Quantum frequency resampling

IF 6.6 1区 物理与天体物理 Q1 PHYSICS, APPLIED
Emanuele Tumbiolo, Simone Roncallo, Chiara Macchiavello, Lorenzo Maccone
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Abstract

In signal processing, resampling algorithms can modify the number of resources encoding a collection of data points. Downsampling reduces the cost of storage and communication, while upsampling interpolates new data from limited one, e.g., when resizing a digital image. We present a toolset of quantum algorithms to resample data encoded in the probabilities of a quantum register, using the quantum Fourier transform to adjust the number of high-frequency encoding qubits. We discuss advantage over classical resampling algorithms.

Abstract Image

量子频率重采样
在信号处理中,重采样算法可以修改编码数据点集合的资源数量。下采样降低了存储和通信的成本,而上采样从有限的数据中插入新数据,例如,当调整数字图像的大小时。我们提出了一套量子算法工具集,使用量子傅立叶变换来调整高频编码量子位的数量,对量子寄存器概率中编码的数据进行重新采样。我们讨论了优于经典重采样算法的优点。
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来源期刊
npj Quantum Information
npj Quantum Information Computer Science-Computer Science (miscellaneous)
CiteScore
13.70
自引率
3.90%
发文量
130
审稿时长
29 weeks
期刊介绍: The scope of npj Quantum Information spans across all relevant disciplines, fields, approaches and levels and so considers outstanding work ranging from fundamental research to applications and technologies.
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