.png){kind=icon}
返回
Eigen-Spectrum Estimation and Source Detection in a Massive Sensor Array Based on Quantum Assisted Hamiltonian Simulation Framework
.png){kind=icon}
PRE
AI
DOI：10.1109/TCOMM.2022.3167057.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
In this work, we propose quantum assisted eigenvalue estimation and target detection algorithms for a large sensor array via Hamiltonian simulation. Quantum algorithms provide complexity advantage of a certain class of problems on a quantum computer with fewer physical resources as compared to their classical counterparts. The proposed algorithms make use of the quantum phase estimation (QPE) as its core computing component. We have introduced an analytical quantum framework to map from classical to quantum in the context of target detection. Target detection involves an appropriate choice of threshold based on the probability of detection or false alarm. We exploited the massive sensor array structure and invoked the random matrix theory to propose an optimal threshold. It also takes into account the quantum measurement noise in the framework. Numerical simulations are performed to ascertain the efficacy of the proposed framework. The results suggest near term applications of the quantum algorithm for large-scale linear systems.
Keyword:
Quantum computing
Estimation
Eigenvalues and eigenfunctions
Signal processing algorithms
Sensor arrays
Covariance matrices
Computational modeling
Quantum signal processing
quantum eigenvalue estimation
quantum phase estimation
Hamiltonian simulation
array signal processing
期刊
IF:
8.3
论文数:
1.2W
被引数:
3.6W
机构
引用论文
Quantum-Assisted Indoor Localization for Uplink mm-Wave and Downlink Visible Light Communication Systems上行毫米波和下行可见光通信系统的量子辅助室内定位.png)
IEEE ACCESS
OAAI
IEEE ACCESSIF3.6
OAAI分享收藏
查看更多内容