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arXiv:1405.2354

Gates for Adiabatic Quantum Computing

Richard H. Warren

Published May 7, 2014• 2 citations
arXivHTMLPDF

Abstract

The goal of this paper is to introduce building blocks for adiabatic quantum algorithms. Adiabatic quantum computing uses the principle of quantum annealing, which implies that a carefully controlled energy solution is optimal and corresponds to minimizing a discrete function. The input function can be influenced by rewards and penalties to favor a solution that meets restrictions that are imposed by the problem. We show how to accomplish this influence for gates in adiabatic quantum computing, particularly the controlled-NOT gate (CNOT gate) which is fundamental to all quantum gates on two or more qubits. In addition, we adapt the Toffoli gate, the Fredkin gate, and the Hadamard gate to the Ising objective function which is a foundation for discrete optimization on D-Wave System machines. The quantum work in this paper encompasses Boolean operations, some of which are used to construct gates. We think the possible advantages of the building blocks in this paper will enhance quantum algorithms on D-Wave System computers.

DOI
10.48550/arxiv.1405.2354

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The goal of this paper is to introduce building blocks for adiabatic quantum algorithms. Adiabatic quantum computing uses the principle of quantum annealing, which implies that a carefully controlled energy solution is optimal and corresponds to minimizing a discrete function. The input function can be influenced by rewards and penalties to favor a solution that meets restrictions that are imposed by the problem. We show how to accomplish this influence for gates in adiabatic quantum computing, particularly the controlled-NOT gate (CNOT gate) which is fundamental to all quantum gates on two or more qubits. In addition, we adapt the Toffoli gate, the Fredkin gate, and the Hadamard gate to the Ising objective function which is a foundation for discrete optimization on D-Wave System machines. The quantum work in this paper encompasses Boolean operations, some of which are used to construct gates. We think the possible advantages of the building blocks in this paper will enhance quantum algorithms on D-Wave System computers.
We introduce a class of quantum adiabatic evolutions that we claim may be interpreted as the equivalents of the unitary gates of the quantum gate model. We argue that these gates form a universal set and may therefore be used as building blocks in the construction of arbitrary ``adiabatic circuits,'' analogously to the manner in which gates are used in the circuit model. One implication of the above construction is that arbitrary classical boolean circuits as well as gate model circuits may be directly translated to adiabatic algorithms with no additional resources or complexities. We show that while these adiabatic algorithms fail to exhibit certain aspects of the inherent fault tolerance of traditional quantum adiabatic algorithms, they may have certain other experimental advantages acting as quantum gates.
Abstract Adiabatic quantum computing is a universal model for quantum computing whose implementation using a gate-based quantum computer requires depths that are unreachable in the early fault-tolerant era. To mitigate the limitations of near-term devices, a number of hybrid approaches have been pursued in which a parameterized quantum circuit prepares and measures quantum states and a classical optimization algorithm minimizes an objective function that encompasses the solution to the problem of interest. In this work, we propose a different approach starting by analyzing how a small perturbation of a Hamiltonian affects the parameters that minimize the energy within a family of parameterized quantum states. We derive a set of equations that allow us to compute the new minimum by solving a constrained linear system of equations that is obtained from measuring a series of observables on the unperturbed system. We then propose a discrete version of adiabatic quantum computing that can be implemented in a near-term device while at the same time is insensitive to the initialization of the parameters and to other limitations hindered in the optimization part of variational quantum algorithms. We compare our proposed algorithm with the variational quantum eigensolver on two classical optimization problems, namely MaxCut and number partitioning, and on a quantum-spin configuration problem, the transverse-field ising chain model, and confirm that our approach demonstrates superior performance.
In the recent years the field of adiabatic quantum computing has gained importance due to the advances in the realisation of such machines, especially by the company D-Wave Systems. In contrast to a quantum computer in the conventional sense, an adiabatic quantum computer can solve a discrete optimisation problem by encoding the objective function into a quantum mechanical system. By carefully evolving the system in time from an initial state into the lowest energy state, the optimisation problem is solved. Due to the quantum nature of the device it is assumed that there is a substantial speedup compared to classical HPC facilities. The D-Wave machines are capable of finding the minimum of a subclass of the Ising model, a quadratic unconstrained binary optimisation problem. In this paper, we present a way of mapping more general problems to the subclass of Ising problems in order to make them solvable on an adiabatic quantum computer. As an example, we choose the maximum clique problem where one needs to find the maximal complete subgraph in an undirected graph. The corresponding decision problem is NP-complete. It has applications in social media or computational chemistry. Moreover, the solution of the maximum clique problem can be used to increase the number of logical variables which can be realised on a D-Wave machine. In addition, we investigate the applicability of adiabatic quantum computing to the scheduling optimisation of satellite missions performed by the German Aerospace Center.
Quantum physics has the potential to revolutionize computer science by building what is called a quantum computer. Quantum computers can perform tasks that are impossible with Turing-machine based classical computers (e.g., generating random sequences of bits) and can outperform classical computers (to different degrees) in a variety of classical computation problems. Several different models of quantum computing exist. Based on the Adiabatic Theorem in physics, Adiabatic Quantum Computing is a novel computing framework that is drastically different from the more traditional quantum logic gate model. Traditionally, quantum computing has only been tested on devices with a very small number of qubits, severely limiting their uses in practice. In recent years however, advances in engineering and physics have allowed the construction for (relatively) large machines called quantum annealers that do what is known as a specific type of adiabatic quantum computation called quantum annealing. Solving classical computation problems with the quantum annealing framework is not an easy task and there are many obstacles to overcome if we want to achieve any kind of speedups over classical algorithms. In this thesis, we present quantum annealing solutions to several classical problems including the Hamiltonian Cycle Problem, Mixed Dominating Set Problem, Graph Isomorphism Problem, Densest k-Subgraph Problem and the Maximum Weighted Independent Set Problem. Experimental results of these quantum solutions on DWave quantum annealers are also reported. We also look at some of the bottlenecks in the quantum annealing framework and propose several novel approach to mitigate their effects on the efficiency of the quantum solutions.
Reversible Computing circuits are characterized by low power consumption and their proximity to circuits for quantum computing. The Fredkin gate was one of the earliest proposed controlled reversible circuits, which however, was soon superseded by the Toffoli gate, the NOT, and CNOT gates, which constituting a flexible functionally complete set could also realize the Fredkin gate as a building block. In quantum computing circuits, the Fredkin gate (under the name controlled SWAP) plays an important role regarding the superposition of states. The present paper studies extensions of the Fredkin gate in terms of mixed polarity in the reversible domain and an application in quantum computing.
To build a general-purpose quantum computer, it is crucial for the quantum devices to implement classical boolean logic. A straightforward realization of quantum boolean logic is to use auxiliary qubits as intermediate storage. This inefficient implementation causes a large number of auxiliary qubits to be used. In this paper, we have derived a systematic way of realizing any general m-to-n bit combinational boolean logic using elementary quantum gates. Our approach transforms the m-to-n bit classical mapping into a t-bit unitary quantum operation with minimum number of auxiliary qubits, then a variation of Toffoli gate is used as the basic building block to construct the unitary operation. Finally, each of these building blocks can be decomposed into one-bit rotation and two-bit control-U gates. The efficiency of the network is taken into consideration by formulating it as a constrained set partitioning problem.