Results 21 to 30 of about 3,788 (102)

Quantifying the impact of precision errors on quantum approximate optimization algorithms

Physical Review Research
The quantum approximate optimization algorithm (QAOA) is a hybrid quantum-classical algorithm that seeks to achieve approximate solutions to optimization problems by iteratively alternating between intervals of controlled quantum evolution.
Gregory Quiroz, Paraj Titum, Phillip Lotshaw, Pavel Lougovski, Kevin Schultz, Eugene Dumitrescu, Itay Hen   +6 more
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Qualitative properties of solutions to generalized eigenvalue problems [PDF]

Arab Journal of Mathematical Sciences
PurposeThis paper investigates the qualitative properties of solutions to a fractional (p,)-Laplace eigenvalue problem with nonhomogeneous terms.
Abdelhamid Gouasmia, Oumaima Ouennas, Amel Bekhouche   +2 more
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A Four‐Dimensional Variational Constrained Neural Network‐Based Data Assimilation Method

Journal of Advances in Modeling Earth Systems
Advances in data assimilation (DA) methods and the increasing amount of observations have continuously improved the accuracy of initial fields in numerical weather prediction during the last decades. Meanwhile, in order to effectively utilize the rapidly
Wuxin Wang, Kaijun Ren, Boheng Duan, Junxing Zhu, Xiaoyong Li, Weicheng Ni, Jingze Lu, Taikang Yuan   +7 more
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Reinforcement Learning in Different Phases of Quantum Control

Physical Review X, 2018
The ability to prepare a physical system in a desired quantum state is central to many areas of physics such as nuclear magnetic resonance, cold atoms, and quantum computing.
Marin Bukov, Alexandre G. R. Day, Dries Sels, Phillip Weinberg, Anatoli Polkovnikov, Pankaj Mehta   +5 more
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Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring

Sensors, 2017
Single-image blind deblurring for imaging sensors in the Internet of Things (IoT) is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process.
Naixue Xiong, Ryan Wen Liu, Maohan Liang, Di Wu, Zhao Liu, Huisi Wu   +5 more
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Quantum-Inspired Optimization for High-Dimensional Data Classification in Healthcare Analytics

Journal of Technology Informatics and Engineering
High-dimensional medical datasets pose a persistent challenge for artificial intelligence because traditional classification algorithms often incur escalating computational costs and reduced predictive accuracy.
Hanae Sugimoto, Kaito Morishita
doaj   +1 more source

An Adaptive Variance Adjustment Strategy for a Static Background Error Covariance Matrix—Part I: Verification in the Lorenz-96 Model

Applied Sciences
Accurate initial conditions are crucial for improving numerical weather prediction (NWP). Variational data assimilation relies on a static background error covariance matrix (B), yet its variance estimation is often inaccurate, affecting assimilation and
Lilan Huang, Hongze Leng, Junqiang Song, Dongzi Wang, Wuxin Wang, Ruisheng Hu, Hang Cao   +6 more
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Application of Variational Quantum Linear Solver in the Numerical Simulation of Steady Flow Over High-Speed Aircrafts

气体物理
CFD methods encounter bottlenecks such as high computational costs and lengthy simulation time when applied to the numerical simulation of large-scale complex flows.
Yiwei FENG, Leyu CHEN, Fuxin CUI, Tengyang MA, Chuangchao YE, Liang XU   +5 more
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Adaptive Variational Mode Decomposition and Principal Component Analysis-Based Denoising Scheme for Borehole Radar Data

Remote Sensing
To address the significant impact of noise on the target detection performance of borehole radar (BHR), a key type of ground-penetrating radar (GPR), a denoising scheme based on the whale optimization algorithm (WOA) for adaptive variational mode ...
Ding Yang, Cheng Guo, Raffaele Persico, Yajie Liu, Handing Liu, Changjin Bai, Chao Lian, Qing Zhao   +7 more
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Learning Topological States from Randomized Measurements Using Variational Tensor-Network Tomography

PRX Quantum
Learning faithful representations of quantum states is crucial to fully characterizing the variety of many-body states created on quantum processors. While various tomographic methods, such as classical shadow and matrix product state (MPS) tomography ...
Yanting Teng, Rhine Samajdar, Katherine Van Kirk, Frederik Wilde, Subir Sachdev, Jens Eisert, Ryan Sweke, Khadijeh Najafi   +7 more
doaj   +1 more source