Quantum Inverse Fast Fourier Transform

Mayank Roy, Devi Maheswaran
{"title":"Quantum Inverse Fast Fourier Transform","authors":"Mayank Roy, Devi Maheswaran","doi":"arxiv-2409.07983","DOIUrl":null,"url":null,"abstract":"In this paper, an algorithm for Quantum Inverse Fast Fourier Transform\n(QIFFT) is developed to work for quantum data. Analogous to a classical\ndiscrete signal, a quantum signal can be represented in Dirac notation,\napplication of QIFFT is a tensor transformation from frequency domain to time\ndomain. If the tensors are merely complex entries, then we get the classical\nscenario. We have included the complete formulation of QIFFT algorithm from the\nclassical model and have included butterfly diagram. QIFFT outperforms regular\ninversion of Quantum Fourier Transform (QFT) in terms of computational\ncomplexity, quantum parallelism and improved versatility.","PeriodicalId":501034,"journal":{"name":"arXiv - EE - Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - EE - Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.07983","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this paper, an algorithm for Quantum Inverse Fast Fourier Transform (QIFFT) is developed to work for quantum data. Analogous to a classical discrete signal, a quantum signal can be represented in Dirac notation, application of QIFFT is a tensor transformation from frequency domain to time domain. If the tensors are merely complex entries, then we get the classical scenario. We have included the complete formulation of QIFFT algorithm from the classical model and have included butterfly diagram. QIFFT outperforms regular inversion of Quantum Fourier Transform (QFT) in terms of computational complexity, quantum parallelism and improved versatility.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
量子反快速傅里叶变换
本文开发了一种用于量子数据的量子反快速傅里叶变换(QIFFT)算法。与经典离散信号类似,量子信号可以用狄拉克符号表示,QIFFT 的应用是从频域到时域的张量变换。如果张量只是复数项,那么我们得到的就是经典方案。我们在经典模型中加入了 QIFFT 算法的完整表述,并附上了蝶形图。QIFFT 在计算复杂性、量子并行性和通用性方面都优于量子傅里叶变换(QFT)的常规转换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Blind Deconvolution on Graphs: Exact and Stable Recovery End-to-End Learning of Transmitter and Receiver Filters in Bandwidth Limited Fiber Optic Communication Systems Atmospheric Turbulence-Immune Free Space Optical Communication System based on Discrete-Time Analog Transmission User Subgrouping in Scalable Cell-Free Massive MIMO Multicasting Systems Covert Communications Without Pre-Sharing of Side Information and Channel Estimation Over Quasi-Static Fading Channels
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1