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Foundation, Progress and Future of Photonics, Plasmonics and Information Optics
Published in Arpan Deyasi, Pampa Debnath, Asit K. Datta, Siddhartha Bhattacharyya, Photonics, Plasmonics and Information Optics, 2021
Pampa Debnath, Arpan Deyasi, Siddhartha Bhattacharyya
Since all-optical architectures are yet to be capable of designing two-photon logic gates,the concept of plasmonicsis utilized by a group of researchers [81] which can successfully able to measure the photon–polariton interaction [82], and the limitations imposed by the Quantum Zeno effect will not be applicable. Here optical nonlinearity playsa crucial role in designing photonic circuits at sub-wavelength level. Design of waveguide with field confinement property plays an integral part of the real-world implementation, and very recently grapheme is proposed as the appropriate candidate [83] for that purpose. With suitable material, quantum information processing will change the present model of information transfer, and ultimately lead towards a secured communication.
Quantum-computing with AI & blockchain: modelling, fault tolerance and capacity scheduling
Published in Mathematical and Computer Modelling of Dynamical Systems, 2019
In the future quantum cloud-computing and communication system (see, Figure 2 for a newly designed example), the traditional binary (zero or one) bit based data packets will be replaced by quantum data packets. Each of them will consist of user’s data payload and packet head that indicates the service requirements managed by system software called quantum blockchain in Dai [2] (see, Figure 4 for detail). The length of a quantum data packet is the number of qubits randomly walking over the Bloch sphere as shown in the lower-right graph of Figure 6. Note that, the random step size for each walk along a particular direction over the sphere may be greater than the unity. Furthermore, the packet length is also random from one quantum data packet to another one. However, no matter whether in a quantum computer or in a quantum communication channel, the service time and quality for a quantum data packet depends on the measurement of each single source qubit. Currently, there are numerous physical realizations of quantum computers, which are mainly based on four quantum computing models of practical importance besides the theoretical quantum Turing machine (see, e.g. Deutsch [3], Feynma [4], Nielsen and Chuang [6]). However, the error from the measurement or unitary operation is still the issue. In general, due to the non-cloning theorem (see, e.g. Niestegge [30], Wootters and Zurek [31]), unknown pure quantum states cannot be copied unless they are orthogonal. Nevertheless, according to Niestegge [30] and references therein, the approximate or imperfect cloning of quantum states is possible, e.g. via a generalized non-Gaussian mutual information formula (see, e.g. Dai [23]) by developing a quantum channel between quantum states and their measurements (or their received states) in a probabilistic way. Furthermore, the quantum Zeno effect or called Zeno’s paradox (i.e. the inhibition of transitions between quantum states by frequent measurements, see, e.g. Itano et al. [32], Misra and Sudarshan [33]) is the other concerned issue. Nevertheless, inside the recently realized IBM 50 qubit quantum computer, the quantum coherence time (the time gap to keep a channel stable (i.e. to keep the number of quantum states the same)) can last up to 90 μs to reduce the influence of Zeno effect, which is enough for the quantum computer to perform the required operation and realize one 20-qubit quantum entanglement in 187 ns (see, e.g. the latest announcement in Song et al. [34]). Therefore, with the hope to reduce the error, we develop a quantum channel method in performing the measurement and computation, which is evolved from the one currently being implemented in MIMO wireless channel (see e.g. Dai [2,24]). An example of such a quantum channel is presented in the lower graph of Figure 7 and illustrated via a comparison with an MIMO channel in the upper-left graph of the figure.