Deriving differential approximation results for $k\,$CSPs from combinatorial designs
<|reference_start|>Deriving differential approximation results for $k\,$CSPs from combinatorial designs: Traditionally, inapproximability results for $\mathsf{Max\,k\,CSP\!-\!q}$ have been established using balanced $t$-wise independent distributions, which are related to orthogonal arrays of strength $t$. We contribute to the field by exploring such combinatorial designs in the context of the differential approximation measure. First, we establish a connection between the average differential ratio and orthogonal arrays. We deduce a differential approximation ratio of $1/q^k$ on $(k +1)$-partite instances of $\mathsf{k\,CSP\!-\!q}$, $\Omega(1/n^{k/2})$ on Boolean instances, $\Omega(1/n)$ when $k =2$, and $\Omega(1/\nu^{k -\lceil\log_{p^\kappa} k\rceil})$ when $k\geq 3$ and $q\geq 3$, where $p^\kappa$ is the smallest prime power greater than $q$. Secondly, by considering pairs of arrays related to balanced $k$-wise independence, we establish a reduction from $\mathsf{k\,CSP\!-\!q}$ to $\mathsf{k\,CSP\!-\!k}$ (with $q>k$), with an expansion factor of $1/(q -k/2)^k$ on the differential approximation guarantee. This, combined with the result of Yuri Nesterov, implies a lower differential approximability bound of $0.429/(q -1)^2$ for $\mathsf{2\,CSP\!-\!q}$. Finally, we prove that every Hamming ball with radius $k$ provides a $\Omega(1/n^k)$-approximation of the instance diameter. Our work highlights the utility of combinatorial designs in establishing approximation results.<|reference_end|>
@article{culus2024deriving,
    title={Deriving differential approximation results for $k\,$CSPs from
  combinatorial designs},
    author={Jean-Franc{c}ois Culus and Sophie Toulouse},
    journal={arXiv preprint arXiv:2409.03903},
    year={2024},
    archivePrefix={arXiv},
    eprint={2409.03903},
    primaryClass={math.CO cs.CC}
}