About the Journal
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.
Indexing and Abstracting
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.
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Open Access
ARTICLE
IQAOA for Two Routing Problems: A Methodological Contribution with Application to TSP and VRP
Journal of Quantum Computing, Vol.6, pp. 25-51, 2024, DOI:10.32604/jqc.2024.048792 - 25 October 2024
Abstract The paper presents a novel quantum method for addressing two fundamental routing problems: the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP), both central to routing challenges. The proposed method, named the Indirect Quantum Approximate Optimization Algorithm (IQAOA), leverages an indirect solution representation using ranking. Our contribution focuses on two main areas: 1) the indirect representation of solutions, and 2) the integration of this representation into an extended version of QAOA, called IQAOA. This approach offers an alternative to QAOA and includes the following components: 1) a quantum parameterized circuit designed to simulate… More >
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Open Access
ARTICLE
Optimized General Uniform Quantum State Preparation
Journal of Quantum Computing, Vol.6, pp. 15-24, 2024, DOI:10.32604/jqc.2024.047423 - 24 April 2024
Abstract Quantum algorithms for unstructured search problems rely on the preparation of a uniform superposition, traditionally achieved through Hadamard gates. However, this incidentally creates an auxiliary search space consisting of nonsensical answers that do not belong in the search space and reduce the efficiency of the algorithm due to the need to neglect, un-compute, or destructively interfere with them. Previous approaches to removing this auxiliary search space yielded large circuit depth and required the use of ancillary qubits. We have developed an optimized general solver for a circuit that prepares a uniform superposition of any N More >
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Open Access
ARTICLE
3-Qubit Circular Quantum Convolution Computation Using the Fourier Transform with Illustrative Examples
Journal of Quantum Computing, Vol.6, pp. 1-14, 2024, DOI:10.32604/jqc.2023.026981 - 30 January 2024
Abstract In this work, we describe a method of calculation of the 1-D circular quantum convolution of signals represented by 3-qubit superpositions in the computational basis states. The examples of the ideal low pass and high pass filters are described and quantum schemes for the 3-qubit circular convolution are presented. In the proposed method, the 3-qubit Fourier transform is used and one addition qubit, to prepare the quantum superposition for the inverse quantum Fourier transform. It is considered that the discrete Fourier transform of one of the signals is known and calculated in advance and only More >
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Open Access
ARTICLE
Study on Quantum Finance Algorithm: Quantum Monte Carlo Algorithm based on European Option Pricing
Journal of Quantum Computing, Vol.4, No.1, pp. 53-61, 2022, DOI:10.32604/jqc.2022.027683
Abstract As one of the major methods for the simulation of option pricing, Monte Carlo method assumes random fluctuations in the distribution of asset prices. Under certain uncertainties process, different evolution paths could be simulated so as to finally yield the expectation value of the asset price, which requires a lot of simulations to ensure the accuracy based on huge and expensive calculations. In order to solve the above computational problem, quantum Monte Carlo (QMC) has been established and applied in the relevant systems such as European call options. In this work, both MC and QM More >
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Open Access
ARTICLE
Online News Sentiment Classification Using DistilBERT
Journal of Quantum Computing, Vol.4, No.1, pp. 1-11, 2022, DOI:10.32604/jqc.2022.026658
Abstract The ability of pre-trained BERT model to achieve outstanding performances on many Natural Language Processing (NLP) tasks has attracted the attention of researchers in recent times. However, the huge computational and memory requirements have hampered its widespread deployment on devices with limited resources. The concept of knowledge distillation has shown to produce smaller and faster distilled models with less trainable parameters and intended for resource-constrained environments. The distilled models can be fine-tuned with great performance on a wider range of tasks, such as sentiment classification. This paper evaluates the performance of DistilBERT model and other More >
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Open Access
ARTICLE
Research on Rainfall Estimation Based on Improved Kalman Filter Algorithm
Journal of Quantum Computing, Vol.4, No.1, pp. 23-37, 2022, DOI:10.32604/jqc.2022.026975
Abstract In order to solve the rainfall estimation error caused by various noise factors such as clutter, super refraction, and raindrops during the detection process of Doppler weather radar. This paper proposes to improve the rainfall estimation model of radar combined with rain gauge which calibrated by common Kalman filter. After data preprocessing, the radar data should be classified according to the precipitation intensity. And then, they are respectively substituted into the improved filter for calibration. The state noise variance and the measurement noise variance can be adaptively calculated and updated according to the input observation More >
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Open Access
ARTICLE
A Top-down Method of Extraction Entity Relationship Triples and Obtaining Annotated Data
Journal of Quantum Computing, Vol.4, No.1, pp. 13-22, 2022, DOI:10.32604/jqc.2022.026785
Abstract The extraction of entity relationship triples is very important to build a knowledge graph (KG), meanwhile, various entity relationship extraction algorithms are mostly based on data-driven, especially for the current popular deep learning algorithms. Therefore, obtaining a large number of accurate triples is the key to build a good KG as well as train a good entity relationship extraction algorithm. Because of business requirements, this KG’s application field is determined and the experts’ opinions also must be satisfied. Considering these factors we adopt the top-down method which refers to determining the data schema firstly, then… More >
