We study the problem of finding $K$ collision pairs in a random function $f : [N] \rightarrow [N]$ by using a quantum computer. We prove that the number of queries to the function in the quantum random oracle model must increase significantly when the size of the available memory is limited. Namely, we demonstrate that any algorithm using $S$ qubits of memory must perform a number $T$ of queries that satisfies the tradeoff $T^3 S \geq \Omega(K^3 N)$. Classically, the same question has only been settled recently by Dinur [Eurocrypt'20], who showed that the Parallel Collision Search algorithm of van Oorschot and Wiener achieves the optimal time-space tradeoff of $T^2 S = \Theta(K^2 N)$. Our result limits the extent to which quantum computing may decrease this tradeoff. We further show that any improvement to our lower bound would imply a breakthrough for a related question about the Element Distinctness problem. Our method is based on a novel application of Zhandry's recording query technique [Crypto'19] for proving lower bounds in the exponentially small success probability regime.
翻译:我们研究在随机函数中寻找 $K$ 相撞对方的问题 : [N]\ rightrow [N] 美元 。 我们用量子计算机研究 。 我们证明, 当可用内存的大小有限时, 对量子随机质模型函数的查询数量必须大幅增加。 也就是说, 我们证明, 任何使用 $S 的记忆Qbits 的算法都必须执行数量T$T 3 S\geq\ omega (K)$3 N) 。 典型地说, 同一问题直到最近才由 Dinur [Eurocrypt'20] 解决, 他显示, vanorschot 和 Wiener 的平行串通搜索算算算算法实现了 $T+2 S =\ Theta (K) $的最佳时间空间交易。 我们的结果限制了量子计算能够减少这种交易的程度。 我们进一步表明, 任何对我们的低约束意味着, 与Elecleclecrition 问题相关的一个突破。 我们的方法是基于一个新型的Z 成功技术的试 。