diff --git a/applications/lofar2/model/lofar2_station_sdp_firmware_model.ipynb b/applications/lofar2/model/lofar2_station_sdp_firmware_model.ipynb
index bc89897d52492e1ac09a26718b35e1d832bcf88d..02fbcf3672e682874c938748f828ffb6125942ef 100644
--- a/applications/lofar2/model/lofar2_station_sdp_firmware_model.ipynb
+++ b/applications/lofar2/model/lofar2_station_sdp_firmware_model.ipynb
@@ -19,7 +19,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "id": "2b477516",
    "metadata": {},
    "outputs": [],
@@ -38,7 +38,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "e1b6fa12",
    "metadata": {},
    "outputs": [
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "eb325c9c",
    "metadata": {},
    "outputs": [
@@ -98,7 +98,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "3e71626f",
    "metadata": {},
    "outputs": [
@@ -135,7 +135,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 6,
    "id": "def6eba7",
    "metadata": {},
    "outputs": [
@@ -166,10 +166,10 @@
     "\n",
     "# . DFT size\n",
     "N_points = 1024\n",
-    "N_bins = N_points // 2 + 1  # positive frequency bins including DC and F_s/2\n",
+    "N_bins = N_points // 2 + 1  # positive frequency bins including DC and f_s/2\n",
     "\n",
     "# . select a bin\n",
-    "i_bin = 200   # bin index in range(N_points // 2 )\n",
+    "i_bin = 200   # bin index in range(N_bins)\n",
     "\n",
     "# . time and frequency axis\n",
     "f_s = f_adc  # sample frequency\n",
@@ -207,7 +207,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 7,
    "id": "0ec00484",
    "metadata": {},
    "outputs": [
@@ -221,10 +221,11 @@
       "subband_weight_im = 0\n",
       "\n",
       "G_subband = 0.994817 * 0.5 * 2**4 * 1.0 = 7.958536\n",
-      "    . G_fir_dc = 0.994817\n",
-      "    . G_fft_real_input_sine = 0.5\n",
-      "    . W_sub_gain = 4\n",
-      "    . subband_weight_gain = 1.0\n"
+      "  . G_fir_dc = 0.994817\n",
+      "  . G_fft_real_input_sine = 0.5\n",
+      "  . W_sub_proc = 4.5\n",
+      "  . W_sub_gain = 4\n",
+      "  . subband_weight_gain = 1.0\n"
      ]
     }
    ],
@@ -235,7 +236,7 @@
     "\n",
     "# . Signal level bit growth to accomodate processing gain of FFT\n",
     "W_sub_proc = np.log2(np.sqrt(N_sub))\n",
-    "W_sub_gain = 4\n",
+    "W_sub_gain = 4  # use W_sub_gain instead of W_sub_proc\n",
     "\n",
     "# Subband equalizer (E_sub)\n",
     "subband_weight_gain = 1.0\n",
@@ -255,13 +256,14 @@
     "print(f\"G_subband = {G_fir_dc} * {G_fft_real_input_sine} * 2**{W_sub_gain} * {subband_weight_gain} = {G_subband}\")\n",
     "print(\"  . G_fir_dc =\", G_fir_dc)\n",
     "print(\"  . G_fft_real_input_sine =\", G_fft_real_input_sine)\n",
+    "print(\"  . W_sub_proc =\", W_sub_proc)\n",
     "print(\"  . W_sub_gain =\", W_sub_gain)\n",
     "print(\"  . subband_weight_gain =\", subband_weight_gain)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 8,
    "id": "4d197368",
    "metadata": {},
    "outputs": [
@@ -275,10 +277,10 @@
       "beamlet_weight_im = 0\n",
       "\n",
       "BF for coherent input:\n",
-      "  . W_bf_proc = 10.00 for N_ant = 10\n",
+      "  . bf_proc = 10.00 for N_ant = 10\n",
       "\n",
       "BF for incoherent input:\n",
-      "  . W_bf_proc = 3.16 for N_ant = 10\n",
+      "  . bf_proc = 3.16 for N_ant = 10\n",
       "\n"
      ]
     }
@@ -329,12 +331,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 9,
    "id": "f66c5028",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "P_bit_dB = 6.02 dB\n"
+     ]
+    }
+   ],
    "source": [
     "# Bit\n",
+    "# . Each bit yields a factor 2 in voltage, so a factor 2**2 = 4 in power \n",
     "P_bit = 2**2\n",
     "P_bit_dB = 10 * np.log10(P_bit)\n",
     "print(f\"P_bit_dB = {P_bit_dB:.2f} dB\")"
@@ -342,12 +353,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 10,
    "id": "a9fca052",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "P_quant = 0.083333\n",
+      "P_quant_dB = -10.79 dB = -1.8 bit\n",
+      "sigma_quant = 0.29 q\n"
+     ]
+    }
+   ],
    "source": [
     "# Quantization noise\n",
+    "# . The quantization noise power is q**2 * 1 / 12, so the standard deviation\n",
+    "#   of the quantization noise is q * sqrt(1 / 12) < q = one LSbit\n",
+    "# . The quantization noise power is at a level of -10.79 dB or -1.8 bit.\n",
+    "# . The 0 dB power level corresponds to the power of one LSbit, so q**2 \n",
     "P_quant = 1 / 12  # for W >> 1 [2]\n",
     "P_quant_dB = 10 * np.log10(P_quant)\n",
     "sigma_quant = np.sqrt(P_quant)\n",
@@ -359,14 +385,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 11,
    "id": "d9972b6b",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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\n",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "# System noise\n",
     "n = np.arange(1,9)\n",
-    "sigma_sys = n\n",
+    "sigma_sys = n   # = n * q, so n LSbits\n",
     "P_sys = sigma_sys**2\n",
     "P_tot = P_sys + P_quant\n",
     "sigma_tot = np.sqrt(P_tot)\n",
@@ -381,10 +420,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 12,
    "id": "be2d952f",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "W_adc = {W_adc} bits\n",
+      "FS = 8192\n",
+      "sigma_fs_sine = 5792.6 q\n",
+      "P_fs_sine_dB = 75.26 dB = 12.5 bit\n"
+     ]
+    }
+   ],
    "source": [
     "# FS sine\n",
     "P_fs_sine = FS**2 / 2\n",
@@ -397,10 +447,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "a9e7fabc",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "SNR_dB = P_fs_sine_dB - P_quant_dB = 75.26 - -10.79 = 86.05 dB\n"
+     ]
+    }
+   ],
    "source": [
     "# SNR\n",
     "SNR = P_fs_sine / P_quant\n",
@@ -412,10 +471,23 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "id": "92852a53",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Power at -50dBFS = 25.26 dB, so sigma = 18.3 q, ampl = 25.9 q\n",
+      "\n",
+      "sigma = 16 q corresponds to:\n",
+      "  . Power = 24.08 dB, so at -51.2 dBFS\n",
+      "  . Range 3 sigma = +-48 q\n",
+      "  . Sine with amplitude A = sigma * sqrt(2) = 22.6 q\n"
+     ]
+    }
+   ],
    "source": [
     "# -50 dbFS level\n",
     "Power_50dBFS = P_fs_sine_dB - 50  \n",
@@ -445,10 +517,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "id": "a04af043",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ADC sigma = 5792.6 q = 12.5 bits: P_ast = 6.710886e+15, uses 52.6 bits, is 0 dBFS = FS sine\n",
+      "ADC sigma =   18.3 q =  4.2 bits: P_ast = 6.710886e+10, uses 36.0 bits, is -50dBFS\n",
+      "ADC sigma =   16.0 q =  4.0 bits: P_ast = 5.120000e+10, uses 35.6 bits\n"
+     ]
+    }
+   ],
    "source": [
     "# ADC power statistic (AST)\n",
     "sigma = sigma_fs_sine\n",
@@ -469,10 +551,26 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "id": "0b2ac36c",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Signal input level --> Expected subband level and SST level:\n",
+      "\n",
+      " ampl_si   ampl_sub    #bits           SST  #bits\n",
+      "  8192.0    65196.3  15.9925  8.301877e+14   49.6\n",
+      "    25.9      206.2   7.6877  8.301877e+09   33.0\n",
+      "    16.0      127.3   6.9925  3.166915e+09   31.6\n",
+      "\n",
+      "sigma_si  sigma_sub    #bits           SST  #bits\n",
+      "    22.6      180.1   7.4925  6.333830e+09   32.6\n"
+     ]
+    }
+   ],
    "source": [
     "# Subband filterbank (F_sub)\n",
     "ampl_sub_fs = FS * G_subband  # subband amplitude for FS signal input sine\n",
@@ -502,7 +600,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "id": "f0b09a83",
    "metadata": {},
    "outputs": [],
diff --git a/applications/lofar2/model/signal_statistics.ipynb b/applications/lofar2/model/signal_statistics.ipynb
index 4a1f8fbc19bb9b89aad3bd2aadc7b49fab78a42f..1c09874019802d28d0c03e95ebbe661b46761a37 100644
--- a/applications/lofar2/model/signal_statistics.ipynb
+++ b/applications/lofar2/model/signal_statistics.ipynb
@@ -13,8 +13,8 @@
     "\n",
     "Status:\n",
     "* coherent summator (= voltage beamformer): SNR of coherent input improves by the number of inputs N\n",
-    "* incoherent summator (= auto correlation, power beamformer): SNR does not improve, but accuracy of power mean measurement (its variance) does improves by factor N. Summing powers from N inputs or summing N powers from one input is equivalent.\n",
-    "* correlator: SNR of coherent input improves by sqrt(N) for integration over N cross powers in time. Hence if the input SNR of the input signal is -20 dB (i.e. sigma_coh / sigma_sys = 0.1) then it takes N = 10000 to improve the SNR by a factor 100 = +20 dB to 0 dB.\n",
+    "* incoherent summator (= auto correlation, power beamformer): SNR does not improve, but accuracy of mean power measurement does improves by factor N, so the std of the mean power measurement reduces by N. Summing powers from N inputs (like in an incoherent beamformer) or summing N powers in time from 1 input (like in subband auto power statistics) is equivalent.\n",
+    "* correlator: SNR of coherent input improves by sqrt(N) for integration over N cross powers in time. Hence if the input SNR of the input signal is -20 dB (i.e. sigma_coh / sigma_sys = 0.1) then it takes integratiopn over N = 10000 cross powers in time to improve the SNR of the correlator output by a factor 100 = +20 dB to 0 dB.\n",
     "\n",
     "References:\n",
     "\n",
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 34,
    "id": "2b477516",
    "metadata": {},
    "outputs": [],
@@ -45,19 +45,19 @@
     "* mean power = var + mean**2\n",
     "* rms = sqrt(mean power) = sqrt(var + mean**2)\n",
     "\n",
-    "Coherent and incoherent signals. With S signals, the std of their sum:\n",
+    "Signal with coherent or incoherent samples. With N samples, the std of their sum:\n",
     "    \n",
-    "* increases by S for coherent signals\n",
-    "* increases by sqrt(S) for incoherent signals\n",
+    "* increases by N for coherent signals\n",
+    "* increases by sqrt(N) for incoherent signals\n",
     "\n",
-    "Coherent averaging by summing the signal voltages improves the SNR of a signal by a factor N^2 / N = N, because the signal power increases by a factor N^2, while the incoherent noise adds as powers, so the noise power increases by a factor N.\n",
+    "Coherent averaging by summing the signal voltages improves the SNR of a signal by a factor N^2 / N = N, because the coherent signal power increases by a factor N^2, while the incoherent noise adds as powers, so the noise power increases by a factor N.\n",
     "\n",
-    "Incoherent averaging by summing the signal powers does not improve the SNR, because the phase information of the signal is lost in the powers. Incoherent averaging does reduce the variance of the signal power estimate by a factor N, so it mkes the measurement more accurate."
