Journal of Quantum Computing

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.

  • Flight Delay Prediction Using Gradient Boosting Machine Learning Classifiers
  • 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 difficult. In view of the… More
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  • Analysis of Flight Punctuality Rate Based on Complex Network
  • Abstract Aviation service plays an indispensable role in the process of social and economic development. In this process, the problem of flight punctuality becomes more and more serious. Flight delay will bring a variety of implicit and explicit losses to individual passengers and airlines, so it is necessary to analyze the influencing factors of flight punctuality rate. Complex network can be used to study various objects with complex relations, obtain the relations of these objects and calculate the influence of different indicators on the objects. This article mainly has carried on the three aspects: Firstly, get the flight data from the… More
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  • A Prediction Method of Trend-Type Capacity Index Based on Recurrent Neural Network
  • Abstract Due to the increase in the types of business and equipment in telecommunications companies, the performance index data collected in the operation and maintenance process varies greatly. The diversity of index data makes it very difficult to perform high-precision capacity prediction. In order to improve the forecasting efficiency of related indexes, this paper designs a classification method of capacity index data, which divides the capacity index data into trend type, periodic type and irregular type. Then for the prediction of trend data, it proposes a capacity index prediction model based on Recurrent Neural Network (RNN), denoted as RNN-LSTM-LSTM. This model… More
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  • Dynamic Target Detection and Tracking Based on Quantum Illumination LIDAR
  • Abstract In the detection process of classic radars such as radar/lidar, the detection performance will be weakened due to the presence of background noise and loss. The quantum illumination protocol can use the spatial correlation between photon pairs to improve image quality and enhance radar detection performance, even in the presence of loss and noise. Based on this quantum illumination LIDAR, a theoretic scheme is developed for the detection and tracking of moving targets, and the trajectory of the object is analyzed. Illuminated by the quantum light source as Spontaneous Parametric Down-Conversion (SPDC), an opaque target can be identified from the… More
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