Double sparse quantum state preparation
AI Breakdown
Get a structured breakdown of this paper — what it's about, the core idea, and key takeaways for the field.
Abstract
Initializing classical data in a quantum device is an essential step in many quantum algorithms. As a consequence of measurement and noisy operations, some algorithms need to reinitialize the prepared state several times during its execution. If the quantum state preparation is not efficient, the quantum state preparation cost can dominate the computational cost of an algorithm. In this work, we propose a quantum state preparation algorithm, called CVO-QRAM algorithm, whose computational cost depends on the number of nonzero probability amplitudes and the maximum number of bits with a value of 1 in one of the patterns to be stored. The proposed algorithm can be an alternative to create sparse states in future noisy intermediate-scale quantum devices.