, $k$-SVP is W[1]-hard to approximate (under randomized reductions) to some constant factor.