Static and dynamic coherence fraction in the Bernstein-Vazirani algorithm
Si-Qi Zhou, Jin-Min Liang, Jiayin Peng, Zhihua Chen, Shao-Ming Fei, and Zhihao Ma

TL;DR
This paper investigates how the coherence fraction of the initial quantum state influences the success probability of the Bernstein-Vazirani algorithm, revealing that coherence fraction alone determines the algorithm's efficiency.
Contribution
It establishes a direct link between the coherence fraction and the success probability of the Bernstein-Vazirani algorithm, highlighting the importance of coherence in quantum computational performance.
Findings
Success probability depends solely on the coherence fraction of the initial state.
Coherence fraction dynamics relate to the algorithm's efficiency.
Quantum coherence fraction influences the effectiveness of quantum algorithms.
Abstract
Quantum entanglement and coherence are crucial resources in quantum information theory. In some scenarios, however, it is not necessary to directly estimate entanglement or coherence measures to quantify the capabilities of a state in quantum information processing. Instead, fully entangled fraction and coherence fraction are two alternatives for entanglement and coherence in specific quantum tasks. Here, we establish a link between the coherence fraction and the Bernstein-Vazirani algorithm, which has several potential applications including cryptography and database search. We show that the success probability of the generalized Bernstein-Vazirani algorithm depends only on the coherence fraction of the initial state rather than its entanglement or coherence. Moreover, we discuss the coherence fraction dynamics and establish a relation between the operator's coherence fraction and the…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Neural Networks and Reservoir Computing
