Journal of Quantum Computing is a high-impact, international journal publishing cutting-edge experimental and theoretical research in all areas of Quantum Computing and Information Science. Topics of interest include quantum computer science, Quantum machine learning, quantum secure communications, quantum information processing, quantum imaging and networking, quantum cryptography, entanglement and discord, quantum algorithms, quantum error correction and fault tolerance, and experimental platforms for quantum information.
Starting from July 2023, Journal of Quantum Computing will transition to a continuous publication model, accepted articles will be promptly published online upon completion of the peer review and production processes.
Open Access
ARTICLE
Journal of Quantum Computing, Vol.4, No.3, pp. 121-133, 2022, DOI:10.32604/jqc.2022.034059
Abstract In this paper, focus has been given to design and implement signed binary subtraction in quantum logic. Since the type of operand may be positive or negative, therefore a novel algorithm has been developed to detect the type of operand and as per the selection of the type of operands, separate design techniques have been developed to make the circuit compact and work very efficiently. Two separate methods have been shown in the paper to perform the signed subtraction. The results show promising for the second method in respect of ancillary input count and garbage output count but at the… More >
Open Access
ARTICLE
Journal of Quantum Computing, Vol.4, No.3, pp. 135-146, 2022, DOI:10.32604/jqc.2022.036706
Abstract The well-known Riccati differential equations play a key role in many fields, including problems in protein folding, control and stabilization, stochastic control, and cybersecurity (risk analysis and malware propagation). Quantum computer algorithms have the potential to implement faster approximate solutions to the Riccati equations compared with strictly classical algorithms. While systems with many qubits are still under development, there is significant interest in developing algorithms for near-term quantum computers to determine their accuracy and limitations. In this paper, we propose a hybrid quantum-classical algorithm, the Matrix Riccati Solver (MRS). This approach uses a transformation of variables to turn a set… More >
Open Access
ARTICLE
Journal of Quantum Computing, Vol.4, No.3, pp. 147-163, 2022, DOI:10.32604/jqc.2022.038358
Abstract In the field of computer research, the increase of data in result of societal progress has been remarkable, and the management of this data and the analysis of linked businesses have grown in popularity. There are numerous practical uses for the capability to extract key characteristics from secondary property data and utilize these characteristics to forecast home prices. Using regression methods in machine learning to segment the data set, examine the major factors affecting it, and forecast home prices is the most popular method for examining pricing information. It is challenging to generate precise forecasts since many of the regression… More >
Open Access
ARTICLE
Journal of Quantum Computing, Vol.4, No.3, pp. 165-181, 2022, DOI:10.32604/jqc.2022.039795
Abstract With the rapid development of society nowadays, this paper begins to study the teaching strategies of promoting students’ deep learning in the Chinese literature scene, and the attitudes and teaching quality of students and teachers when learning Chinese literature. The investigation and analysis show that: (1) For example, the relationship between literary scenes and characters in the famous literary work “Three Kingdoms” is analyzed. The complex character relationships in literature are important to literary scenes and learning. (2) It explains that the suggestions when writing Chinese literary scenes need to be pragmatic, pay attention to modern people’s livelihood, and the… More >
Open Access
ARTICLE
Journal of Quantum Computing, Vol.4, No.3, pp. 183-197, 2022, DOI:10.32604/jqc.2022.039913
Abstract Prior versions of reversible data hiding with contrast enhancement (RDHCE) algorithms strongly focused on enhancing the contrast of grayscale images. However, RDHCE has recently witnessed a rise in contrast enhancement algorithms concentrating on color images. This paper implies a method for color images that uses the RGB (red, green, and blue) color model and is based on bi-histogram shifting and image adjustment. Bi-histogram shifting is used to embed data and image adjustment to achieve contrast enhancement by adjusting the images resulting from each channel of the color images before combining them to generate the final enhanced image. Images are first… More >