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Secured Unmanned Aerial Vehicle-based Fog Computing Network
Published in Shashi Bhushan, Manoj Kumar, Pramod Kumar, Renjith V. Ravi, Anuj Kumar Singh, Holistic Approach to Quantum Cryptography in Cyber Security, 2023
Akshita Gupta, Sachin Kumar Gupta
Quantum key distribution is a technique that guarantees the distributed network's long-term security. The potential of the two interacting users to identify the existence of any third party attempting to obtain knowledge of the information flowing between ground users with the use of quantum key distribution. Quantum key distribution (QKD) uses the laws of quantum mechanics to enable parties, at least in some cases, to exchange cryptographic keys with complete security. A communication system may be developed that detects eavesdropping by using quantum superpositions or quantum entanglement and exchanging information in quantum states. The modification of a system can be possible by using a property called quantum entanglement [21,23]. Quantum keys, i.e., a stream of photons, are distributed via a quantum channel, where encrypted information is transmitted via a public channel. The photons have a property of momentum and angular spin. There are two polarization modes: Rectilinear and diagonal, depending on the spin of photons. The users distributed the keys to other users by sending a stream of randomly polarized photons. If in any case someone attempts to capture the key, the recipient has the ability to read the malicious activity in the network. After that, the received key will be discarded and requests the sender to retransmit new arbitrarily polarized photon streams [24].
Background theory
Published in Michael de Podesta, Understanding the Properties of Matter, 2020
In quantum mechanics, we use the concept of a quantum state to describe the possible states of a particle. The laws of quantum mechanics describe which states are physically realistic, and specify the ways in which a particle moves from one quantum state to another. Each quantum state is characterised by a unique set of quantum numbers that ‘index’ the quantum state. Sometimes quantum numbers have continuously variable values, but commonly quantum numbers are restricted to a set of discrete values, i.e. values outside this set do not describe physically realistic quantum states. For example, for a particle of mass m confined to a cubic box of side L, the physically realistic quantum states have energies described by: () E(nx,ny,nz)=h28mL2[nx2+ny2+nz2]
Electrons in Semiconductors
Published in Hualin Zhan, Graphene-Electrolyte Interfaces, 2020
The quantum state is a concept used to describe the state of an isolated quantum object (e.g., an electron), where the observables (such as momentum) could be predicted. In the context of atomic physics, the state (or state vector) consists of a set of variables including principal quantum number, angular momentum quantum number, magnetic quantum number, and spin z-component. Here in solid-state physics, we start from considering the momentum (and position) of electrons for the quantum state, where spin component could be added later (e.g., g in Eq. 2.19). As electrons with various wavelengths have different momenta according to de Broglie's theorem, the number of waves with different wavelengths can be used as an indication of the number of quantum states.
Optimization of diesel engine dual-variable geometry turbocharger regulated two-stage turbocharging system based on radial basis function neural network-quantum genetic algorithm
Published in Energy Sources, Part A: Recovery, Utilization, and Environmental Effects, 2021
Guangmeng Zhou, Ruilin Liu, Zhongjie Zhang, Chunhao Yang, Haojian Ding
Quantum genetic algorithm (QGA) is a new evolutionary algorithm based on quantum computing theory and genetic algorithm ideas (Chen et al., 2005). Quantum computing uses the properties of superposition, entanglement, and interference of quantum states to solve problems that are difficult to solve in the traditional computing field. The quantum genetic algorithm introduces quantum state vector into genetic coding, and applies quantum probability amplitude representation to chromosome coding, so that one chromosome can express the superposition of multiple states, and quantum gate is used to realize population evolution, so as to realize optimal solution of the problem. Qubits draw on quantum theory and can be expressed as the intermediate state of and :
Quantum algorithm for the computation of the reactant conversion rate in homogeneous turbulence
Published in Combustion Theory and Modelling, 2019
Guanglei Xu, Andrew J. Daley, Peyman Givi, Rolando D. Somma
Inherently, quantum computing derives its possible speedup over classical computing due to some properties of quantum physics that have no classical analogue. One such property is superposition: the underlying units of information — so-called quantum bits, or qubits, can be placed in a superposition state that encodes information in its amplitudes. Another property is quantum entanglement, where quantum states with non-classical correlations exist and the state of each qubit cannot be described independently from the state of the other qubits. Quantum interference is also a key property as it is the reason behind the preparation of quantum states in superposition that are mostly supported in those states that encode information about the solution to a problem. Quantum algorithms that present important quantum speedups, such as Shor's factoring algorithm [22], exploit the properties discussed above.
Counteracting quantum decoherence with optimized disorder in discrete-time quantum walks
Published in Journal of Modern Optics, 2019
Quantum state decoherence occurs as the wavefunction of a quantum system is collapsed, either entirely or partially, by energy dissipation into the environment or by the disclosure of its state information. Typical examples of quantum decoherence include the spontaneous decay in two-level systems and the scattering loss during the propagation of entangled photons (1). On the other hand, disorder describes the disturbance of the system's wavefunction by the chaotic external degrees of freedom it is coupled to, such as inhomogeneous chemical potential in a photosynthetic network (2). While corresponding to different mechanisms, both decoherence and disorder deteriorate the performance of quantum systems. In light of their prevalence in practice, there have been extensive efforts to address each of them, e.g. by applying high magnetic fields and error correction (3,4).