Topology generator

Build quantum network topology

SimQN provides a interface (qns.network.topology.topo.Topology) for topology generators. All topology has the following initiate variables:

nodes_number: the number of nodes in the network
nodes_apps: a list of applications that will be added to all nodes
qchannel_args: the common attribution directory of quantum channels. Its key is the initiate variable’s name of QuantumChannel, for example: {"delay": 0.3, "bandwidth": 10}.
qchannel_args: the common attribution directory of classic channels. Its key is the initiate variable’s name of ClassicChannel, for example: {"delay": 0.3, "bandwidth": 10}.
memory_args: a list of the common attributions directory of the quantum memories. Its key is the initiate variable’s name of QuantumMemory, for example: [{"capacity": 10}, {"capacity": 10, "store_error_model_args": {"t_coh": 1}}]

Topology generators may have more parameters. The following example shows how to use the random topology generator, and it has an optional parameter lines_number:

from qns.network.topology import RandomTopology
from qns.network.network import QuantumNetwork

topo = RandomTopology(
    nodes_number=5,
    lines_number=10,
    qchannel_args={"delay": 0.05},
    cchannel_args={"delay": 0.05},
    memory_args=[{"capacity": memory_capacity}],
    nodes_apps=[EntanglementDistributionApp(init_fidelity=init_fidelity)])

# build the network
net = QuantumNetwork(topo=topo)

SimQn provides several topology generators:

BasicTopology generates several quantum nodes but no quantum channels. All nodes are not connected with each other.
LineTopology connects all nodes to from a line topology.
GridTopology forms a square grid topology. nodes_number should be a perfect square number.
TreeTopology generates a tree topology. It has an additional parameter children_number. Each parent node will connect to children_number child nodes.
RandomTopology generates a connected random topology based on the spanning tree. It has an additional parameter lines_number indicating the number of quantum channels.
WaxmanTopology is another random topology generator based on the Waxman’s algorithm. It has three additional parameters, size, alpha, and bete. The topology is in a \(size*size\) area. Both alpha and bete are parameters of the Waxman’s algorithm.

Users can build their own topology by inheriting the Topology class and implement the build method.

Build classic topology

SimQN is able to generate classic topologies as well. The classic topology is indicated by the variable classic_topo. It is an Enum with the following options:

ClassicTopology.All, all nodes are connected directly by a classic channels
ClassicTopology.Empty, no classic topology will be built
ClassicTopology.Follow, the classic topology will be the same to the quantum topology

from qns.network.topology import RandomTopology, ClassicTopology
from qns.network.network import QuantumNetwork

topo = RandomTopology(
    nodes_number=5,
    lines_number=10,
    qchannel_args={"delay": 0.05},
    cchannel_args={"delay": 0.05},
    memory_args=[{"capacity": memory_capacity}],
    nodes_apps=[EntanglementDistributionApp(init_fidelity=init_fidelity)])

# build the network, classic topology follows the quantum topology
net = QuantumNetwork(topo=topo, classic_topo=ClassicTopology.Follow)

Manage the network

The QuantumNetwork provides the following APIs to get or add nodes, channels, memories and applications:

install, initiate all nodes, channels, memories and applications in one step
add_node, add a new node
get_node, get a quantum nodes by its name
add_qchannel, add a new quantum channel
get_qchannel, get a quantum channel by its name
add_cchannel, add a new classic channel
get_cchannel, get a classic channel by its name
add_memories, add new quantum memories to all nodes

# get node by its name
n1 = net.get_node("n1")

# add a new node
n2 = QNode(name="n2")
net.add_node(n2)

# get a quantum channel by its name
l1 = net.get_qchannel("l1")

# add a quantum channel
l2 = QuantumChannel("l2")
net.add_node(l2)

node_list = net.nodes # get all nodes
qchannel_list = net.qchannels # get all quantum channels
cchannel_list = net.cchannels # get all classic channels

# produce a simulator
s = Simulator(0, 60)

# initiate the whole network
net.install(s)

s.run()