+    "Incoherent averaging by summing the signal powers does not improve the SNR, because the phase information of the signal is lost in the powers. Incoherent averaging does reduce the std of the signal power estimate by a factor N, so incoherent averaging makes the signal power measurement more accurate."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 35,
    "id": "9c55fb7b",
    "metadata": {},
    "outputs": [],
@@ -74,7 +74,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 36,
    "id": "74edfe32",
    "metadata": {},
    "outputs": [
@@ -82,9 +82,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "mean(si) = -0.207540, expected -0.2\n",
+      "mean(si) = -0.206805, expected -0.2\n",
       "std(si) = 0.500000, expected 0.5\n",
-      "rms(si) = 0.541362, expected 0.538516\n"
+      "rms(si) = 0.541081, expected 0.538516\n"
      ]
     }
    ],
@@ -114,7 +114,7 @@
     "Two types:\n",
     "\n",
     "1. Coherent summation in voltage beamformer (e.g. digital BF in LOFAR2 Station, TAB in ARTS)\n",
-    "2. Incoherent summation in power beamformer (e.g. IAB in ARTS)"
+    "2. Incoherent summation in power statistics (e.g. SST, BST), power beamformer (e.g. IAB in ARTS)"
    ]
   },
   {
@@ -130,18 +130,18 @@
     "2. Incoherent signal, add up as power\n",
     "\n",
     "In the voltage beamformer the sky signal in the beamlet direction adds coherently and the sky\n",
-    "signals from other directions and from the receivers noise add incoherently. Hence the SNR of the beamlet signal improves by factor S/sqrt(S) = sqrt(S)."
+    "signals from other directions and the signals from the receivers noise add incoherently. Hence the SNR of the beamlet signal improves by factor S/sqrt(S) = sqrt(S)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 37,
    "id": "89845ec3",
    "metadata": {},
    "outputs": [
     {
      "data": {
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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -153,7 +153,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -246,7 +246,7 @@
    "id": "fd6ffb94",
    "metadata": {},
    "source": [
-    "Incoherent summation of powers from S inputs is equivalent to incoherent summation of S powers in time from a single input. Therefore the incoherent summation does not improve the SNR of the signal, but it does improve the accuracy of the power measurement by a factor S. Hence instead of measuring with one dish for S intervals it is equivalent to sum the powers of S dishes for 1 interval. Hence the field of view of the summed power beam is the same as the field of view of one dish."
+    "Incoherent summation of powers from S inputs is equivalent to incoherent summation of S powers in time from a single input. Incoherent summation does not improve the SNR of the signal, but it does improve the accuracy of the power measurement by a factor S. Hence instead of measuring with one dish for S intervals it is equivalent to sum the powers of S dishes for 1 interval. Hence the field of view of the summed array power beam is the same as the field of view of one dish."
    ]
   },
   {
@@ -267,13 +267,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 43,
    "id": "8713e865",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -285,7 +285,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -297,7 +297,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -324,31 +324,50 @@
     "\n",
     "# Input signal\n",
     "sigma = 1.0\n",
-    "pow_mean = sigma**2\n",
+    "expected_pow_mean = sigma**2\n",
     "\n",
     "# Auto correlator mean(A * A)\n",
     "auto_mean_arr = []\n",
-    "auto_std_arr = []\n",
-    "measure_SNR_arr = []\n",
-    "measure_SNR_dB_arr = []\n",
+    "auto_mean_SNR_arr = []\n",
+    "auto_mean_SNR_dB_arr = []\n",
     "for N_samples in N_samples_arr:\n",
     "    # Signal input A\n",
     "    sA = np.random.randn(N_samples)\n",
     "    sA *= sigma / np.std(sA)\n",
     "\n",
     "    # Auto correlate A\n",
+    "    # . the auto_mean is the mean power\n",
     "    auto_mean = np.mean(sA * sA)\n",
     "    auto_mean_arr.append(auto_mean)\n",
-    "    auto_std = np.std(sA * sA)\n",
-    "    auto_std_arr.append(auto_std)\n",
+    "    # . the np.std(sA * sA) is not useful, because for powers all info is already in the auto_mean\n",
     "\n",
     "    # Accuracy of the power measurement\n",
-    "    measure_SNR = auto_mean / np.abs(auto_mean - pow_mean)\n",
-    "    measure_SNR_dB = 10 * np.log10(measure_SNR)\n",
-    "    measure_SNR_arr.append(measure_SNR)\n",
-    "    measure_SNR_dB_arr.append(measure_SNR_dB)\n",
+    "    auto_mean_SNR = auto_mean / np.abs(auto_mean - expected_pow_mean)\n",
+    "    auto_mean_SNR_dB = 10 * np.log10(auto_mean_SNR)\n",
+    "    auto_mean_SNR_arr.append(auto_mean_SNR)\n",
+    "    auto_mean_SNR_dB_arr.append(auto_mean_SNR_dB)\n",
     "    \n",
-    "    #print(f\"{N_samples}, {auto_mean:9.6f}, {auto_std:9.6f}, {measure_SNR_dB:.0f}\")\n",
+    "    #print(f\"{N_samples}, {auto_mean:9.6f}, {auto_mean_SNR_dB:.0f}\")\n",
+    "    \n",
+    "# Determine accuracy of the auto_mean by using N_measure to measure auto_mean_std using std()\n",
+    "# instead of using auto_mean_SNR = auto_mean - expected_pow_mean\n",
+    "N_measure = 10\n",
+    "\n",
+    "auto_mean_std_log10_arr = []\n",
+    "for N_samples in N_samples_arr:\n",
+    "    am_arr = []\n",
+    "    for R in range(N_measure):\n",
+    "        # Signal input A\n",
+    "        sA = np.random.randn(N_samples)\n",
+    "        sA *= sigma / np.std(sA)\n",
+    "\n",
+    "        # Auto correlate A\n",
+    "        am = np.mean(sA * sA)\n",
+    "        am_arr.append(am)\n",
+    "    auto_mean_std = np.std(np.array(am_arr))\n",
+    "    auto_mean_std_log10 = 10 * np.log10(auto_mean_std)\n",
+    "    auto_mean_std_log10_arr.append(auto_mean_std_log10)\n",
+    "\n",
     "\n",
     "plt.figure(1)\n",
     "plt.plot(N_samples_arr, auto_mean_arr, 'g')\n",
@@ -358,18 +377,18 @@
     "plt.grid()\n",
     "\n",
     "plt.figure(2)\n",
-    "plt.plot(N_samples_arr, auto_std_arr, 'g')\n",
-    "plt.title(\"Auto correlator std\")\n",
-    "plt.xlabel(\"Number of samples\")\n",
-    "plt.ylabel(\"Auto power std\")\n",
-    "plt.grid()\n",
-    "\n",
-    "plt.figure(3)\n",
-    "plt.plot(N_samples_arr_log, measure_SNR_dB_arr, 'r')\n",
+    "plt.plot(N_samples_arr_log, auto_mean_SNR_dB_arr, 'r')\n",
     "plt.title(\"Auto correlator\")\n",
     "plt.xlabel(\"Number of samples (log10)\")\n",
     "plt.ylabel(\"SNR of power measurement [dB]\")\n",
-    "plt.grid()"
+    "plt.grid()\n",
+    "                           \n",
+    "plt.figure(3)\n",
+    "plt.plot(N_samples_arr_log, auto_mean_std_log10_arr, 'g')\n",
+    "plt.title(\"Auto correlator mean power std\")\n",
+    "plt.xlabel(\"Number of samples (log10)\")\n",
+    "plt.ylabel(\"Auto mean power std (log10)\")\n",
+    "plt.grid()\n"
    ]
   },
   {
@@ -389,9 +408,18 @@
     "### 3.2 Cross powers"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "4fc1cbf5",
+   "metadata": {},
+   "source": [
+    "**Conclusion:**\n",
+    "The expected coherent cross power is pow_coh and the measurement of cross_coh_mean = pow_coh becomes more accurate when N_samples increases. The incoherent cross power is cross_incoh_mean and goes to zero. The SNR of the coherent correlator is proportional to 1 / cross_incoh_mean. Dividing by almost zero causes the SNR to fluctuate, but in general the SNR of the coherent signal improves by sqrt(N_samples)."
