74 lines
2.4 KiB
Python
74 lines
2.4 KiB
Python
from collections import deque
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import matplotlib.pyplot as plt
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import numpy as np
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import json
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from pyqcs import State, H, X, S, CZ, M, list_to_circuit
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from pyqcs.graph.state import GraphState
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from pyqcs.util.random_circuits import random_circuit
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from measure_circuit import execution_statistics
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def S_with_extra_arg(act, i):
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return S(act)
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def test_scaling_qbits(state_factory
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, nstart
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, nstop
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, ngates_per_qbit
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, ncircuits
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, **kwargs):
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results = deque()
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for qbits in range(nstart, nstop):
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measurement_circuit = list_to_circuit([M(i) for i in range(qbits)])
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circuits = [random_circuit(qbits, ngates_per_qbit * qbits, X, H, S_with_extra_arg, CZ)
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| measurement_circuit
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for _ in range(ncircuits)]
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state = state_factory(qbits)
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print("running test with", qbits, "qbits")
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N, avg, std_dev = execution_statistics(circuits, state, scale=qbits, **kwargs)
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results.append([qbits, N, avg, std_dev])
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return np.array(results, dtype=np.double)
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if __name__ == "__main__":
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nstart = 4
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nstop = 16
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ncircuits = 50
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ngates_per_qbit = 100
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seed = 0xdeadbeef
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np.random.seed(seed)
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results_naive = test_scaling_qbits(State.new_zero_state
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, nstart
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, nstop
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, ngates_per_qbit
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, ncircuits
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, repeat=10)
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np.random.seed(seed)
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results_graph = test_scaling_qbits(GraphState.new_zero_state
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, nstart
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, nstop
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, ngates_per_qbit
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, ncircuits
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, repeat=10)
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np.savetxt("qbit_scaling_naive.csv", results_naive)
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print("saved naive results to qbit_scaling_naive.csv")
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np.savetxt("qbit_scaling_graph.csv", results_graph)
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print("saved graph results to qbit_scaling_graph.csv")
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meta = {"nstart": nstart
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, "nstop": nstop
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, "ncircuits": ncircuits
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, "ngates_per_qbit": ngates_per_qbit
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, "seed": seed}
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with open("qbit_scaling_meta.json", "w") as fout:
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json.dump(meta, fout)
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print("saved meta data to qbit_scaling_meta.json")
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