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Effective Machine Communication Using Quantum Techniques Provides Improvement in Performance and Privacy through IoT Application
Published in Nishu Gupta, Srinivas Kiran Gottapu, Rakesh Nayak, Anil Kumar Gupta, Mohammad Derawi, Jayden Khakurel, Human-Machine Interaction and IoT Applications for a Smarter World, 2023
Devendar Rao, Ramkumar Jayaraman, Laura Pozueco
Let us see with an example as shown in Figure 16.4; let's take an Exclusively-OR (XOR) gate and perform it in both classical and quantum circuit. The XOR gate will obtain output bit “1” when both the input bits are different and output bit “0” when both bits are same. In classical circuit, with one output, two input bits cannot be generated, but in quantum circuit, we retain the original one input along with the XOR calculated value, helping to reverse the operation. For construction of efficient quantum circuits, many unitary operation gates are involved in circuits along with ancillary bits. The maximum number of ancillary bits involved during a construction of “n” bit input bits will be “n − 1” ancillary bits. The general construction of effectively converting a classical circuit to quantum circuits [11] is shown in Figure 16.5.
Quantum Computation for Big Information Processing
Published in Neeraj Kumar, N. Gayathri, Md. Arafatur Rahman, B. Balamurugan, Blockchain, Big Data and Machine Learning, 2020
Tawseef Ayoub Shaikh, Rashid Ali
A gate is an abstraction that represents information processing. Gates are also used for information in a quantum computer, but in this case, the gates are unitary operations. Since a unitary operator U is one where the adjoint is equal to the inverse, meaning U† = U−1. The defining relation for a unitary operator is thus: () UU†=U†U=I
Quantum algorithm for solving the test suite minimization problem
Published in Cogent Engineering, 2021
Hager Hussein, Ahmed Younes, Walid Abdelmoez
One of the quantum properties is entanglement, which means that each object of the quantum system can’t be described independently, and instead, the quantum state has to be described for the whole system (Menon & Ritwik, 2014). Another feature in quantum computing is the parallelism where it takes a quantum computer a single step to operate on inputs with a single gate, while the classical computer takes steps for the same input size. Parallelism does not require additional hardware or to wait for other processes to complete, but it performs multiple operations at a time. Quantum gates are unitary operators, considering that a gate has inputs, and then it can be represented as unitary matrix assuming that state and state . Examples of such gates are:
One- and two-dimensional quantum lattice algorithms for Maxwell equations in inhomogeneous scalar dielectric media I: theory
Published in Radiation Effects and Defects in Solids, 2021
George Vahala, Linda Vahala, Min Soe, Abhay K. Ram
Here, we continue our studies of a QLA for Maxwell equations in inhomogeneous media. In our earlier papers (17, 30) we presented QLA for 1D propagation of electromagnetic fields in a scalar dielectric medium. These QLAs were based on the Riemann–Silberstein vectors, which in essence define the two polarizations of an electromagnetic pulse. For homogeneous dielectrics, with constant refractive index , there is a remarkable similarity between the Dirac equation and the 4-vector Riemann-Silberstein representation of Maxwell equations. Thus the Pauli spin- matrices play a significant role in the development of a QLA. Khan (21) showed that for inhomogeneous media, the terms proportional to the gradient of the refractive index, , will lead to non-unitary operators in the time evolution of Maxwell equations. When one determines a QLA for Maxwell equations in an inhomogeneous medium, some of the evolution operators will necessarily be Hermitian, rather than unitary. In particular, for 1D propagation in the $y-direction (17) two of the evolution operators are Hermitian, while for 1D x- and z-propagation only one of the operators is Hermitian. Interestingly, Childs and Wiebe (22) have shown that algorithms utilizing sum of unitary operators (rather than the standard product of unitary operators) can still be encoded onto a quantum computer. The non-unitarity can be readily handled by a quantum-classical interchange of tasks: the untiary operations being assigned to quantum computations and the non-unitary operators to classical computations. This is an active area of research, as can be seen in the recent preprint considering a measurement-based non-unitary representation of the Grover search algorithm (31).