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 44,
    "id": "470fd269",
    "metadata": {},
    "outputs": [
@@ -404,7 +432,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
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\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -416,19 +444,7 @@
     },
     {
      "data": {
-      "image/png": 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\n",
-      "text/plain": [
-       "<Figure size 432x288 with 1 Axes>"
-      ]
-     },
-     "metadata": {
-      "needs_background": "light"
-     },
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "image/png": 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\n",
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qBRfolPvuy7gIYKom6FNDuYBEpKOIfE9E/u5t3xWRjiHvFeABYL6q3hI4H1xP4IvAnDDlORyOCGloMFdIMUQB+bN3fRdQJgPBiVxA/ftDjx6w55527LuEosoIungxPPEEpX4aiggJ6wK6G3uLv8s7vsg7960Q9x7jXT9bRGZ4534BnC8iozEX0DLg0pB1cTgcUeF3gl26fNpBFqQA+KGuEBOAdNu5e3dsYfkgP/0pnH9+bHZwMD/Q0KGZ19lnzRoAdvXrl31ZcYQVgLGqeljg+E0RmRnmRlV9F8sZFI8L+3Q48k0wOqakBLp1K9xcQH7H37mz7dMVgPhU0D4DB9rmExSAKFi9GoBdfftGU16AsFFADSKyj38gIiOAhshr43A4WpdgfDxAt26UFmIqiChcQMkEIJ5cCECPHjT49Y+QsBbA1UCliCzF3ub3JkHEjsPhaGcELQCA7t2dCygZ8amgkxG1AKxZA4MHR1NWHGEF4F1gP2B/73hBTmrjcDhal3gLoFAFIAoXUPxiMMnIhQWQIwEI6wJ6X1XrVHWWt9UB7+ekRg6Ho/VIYAEU7EzgbF1A+RSAQYNSX5cBLVoAIjIQS9vQVUQOJzaY2xPolpMaORyO1iORBbBpU/7qkytqa8GPool6EDie7t2htDQaAVDNqwvoNODrwFDglsD57Vgop8PhaM8kGgPwok4KiqALKNdjACLRLQqzZYvVMx8CoKqPAI+IyP+o6nM5qYHD4cgfCaKAnAsoCWFdQBBdQjhfjPM5CKyqz4nImcBBQJfA+d/mpFYOh6N18Dv7YooCyvUgMEQnAN4kMAYNgsbG7MuLI2wqiHuwhHBXYuMA52KhoA6Hoz0TzJIJhSsAiVxAuZoHAJllBFWF+fObnsuxBRA2CuhoVb0Y2KyqvwGOAkbmpEYOh6P1SGQBFMtEsEwsgJKSmAXREplYAE89BQceCLNmxc75ApCjKKCwAuD/i9gpIoOBeiA3NXI4HK1HAgugpL7eksQVCg0NUF8fa2OnTrbPRAD8NYBTkYkAPPSQ7adPj51bvdoGlNNMWx2WsALwkoj0Bm4CpmPJ257MSY0cDkfrEW8BeIvCsHNnfuqTC+LbKGJv8ZkMAodx/0D6ArBqFbz+un2eE0iMnMMQUAg/CHyd9/E5EXkJ6KKq7WPJG4fDkZwEYaCA+bt79MhPnaIm3sqBzBaG37YtfQFQDWcxPP64XVteDnPnxs7ncBYwpJ4I9qUWvkNV/xF9lRwOR6tRW2udod9JBQWgUEgkAF26pC8Aq1bBkJDLmffqZVE71dWphVQVHnkEjj4ahg+Ht9+Ofbd6NRxzTHr1TINUFsDZLXyngBMAh6M9ExwchcIUgHgXkP85XRfQ8uVwyinhrg2mg0glAB9+CPPmwT33wObNZg1s3Wq+/3y6gFT1Gzl7ssPhyD/+gvA+hSgAUbiA6uvtbXyvvcJdn86iMI8+agPT550H775r5+bNg/33N5HKoQCEnQdQLiIPiMh/vOMDReSSkPfuKSKVIjJPROaKyPe9831E5DURWeTt98i8GQ6HIyOC8fEQE4BCGgRO5gJKxwJYtcpcNZkIAMD69fZmH099PTz5JJx9NuyxBxx0kJ2fMyfnIaAQPgroYWxRd1+KFgI/CHnvbuDHqnogcCRwhYgcCPwMeENV9wPe8I4dDkdrEpwhC7EooEKyAJK5gNKxAFassH2mAnDbbfC1r8EnnzS9rrIS1q2Diy6y42HD7G8wd25sFnC+LQCgn6o+AzQCqOpuQq4IpqprVHW693k7MB/LMHoO8Ih32SPAF8JX2+FwREIyC6CQBCAKF9Dy5bbfO2QChHgB8Ad2q6qaXjdvnu3Hj7d9SYlNBps7N+ezgCH8gjA7RKQvNvCLiBwJpB0GKiLDgMOBSUC5qnoSxydAeZJ7JgATAMrLy5k4cWK6jwWguro643vbGq4tbY/22o7D1qyhZNcuPvTq3nndOo4CFkyfzpocuh5ai+rqauZ8+CEHA1PnzqXac/scWlND6ebNn7Y7FXu99RYjgLc//pjGENlSO61fz9HAgsmTWdunD+MnTaIEmPOf/7AhIK77vPcegzt35p1Zsz6NxNq/Xz/6TJ7MqmHD7JmLFtFYVZWbf2OqmnIDxgD/xTr9/2IuoEPD3BsoowyYBnzJO94S9/3mVGVUVFRoplRWVmZ8b1vDtaXtkbAdCxaoVlSobtzY6vUJzdFHq554Yux440ZVUL3ttvzVKUIqKytVn3jC2jR/fuyLs85SHTMmfEETJqj27x/++u3b7Zk33KD69tv2GVRvv73pdeeeqzpyZNNzN91k1154oWqvXk3bkiHAVE3Qp6Z0AYlIKXCctx0NXAocpKqzWryxaRkdgeeAxzU2d2CtiAzyvh8ErAtbnsPRLpg8GaZNi5n5bZH4MYBidQH985/wn/8kL2P58vDuH2i6KIzv/unQobkLqKoK9tyz6bmDD7b966/n1P0DIcYAVLUBOF9Vd6vqXFWdo6r1YR8gIgI8AMxX1eCiMi8C/+t9/l/ghTTq7XC0fbZssX1bXmErPgy0Uye0pKT4ooD+7//gO9+x9/RErFgRfgAYzJ3jzwZ+5x2L7tl7b1i5snm58QLgRwKtXZvTCCAIPwj8XxG5U0Q+KyJj/C3kvccAFwEnisgMbzsD+CNwiogsAk72jh2OwqE9CED8RDARGrp0KSwLIFEUULwFUFVlb/lTpjS/XzV9AQATgE2b4L334LOftY4+KAD19RbpEy8AQ4faJDDIuQUQdhB4tLcPLgCjwImpblTVd4mtJRzPSSGf73C0P9qDAMRbAEBDly50aKsCoAo33GBhky2lZdi921wwkDoVxLZtsH27fX7mGRg3rmlZmzebIKbjAgITgHfesbKPPdbSQrzzTuz71autPfECIGJWwPvv598F5I0BvKiqJ8RtKTt/h6Oo8QVg48a8VqNF4i0AoLEtWwCLF8PPf26585NRUwP77AM33RQ7Li2Fjh1j1wRdQP5beefO8Oyzzd1AfghoJhaAX7ZvAaxaFVvZyx8PiBcAiLmB8u0C8scAcloLh6MQaccWQJsVAL8zjp9QFeSZZ8xl8/zzdpygjU1cQH5HfPHFdt/kyU2vTXcSmI8/F2DYMHPrDB1qlsnatU2fm6hcfyA43xaARzZjAA5Hy3z0kf3HKDTaugCoNo8CAhq6dm37AuDPkk3EXXfZfsoUSnfsSGjl0KWL/ZtraIi9pV9+uVkJzzzT9FpfADJxAYG9/UPsTd9/XksWwJFH2n7UqPSemSZhBWA0tiD8b4Gbve1POaqTo4josG0bHHIIPP10vqsSPf4s0LYqAL4LJO7tuLFz57YbBZTKApg61d7gv/QlaGig96xZyQUA7DdYudL87gceCKed1twNtHy5Xd+vX3p1jRcAPymc3/FXVdk1ibKFfuYz1sZDD03vmWkSdkGYE3JaC0fR0mH7dnsTiw+PKwTaugWQaHCUduICSmYB3HWXxeDffTf8+9/0nj7d4u8TuYDALKCqKluIpVMnOPdceOklmDQp9hbuRwCFWdglSBgLINHbv095wuQIkRI2G2gvEblFRKZ6280i0ivXlXMUPiW7dtkHv7MsJNq6ACQKjwR29+hh2SvbIi1ZABs3WmbNr30NBgyAY45hjw8/DGcB+G/nn/+8CUHQDZRJCCiYFfLjH1taZ4C+fe25vgWQaA5AKxPWBfQgsB04z9u2AQ/lqlKO4qHUF4B0F9Bu66hGFwW0a5e5Al56KetqNSGJBVAzeLCFKPrftyWWLbP9pk3N0zk//LCJ2uWX2/GJJ1K2ZIl1uMkEoLa2qQD07g1nnAGPPRYrf8WK9P3/AGPGwJ/+FLMcROw5YS2AViCsAOyjqr9S1aXe9htgRC4r5igOCtYC2LnTXFtlZRYHXh968nxzPvkEZs+GqBOBJbEAavzIk6VLo31etviuwgED7NiPpgET3Hvusayavt/8JG+a0fTpqV1AwUVbrrjCLKCnnzYRWLMmMwsgEUOH2vNqamDDhnYjADUiMt4/EJFjgDb4euBob5T4b1mFJgB+e/bZx/abN2delu+O8d0fUdGSBQCwZEm0z0uHdevMdTJzZuzc6tUWteP75oPjABs32hyBLwWWMa+oYLe/vkEyC2D9epsIFuyITzrJBoRvv73lUM1M8GcD+1ZAOxGA7wB/EZFlIrIMuBO4LGe1chQNBWsB+O0Z4RnK2YwD+ALguz+iIokFUOvPsM2nAEyeDAsXwssvx875AviZz9g+OA7g/zYjAo6JDh3Ycthh9jleAHwLwG9j0AIQge99zywHf8JZJi6gRPiTwfy2tAcBUNUZqnoYcCiWBvpwVZ2Z6j6HIxUFbwFEIQAbNtg+VxZAnADU9+xpuWhyJQCqsGBBy9csWmT7GTNi5/z2J7IAPv7Y9sOHNylmyxhvulK8C8g/TiQAYAPJvXtb2gmI1gW0e7eFq0ZZboaEjQK6XkR6q+o2Vd0mInuIyO9yXTlH4VNSqIPAvgD4HVI2A8G+BbB+fbThmb4FEP92LGKuq1wJwKuv2gSnSZOSX7Nwoe2DLiBfAI44wuqYyAIYNqxJMZsPP9w+JHMB+UIT/ybevTt861uWvwdSL+weFv85778fbbkZEtYF9DlV3eIfqOpm4Iyc1MhRVDgLIATBkEx/VmoUJHEBAbkVgI8+sr2fqiERfse8YEHMUlm+HPr3N+ukX7/mFkCfPrEsmh47hg83EY7v4H0X0OLFtk+UcuGKK2yJxkGDYtdni9/hv/eetSXRb9+KhBWAUhH59BcQka5ARL+Io5j51ALYudPCHQuFXAlAlOMASQaBAROAZcts0DVqfBH7f/8v+TULF5oLprER5syxc8FFWQYNamoBfPxxs7d/wDrwWbPgmmuanvc73sWLLaooUQc/bJjlBzr66BCNCokvRG0gAgjCC8DjwBsicomIXAK8RmxBd4cjY0qDnX4huYF8AdhrL8tEma0A9Oljn6McB2jJAth3XwtdjV/BKgp8AZg3L3GoaU2NPfecc+zYdwMFBWDgwKYWwLJlzfz/n1JWZrOBg/htjo8AiufBB+Hvf2+xOWnRp0/s2e1FAFT1BuB3wAHedp2q3hjmXhF5UETWicicwLlfi8iquAViHEVISVAAWtsNVF/ffDJRVGzZYv/Ru3aFPfbIXgAOPdQ6sSgFIJUFADEXSZSsWBErP5EV4D/ztNOs854xI7YoS9AC8AVAtWUBSETwjb8lP3y66R9SIRLr+NuLAACo6suqepW3vZLGMx4GTk9w/lZVHe1t/06jPEcBUZJPC+DHP4bPfS43ZW/dai4MsLe+bAeBy8utw4jSBZRqDAByMw5QVQXHHQcHHJBYAHz///77w2GHmQWwfr0JVtACWLvWXERr11pbErmAkhFsc2sPxPrPa08CkCmq+jbQRpOhOPJNSfANvLUtgIULY51N1GzZ0lQAsrUA+ve3Di4XFkAiARgyxHLiRC0AwZm1Z58Nb73VXPj9CKD99osJgC98QQugvt5+1yQhoC2STwFojxZADviuiMzyXER75LEejjySVxfQli3mA85V2VEIQH29ldW/v3V+UVsAHTvGlk4MUlpqHWrUArBqle333NMEYPdueCXOobBwob3h9+gBo0dbKo233rLvggIANhDsC0A6FkDQBdTaHXEbsgBCpYMWke+r6u2pzqXB3cB12LrC12HrC3wzybMnABMAysvLmZhhPpTq6uqM721rFFJb9t2xg8bSUkoaGlgwaRJr0s25ngXjVq+m6/btvPXmmxYtkgXxf5MxVVXU9+zJ7IkTGVVfT6/Vq5mUwd+s08aNHA0s3LyZjsDwNWt469VX0U6dsqovwL6LFjGwUyfejauX35ZDevem88yZTI3w31rvGTMYDczcvJnNdXUc07MnG++/n4/8/D7A6KlTYcAAZkycSI/du6kAtj76KL2Ad6uq2L1lC73WrOFwYObLL9Pjo48YAby9YgWN69YlbEsijispQRob+XD9era24v+n8oYGRpWU8P4nn7Arjefm5P+9qqbcgOkJzn0Y5l7v2mHAnHS/i98qKio0UyorKzO+t61RSG1Ze9xxqkOHqoLqTTe17sMHDrTnbt2adVHN/ib77af61a/a5+9/X7VXr8wKnjXL6vjss6oPPWSfFy3KvKJBLr1UdcCAZqc/bcuVV6qWlak2NkbzPFXVRx+1NixYYMcXXaTap49qfX3smgEDVC+5xD7v2KFaUqIqotqjR6wuCxdaOY8+qvqtb6mWlyd8XIv/V7p1szIWL86+Xemwa5fqhx+mfVs2/++BqZqgT23xtUdEzheR/wcMF5EXA1slWfj1RSS40vEXgTnJrnUUNiW7dtmknpKS1h8E9l1OuXADxbuAtm7NbNlLfw6APwYA0bmBEuXJD7LPPjYTNsq1AfwQUN/9cfbZ5h57+2073rrVEsGNHGnH3brZZ1Vz//hROQMH2n7NGvs90nH/+PjjAH7uo9aiY0dzbbUBUrmA3gPWAP0wN43PdmBWmAeIyJPA8UA/EVkJ/Ao4XkRGYy6gZcCl6VTaUTiU7Npl/8l79WrdMYC6ulgUTNQC4K8FEBQAsIyg/funV1ZQAPzOOqqB4ESLpQcJhoIGXDRZsWJF07aceabN3n34YTjxxNigvC8AYAPBH33UtJPv0cPSNfhjAGPHpl+XLl3axGzcfNKiAKjqcmA5cFSmD1DV8xOcfiDT8hyFRWldnXWUvXu3rgAErY2oBaCmxgZv4wVg06bMBaBfP5tPUFLSehbAvvvafsmS6GbDxq+C1a0bXHABPPII3HFHTAD22y92zejRlps/PiPnwIGWVnnFClvKMV06d26VZRfbMmGTwX1JRBaJyFYR2SYi20UkR+ETjmKiZNcuewNrbQEIPitqAfDLTiQA6bJ+vbk9+vY118GQIa1nAQwfbs+OMhKoqqp5BsxvftPE6KmnLALIT0bn46d0jheAQYMsZXN9fXohoD69emV2XwERKgoIuBE4W1Xn57IyjuKjpK7O3kJ79WrdMYDgs6J+btQC0KdPLFQzqlDQ+nrLkeMvWJ6Izp0tZDEqAVA18fJX6vI54gg45BB44AFz/ey1V1Nh+sxn7Hx8XQcOhHfftc+ZdOR/+5u5koqYsAKw1nX+jlxQUl8fswBacwGS1rQA+va1faYCEHQbDRsWGzDNhhdftBm0X/96y9dFmRV061YbVI63AETMCvjhD03c4gdI+/RJvH7AoEAsSSaDwAcfnP49BUbY4OepIvK0FxX0JX/Lac0cRcGnFkAxuIAySQcRLwB7722TqTKJKAry17+aL/70RFlaAhxyiLlZonA7xUcABfna18zFtX590wHglvAjgUTyvrBKeyWsAPQEdgKnAmd721m5qpSjeMjbGEAuB4HjBaBXL+ukorIAGhpia8pmwpIl8NprtuBJolnAQa66ygaef/zjcGWvWWOuHJvj05SW1tft1y+W/TM4ANwSvgUweHB0+fqLjLDZQL+RYEs4c9fhSIcmYwDbt+cm/3wi/E66pCR6AfDFpVev2DMyzQiayAKA7N7I77/f6nTJJamv3Wsv+MUv4Lnn4I03Ul9/7bUmLMG1fH18CyDZ2/qECbb3B31T4QtAkQ/kZkPYKKCRIvKGn9JZRA4VkWtS3edwtIiqrQfgWwCQu9w88Wzdap1geXnuB4Ehs3xAjY3mNoq3ACDzgeBduyzH/VlnhZ8AddVVtrDNlVfa4HEytm2DJ5+0z9de29wKWLHC3Dy+6yaeU06xeP/jjgtXL7+cTPz/DiC8C+g+4OdAPYCqzgK+mqtKOYoEPxOoPwYArecG2rLF3tB79cqNC6hz56aRLJkIwObNJgLB/Eh77mnupEQLqYThxRdtpu2lacy97NIFbr0V5s+HO+9Mft2TT9qaxZddZouex6d6rqoy0Wkp79L++4fPwe8sgKwJKwDdVHVy3LksR6EcRU8wH30+BKB3b5uFmgsBCL79g0UCpTsIHJwF7NOli3WSH36YWd0efthcMKedlt59Z59tA8bXXZfcCrjvPlu45o47bBLZtdeagPmsWBHtYO2AAfD739uyjY6MCCsAG0RkHyx1AyLyZSxFhMOROcEVqVpbAPwFW1pLADKxABIJAEBFBUybllndFi2Co45KPfgbj4j56DdvjsXeB5k2zbYJE2zlsl/9yvL4Bxd+j1oARGx8wp+x7EibsAJwBfBXYJSIrAJ+AFyWq0o5ioSgBeAPmLa2C6i9CsDq1U0XRQ/Lhg1NXUrpcMoptkhMolW87rvPhPzCC+34/PPNUvnVr0zo/cglF67ZpkgpACJSClyuqicD/YFRqjreyxPkcGROIhdQa80G9i2AXMxATiYAW7akF+XUkgBA+lbA7t2Z5SPyKSuzhG0vvdT0fHU1PP44nHderN2lpXDDDbbw+7HHWl0bGtrEIiiOGCkFQFUbgPHe5x2quj3ntXIUB