text stringlengths 0 8.13M |
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2 |
DQC O: Distributed Quantum Computing for |
Collaborative Optimization in Future Networks |
Napat Ngoenriang, Minrui Xu, Jiawen Kang, Dusit Niyato, Han Yu, and Xuemin (Sherman) Shen |
Abstract—With the advantages of high-speed parallel pro- The principles of quantum mechanics are used to enable |
cessing, quantum computers can efficiently solve large-scale quantum bits (i.e., qubits) in quantum computers which are |
complex optimization problems in future networks. However, |
superior to classical computers based on binary bits. For |
due to the uncertain qubit fidelity and quantum channel noise, |
example, Shor’s [3] algorithm and Grover’s [4] algorithm, |
2202 distributed quantum computing which relies on quantum net- |
works connected through entanglement faces a lot of challenges two well-known quantum algorithms, were developed to ef- |
for exchanging information across quantum computers. In this ficiently solve factorization and search for unstructured data, |
paper, we propose an adaptive distributed quantum computing respectively, These tasks are highly challenging for classical |
approachtomanagequantumcomputersandquantumchannels |
peS computers. However, scaling up quantum computers is a key |
for solving optimization tasks in future networks. Firstly, we |
challenge in deploying quantum computers in practice. To |
describe the fundamentals of quantum computing and its dis- |
tributed concept in quantum networks. Secondly, to address the date, only a small number of qubits can be implemented |
61 uncertaintyoffuturedemandsofcollaborativeoptimizationtasks in a single quantum computer. Moreover, quantum tasks |
and instability over quantum networks, we propose a quantum usually require the use of multiple qubits in more complex |
resourceallocationschemebasedonstochasticprogrammingfor |
applications. Due to the instability of qubits and the amount |
]CD.sc[ minimizing quantum resource consumption. Finally, based on |
of information required, it becomes more difficult to manage |
the proposed approach, we discuss the potential applications |
for collaborative optimization in future networks, such as smart and control information in quantum computers with a small |
grid management, IoT cooperation, and UAV trajectory plan- number of qubits. Thus, distributed quantum computing has |
ning. Promising research directions that can lead to the design been proposed in an attempt to alleviate this problem [5]. |
and implementation of future distributed quantum computing |
Theconceptofdistributedquantumcomputing,whichrefers |
frameworks are also highlighted. |
tomultipleinterconnectedquantumcomputers,wasintroduced |
1v78820.0122:viXra Index Terms—Distributed quantum computing, quantum net- |
to accelerate and perform collaboratively quantum computa- |
works, resource allocation |
tions through quantum networks. However, due to the prin- |
ciples of quantum mechanics, qubits cannot be duplicated or |
I. INTRODUCTION |
cloned.Distributedquantumcomputingrequiresquantumtele- |
Inthequantumera,theadvancementofquantumcomputing |
portation,inwhichqubitsareteleportedbetweentwoquantum |
and communication has attracted significant interest from |
computers. In this way, a large, complex computational task |
researchers, government organizations and the industry [1]. |
can be accomplished jointly by multiple quantum computers. |
Quantum computers provide effective solutions to complex |
It has been shown that the most commonly used quantum |
optimizationproblemsinaresourceefficientmanner,afeatnot |
algorithms benefit from their distributed counterparts. For |
possible for classical computers to achieve. The recent adop- |
example,distributedGrover’salgorithm[4]incurssignificantly |
tionofquantumcomputinghasfurtherboostedtechnologyin- |
shorter query time than Grover’s algorithm, and distributed |
novations such as artificial intelligence (AI), intelligent traffic |
Shor’s algorithm [3] is less complex than Shor’s algorithm. |
monitoring, weather forecasting, improved battery chemistry, |
The distributed versions of both algorithms increase their |
andlife-savingpharmaceuticals[1].Theproliferationofquan- |
viability of solving complex problems in practice. |
tumcomputinghasalsoevolvedtoacceleratecomputationfor |
Although distributed quantum computing has many advan- |
various applications and services in future networks, which |
tagesoverasinglequantumcomputerandclassicalcomputers, |
mustbedesignedefficientlyusinglimitedresourcestoperform |
designing efficient large-scale distributed quantum comput- |
a wide range of heterogeneous tasks [2]. |
ing still faces many challenges. Firstly, the effectiveness of |
using quantum computers is determined by the demand of |
N. Ngoenriang is with the School of Information Science and Technol- |
the applications, like military communication. This is un- |
ogy, Vidyasirimedhi Institute of Science and Technology, Thailand (e-mail: |
naphat.n s17@vistec.ac.th. known at the time of deployment, making planning difficult. |
M. Xu, H. Yu and D. Niyato are with the School of Computer Science Secondly, the availability and computing power of quantum |
andEngineering,NanyangTechnologicalUniversity,Singapore(e-mail:min- |
computers, which may vary over time, also affects whether |
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