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vary_p_cz_comp.py
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vary_p_cz_comp.py
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import calc_log_e_rate_arbitrary_error_model
import matplotlib.pyplot as plt
from compiled_surface_code_arbitrary_error_model import *
correction_table = load_lookup_table("correction_table_depolarising.json")
bitflip_table = load_lookup_table("correction_table_classical_bitflip.json")
#ps = [0.01, 0.007, 0.005]
ps = [0.01]
runs = 2000
run_name = "test_cz_comp"
log_e_rate_list = []
for p in ps:
p_set = [34*[p/10], # py
34*[p/10], # p1q_deph
24*[p], # p2q_deph
24*[0], # p_ctrl_leak
48*[0]] # p_env_leak
e_model, model_probs = instantiate_error_model(p_set, 'cz_PDD_model')
print(e_model['gates'], model_probs)
filename = run_name+"_p={}".format(p)
log_e_rate = calc_log_e_rate_arbitrary_error_model.calculate_log_e_rate(runs, filename, correction_table, e_model,
model_probs, bitflip_table,
cz_compilation=True) # choose if using experimental new compilation
log_e_rate_list.append(log_e_rate)
#log_e_rate = calculate_log_e_rate.calculate_log_e_rate(100, "this_file3", 0.7)
plt.scatter(ps, log_e_rate_list)
plt.ylabel('logical error rate')
plt.xlabel('p')
plt.show()