/l0AeXDAvC/C0swEVyQww8390e6AuBbINksunP22eZGCs7MfeIJEwE/jNPnnHPghRcssuf44+2cswDaFGFdQB966wBc5GYCOyIjaAH07Gmf8zEIvH1708HKqMoOkkk+oPXrrX7xk5x69LDZsukKwIYNts9GAM480/a+G6iuzgZix42zsYV4zj4bPvjAJmuBi9hpY4QVgC7ARuBE3ExgR1QELYDSUuvsWkMAGhut0/cFQNXCF6Mgfi0AHz8fUDqLq6xfn7yzrqiwFA1BLr8c/v73lsuDzF1AYBPRDj00JgD33GODu9dfnzx886CDYPJk+Ne/4IADMn+2I3JCJYNT1W/kuiKOIiRoAUDrLQqzbZt11L162aIi/rkoMkPW1tpkq3gB8Gfwfvxx+Nz68bOAg1RUmOtl3ToLh/zwQ7j7bnjvPfjylxPfE4UFAPZW/8c/Wsf/+9/buEB8hs94+vSBM87I7rmOyMn5TGAReVBE1vn3euf6iMhr3hoDr4nIHplV39GuCVoAYJ1mawwCB2fq+tFHUT030SxgsKyaIrEFT8KwYUNyARgzxva+G+jBB20/c6b53JOVB9EIQEMDfPGLJlLXX59deY680RozgR8G4lMO/gx4Q1X3A97wjh3FRrwF0FoJ4YK5evyxh6gGgpMJQOfOZgUsXBi+rJYsgMMPt/20afY7Pv44nHCCiczTTycvD2LuqEwZO9asjunT4QtfsHz9jnZJzmcCq+rbNF9A/hzgEe/zI8AXQtbDUUgksgBaQwCCnXTUAuCLS7wAgGW5DGsBqLYsAL16WXnTpsE//2kTtH7xC8uj89RTibNxbtiQeFA5XUpKLJeQiM0MdrRbwi4IE/VM4HJV9e//BEi6MKeITAAmAJSXlzNx4sSMHlhdXZ3xvW2NQmnLkNmz2Q94d+pUdi9axKjaWnp98gmTcty2vv/9L4cAUxcvRjt0YCww9/33Wd+pU8Zl+n+TPpMncygwfelStsW1Y79u3Sh/7z3eraxMme+mdMcOPrtrF0u2baMqye9xwJ570uu999i5ciXdysv5oKSEwYcfzshbb2XKgw+yI7isInDA3Ln0LCtL+fuG+ffV8cwz6X7wwWzZsAHa8L/FQvm/Ajlqi6qm3IARwOvYmgCrgHeBYWHu9e4fBswJHG+J+35zmHIqKio0UyorKzO+t61RMG254QZVUN2xw46/+13V3r1z/9xHHrHnLl6suny5fX7ggayK/PRvctddVt78+c0vuvVW+27dutQFTpli1z7zTPJrbrrJrhFR/dWv7Ny6daqlpao//3nz6089VXXcuJSPLph/X+ra4gNM1QR9atj1AJZq85nAy7LQnbUiMgjA26/LoixHeyXRGMC2bdHG5CcikQsoikHgLVvgt7+1CJ1Ei5r4K12FGQeY7Hlcx41Lfo0/IxjgG16gXv/+cPLJid1ALQ0qO4qSsFFAnUXkAuD7wA9F5FoRuTaL574I/K/3+X+BF7Ioy9FeqamhsWPHWHrg3r2t86+uzu1z/c6+Z89Y6GcUYwA/+5mFZd57b+Jka74ohBkHmDzZBlpbmjnrRwKddFIszBTgK1+xcNOpU5ten00eIEdBEnYQ+AVs4HY3sCOwpUREngTeB/YXkZUicgnwR+AUEVkEnOwdO4qN2loag3731koHsWWLxf937GgddffuWQtAz9mzbZ3dH/wg1jHHM2yYPS+sAIwb1/JYQa9elp//ppuanv/iF61tzz7b9HxLE8scRUnYQeChqppi9ejEqOr5Sb5KMXPEUfDU1CQXgJbefLdvN7dRx46ZPddPBOeTbT6gXbvY/+abrc6/+U3y6zp2tFQIqQRg61aL5f9qiEjrK65ofq53b5utO3t27NzOnRZ15VxAjgBhLYD3ROSQnNbEUXzEWwBhU0JXVMAf/pD5c/1EcMHnZiMATz9N9+XL7W28rKzla8OEgk6bZv77lvz/qRg+vOmqYVFNAnMUFC1aACIyGwv97AB8Q0SWAnWAAKqqh+a+io6CpaaGhmBMepiU0Dt3Wgea6Zq40DxXT8+e2Q0Cf/QRWlKCfO5zqa/dbz94+23r4JO5d6ZMsf3YsZnXafhwW/6xsdHGWJJlFnUUNalcQC7hmyN3ZDIGsHKl7bMZKN66takrJFsX0PLl1PXvT5cOITyqI0da4rk1a2IZMuOZPNlSR2QzY3fECMtJtGaNrcPrLABHAlp0Aanqcn8DehPLBNpb3YIwjmypqaExkQWweXPye6qqbJ+NACSyALIUgNrypHMZmxImEsgfAM4GP+2y7wbyBcCNATgChA0D/T7wODDA2x4TkStzWTFHERBvAfTpA926WQhjMqIQgKgHgZcvp3bgwHDXphKA1avNyolKAPzf0lkAjgSEjQK6BPiMqu4AEJEbsNDOO3JVMUcREB8FVFJi68gmy2YJ2QuAn68/qkHg+npYtYpaf8WrVOy1l62rm2wymO//z1YA9t7bxhh8AVi/3kJQE+UochQtYaOABAguZtrgnXM4MifeAgATgOByg/FkKwA1NdZpJ7IAMpmBvHIlNDaGdwGVlpp/PpkFMHmyXTN6dPp1CdK5s/n+gy6gvn1jk+4cDsILwEPAJBH5tYj8GvgAeCBntXIUB4kEYNQoi/DxM4XGk60ABFNB+2SzKthyGwqrC+sCAhsIbkkADjnEXGHZMnx4UxeQc/844gibC+gW4BtYWudNwDdU9bYc1svRFnnnHTjiiFgOn2yJHwQGEwDV5B1ktlFAifL1Z5MS2hOA0BYA2DjAkiXNLY7GRkvfkK37x2fEiKYuICcAjjjCDgIfCSxS1T+r6p+BJSLiVoEoNt580yYprVoVTXnJXECQfBwgaAEkynmfikQC4FsDWQhA3YAB4e/Zbz8TUV/MfBYssPpFJQDDh9vfqq7OJYJzJCSsC+huIPjKVe2dcxQTXmfXYphmOsRPBINYxsxE4wDbt5sLp18/6/x37kz/mclcQJC5AAwc2FzIWsJv49y5Tc+/9Zbtjz02/XokYvhw+52WL3cuIEdCQg8CezmlAVDVRsJHEDkKhRUrbB+FAKgmtgC6dbMIlkQWgP/2f8ABts/EDdSSCyiT2cDLlzfNxBmGsWMtL1BlZdPzEyfa5LB9902/HokYMcL2S5bAxo1OABzNCCsAS0XkeyLS0du+DyxNeZejsIhSAOrrobEx8ZvzqFG5E4BcWADDhqV3T1kZHHMMvPJK7JyqCcDxx6dcLSw0/lyA6dNtEXcnAI44wgrAZcDR2GpgK4HP4C3T6CgSVKMVAG8gOaEA+KGg8T5+XwBGjbJ91BZAugLQ2Gi/SboWAMBpp8GsWZaqAay9a9eaAETFoEEWDurPLXBjAI44wkYBrVPVr6rqAFUtV9ULVNWt4lVMrF9vg4kQTb5+L8yzWRQQWAe/Y0fzweaqKns79geKMxWAjh1jC9FD5oPAn3xi+XYyEYBTT7X9a6/Z3l/rNUoBKCkx68RfXcxZAI443KwQRziWB1I/5doC8N/w491AVVUwcCDssYcdZ+oC6tWrqZsl01XB/N8kEwEYPdreyF991Y6j9v/7DB8eszKcADjiyKsAiMgyEZktIjNEZGrqOxx5w3f/QDQC0JIFkCwUtKoK9twzlnM/EwHYtKl5OgR/VbB0B4GzEYCSEjjlFBOAxkYTgBNOiM7/7+OPA4BzATma0aIAeIO9iMgxOazDCao6WlWPyOEzHNniC0D//rm3AAYNsrfy+FDQTAVg4UK4+mo46CB4+mlINGkrk4Rw2QgA2DjA+vVWp6j9/z5+JBA4C8DRjFQWwDe8vUv6VuysWGFvyfvsE6kF0JBIAESaRwKp2sSpdAWgrg5OPhluv92E5aab4Mknm1+XqQDssUfMhZQup5xi+2uvtX0uBMC3ALp2jSa9hKOgSBXLP99buH2wiMwKnI9qRTAFXhURBf6qqvfGXyAiE/AijsrLy5noD5alSXV1dcb3tjXy0ZaDpk2jW79+1KrSsaqK6Vk+v/eHHzIa2NHQkLAto3r3pveMGXzgfddh+3bG79jB4ro6Vk+fzrHAklmzqEpRj8HPP8/Iqipm3ngjm/0VtpYssS3AGBHqly1jdhrtOmT6dDr168e0iRMz/pscMWIEZYsXU9evH+9XVTWfHZwlZRs3cgRQ27Pnp79lKtz/lbZJTtqiqi1uwEBgJrB3/Jbq3hBlD/H2A7xnHNvS9RUVFZoplZWVGd/b1shLW444QvX001UvuEB1n32yL+9f/1IFnXrXXYm//93vVEF1+3Y7njnTjp95RrWxUbWkRPWaa1p+xs6dqoMGqY4fb/e0xMknqx59dHptOOgg1S98QVWz+JtcdZW168ILM7s/FZs3W/ljxoS+xf1faZtk0xZgqiboU1MOAqvqJ6p6GLAG6OFtqzWCFcFUdZW3Xwc8D0SUBMUROcuXWy773r1zPwYAsUggP2++Pwdgzz3NRVRWltoFdM89FgFz3XWpB1fTXRdY1bKWZur/9zntNNvnwv0D9vfq3dv5/x0JCZsM7jhgEfAX4C5goYhklbBERLqLSA//M3AqMCebMh05oqbGBiv32st83lu2ZJY7P75MWhCA+EigoABAagHYsQP++Ec48