sf.apps.similarity.prob_orbit_mc¶

prob_orbit_mc(graph, orbit, n_mean=5, samples=1000, loss=0.0)[source]¶

Gives a Monte Carlo estimate of the probability of a given orbit for the input graph.

To make this estimate, several samples from the orbit are drawn uniformly at random using orbit_to_sample(). The GBS probabilities of these samples are then calculated and the sum is used to create an estimate of the orbit probability.

Example usage:

>>> graph = nx.complete_graph(8)
>>> prob_orbit_mc(graph, [2, 1, 1])
0.03744399092424391

Parameters

graph (nx.Graph) – input graph encoded in the GBS device
orbit (list[int]) – orbit for which to estimate the probability
n_mean (float) – total mean photon number of the GBS device
samples (int) – number of samples used in the Monte Carlo estimation
loss (float) – fraction of photons lost in GBS

Returns

Monte Carlo estimated orbit probability

Return type

float

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sf.apps.similarity.prob_orbit_mc¶

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