vary_p_cz_comp.py

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()