cRwnWvfviYWYdu1aZM9I1sBOOkkGwS+6KLsymmJ886LjTc4HAHChoHeApyqqsep6rHAacCtWT67HHhXRGYCk4F/qerLWZbpyAV+5+sLQGOjJWbLBt8CSBQGCpYxs2tXePRRe15VlYVr+nn3UwnAnXfCunX29h+GY46xTn327HDXZxsB5CNiHXSy3yEK/vpXuOqq3JXvaLeETejWUVU/jclT1YUi0jGbB6vqUuCwbMpwtBJ+COhee1kOH2i+rGK6pLIAOneGm2+Gyy+HW24xARg82EQAWhaAHTss2uf00+Hoo8PV5+STbf/aa3BYiH+WUQmAw5FHwloAU0XkfhE53tvuA9zErWIhKAD+LNxsxwFSWQAAl10G//M/8POf20Qp3/0DJgDJrJD77rPsl7/8Zfj6DBliSeZefz3c9dOn2z7dRHAORxsirAB8B5gHfM/b5nnniovaWoshz2QhkvbM8uXmqhgyJDaLNioBaCmPvgjcfz8MHRqbBOaTzAKoq7O3/+OPD//273PKKfD2201XPFO1fD9BNm2CO+6Az3/exg4cjnZK2GRwdap6i6p+ydtuVdW6XFeuzfHcc3DBBfD++63zvJtugv/+t3We1RIrVpj7pVOn6CyAmhro0AH1XTrJ6N3bBkk7dGiaJyeZADzyCKxeDb/4Rfp1Ovlkq9d778XO/frXZvksXhw7d8MNNmns979P/xkORxvCLeqSDsuW2X7y5PTfLtOlthZ+9jM4/3wboAyw/w03WIrfq6+O9pnV1fYG/Prr9tZ7++3mc1+xwjpBiAlAMCNoQ4O5aNavt46xtBS+/vWYvz4RtbXQpUu4eo0bZ4OzQ4bEziUSgN27rXMeOzbm00+H4483oXn9dYseWrfORLimBs45Bz74wNr35z/DhRfCwQen/wyHow3hBCAdfF+4n189lyxcaNEv8+c3Pd/QwIA33zQfd7YCsHYtvPCCrfM7bRrMnGmdaIcOth83Di6+2NpdUWH3JLIA/v1vc4cEGTWqmXA1oaamaUrmVPjzAnx69GguAE8/DUuX2qBxJknVevSAI4+0geDrr7dB6Lo6uOsuuPJKC9UcMMB+m9/8Jv3yHY42RsbZQEVkrygr0i7wBWBqK4x/+x3/Rx81jU1fvpzSXbtsPdmGhszKVjVXyahRcOml8Oyz5mq5+mp7+9261Tr8X/7SOuqqqpgF0KOHZbIMCsCiRbafPBle9iJ516VYLiIdCyARvgUQHI+54w5L+Hb22ZmXe/LJJoYLFsBf/gJf/Sp85zsmKi+8YAPMEyY0TbLmcLRTUgqAiBwlIl8WkQHe8aEi8gTQBpzTWVJXl97iJr4ALFwYzaIoLTFvnu137myaHyZ4fmkGq3KuXg1nnWUumoMPtrf+jRut47/+epuY1K0b3HijtfdXv7LfyRcAkeazgZcvN2E44ojYco0bN7Zcj3QtgHjKykwA6wJDUUuWwPjxJlCZcsopJirnnmu/8TXX2Pkrr4Rvfxv69ImdczjaOanSQd8EPAj8D/AvEfkd8CowCdgv99XLMT/8oU048t9gW8JfEtHv4KZNy23dgq6fYFZMXwAg/KQln5oa+NznbDHy22+Ht96CQw9N7C458USLo7/5ZjveK2Dw7bFHUwHwxwhEYlExqQQgCgsAYm6g3bvtmYlSPafDuHEmZrNn2wQt/+8tAvfea9bQoEHZPcPhaCOkelU6EzhcVc/HUjX8ADhSVW9X1doW72wPzJ4NGzZYR7d2bcvXbtlinc2XvmTHuXYDzZ9vnZH/2WfePOp79rQOKV0BuOoqW4f2uefge99L/aZ8ww0xF0twwpOfDsInuC5ut27WsbeGBQAxAdiwweo6YEDmZYKNf5xwgn1O9KbvUio7CohUAlDrd/SquhlYpKrLcl6r1uLjj81tsWaNuUVaSi3gu39Gjzb/by4HgnfvNjfTccdZZxsnANv3289CImfNSl5GPM8/b4OZP/qRWQFhOPRQG/gsKWkuAIksAIhZARs2tFx21BaAP+aQrQUAlj7i0UddlI+j4EklACNE5EV/A4bHHbcPGhrotGlT03N1deYPP/tsix6ZPt1CLpNN8grOhh07NrcCsHSphWEeeKC5IHwXkCrMm8fOvfeGQw4JbwGsWAGXXGIDu3/4Q3p1ufNOePPNpssoBgVgxw7r7IMuor59W98C8C24bC0AiAmfw1HgpAoDPSfu+OZcVSSnTJhAxQsvxNw3YAOXqrZi0tlnW+bIn/zEJl6NH9+8jHgBePppe+uMosOJx3/jP+AAi9R56SU7rqqCHTvYsffelr74+edtoDKVW+KXvzRBeeopm8yVDj16mCUSJDgIHEwU5xNGANqyBeBwFAktWgCq+lZLW2tVMmv23ZfOGzc2zR3z8ce295fMu/xy69j+/OfEZaxYYZ3ngAHmNoLcjQP4AjBqlInAunWWfsAbAN45bJi9papaOGgqZs2yTjw4kzYbfAvAHxiHtmMBOAFwOEKTKgqoUkTeTLK90VqVzJqRI20fnM4fLwDdu8O3vgX/+EfiZflWrLBcNCUlMGaM+bpzKQBDhli2TT8K5aOPPhWAHb4LCFK7gVSt3VF1/mACUF9vnbgvAMExgn798mMBdOqUXYZSh6PISDUGcBVwddz2HLAP0DO3VYsQXwD81aXABKBz56YhfZdfbpOu7r67eRnBgc4ePaxjztU4wLx5sY7fnwHrC8CAAezu1csGort2TS0A69ZZJxm1AIBZAcuXmygOHhz73rcAWlpcpaYmWgFYu9ass0xmADscRUoqF9A0fwPKgBuA84HLVHVstg8XkdNFZIGILBaRn2VbXlL22cf2QQFYutTeWoOhkMOHW0qDe+9tmhESmgoAmBtoypToM4OqWmfvC8CwYSZU8+ebABx4oJ0vLbUolVSRQP4chygFIJgRdMUKs1Y6BIaT+va1zr+lJRZra6N1AeVqPMbhKGDCzAQ+TUTeAX4J/F5Vx6vqf7J9sIiUYktMfg44EDhfRA7MttyEdOtG7YABzS0A3/0T5MorLarlqadi5+rrLWIoKABjx9pbp78wSFSsXGmdWrCjHzmyuQBAuEgg3+2VKwsgXhgh3GSwbC0Af+A7aAE4/7/DkRapxgCmAH8FngJ+AmwVkTH+luWzxwGLVXWpqu7ynhEfdRQZNUOHNp3xm0wATjzROtk77oidW73a3miDHd1pp5nP+bvfzW593MZGSyvsv8kHI4B8DjgA3n3X3qjjBWD9+pYnsS1ebCIS5cIl2QrA7t2WxiEbC6CkxMZt/IF9ZwE4HGmTKgx0B1ANfBlLBxF0sCpwYhbPHgJUBY5XAp+Jv0hEJgATAMrLy5k4cWJGDxtWXk7ZO+/w38pKSnfu5LObNrGksZGqBOUNOeEE9vvLX5j02GPUDB1Kr1mzOByYuXkzmwPXD77sMkb++c8s+c53qDr//IzqVf7yyxxwww3U3n470+69l/LXX2df4L+bNlHvPWtYly4M89wpM3btorq6mokTJ9K7oYHRwMzHHmOzn60zjgPfe48e5eVMinBdgS6rVnEk8NF77zFyxQqqjjySjwO/S4/ly6kAZlVWsslb+jFI6c6dfBZYsmrVp23JhKM7dWLDwoUsrKzk2E8+YWVdHUszLCtbsmlHW8O1pW2Sk7aoal42TFTuDxxfBNzZ0j0VFRWaKYsuv1wVVNevV50xwz4/80zii5csse9vu82OH3vMjufPb3pdY6Pqeeeplpaqvv1283IaG1Vfe021ri7xc6qrVQcPVh01SrVzZ9VTT1X91rdU+/Sxe32efNKeD6qffKKVlZV2ft06O3fzzckbXlGhetppyb/PhI0b7bk//ant77qr6feLFtn5Rx5JfL9f7zvvjLUlE/bZR/WCC1S3bLHy/vSnzMvKkqza0cZwbWmbZNMWYKom6FNTuYDGisjAwPHFIvKCiPxZRPpkqT2rgMAafwz1zuWEnUOH2oeFC2MhoMlS+o4YYdE3//63HfuhjsElCcEiTu67z67/6lebu2Luu8+yS951V+Ln3HijuZceeMDmH7z6qqVpPvDAptEsfiRQnz5N3Rz9+5vfO9k4QC5CQCEWajljhu3TdQH5VkE2YwAQSwnt5gA4HBmRahD4r8AuABE5Fvgj8CiwFbg3y2dPAfYTkeEi0gn4KpCz9BI1fue9aFHzOQCJOOMMW+WqutoEoG9f8znH07On5dPfvBm+/OXY+rFLlljeHYCHH25+38qVttrUeefZ6mLf/rYtvlJf39T/DzYILNJcGMCuDQ5uB9m40cYNohaA0lJr98yZdhwvAL16mY8+mQBs22Z7P5InU3wB8GcBuzEAhyMtUglAqar6SXS+Atyrqs+p6i+BrHoVVd0NfBd4BZgPPKOqIaa1ZkbtwIHWcfkWQM+escHMRJx5pnXmb74ZmwSWjMMOs7f4d9+FH/zABjgvvthCI3/6U+so/c7S5xe/sAHgG26wYxGbf3DuuSYKQbp1s6ij+JQMYCKWbF2AXEQA+eyxB3zyiX2OF4CSErNWkgnAkiW2z3ZRFWcBOBxZkWoQuFREOnid9Ul4g7Eh702Jqv4b+He25YR6VocO1uEsXGgx6MOHtzxpaPx4m/D1r