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rui001@e.ntu.edu.sg;han.yu@ntu.edu.sg);dniyato@ntu.edu.sg). |
J. Kang is with the School of Automation, Guangdong University of quantum tasks can be fully computed. Thirdly, distributed |
Technology,China(e-mail:e-mail:kavinkang@gdut.edu.cn. quantumcomputingmaysufferfromfidelitydegradation.This |
X. (Sherman) Shen is with the Department of Electrical and Computer |
is unavoidable at the moment, and reduces the efficiency of |
Engineering, University of Waterloo, Waterloo, ON, Canada, N2L 3G1 (e- |
mail:sshen@uwaterloo.ca). quantum teleportation in quantum networks. Thus, deploying |
Provision of the deployed |
Applications require the |
quantum computers Entanglement |
use of quantum computing |
Superposition |
Military |
Measurement/Interference |
Properties of quantum mechanics |
Minimize costs of using the |
deployed quantum computers |
under quantum resources |
Quantum computer |
Internet of Things Smart Grid |
operator |
Provision of on-demand Perform quantum computing on |
quantum computer deployment distributed quantum computing |
Fig. 1: The adaptive resource allocation approach with two-stage stochastic programming for distributed quantum computing. |
quantum resources in distributed quantum computing in its 2n possible outcomes and have the same chance of being |
current form may result in highly inefficient utilization of measured for each. Therefore, quantum computers can store |
quantum computing resources due to the inherent uncertainty and manipulate more information than classical computers, |
in real-world circumstances. providing far more diverse possibilities and opportunities. |
To address the above challenges, in this paper, we propose 2) Interference: Qubits must be subjected to some kind |
an adaptive resource allocation approach towards efficient of measurement in order to represent and store their values |
and scalable distributed collaborative quantum computing. It and results. If one intervenes in the process, it is possible to |
consists of deterministic and stochastic programming models measure and see the results of the paths. When the process is |
for quantum resource allocation with uncertainty in collabo- interrupted, the states of the qubits collapse to classical bits, |
rative settings to help quantum computer operators minimize and the computation results appear. For example, the result of |
total deployment costs. It jointly considers the uncertainty of a coin toss is known definitively (e.g., heads or tails) when |
future quantum computing demands, the computing power of the coin reaches the bottom. |
quantum computers, and the fidelity in distributed quantum 3) Entanglement: Two qubits can be entangled with each |
computing in order to optimally deploy and utilize quantum otherasanentanglementpair[5],whichmeansthatwhenone |
computers. We conduct extensive experiments to reveal the qubit is measured, the other qubit can also be known because |
importance of the optimal deployment of quantum computers of their entangled nature. In addition, a pair of entanglement |
in distributed quantum computing. In comparison to other qubitsisentangledmaximallyalsoknownasaBellstatewhen |
resource allocation models, the proposed approach can reach the results of measuring one of them will certainly affect |
the lowest total deployment cost. Finally, we highlight oppor- the outcome of measuring the other one later. The fidelity |
tunities and challenges in distributed quantum computing for of entanglement pairs is the metric of attenuation for the |
various military applications in future networks. entangledqubitsbetweentworemotequantumcomputers.The |
fidelity scale runs from 0 to 1, where 1 indicates the best |
performance that the entanglement can achieve. |
II. FUNDAMENTALSOFQUANTUMCOMPUTING The main analogies between classical computing and the |
technology used to realize a true quantum computer are the |
A. Quantum Computing |
following. In classical computing, a circuit is a computational |
Three properties of quantum mechanics define quantum |
model that enables the processing of input values through |
computing: superposition, interference, and entanglement, as |
gates and operations. Similarly, the quantum circuit model |
shown in Fig. 1. |
proceeds with implementations on qubits and involves an |
1) Superposition: In classical computers, the binary bits |
ordered sequence of quantum gates that permit logical in- |
0 and 1 are used to encode information for computations. |
teraction between qubits. In particular, the measurement of |
A superposition in quantum computing allows the encoding |
qubits must occur near the end of the quantum circuit. A |
of qubits in a combination of two classical binary states. A |
quantum processor is a small quantum computer that can |
well-known example of quantum mechanics is the tossing of |
executequantumgatesonasmallnumberofqubitsandallows |
a coin. When a coin is tossed in the air, the exact outcome is |
the entanglement of qubits inside. |
unknown, and its probability values reflect qubits. Each qubit |
B. Distributed Quantum Computing |
can be expressed as a linear combination of binary states, |
where the coefficients correspond to the probabilities of the Theconceptofdistributedquantumcomputingreliesonthe |
qubit amplitudes. Due to the superposition, n qubits can store following principles: |
Ref. Scenarios Problems Performance Metrics Quantum Algorithms |
[6] Quantum-enhancedsmartgrid Paradigm and elements of Grid efficiency, security, and Quantum Fourier transform, |
quantum computing in power stability quantumsearch,andquantum |
systems neural networks |
[2] Realizing IoT environments IoT-sensor space problem Data accuracy and data tem- Quantum-basedalgorithmand |
porary efficiency quantum Fourier transform |
[7] UAV-mounted wireless net- Trajectory and uplink trans- Convergenceperformanceand Quantum-based action selec- |
works mission rate optimization learningqualityoftrajectories tion strategy |
[8] Quantum machine learning Improvement computation of Computation complexity Quantum mechanics, Shor’s, |
machine learning algorithms and Grover’s algorithm |
[9] Entanglement flow in quan- Maximization of fidelity over Entanglement rate and router Quantum router architecture |
tum networks long-distance links infidelity design |
[10] Adaptive measurements in Estimation state of qubits Successprobabilityofestima- Grover’s algorithm |
quantum tion |
[11] Resource allocation in quan- Quantum network flow opti- The number of served apps, (Weighted round robin algo- |
tum networks mization the Bell pair capacity, and rithm for resource allocation) |
Jain’s fairness |
TABLE I: Summary of representative related works demonstrated through scenarios, problems, performance metrics, and |
quantum algorithms |
1) Quantum Networks through Entanglement: To enable QPUs, which are subsequently utilized to read output after |
distributed quantum computing, a quantum network must be a measurement. The QPUs should have specialized space to |
developedtoconnectquantumcomputers.However,duetothe store and operate matter qubits that improve the ability of |
non-cloning theorem in quantum mechanics, qubits cannot be distributed quantum computing to work quickly and consis- |
duplicated or cloned across quantum computers. Thus, two tently. In addition, network communication is also needed for |
quantum computers must exchange or transfer qubits through QPUs to send signals across the network while measuring |
the concept of quantum teleportation. In quantum telepor- and reading qubits. The effort required to input data and the |
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