On the stochastic analysis of a quantum entanglement switch

Gayane Vardoyan, Saikat Guha, Philippe Nain, Don Towsley

Research output: Contribution to journalConference articlepeer-review

21 Scopus citations


We study a quantum entanglement switch that serves k users in a star topology. We model variants of the system using continuous-time Markov chains (CTMCs) and obtain expressions for switch capacity and the expected number of qubits stored in memory at the switch. Using CTMCs allows us to obtain a number of analytic results for systems in which the links are homogeneous or heterogeneous and for switches that have infinite or finite buffer sizes. In addition, we can easily model the effects of decoherence of quantum states using this technique. From numerical observations, we discover that decoherence has little effect on capacity and expected number of stored qubits for homogeneous systems. For heterogeneous systems, especially those operating close to stability constraints, buffer size and decoherence can significantly affect performance. We also learn that, in general, increasing the buffer size from one to two qubits per link is advantageous to most systems, while increasing the buffer size further yields diminishing returns.

Original languageEnglish (US)
Pages (from-to)27-29
Number of pages3
JournalPerformance Evaluation Review
Issue number2
StatePublished - Dec 4 2019
Event2019 Workshop on MAthematical Performance Modeling and Analysis, MAMA 2019, in conjunction with ACM SIGMETRICS / IFIP Performance 2019 - Phoenix, United States
Duration: Jun 28 2019Jun 28 2019

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications


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