3+ZAKTqrM4/31wiN95oq0m99x489pilmr7lFssu6efWnzwZ/vY3yz0UjM7p1g2eeSZx+ZMmJZ5zMGKEdcSJcgLlWgCWL7e3/USzb1uaDRysV7wwpkNZmeUicgLgcGREKgvgSeAtEXkBqAHeARCRfTE3UPti5MiYBdCS+wcsxPOUU2wcIFGoYyKuvx5OPdWshnPPhQsuMNfRWWfB449b+GNjI1xxhc1A/r//S6/+iQTLb4e/YH2QxYvtnlRtzQTfekr2u7SUEnrRIvu+JQssDP66wOvWWTv79cuuPIejyEg1E/j3wI+Bh4Hx3miyf9+Vua1aDvBX/wojAGBuoJUrzWcdRgBKS20C2fXXwz33xDrsiy+2t9RXXoEHH7QcQjfeaG6obPEtE39cI8jixVbvzp2zf048/mzglgSgJQtgvwgWlAu6gPr2bTob2eFwpCTl/xhV/SDBuSSjjm2ckSNjEShhBCC4cEoYAQB7q/35z5ueO+MM66DuuMOWkhw/Hi68MFx5qfDbkWgcIKqONhFhLIBky2YuWgTHHpt9HYKDwG4A2OFImyxWz26H+EnhIJwADBpkmT8hvAAkolMncwe98oqldb7jjuiSlpWX24zaZBZALvz/EE4AElkAtbXmt4/KAti1y6w05/93ONLGCUAqzjrL9tmmUvj6121/2WW2rGRU+D7+eAtg82brgHMtAME00EH69bPOfufOpueXLrXB7Cjq5YeRLl3qLACHIwOKy2k6ZIhNPqqtDd+hX301HHlk07TRmTBmjM0r+EyzbBfZM2JEcwvAD7XMpwUAzZeL9PMxRWUB+M9wFoDDkTbFZQGUlFjHM2BA4kldiSgrC7+IeiqOOy772a+J8C2AYJhoLtJABxkzxp4bTE4XJNls4ChDU4MTyZwF4HCkTXFZAGBhmqtX57sW0TJihA2GbtwYC4X0O9psJ1sl48gjk09Ag+QCEFUIKDQVAGcBOBxpU3wC8Kc/5bsG0ROMBAoKwNCh2aVczga/HoksgKisEmcBOBxZUVwuoEIl0VyAadOSu2dag5YsgKhCU50F4HBkhROAQiB+LsCqVTB3rs1kzhd9vGSxwdnAfghoLiwAJwAOR9o4ASgEysosNbRvAbz6qu1PPTV/derY0WY6By0Af6A6FxaAcwE5HGnjBKBQCM4FePVVGDjQlozMJ/GTwfyB6agFoKyseSI8h8OREicAhYI/F6ChAV57zd7+o5ptnCnxGUGjDk31Q3nd27/DkRFOAAqF4cMtPfOUKdbpnnZavmuU2AKIKgQULPlbly7O/+9wZIgTgEJhxAh7+3/gATs++eT81geap4RetCj6iWllZc4CcDgyJC8CICK/FpFVIjLD287IRz0KCj8S6IknbJZuW+gU4y2AKENAfU44AY4/PtoyHY4iIZ8TwW5V1QKclZUn/LkAO3fmN/onSN++tpZCfb1ZJ1GGgPokW0HN4XCkpPhmAhcqe+5pC9I0NLQN/z80nQ38t79ZCGgwI6vD4cgroonWmc31Q0V+DXwd2AZMBX6sqpuTXDsBby3i8vLyiqeeeiqjZ1ZXV1MWjBtvxyRry2cuuIBOmzfz7osvoh075qFmTen/5pscdN11bB85kh4LF7LhqKOYd+21NAYS4hXK36VQ2gGuLW2VbNpywgknTFPVI5p9oao52YDXgTkJtnOAcqAUG4P4PfBgmDIrKio0UyorKzO+t62RtC2XXmpbW+G111RBtXNn1TvvVG1sbHZJofxdCqUdqq4tbZVs2gJM1QR9as5cQKoaKgxFRO4DXspVPYqKe+7Jdw2acswxtp7CxRfDwQfnuzYOhyOOvIwBiMggVV3jHX4RswwchUbXrnDjjfmuhcPhSEK+BoFvFJHRgALLgEvzVA+Hw+EoWvIiAKp6UT6e63A4HI4Ybiaww+FwFClOABwOh6NIcQLgcDgcRYoTAIfD4ShSnAA4HA5HkeIEwOFwOIqUvOQCyhQRWQ8sz/D2fsCGlFe1D1xb2h6F0g5wbWmrZNOWvVW1f/zJdiUA2SAiUzVRMqR2iGtL26NQ2gGuLW2VXLTFuYAcDoejSHEC4HA4HEVKMQnAvfmuQIS4trQ9CqUd4NrSVom8LUUzBuBwOByOphSTBeBwOByOAE4AHA6Ho0gpeAEQkT1FpFJE5onIXBH5fr7rlCki0kVEJovITK8tv8l3nbJBREpF5EMRadcrwonIMhGZLSIzRGRqvuuTDSLSW0T+LiIfich8ETkq33VKFxHZ3/tb+Ns2EflBvuuVKSLyQ+//+xwReVJEuqS+K2TZhT4GICKDgEGqOl1EegDTgC+o6rw8Vy1tRESA7qpaLSIdgXeB76vqB3muWkaIyI+AI4CeqnpWvuuTKSKyDDhCVdv9hCMReQR4R1XvF5FOQDdV3ZLnamWMiJQCq4DPqGqmk0jzhogMwf6fH6iqNSLyDPBvVX04ivIL3gJQ1TWqOt37vB2YDwzJb60yw1vfudo77Oht7VLBRWQocCZwf77r4jBEpBdwLPAAgKruas+dv8dJwJL22PkH6AB0FZEOQDdgdVQFF7wABBGRYcDhwKQ8VyVjPLfJDGAd8Jqqtte23Ab8BGjMcz2iQIFXRWSaiEzId2WyYDiwHnjIc83dLyLd812pLPkq8GS+K5EpqroK+BOwAlgDbFXVV6Mqv2gEQETKgOeAH6jqtnzXJ1NUtUFVRwNDgXEicnCeq5Q2InIWsE5Vp+W7LhExXlXHAJ8DrhCRY/NdoQzpAIwB7lbVw4EdwM/yW6XM8VxYnweezXddMkVE9gDOwcR5MNBdRL4WVflFIQCev/w54HFV/Ue+6xMFnmleCZye56pkwjHA5z3f+VPAiSLyWH6rlDneWxqqug54HhiX3xplzEpgZcCq/DsmCO2VzwHTVXVtviuSBScDH6vqelWtB/4BHB1V4QUvAN7A6QPAfFW9Jd/1yQYR6S8ivb3PXYFTgI/yWqkMUNWfq+pQVR2GmehvqmpkbzWtiYh094IL8NwlpwJz8lurzFDVT4AqEdnfO3US0O6CJQKcTzt2/3isAI4UkW5eX3YSNo4ZCR2iKqgNcwxwETDb850D/EJV/52/KmXMIOARL7KhBHhGVdt1CGUBUA48b/836QA8oaov57dKWXEl8LjnPlkKfCPP9ckIT4xPAS7Nd12yQVUnicjfgenAbuBDIkwJUfBhoA6Hw+FITMG7gBwOh8ORGCcADofDUaQ4AXA4HI4ixQmAw+FwFClOABwOh6NIcQLgyBgRURG5OXB8lYj8OqKyHxaRL0dRVornnOtlvazM9bNS1GOZiPSLoJwfiMjF3ueMf0MRGSUi74tInYhcFffd6SKyQEQWi8jPAuefEpH9smuBozVxAuDIhjrgS1F0XFHiJc0KyyXAt1X1hFzVp7Xw2v1N4IkIitsEfA/LQxN8RinwF2yW7YHA+SJyoPf13Vh+J0c7wQmAIxt2Y5NSfhj/Rfzbp4hUe/vjReQtEXlBRJaKyB9F5EJvnYPZIrJPoJiTRWSqiCz08gf5yfBuEpEpIjJLRC4NlPuOiLxIgtmrInK+V/4cEbnBO3ctMB54QERuirt+kIi87eWTnyMin/XO3+3Vqcl6DN4b/B+866eKyBgReUVElojIZYE6vi0i//LeoO8RkWb/B0Xka97vMUNE/uq1udT7Ted47Wj2mwMnYqkPdico8yQvwdtsEXlQRDp7588Qy/0/TUT+LN7aDKq6TlWnAPVxRY0DFqvqUlXdhaXyOMf77h3vb1YME0wLAicAjmz5C3ChWCrhsBwGXAYcgM3SHqmq47DU0FcGrhuGdThnAveILYRxCZYRcSwwFvi2iAz3rh+DrY8wMvgwERkM3IB1kKOBsSLyBVX9LTAVuFBVr46r4wXAK17ivcOAGd75/1PVI4BDgeNE5NDAPSu8698BHga+DBwJBBfuGee18UBgH+BLcXU9APgKcIxXVgNwoVfvIap6sKoeAjxEc47B1rtogve7PQx8xbu3A/Ad7/xfgc+pagXQP0GZ8QwBqgLHK71zqGojsBj7vRztACcAjqzwMqs+irkLwjLFW6ehDlgC+OltZ2Odvs8zqtqoqouwtASjsFw7F3tpPSYBfQHf7zxZVT9O8LyxwEQvodZu4HEs732LdQS+4Y1pHOKtJQFwnohMx6bkH4R15D4vBtoxSVW3q+p6oE68HE5eHZeqagOWp2Z83HNPAiqAKV4bTwJGeO0fISJ3iMjpQKKMtoOwdM7x7I8lFFvoHT/itX8UsDTwm0WRN2cdlrXS0Q5wppojCm7DcpUE30p3471geG6OToHv6gKfGwPHjTT9Nxmfp0QBAa5U1VeCX4jI8Vj64khQ1bfF0jqfCTwsIrdgb/ZXAWNVdbOIPAwEl+cLtiO+jX67ErUpiACPqOrP4+skIocBp2HW03mYvz9ITVx9csEqYM/A8VDvnE8Xrx6OdoCzABxZo6qbgGcw94zPMuxNFiwne8cMij5XREq8cYERwALgFcx90RFAREZK6kVLJmPumn7eIOb5wFst3SAiewNrVfU+zDU1BuiJicxWESnHBkLTZZyIDPdE8SvYcn9B3gC+LCIDvHr0EZG9vYH2ElV9DriGxGma5wP7Jji/ABgmIv53F2HtX4BZFcO8818JUf8pwH5eGzph2VxfDHw/knaaDbUYcRaAIypuBr4bOL4PeEFEZgIvk9nb+Qqs8+4JXKaqtSJyP+Ymmi4igrk8vtBSIaq6RixcsRJ7w/6Xqr6Q4tnHA1eLSD1QDVysqh+LyIdYCu4q4L8ZtGkKcCfWUVdi6wcE6zpPRK7BVhgrwQZhr8Deqh8KDBo3sxCA/wB/iz/p/W7fAJ71BminAPeoap2IXA68LCI7vPMAiMhAbHykJ9Aotqj6gaq6TUS+iwlxKfCgqs717ikHary00o52gMsG6nC0Ep6b6ipVPSuHz3ge+Ik3bhLm+jJVrfbE9C/AIlW9NcNn/xDYpqoPZHK/o/VxLiCHo7D4GTYYHJZve4PNc4FeWFRQpmzBBpgd7QRnATgcDkeR4iwAh8PhKFKcADgcDkeR4gTA4XA4ihQnAA6Hw1GkOAFwOByOIuX/Azm5Pr6uSF9+AAAAAElFTkSuQmCC\n",
