Nature2010.ipynb

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   "source": [
    "import numpy as np\n",
    "from scipy.optimize import brentq\n",
    "n = 4E5 # experiment run number\n",
    "score = 0.803 # CHSH score, classcial threshold 0.75\n",
    "convertedScore = (score - 0.5) * 8.0 # convert to [2, 2sqrt(2)]\n",
    "delta = 2/np.sqrt(n) # confidence level\n",
    "epFun = lambda x: np.exp(-n*x**2/2.0/(4+2*np.sqrt(2))**2)-delta\n",
    "epsilon = brentq(epFun, 0, 1)\n",
    "entropy = 1-np.log2(1+np.sqrt(2-(convertedScore - epsilon)**2/4))\n",
    "entropy"
   ]
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       "0.003162277660168379"
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   "source": [
    "delta"
   ]
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   "source": [
    "scorelis = np.linspace(0.7501, (2+np.sqrt(2))/4-0.0001, 200)\n",
    "resultlis = np.array([])\n",
    "for score in scorelis:\n",
    "    convertedScore = (score - 0.5) * 8.0 # convert to [2, 2sqrt(2)]\n",
    "    delta = 2/np.sqrt(n) # confidence level\n",
    "    epFun = lambda x: np.exp(-n*x**2/2.0/(4+2*np.sqrt(2))**2)-delta\n",
    "    epsilon = brentq(epFun, 0, 1)\n",
    "    entropy = 1-np.log2(1+np.sqrt(2-(convertedScore - epsilon)**2/4))\n",
    "    resultlis = np.append(resultlis, entropy)\n",
    "np.savetxt('Nature2010.txt', np.vstack((scorelis, resultlis)).transpose())"
   ]
  }
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