2020 ◽  
Vol 34 (35) ◽  
pp. 2050401
Author(s):  
Mohammed Zidan

This paper shows a novel quantum computing model that solves quantum computing problems based on the degree of entanglement. We show two main theorems: the first theorem shows the quantum circuit that can be used to quantify the concurrence value between two adjacent qubits. The second theorem shows the quantum circuit of a proposed operator, called [Formula: see text] operator, which can be used to differentiate between the non-orthogonal states in the form [Formula: see text], with arbitrary accuracy, using the concurrence value. Then, the mathematical machinery for implementing the proposed model and its techniques using the circuit model is investigated extensively.


2018 ◽  
Vol 35 (23) ◽  
pp. 235013 ◽  
Author(s):  
Tomoro Tokusumi ◽  
Akira Matsumura ◽  
Yasusada Nambu

2017 ◽  
Vol 17 (13&14) ◽  
pp. 1096-1104
Author(s):  
Stephen Brierley

The quantum circuit model allows gates between any pair of qubits yet physical instantiations allow only limited interactions. We address this problem by providing an interaction graph together with an efficient method for compiling quantum circuits so that gates are applied only locally. The graph requires each qubit to interact with 4 other qubits and yet the time-overhead for implementing any n-qubit quantum circuit is 4 log n. Building a network of quantum computing nodes according to this graph enables the network to emulate a single monolithic device with minimal overhead.


Author(s):  
Phillip Kaye ◽  
Raymond Laflamme ◽  
Michele Mosca

In Section 1.3, we introduced the circuit model of (classical) computation. We restricted attention to reversible circuits since they can simulate any non-reversible circuit with modest overhead. This model can be generalized to a model of quantum circuits. In the quantum circuit model, we have logical qubits carried along ‘wires’, and quantum gates that act on the qubits. A quantum gate acting on n qubits has the input qubits carried to it by n wires, and n other wires carry the output qubits away from the gate. A quantum circuit is often illustrated schematically by a circuit diagram as shown in Figure 4.1. The wires are shown as horizontal lines, and we imagine the qubits propagating along the wires from left to right in time. The gates are shown as rectangular blocks. For convenience, we will restrict attention to unitary quantum gates (which are also reversible). Recall from Section 3.5.3 that non-unitary (non-reversible) quantum operations can be simulated by unitary (reversible) quantum gates if we allow the possibility of adding an ancilla and of discarding some output qubits. A circuit diagram describing a superoperator being implemented using a unitary operator is illustrated in Figure 4.2. In the example of Figure 4.1, the 4-qubit state |ψi⟩= |0⟩⊗ |0⟩⊗ |0⟩⊗ |0⟩ enters the circuit at the left (recall we often write this state as |ψi⟩ = |0⟩|0⟩|0⟩|0⟩ or |ψi⟩ = |0000⟩.) These qubits are processed by the gates U1, U2, U3, and U4. At the output of the circuit we have the collective (possibly entangled) 4-qubit state |ψf⟩. A measurement is then made of the resulting state. The measurement will often be a simple qubit-by-qubit measurement in the computational basis, but in some cases may be a more general measurement of the joint state. A measurement of a single qubit in the computational basis is denoted on a circuit diagram by a small triangle, as shown in Figure 4.1 (there are other symbols used in the literature, but we adopt this one). The triangle symbol will be modified for cases in which there is a need to indicate different types of measurements.R50


Author(s):  
Sergey Ulyanov ◽  
Andrey Reshetnikov ◽  
Olga Tyatyushkina ◽  
Vladimir Korenkov

All the quantum algorithms are based on a certain quantum computing model, varying from the quantum circuit, one-way quantum computation, adiabatic quantum computation and topological quantum computation. These four models are equivalent in computational power; among them, the quantum circuit model is most frequently used. In the circuit model, it has been proved that arbitrary single-qubit rotations plus twoqubit controlled-NOT gates are universal, i.e. they can provide a set of gates to implement any quantum algorithm. This article discusses the goal for this research: it is to given a lightning-fast (as-barebones-as-possible) definition of the quantum circuit model computing and leisurely development of quantum computation before actually getting around to sophisticated algorithms. In this article the main ideas of quantum software engineering is described.


Quantum ◽  
2021 ◽  
Vol 5 ◽  
pp. 421 ◽  
Author(s):  
Miriam Backens ◽  
Hector Miller-Bakewell ◽  
Giovanni de Felice ◽  
Leo Lobski ◽  
John van de Wetering

Translations between the quantum circuit model and the measurement-based one-way model are useful for verification and optimisation of quantum computations. They make crucial use of a property known as gflow. While gflow is defined for one-way computations allowing measurements in three different planes of the Bloch sphere, most research so far has focused on computations containing only measurements in the XY-plane. Here, we give the first circuit-extraction algorithm to work for one-way computations containing measurements in all three planes and having gflow. The algorithm is efficient and the resulting circuits do not contain ancillae. One-way computations are represented using the ZX-calculus, hence the algorithm also represents the most general known procedure for extracting circuits from ZX-diagrams. In developing this algorithm, we generalise several concepts and results previously known for computations containing only XY-plane measurements. We bring together several known rewrite rules for measurement patterns and formalise them in a unified notation using the ZX-calculus. These rules are used to simplify measurement patterns by reducing the number of qubits while preserving both the semantics and the existence of gflow. The results can be applied to circuit optimisation by translating circuits to patterns and back again.


2019 ◽  
Vol 2 (7-8) ◽  
pp. 1800078 ◽  
Author(s):  
Yunpu Ma ◽  
Volker Tresp ◽  
Liming Zhao ◽  
Yuyi Wang

2017 ◽  
Vol 19 (6) ◽  
pp. 063017 ◽  
Author(s):  
Daiqin Su ◽  
C T Marco Ho ◽  
Robert B Mann ◽  
Timothy C Ralph

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