Feasibility Analysis of Grover-meets-Simon Algorithm
Qianru Zhu, Huiqin Xie, Qiqing Xia, Li Yang

TL;DR
This paper analyzes the feasibility of the Grover-meets-Simon quantum algorithm, concluding that it is not effective as an attack method when measurements are deferred to the end, due to issues with quantum measurement collapse and iterative processes.
Contribution
The paper provides a detailed feasibility analysis of the combined Grover-meets-Simon quantum algorithm, focusing on measurement timing and its impact on algorithm effectiveness.
Findings
Deferred measurement of Simon's algorithm is feasible within the combined algorithm.
The combined algorithm is ineffective as an attack when measurements are placed at the end.
Measurement collapse and iterative issues hinder the effectiveness of the combined approach.
Abstract
Quantum algorithm is a key tool for cryptanalysis. At present, people are committed to building powerful quantum algorithms and tapping the potential of quantum algorithms, so as to further analyze the security of cryptographic algorithms under quantum computing. Recombining classical quantum algorithms is one of the current ideas to construct quantum algorithms. However, they cannot be easily combined, the feasibility of quantum algorithms needs further analysis in quantum environment. This paper reanalyzes the existing combined algorithm Grover-meets-Simon algorithm in terms of the principle of deferred measurement. First of all, due to the collapse problem caused by the measurement, we negate the measurement process of Simon's algorithm during the process of the Grover-meets-Simon algorithm. Second, since the output of the unmeasured Simon algorithm is quantum linear systems of…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Chaos-based Image/Signal Encryption · Cryptography and Data Security
