Fig. 4: Performance analysis of the quantum switch with nine users using NetSquid.

a Capacity as a function of the buffer size (number of quantum memories that the switch has available per user) for either 2 −or 4− qubit Greenberger–Horne–Zeilinger (GHZ)-states. For each scenario, the generation rate μ of pairs varies per user. For the blue scenario (2-partite entanglement, μ = [1.9, 1.9, 1.9, 1, 1, 1, 1, 1, 1] MHz), the capacity was determined analytically by Vardoyan et al. using Markov Chain methods⁵⁶. Here we extend this to 4-partite entanglement (orange scenario, same μs), for which Vardoyan et al. have found an upper bound (by assuming unbounded buffer and each μ = maximum of original rates = 1.9 MHz) but no exact analytical expression. The green scenario (μ = [15, 1.9, 1.9, 1, 1, 1, 1, 1, 1] MHz) does not satisfy the stability condition for the Markov chain for unbounded buffer size (each leaf’s rate < half of sum of all rates) so in that case steady-state capacity is not well-defined. We note that regardless of buffer size, the switch has a single link to each user, which is the reason why the capacity does not scale linearly with buffer size. b Average fidelity of the produced entanglement on the user nodes (no analytical results known) with unbounded buffer size. The fact that the green curve has lower fidelity than the blue one, while the former has higher rates, can be explained from the fact that the protocol prioritises entanglement which has the longest storage time (see Supplementary Note 3). Each data point represents the average of 40 runs (each 0.1 ms in simulation). Standard deviation is smaller than dot size.