Purest Quantum State Identification
Yingqi Yu, Honglin Chen, Jun Wu, Wei Xie, Xiangyang Li

TL;DR
This paper introduces a new framework for identifying the least noisy quantum states among multiple unknown states, using adaptive and coherent measurement strategies to improve accuracy and quantify quantum memory advantages.
Contribution
It formulates a rigorous paradigm for purest quantum state identification, deriving optimal algorithms and bounds that demonstrate the power of coherent measurements over incoherent strategies.
Findings
Adaptive algorithm achieves exponentially decreasing error with N
Coherent measurement protocol outperforms incoherent strategies
Lower bounds show limitations of fixed two-outcome incoherent POVMs
Abstract
Quantum noise constitutes a fundamental obstacle to realizing practical quantum technologies. To address the pivotal challenge of identifying quantum systems least affected by noise, we introduce the purest quantum state identification, which can be used to improve the accuracy of quantum computation and communication. We formulate a rigorous paradigm for identifying the purest quantum state among unknown -qubit quantum states using total quantum state copies. For incoherent strategies, we derive the first adaptive algorithm achieving error probability , fundamentally improving quantum property learning through measurement optimization. By developing a coherent measurement protocol with error bound , we demonstrate a significant separation from…
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Taxonomy
TopicsQuantum Mechanics and Applications · Quantum Information and Cryptography
