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Quantum Machine Learning and Big Data for Real-Time Applications
Published in Om Prakash Jena, Sabyasachi Pramanik, Ahmed A. Elngar, Machine Learning Adoption in Blockchain-Based Intelligent Manufacturing, 2022
Using a literature review, we found that quantum computing comes in four flavors, as seen in Figure 9.1. A variety of ways utilize quantum computing in combination with other cutting-edge methods. The combination of quantum computing with ML (QML) has opened up a new field in which intriguing findings may be discovered by combining conventional methods with quantum approaches. Methods include quantum SVMs, quantum supervised and unsupervised learning, and quantum classified and reclassified learning, as well as quantum reinforcement and collaborative learning. Regardless of technique, the results achieved with a quantum computing approach are superior to those produced with a traditional ML approach. When it comes to quantum computers and deep learning, breakthroughs have been made in artificial neural networks, such as quantum deep learning and quantum NLP [13]. Compared to the traditional neural network and deep learning approaches, these are more adaptable and accurate in terms of results. The new benchmark for output obtained with updated techniques in QML diabetic diagnosis, English-to-Hindi translation, fame semantic, nonalgorithmic, and deep learning approach on the diabetic patients’ data set was set by quantum computing with AI and its applications. Quantum computing emerges to tackle optimization issues such as optimization for QML, a generative model for optimization, template matching, quantum theory for information retrieval, and quantum circuit optimization.
Elements of Quantum Electronics
Published in Michael Olorunfunmi Kolawole, Electronics, 2020
A quantum circuit is a compact representation of a computational system, consisting of quantum gates and quantum bits (qubits) as input. As noted in Chapter 2, Section 3 (Logic circuits design), the goal of electronic circuits’ design is to build hardware that will compute given function(s). We can build quantum circuits of any complexity out of these simple quantum gates (barest essentials). Efficient design of quantum circuits to performing arithmetic operation and other axillary functions needs special attention in quantum systems and, as well as in computing, and should be fault tolerant because reversible requirement makes quantum circuit design more difficult than classical circuit design. As such, the number of qubits is an important metric in a quantum circuit design and must be kept minimal. Few examples of quantum circuits derived from quantum gates are described as follows.
Photonics: A Dream of Modern Technology
Published in Tarun Kumar Gangopadhyay, Pathik Kumbhakar, Mrinal Kanti Mandal, Photonics and Fiber Optics, 2019
Sourangshu Mukhopadhyay, Shuvra Dey, Subhendu Saha
In quantum computation, quantum gate is an elementary quantum circuit acting on a small number of qubits. Quantum logic gates are reversible. These quantum logic gates are represented by unitary matrices, for example an n-qubit quantum gate can be described by a 2n × 2n unitary matrix. There are several quantum logic gates, such as Hadamard gate, Pauli-X, Y, Z gates, CNOT gate, Toffoli gate, Fredkin gate [15], etc.
Spectral single photons characterization using generalized Hong–Ou–Mandel interferometry
Published in Journal of Modern Optics, 2022
This entangling gate is now written, thanks to time–frequency operators, in order to make a direct mathematical connection with the widely known quadrature position-momentum formalism and also to identify the physical mechanisms that are needed for performing such an operation. The Hamiltonian corresponding to this gate is given by where are constants whose explicit forms depend on the physical mechanism producing such a non-linear effect. To obtain a balanced-frequency beam-splitter, the relation between the coefficients must verify which represents the angle characterizing the reflectivity and the transmission in the spectral-temporal domain . A quantum circuit diagram is represented in Figure 1. The mathematical structure of the frequency beam-splitter operation in Equation (18) is similar to the one describing the Kerr interaction or a three-photon absorption effect. The introduction of time–frequency operators will help us to find the appropriate physical mechanism to perform such an operation.
Quantum-computing with AI & blockchain: modelling, fault tolerance and capacity scheduling
Published in Mathematical and Computer Modelling of Dynamical Systems, 2019
A -qubit may be measured in a quantum computer or a quantum communication network. In the later case, some switch functionality may also be involved (e.g. for an entanglement between two qubits and see Sawerwain and Wiśniewska [37] for a reference). Thus, we add a switch gate to our quantum channel. For a quantum state with complex coefficients , its corresponding state after switching is denoted by . If the quantum gate takes an identity matrix , this gate placed in a quantum circuit does not perform any operation on the -qubit, e.g. . However, in a general situation, the gate will do the required switch operations. For examples, we can take to be a -qubit Pauli gate or a -qubit gate to perform the switch functionality,
Quantum computing methods for electronic states of the water molecule
Published in Molecular Physics, 2019
Teng Bian, Daniel Murphy, Rongxin Xia, Ammar Daskin, Sabre Kais
Some work has been done on this track to solve the resonance problem by quantum computers. By designing a general quantum circuit for non-unitary matrices, Daskin et al. [36] explored the resonance states of a model non-Hermitian Hamiltonian. To be specific, he introduced a systematic way to estimate the complex eigenvalues of a general matrix using the standard iterative phase estimation algorithm with a programmable circuit design. The bit values of the phase qubit determines the phase of eigenvalue, and the statistics of outcomes of the measurements on the phase qubit determines the absolute value of the eigenvalue. Other approaches for solving complex eigenvalues can also be applied for this resonance problem. For example, Wang et al. [37] proposed a measurement-based quantum algorithms for finding eigenvalues of non-unitary matrices. Terashima and Ueda [38] introduced a universal non-unitary quantum circuit by using a specific type of one-qubit non-unitary gates, the controlled-NOT gate, and all one-qubit unitary gates, which is also useful for finding the eigenvalues of a non-hermitian Hamiltonian matrix.