论文标题

量子搜索缩放的哈希功能预映射

Quantum Search for Scaled Hash Function Preimages

论文作者

Ramos-Calderer, Sergi, Bellini, Emanuele, Latorre, José I., Manzano, Marc, Mateu, Victor

论文摘要

我们在量子模拟器中介绍了Grover算法的实现,以对两个缩放哈希函数的预图进行量子搜索,其设计仅使用模块化添加,单词旋转和位置独家或。我们的实施提供了精确评估的手段,以旨在查找给定哈希摘要的前图的完整量子电路的门数和深度的缩放。量子甲骨文的详细构造表明,与基于模块化添加,XOR门和旋转的其他哈希功能相比,与其他哈希函数相比,与其他哈希函数相比,钻头的存在和门或门的存在以及初始状态的重复使用需要额外的量子资源。我们还在沿计算的每个步骤中跟踪量子寄存器中存在的纠缠熵,这表明它在量子甲骨文的第一个动作的内核上变得最大,这意味着没有基于张紧网络的经典模拟是相关的。最后,我们表明,在格罗弗(Grover)算法的几步之后,基于对量子寄存器进行采样的策略,只能在缓解错误方面提供一些边际实践优势。

We present the implementation of Grover's algorithm in a quantum simulator to perform a quantum search for preimages of two scaled hash functions, whose design only uses modular addition, word rotation, and bitwise exclusive or. Our implementation provides the means to assess with precision the scaling of the number of gates and depth of a full-fledged quantum circuit designed to find the preimages of a given hash digest. The detailed construction of the quantum oracle shows that the presence of AND gates, OR gates, shifts of bits and the reuse of the initial state along the computation, require extra quantum resources as compared with other hash functions based on modular additions, XOR gates and rotations. We also track the entanglement entropy present in the quantum register at every step along the computation, showing that it becomes maximal at the inner core of the first action of the quantum oracle, which implies that no classical simulation based on Tensor Networks would be of relevance. Finally, we show that strategies that suggest a shortcut based on sampling the quantum register after a few steps of Grover's algorithm can only provide some marginal practical advantage in terms of error mitigation.

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