       "text/plain": [
        "<Figure size 432x288 with 1 Axes>"
       ]
@@ -443,8 +459,8 @@
     "# Number of samples N_samples in time for input A and input B, try N_samples in N_samples_arr\n",
     "N_steps = 100\n",
     "\n",
-    "N_min = 10\n",
-    "N_max = 10000000\n",
+    "N_min = 100\n",
+    "N_max = 100000000\n",
     "n_incr = (N_max / N_min)**(1 / N_steps)\n",
     "N_samples_arr = []\n",
     "for s in range(N_steps + 1):\n",
@@ -463,11 +479,8 @@
     "\n",
     "# Correlator mean(A * B)\n",
     "cross_coh_mean_arr = []\n",
-    "cross_coh_std_arr = []\n",
     "cross_incoh_mean_arr = []\n",
-    "cross_incoh_std_arr = []\n",
     "cross_sys_mean_arr = []\n",
-    "cross_sys_std_arr = []\n",
     "cross_SNR_arr = []\n",
     "cross_SNR_dB_arr = []\n",
     "for N_samples in N_samples_arr:\n",
@@ -487,18 +500,11 @@
     "    # Correlate A and B\n",
     "    cross_coh_mean = np.mean(si_coh * si_coh)\n",
     "    cross_coh_mean_arr.append(cross_coh_mean)\n",
-    "    cross_coh_std = np.std(si_coh * si_coh)\n",
-    "    cross_coh_std_arr.append(cross_coh_std)\n",
     "    cross_incoh_mean = np.mean(sA_incoh * sB_incoh)\n",
     "    cross_incoh_mean_arr.append(cross_incoh_mean)\n",
-    "    cross_incoh_std = np.std(sA_incoh * sB_incoh)\n",
-    "    cross_incoh_std_arr.append(cross_incoh_std)\n",
     "    cross_sys_mean = np.mean(sA_sys * sB_sys)\n",
     "    cross_sys_mean_arr.append(cross_sys_mean)\n",
-    "    cross_sys_std = np.std(sA_sys * sB_sys)\n",
-    "    cross_sys_std_arr.append(cross_sys_std)\n",
     "    #print(f\"{N_samples}, {cross_coh_mean:9.6f}, {cross_incoh_mean:9.6f}, {cross_sys_mean:9.6f}\")\n",
-    "    #print(f\"{N_samples}, {cross_coh_std:9.6f}, {cross_incoh_std:9.6f}, {cross_sys_std:9.6f}\")\n",
     "\n",
     "    # SNR definitions of the coherent correlator\n",
     "    # . using cross_coh_mean shows the cross_SNR imrpovement for all N_max\n",
@@ -508,11 +514,12 @@
     "    # . the cross_coh_mean and cross_sys_mean become pow_coh, so constant > 0. Therefor it is\n",
     "    #   also possible to define relative cross_SNR using 1 divided by the error in cross_coh_mean\n",
     "    #   or the value of cross_incoh_mean, which both go to zero.\n",
-    "    cross_SNR = np.abs(cross_coh_mean / cross_incoh_mean)\n",
+    "    #cross_SNR = np.abs(cross_coh_mean / cross_incoh_mean)\n",
     "    #cross_SNR = np.abs(1 / (cross_coh_mean - pow_coh))\n",
     "    #cross_SNR = np.abs(1 / cross_incoh_mean)\n",
     "    cross_SNR = np.abs(cross_sys_mean / cross_incoh_mean)\n",
     "    #cross_SNR = np.abs(cross_sys_mean / (cross_sys_mean - cross_coh_mean))\n",
+    "    \n",
     "    cross_SNR_dB = 10 * np.log10(cross_SNR)\n",
     "    cross_SNR_arr.append(cross_SNR)\n",
     "    cross_SNR_dB_arr.append(cross_SNR_dB)\n",
@@ -527,14 +534,6 @@
     "plt.grid()\n",
     "\n",
     "plt.figure(2)\n",
-    "plt.plot(N_samples_arr, cross_coh_std_arr, 'g', N_samples_arr, cross_incoh_std_arr, 'b', N_samples_arr, cross_sys_std_arr, 'r')\n",
-    "plt.title(\"Correlator std\")\n",
-    "plt.xlabel(\"Number of samples\")\n",
-    "plt.ylabel(\"Cross power std\")\n",
-    "plt.legend(['cross_coh', 'cross_incoh', 'cross_sys'])\n",
-    "plt.grid()\n",
-    "\n",
-    "plt.figure(3)\n",
     "plt.plot(N_samples_arr_log, cross_SNR_dB_arr, 'r')\n",
     "plt.title(\"Correlator\")\n",
     "plt.xlabel(\"Number of samples (log10)\")\n",
@@ -542,15 +541,6 @@
     "plt.grid()"
    ]
   },
-  {
-   "cell_type": "markdown",
-   "id": "4fc1cbf5",
-   "metadata": {},
-   "source": [
-    "**Conclusion:**\n",
-    "The expected coherent cross power is pow_coh and the measurement of cross_coh_mean = pow_coh becomes more accurate when N_samples increases. The incoherent cross power is cross_incoh_mean and goes to zero. The SNR of the coherent correlator is proportional to 1 / cross_incoh_mean. Dividing by almost zero causes the SNR to fluctuate, but in general the SNR of the coherent signal improves by sqrt(N_samples)."
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": null,