IET Quantum Communication最新文献

In this article, a protocol for information lossless teleportation using W states is proposed. Firstly, the information lossless teleportation of an unknown state with a maximally entangled W-state channel, which protects the original unknown state information even in case of teleportation failure is investigated. Next, we generalise our scheme to non-maximally entangled W-state channels. Finally, the principle of the proposed scheme is validated by performing experiments on the quantum circuit simulator Quirk. Our study shows that W states can be used to teleport any quantum state without information loss through single-qubit measurements and local unitary operations.

This paper applies a quantum machine learning technique to predict mobile users' trajectories in mobile wireless networks by using an approach called quantum reservoir computing (QRC). Mobile users' trajectories prediction belongs to the task of temporal information processing, and it is a mobility management problem that is essential for self-organising and autonomous 6G networks. Our aim is to accurately predict the future positions of mobile users in wireless networks using QRC. To do so, the authors use a real-world time series dataset to model mobile users' trajectories. The QRC approach has two components: reservoir computing (RC) and quantum computing (QC). In RC, the training is more computational-efficient than the training of simple recurrent neural networks since, in RC, only the weights of the output layer are trainable. The internal part of RC is what is called the reservoir. For the RC to perform well, the weights of the reservoir should be chosen carefully to create highly complex and non-linear dynamics. The QC is used to create such dynamical reservoir that maps the input time series into higher dimensional computational space composed of dynamical states. After obtaining the high-dimensional dynamical states, a simple linear regression is performed to train the output weights and, thus, the prediction of the mobile users' trajectories can be performed efficiently. In this study, we apply a QRC approach based on the Hamiltonian time evolution of a quantum system. The authors simulate the time evolution using IBM gate-based quantum computers, and they show in the experimental results that the use of QRC to predict the mobile users' trajectories with only a few qubits is efficient and can outperform the classical approaches such as the long short-term memory approach and the echo-state networks approach.

In the technologically changing world, the demand for ultra-reliable, faster, low power, and secure communication has significantly risen in recent years. Researchers have shown immense interest in emerging quantum computing (QC) due to its potentials of solving the computing complexity in the robust and efficient manner. It is envisioned that QC can act as critical enablers and strong catalysts to considerably reduce the computing complexities and boost the future of sixth generation (6G) and beyond communication systems in terms of their security. In this study, the fundamentals of QC, the evolution of quantum communication that encompasses a wide spectrum of technologies and applications and quantum key distribution, which is one of the most promising applications of quantum security, have been presented. Furthermore, various parameters and important techniques are also investigated to optimise the performance of 6G communication in terms of their security, computing, and communication efficiency. Towards the end, potential challenges that QC and quantum communication may face in 6G have been highlighted along with future directions.

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.

In recent years, numerous research advancements have extended the limit of classical simulation of quantum algorithms. Although, most of the state-of-the-art classical simulators are only limited to binary quantum systems, which restrict the classical simulation of higher-dimensional quantum computing systems. Through recent developments in higher-dimensional quantum computing systems, it is realised that implementing qudits improves the overall performance of a quantum algorithm by increasing memory space and reducing the asymptotic complexity of a quantum circuit. Hence, in this article, QuDiet, a state-of-the-art user-friendly python-based higher-dimensional quantum computing simulator is introduced. QuDiet offers multi-valued logic operations by utilising generalised quantum gates with an abstraction so that any naive user can simulate qudit systems with ease as compared to the existing ones. Various benchmark quantum circuits is simulated in QuDiet and show the considerable speedup in simulation time as compared to the other simulators without loss in precision. Finally, QuDiet provides a full qubit-qudit hybrid quantum simulator package with quantum circuit templates of well-known quantum algorithms for fast prototyping and simulation. Comprehensive simulation up to 20 qutrits circuit on depth 80 on QuDiet was successfully achieved. The complete code and packages of QuDiet is available at https://github.com/LegacYFTw/QuDiet.

