Fine-grained hardness of CVP(P) -- Everything that we can prove (and nothing else)

We show a number of fine-grained hardness results for the Closest Vector Problem in the $\ell_p$ norm ($\mathrm{CVP}_p$), and its approximate and non-uniform variants. First, we show that $\mathrm{CVP}_p$ cannot be solved in $2^{(1-\varepsilon)n}$ time for all $p \notin 2\mathbb{Z}$ and $\varepsilon > 0$, assuming the Strong Exponential Time Hypothesis (SETH). Second, we extend this by showing that there is no $2^{(1-\varepsilon)n}$-time algorithm for approximating $\mathrm{CVP}_p$ to within a constant factor $γ$ for such $p$ assuming a "gap" version of SETH, with an explicit relationship between $γ$, $p$, and the arity $k = k(\varepsilon)$ of the underlying hard CSP. Third, we show the same hardness result for (exact) $\mathrm{CVP}_p$ with preprocessing (assuming non-uniform SETH). For exact "plain" $\mathrm{CVP}_p$, the same hardness result was shown in [Bennett, Golovnev, and Stephens-Davidowitz FOCS 2017] for all but finitely many $p \notin 2\mathbb{Z}$, where the set of exceptions depended on $\varepsilon$ and was not explicit. For the approximate and preprocessing problems, only very weak bounds were known prior to this work. We also show that the restriction to $p \notin 2\mathbb{Z}$ is in some sense inherent. In particular, we show that no "natural" reduction can rule out even a $2^{3n/4}$-time algorithm for $\mathrm{CVP}_2$ under SETH. For this, we prove that the possible sets of closest lattice vectors to a target in the $\ell_2$ norm have quite rigid structure, which essentially prevents them from being as expressive as $3$-CNFs. We prove these results using techniques from many different fields, including complex analysis, functional analysis, additive combinatorics, and discrete Fourier analysis. E.g., along the way, we give a new (and tighter) proof of Szemerédi's cube lemma for the boolean cube.