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Open Access
ARTICLE
Research on Service Function Chain Orchestrating Algorithm Based on SDN and NFV
Journal of Quantum Computing, Vol.4, No.1, pp. 39-52, 2022, DOI:10.32604/jqc.2022.027560
Abstract Software defined network (SDN) and network function virtualization (NFV) have become a new paradigm of a new generation of network architecture. SDN and NFV can effectively improve the flexibility of deploying and managing service function chains (SFCs). By combining SDN and NFV and applying them to the resource orchestration problem of SFC deployment, the three-tier architecture consisting of SDN controller, network function virtualization and physical underlying computing resource layer in the process of heterogeneous network resource mapping is considered. And an optimization algorithm for active control resources based on SDN and NFV is proposed. Firstly,… More >
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Open Access
ARTICLE
3-Qubit Circular Quantum Convolution Computation Using the Fourier Transform with Illustrative Examples
Journal of Quantum Computing, Vol.6, pp. 1-14, 2024, DOI:10.32604/jqc.2023.026981
Abstract In this work, we describe a method of calculation of the 1-D circular quantum convolution of signals represented by 3-qubit superpositions in the computational basis states. The examples of the ideal low pass and high pass filters are described and quantum schemes for the 3-qubit circular convolution are presented. In the proposed method, the 3-qubit Fourier transform is used and one addition qubit, to prepare the quantum superposition for the inverse quantum Fourier transform. It is considered that the discrete Fourier transform of one of the signals is known and calculated in advance and only More >
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Open Access
ARTICLE
Design of a Novel Signed Binary Subtractor Using Quantum Gates
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 More >
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Open Access
ARTICLE
Pancreatic Cancer Data Classification with Quantum Machine Learning
Journal of Quantum Computing, Vol.5, pp. 1-13, 2023, DOI:10.32604/jqc.2023.044555
Abstract Quantum computing is a promising new approach to tackle the complex real-world computational problems by harnessing the power of quantum mechanics principles. The inherent parallelism and exponential computational power of quantum systems hold the potential to outpace classical counterparts in solving complex optimization problems, which are pervasive in machine learning. Quantum Support Vector Machine (QSVM) is a quantum machine learning algorithm inspired by classical Support Vector Machine (SVM) that exploits quantum parallelism to efficiently classify data points in high-dimensional feature spaces. We provide a comprehensive overview of the underlying principles of QSVM, elucidating how different… More >
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Open Access
ARTICLE
Near Term Hybrid Quantum Computing Solution to the Matrix Riccati Equations
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 More >
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Open Access
ARTICLE
T_GRASP: Optimization Algorithm of Ship Avoiding Typhoon Route
Journal of Quantum Computing, Vol.4, No.2, pp. 85-95, 2022, DOI:10.32604/jqc.2022.031436
Abstract A GRASP-based algorithm called T_GRASP for avoiding typhoon route optimization is suggested to increase the security and effectiveness of ship navigation. One of the worst natural calamities that can disrupt a ship’s navigation and result in numerous safety mishaps is a typhoon. Currently, the captains manually review the collected weather data and steer clear of typhoons using their navigational expertise. The distribution of heavy winds and waves produced by the typhoon also changes dynamically as a result of the surrounding large-scale air pressure distribution, which significantly enhances the challenge of the captain’s preparation for avoiding… More >
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Open Access
ARTICLE
Flight Delay Prediction Using Gradient Boosting Machine Learning Classifiers
Journal of Quantum Computing, Vol.3, No.1, pp. 1-12, 2021, DOI:10.32604/jqc.2021.016315
Abstract With the increasing of civil aviation business, flight delay has become
a key problem in civil aviation field in recent years, which has brought a
considerable economic impact to airlines and related industries. The delay
prediction of specific flights is very important for airlines’ plan, airport resource
allocation, insurance company strategy and personal arrangement. The influence
factors of flight delay have high complexity and non-linear relationship. The
different situations of various regions and airports, and even the deviation of
airport or airline arrangement all have certain influence on flight delay, which
makes the prediction more… More >
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Open Access
ARTICLE
New Quantum Private Comparison Using Hyperentangled GHZ State
Journal of Quantum Computing, Vol.3, No.2, pp. 45-54, 2021, DOI:10.32604/jqc.2021.019675
Abstract In this paper, we propose a new protocol designed for quantum private
comparison (QPC). This new protocol utilizes the hyperentanglement as the
quantum resource and introduces a semi-honest third party (TP) to achieve the
objective. This protocol’s quantum carrier is a hyperentangled three-photon GHZ
state in 2 degrees of freedom (DOF), which could have 64 combinations. The TP
can decide which combination to use based on the shared key information
provided from a quantum key distribution (QKD) protocol. By doing so, the
security of the protocol can be improved further. Decoy photon technology is also More >
Copyright © 2024 The Author(s). Published by Tech Science Press.
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