In a recent note we derived information theoretic upper bounds on the rate of $q$-ary $2$-separable codes and on the rate of $q$-ary $B_2$ codes based on an entropy argument applied coordinate-wise to a suitable pair of random suffixes of codewords. In the $B_2$ case, the bound was obtained by maximizing the entropy of the difference $X-Y$ of two independent $q$-ary random variables under the sole constraint $\mathbb{P}(X=Y)\geq 1/q$. In this paper we refine this step by exploiting the full Fourier-analytic structure of the difference distribution $X-Y$. More precisely, we use that the pmf of $X-Y$ is an autocorrelation of a probability mass function on $\{0,\dots,q-1\}$ and therefore its Fourier transform is a nonnegative trigonometric polynomial of prescribed degree. This leads to a natural convex optimization problem over the coefficients of such polynomials whose optimal value yields a strictly smaller upper bound on the entropy of $X-Y$ and, in turn, to improved bounds on the rate of $q$-ary $B_2$ codes. We evaluate the resulting bound numerically via truncated Toeplitz SDPs and show that for $q\in\{9,10,11,12,13\}$ the new rate upper bounds improve upon the best available bounds in the literature.

翻译：暂无翻译