Consider an assignment of bits to the vertices of a connected graph $G(V,E)$ with the property that the value of each vertex is a function of the values of its neighbors. A collection of such assignments is called a {\em storage code} of length $|V|$ on $G$. The storage code problem can be equivalently formulated as maximizing the probability of success in a {\em guessing game} on graphs, or constructing {\em index codes} of small rate. If $G$ contains many cliques, it is easy to construct codes of rate close to 1, so a natural problem is to construct high-rate codes on triangle-free graphs, where constructing codes of rate $>1/2$ is a nontrivial task, with few known results. In this work we construct infinite families of linear storage codes with high rate relying on coset graphs of binary linear codes. We also derive necessary conditions for such codes to have high rate, and even rate potentially close to one. We also address correction of multiple erasures in the codeword, deriving recovery guarantees based on expansion properties of the graph. Finally, we point out connections between linear storage codes and quantum CSS codes, a link to bootstrap percolation and contagion spread in graphs, and formulate a number of open problems.
翻译:将位元分配到连接的图形$G( V, E) 的顶点, 其属性是每个顶点的价值是其邻居的价值的函数。 收集的这种任务被称为一个长度为$V+$(美元美元)的储量代码。 存储代码问题可以等同地写成, 在图表上最大限度地增加一个 [ 猜测游戏] 成功概率, 或者在小速率中构建 $G (V, E) 指数代码。 如果$G$ 包含许多 cluques, 很容易在离1 的值上建立费率代码, 所以自然的问题是在无三角图上建立高利率代码, 在那里, $>1/2$ 的代码是非三维任务, 没有多少已知结果。 在这项工作中, 我们构建线性存储代码的无限组合, 高度依赖二进制线代码的组合图。 我们还为这种代码创造必要的条件, 甚至可能接近于一个。 我们还在代码的代码中纠正多个刻度,, 将回收保证建立在图表的直径存储器和直径存储的代码连接中。 最后, 我们在图表的代码和直径式代码中, 的代码中绘制一个线性代码的代码。