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Abstract Rapid developments in quantum communication are paving the way forward for more advanced technologies. Conventional channels like optical fibres have been a great resource in recent decades. However, they suffer largely from exponential transmissivity decays and are not suitable for very long‐distance communication. Satellite links along w...
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Citations
... The main interest of quantum algorithms in the field of drug discovery is to decrease the cost and time of the research and development process of new drugs as it is true in other fields. QC is being explored in other fields, such as communication [3][4][5][6], physics simulations [7][8][9] and machine learning [10][11][12][13][14]. In the medical field, QC research is being studied to process and classify examination data (medical imaging, blood sampling etc.) [15][16][17][18]. ...
Drug discovery has become a main challenge in the society, following the COVID‐19 pandemic. However, pharmaceutical companies are already using computing to accelerate drug discovery and are increasingly interested in quantum computing (QC), with a view to improving the speed of development process for new drugs. The authors propose a quantum method for generating random sequences based on occurrence in a protein database and quantum algorithms for calculating a similarity rate between proteins. Both concepts can be used for structure prediction in drug design. The aim is to find the proteins closest to the generated protein and obtain an ordering of these proteins. First, the authors will present the construction of a quantum protein generator that defines a protein, called a test protein. The authors will then describe different methods to compute the similarity's rate between each protein in the database and the test protein or, for a case study, the elafin. The algorithms have been extended or adapted to a quantum formalism for use cases, that is, amino acid sequences, and tested to see the added value of quantum versions. The interest is to observe whether QC can be used in the drug discovery process.
... Other fields are exploring the potential of quantum computing such as communication [18,19]. Quantum communication can be classified into two areas. ...
Physics systems are becoming increasingly complex and require more and more computing time. Quantum computing, which has shown its efficiency on some problems, such as the factorisation of a number with Shor's algorithm, may be the solution to reduce these computation times. Here, the authors propose two quantum numerical schemes for the simulation of physics phenomena, based on the finite difference method. The aim is to see if quantum versions of standard numerical schemes offer an advantage over their classical counterparts, either in accuracy, stability or computation time. First, the authors will present the different phenomena studied as well as the classical solution methods chosen. The authors will then describe the implementation of the quantum numerical schemes and present some results obtained on the different physics phenomena beforehand and then compare both approaches, classical and quantum.
Secure Multiparty Computation (SMC) enables multiple parties to cooperate securely without compromising their privacy. SMC has the potential to offer solutions for privacy obstacles in vehicular networks. However, classical SMC implementations suffer from efficiency and security challenges. To address this problem, two quantum communication technologies, Quantum Key Distribution (QKD) and Quantum Oblivious Key Distribution were utilised. These technologies supply symmetric and oblivious keys respectively, allowing fast and secure inter‐vehicular communications. These quantum technologies are integrated with the Faster Malicious Arithmetic Secure Computation with Oblivious Transfer (MASCOT) protocol to form a Quantum Secure Multiparty Computation (QSMC) platform. A lane change service is implemented in which vehicles broadcast private information about their intention to exit the highway. The proposed QSMC approach provides unconditional security even against quantum computer attacks. Moreover, the communication cost of the quantum approach for the lane change use case has decreased by 97% when compared to the classical implementation. However, the computation cost has increased by 42%. For open space scenarios, the reduction in communication cost is especially important, because it conserves bandwidth in the free‐space radio channel, outweighing the increase in computation cost.
