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Quantum computers require quantum processors. An important part of the processor of any computer is the arithmetic unit, which performs binary addition, subtraction, division and multiplication, however multiplication can be performed using…

Quantum Physics · Physics 2018-11-14 Rasha Montaser , Ahmed Younes , Mahmoud Abdel-Aty

The concept of quantum computing has inspired a whole new generation of scientists, including physicists, engineers, and computer scientists, to fundamentally change the landscape of information technology. With experimental demonstrations…

Quantum random number generator harnesses the power of quantum mechanics to generate true random numbers, making it valuable for various scientific applications. However, real-world devices often suffer from imperfections that can undermine…

Quantum Physics · Physics 2023-12-07 Xing Lin , Rong Wang

Generative Adversarial Networks (GANs) have emerged as useful generative models, which are capable of implicitly learning data distributions of arbitrarily complex dimensions. However, the training of GANs is empirically well-known for…

Computer Vision and Pattern Recognition · Computer Science 2021-10-25 Cuong V. Nguyen , Tien-Dung Cao , Tram Truong-Huu , Khanh N. Pham , Binh T. Nguyen

Generative adversarial learning is currently one of the most prolific fields in artificial intelligence due to its great performance in a variety of challenging tasks such as photorealistic image and video generation. While a quantum…

Quantum Physics · Physics 2022-05-27 Zichao Huang , Yuanyuan Chen , Lixiang Chen

In this paper, we propose the Self-Attention Generative Adversarial Network (SAGAN) which allows attention-driven, long-range dependency modeling for image generation tasks. Traditional convolutional GANs generate high-resolution details as…

Machine Learning · Statistics 2019-06-18 Han Zhang , Ian Goodfellow , Dimitris Metaxas , Augustus Odena

Quantum computers may achieve speedups over their classical counterparts for solving linear algebra problems. However, in some cases -- such as for low-rank matrices -- dequantized algorithms demonstrate that there cannot be an exponential…

Quantum Physics · Physics 2023-05-16 Ashley Montanaro , Changpeng Shao

Classical generative adversarial networks (GANs) have been applied to generate adversarial network traffic capable of attacking intrusion detection systems, but they suffer from shortcomings such as the need for large amounts of…

Machine Learning · Computer Science 2026-05-08 Prateek Paudel , Nitin Jha , Abhishek Parakh , Mahadevan Subramaniam

Generative adversarial nets (GANs) have become a preferred tool for tasks involving complicated distributions. To stabilise the training and reduce the mode collapse of GANs, one of their main variants employs the integral probability…

Machine Learning · Computer Science 2020-10-27 Shengxi Li , Zeyang Yu , Min Xiang , Danilo Mandic

Current technological advancements of quantum computers highlight the need for application-driven, practical and well-defined methods of benchmarking their performance. As the existing NISQ device's quality of two-qubit gate errors rate is…

Performance · Computer Science 2023-12-15 Krzysztof Kurowski , Piotr Rydlichowski , Konrad Wojciechowski , Tomasz Pecyna , Mateusz Slysz

Since its invention, Generative adversarial networks (GANs) have shown outstanding results in many applications. Generative Adversarial Networks are powerful yet, resource-hungry deep-learning models. Their main difference from ordinary…

Machine Learning · Computer Science 2021-08-17 Dina Tantawy , Mohamed Zahran , Amr Wassal

Digital-analog quantum computing (DAQC) combines digital gates with analog operations, offering an alternative paradigm for universal quantum computation. This approach leverages the higher fidelities of analog operations and the…

Quantum Physics · Physics 2024-10-07 Aleix Llenas , Lucas Lamata

Neutral atoms have emerged as a promising technology for implementing quantum computers due to their scalability and long coherence times. However, the execution frequency of neutral atom quantum computers is constrained by image processing…

Quantum Physics · Physics 2024-11-21 Xiaorang Guo , Jonas Winklmann , Dirk Stober , Amr Elsharkawy , Martin Schulz

Quantum computing leverages the unique properties of qubits and quantum parallelism to solve problems intractable for classical systems, offering unparalleled computational potential. However, the optimization of quantum circuits remains…

Quantum computing is a game-changing technology for global academia, research centers and industries including computational science, mathematics, finance, pharmaceutical, materials science, chemistry and cryptography. Although it has seen…

Quantum Physics · Physics 2023-03-07 He-Liang Huang , Xiao-Yue Xu , Chu Guo , Guojing Tian , Shi-Jie Wei , Xiaoming Sun , Wan-Su Bao , Gui-Lu Long

Generative Adversarial Network (GAN) is a well known computationally complex algorithm requiring signficiant computational resources in software implementations including large amount of data to be trained. This makes its implementation in…

Emerging Technologies · Computer Science 2020-07-24 Olga Krestinskaya , Bhaskar Choubey , Alex Pappachen James

Trapped ions as one of the most promising quantum-information-processing platforms, yet conventional entangling gates mediated by collective motion remain slow and difficult to scale. Exciting trapped ions to high-lying electronic Rydberg…

Quantum computers take advantage of the superpositional logic of quantum mechanics to allow for dramatic increases in computational efficiency. rf-SQUIDs show potential for quantum computing applications by forming the qubit component of a…

Quantum Physics · Physics 2007-05-23 Christopher Altman

Quantum computing promises to solve previously intractable problems, with neutral atoms emerging as a promising technology. Zoned neutral atom architectures allow for immense parallelism and higher coherence times by shielding idling atoms…

Quantum Physics · Physics 2026-01-15 Yannick Stade , Wan-Hsuan Lin , Jason Cong , Robert Wille

Recent work has shown generative adversarial networks (GANs) can generate highly realistic images, that are often indistinguishable (by humans) from real images. Most images so generated are not contained in the training dataset, suggesting…

Computer Vision and Pattern Recognition · Computer Science 2020-08-11 Miaoyun Zhao , Yulai Cong , Lawrence Carin