A Model for Quantum Queue

Gawron, Piotr; Kurzyk, Dariusz; Puchała, Zbigniew

doi:10.1142/s0219749913500238

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…However, to make a quantum computer programable for the purpose to interact with real-world applications, it should have buffer storage and data read/write capability in addition to its processing capability (see, e.g., the illustration in Figure 4), which falls into the research scope concerning a quantum queueing system for its internal qubit data flow modeling, management, and related performance analysis (see, e.g., Dai [6,7], Gawron et al [9], and Mandayam et al [17]). Nevertheless, since this area is just getting started, a broad view concerning the system framework and research methodology needs to be put forward.…”

Section: Introductionmentioning

confidence: 99%

“…The comparisons between our current research and the existing ones on quantum queueing systems can be summarized as follows. In the study of Gawron et al [9], the authors present a quantum queueing model via the method of discrete time Markov chain. Nevertheless, in our current study, our queueing model is related to batch quantum random walks with multiclass service requirements and hence general doubly stochastic renewal reward random fields (DSRRRFs) over S n are involved.…”

Section: Introductionmentioning

confidence: 99%

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n-Qubit Operations on Sphere and Queueing Scaling Limits for Programmable Quantum Computer

Dai

2021

Preprint

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We study n-qubit operation rules on (n+1)-sphere with the target to help developing a (photon or other technique) based programmable quantum computer. In the meanwhile, we derive the scaling limits (called reflecting Gaussian random fields on a (n + 1)-sphere) for n-qubit quantum computer based queueing systems under two different heavy traffic regimes. The queueing systems are with multiple classes of users and batch quantum random walks over the (n + 1)-sphere as arrival inputs. In the first regime, the qubit number n is fixed and the scaling is in terms of both time and space. Under this regime, performance modeling during deriving the scaling limit in terms of balancing the arrival and service rates under first-in first-out and work conserving service policy is conducted. In the second regime, besides the time and space scaling parameters, the qubit number n itself is also considered as a varying scaling parameter with the additional aim to find a suitable number of qubits for the design of a quantum computer. This regime is in contrast to the well-known Halfin-Whitt regime.

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