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Quantum random walks (QRWs) are random processes in which the resulting probability density of the "walker" state, whose movement is governed by a "coin" state, is described in a non-classical manner. Previously, Q-plates have been used to…

Quantum Machine Learning (QML) has seen significant advancements, driven by recent improvements in Noisy Intermediate-Scale Quantum (NISQ) devices. Leveraging quantum principles such as entanglement and superposition, quantum convolutional…

The classical image segmentation algorithm based on local adaptive threshold can effectively segment images with uneven illumination, but with the increase of the image data, the real-time problem gradually emerges. In this paper, a quantum…

Quantum Physics · Physics 2024-05-14 Lu Wang , Wenjie Liu

Quantum walks are central to a wide range of applications such as quantum search, quantum information processing, and entanglement transport. Gaining control over the duration and the direction of quantum walks (QWs) is crucial to…

This work describes a new algorithm for creating a superposition over the edge set of a graph, encoding a quantum sample of the random walk stationary distribution. The algorithm requires a number of quantum walk steps scaling as…

Quantum Physics · Physics 2019-04-26 Simon Apers

This paper develops a unified framework for quantum wavelet shrinkage, extending classical denoising ideas into the quantum domain. Shrinkage is interpreted as a completely positive trace-preserving process, so attenuation of coefficients…

Quantum Physics · Physics 2025-11-26 Brani Vidakovic

In this paper, we propose a preprocessing method for conventional image and video encoders that can make these existing encoders content-aware. By going through our process, a higher quality parameter could be set on a traditional encoder…

Computer Vision and Pattern Recognition · Computer Science 2020-09-02 Likun Liu , Hua Qi

Hard combinatorial optimization problems, often mapped to Ising models, promise potential solutions with quantum advantage but are constrained by limited qubit counts in near-term devices. We present an innovative quantum-inspired framework…

Quantum Physics · Physics 2024-12-25 Co Tran , Quoc-Bao Tran , Hy Truong Son , Thang N Dinh

Quantized Neural Networks (QNNs), which use low bitwidth numbers for representing parameters and performing computations, have been proposed to reduce the computation complexity, storage size and memory usage. In QNNs, parameters and…

Computer Vision and Pattern Recognition · Computer Science 2017-06-23 Shuchang Zhou , Yuzhi Wang , He Wen , Qinyao He , Yuheng Zou

Quantum inspired evolutionary optimization leverages quantum computing principles like superposition, interference, and probabilistic representation to enhance classical evolutionary algorithms with improved exploration and exploitation…

Computational Engineering, Finance, and Science · Computer Science 2025-11-11 Aman Mittal , Kasturi Venkata Sai Srikanth , Ferdin Sagai Don Bosco , Abhishek Singh , Rut Lineswala , Abhishek Chopra

Quanta Image Sensor (QIS) is a binary imaging device envisioned to be the next generation image sensor after CCD and CMOS. Equipped with a massive number of single photon detectors, the sensor has a threshold $q$ above which the number of…

Computer Vision and Pattern Recognition · Computer Science 2019-03-22 Omar A. Elgendy , Stanley H. Chan

Quantitative phase imaging (QPI) is important in many applications such as microscopy and crystallography. To quantitatively reveal phase information, people could either employ interference to map phase distribution into intensity fringes,…

Optics · Physics 2020-11-11 Xianye Li , Yafei sun , Yikang He , Xun Li , Baoqing Sun

We compare a parameterized quantum kernel (pQK) with a quantum leaky integrate-and-fire (QLIF) neuromorphic computing approach that employs either the Victor-Purpura or van Rossum kernel in a spectral clustering task, as well as the…

Quantum Physics · Physics 2026-04-14 Donovan Slabbert , Dean Brand , Francesco Petruccione

We address the quantum search of a target node on a cycle graph by means of a quantum walk assisted by continuous measurement and feedback. Unlike previous spatial search approaches, where the oracle is described as a projector on the…

Quantum Physics · Physics 2022-11-11 Alessandro Candeloro , Claudia Benedetti , Marco G. Genoni , Matteo G. A. Paris

We perform generalized measurements of a qubit by realizing the qubit as a coin in a photonic quantum walk and subjecting the walker to projective measurements. Our experimental technique can be used to realize photonically any rank-1…

Quantum Physics · Physics 2015-08-11 Zhihao Bian , Jian Li , Hao Qin , Xiang Zhan , Rong Zhang , Barry C. Sanders , Peng Xue

We analyze the realization of a quantum-walk search algorithm in a passive, linear optical network. The specific model enables us to consider the effect of realistic sources of noise and losses on the search efficiency. Photon loss uniform…

Quantum Physics · Physics 2008-02-04 A. Gabris , T. Kiss , I. Jex

We study the query-based attack against image retrieval to evaluate its robustness against adversarial examples under the black-box setting, where the adversary only has query access to the top-k ranked unlabeled images from the database.…

Computer Vision and Pattern Recognition · Computer Science 2021-03-24 Xiaodan Li , Jinfeng Li , Yuefeng Chen , Shaokai Ye , Yuan He , Shuhui Wang , Hang Su , Hui Xue

Computing using a continuous-time evolution, based on the natural interaction Hamiltonian of the quantum computer hardware, is a promising route to building useful quantum computers in the near-term. Adiabatic quantum computing, quantum…

Quantum Physics · Physics 2019-03-06 James G. Morley , Nicholas Chancellor , Sougato Bose , Viv Kendon

Lackadaisical quantum walk(LQW) has been an efficient technique in searching a target state from a database which is distributed on a two-dimensional lattice. We numerically study the quantum search algorithm based on the lackadaisical…

Quantum Physics · Physics 2019-12-04 Pulak Ranjan Giri , Vladimir Korepin

There is currently no unified metric for evaluating the efficiency of quantized neural networks. We propose QuIDE, built around the Intelligence Index I = (C x P)/log_2(T+1), which collapses the compression-accuracy-latency trade-off into a…

Machine Learning · Computer Science 2026-05-13 Xiantao Jiang
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