Quantum computing combines mathematics, quantum physics, and computer science to optimise, learn, and simulate chemical, physical, and biological systems. It offers the ability to solve problems in a unique method and to speed up solutions compared to standard procedures. This computing may solve issues with intractable inputs. With the capabilities of quantum computers and the availability of quantum development kits, quantum computing is expected to become ubiquitous, and the demand for trained people is expected to rise significantly. Quantum technologies are rapidly developing globally with substantial disruptive potential. Quantum technology is opening up new frontiers in computing, communications, and cyber security with widespread applications. The range of quantum technologies is expected to be one of the significant technology disruptions that will change the entire paradigm of computation, communication, and encryption. It is perceived that the countries that achieve an edge in this emerging field will have a more significant advantage in garnering multifold economic growth and dominant leadership roles. It is expected that lots of commercial applications will emerge from the developing theoretical constructs in this area. In India, there is a growing interest in quantum computing and communication with active participation from students, developers, industry, and academia, leading to many recent initiatives and developments. This article provides an overview of some of the recent developments of quantum computing in India and the future ahead.

In its 2020 budget, the Indian government announced the National Mission on Quantum Technologies and Applications, which will be run by the Department of Science and Technology with a budget of 80 billion INR over five years [1]. Among the next-generation technologies that will be pushed by this mission are quantum computers and computing, quantum communication, quantum key distribution, cryptanalysis, quantum devices, quantum sensing, quantum materials, quantum clocks, and so on. The mission will focus on basic science, technology development, building up human and infrastructure resources, innovation, and new businesses to solve problems that are important to the country. By putting the mission into action, India would be able to develop and use quantum computers, secure communications through fibre and free space, quantum encryption and cryptanalysis, and other related technologies. It would also be able to deal with national and regional problems that are unique to India.

International Business Machines (IBM) and the Indian Institute of Technology, Madras (IIT-Madras) joined forces in September 2022 to help India learn more about quantum computing and accelerate research [2]. With this partnership, IIT Madras becomes one of the more than 180 members of the IBM Quantum Network around the world. IIT Madras is also the "first Indian institution" to join t

With the race to build large-scale quantum computers and efforts to exploit quantum algorithms for efficient problem solving in science and engineering disciplines, the requirement to have efficient and scalable verification methods are of vital importance. A novel formal verification method that is targeted at Quantum Fourier Transform (QFT) circuits is proposed. Quantum Fourier Transform is a fundamental quantum algorithm that forms the basis of many quantum computing applications. The verification method employs abstractions of quantum gates used in QFT that leads to a reduction of the verification problem from Hilbert space to the quantifier free logic of bit-vectors. Very efficient decision procedures are available to reason about bit-vectors. Therefore, this method is able to scale up to the verification of QFT circuits with 10,000 qubits and 50 million quantum gates, providing a meteoric advance in the size of QFT circuits thus far verified using formal verification methods.

Classical Cryptography has been in use for a long time. It has been the only way of securing people's communication. However, there are some flaws observed during the execution of classical cryptography. One of them being the staunch belief that the number composed of multiplication of two large prime numbers cannot be factorised easily, which is under a threat thanks to the computational power of the quantum computers. The next flaw is the non-detection of the hacker, both of which can be eliminated by using quantum mechanical principles for encryption purposes, which is known as quantum cryptography. Quantum Key Distribution, which provides an information-theoretically safe solution to the key exchange problem, is the most well-known example of quantum cryptography. The benefit of quantum cryptography is that it makes it possible to perform a variety of cryptographic operations that have been demonstrated or are hypothesised to be impractical when using solely traditional (i.e., non-quantum) communication. Free-space quantum communication has been successfully demonstrated across 300 m by the Indian Space Research Organization (ISRO) in March 2021. With this, ISRO is trying to achieve the same using a satellite-based communication mechanism, which would revolutionise the mode of modern communication. It is justified that the key generation rate depends on factors like the aperture diameter of the sender and receiver, distance between them, the quantum bit error rate, and many more. The results vary with the parameters in the discussion as explained in the upcoming sections. The avenue of different types of losses that occur while transmitting at large distances, such as Atmospheric Loss, Pointing Loss and Geometric Loss, is explored.

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.