Bayesian vs Frequentist Statistical Model for Randomized Benchmarking

002_demo.py

x = np.array([ 
   [1,29,57,85,113,141,169,197,225,253,1,29,57,85,113,141,169,197,225,253],
   [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
   [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] ])

counts = np.array([ 
   [966,675,542,406,362,355,296,284,238,244,960,503,322,342,291,252,245,267,256,250],
   [943,608,487,404,310,276,290,248,250,248,951,623,429,337,279,248,248,251,268,252],
   [971,687,550,391,372,293,278,264,259,260,940,596,424,320,285,251,249,231,253,253],
   [961,660,501,416,316,294,299,268,253,239,966,632,413,339,269,265,276,241,254,262],
   [965,705,561,397,330,287,255,277,235,262,945,558,377,260,275,262,268,260,248,226],
   [967,611,449,347,287,251,235,241,219,222,951,509,334,301,229,225,194,195,220,206],
   [946,573,415,247,238,217,226,212,212,206,925,500,295,268,213,212,209,209,200,209],
   [948,570,363,350,281,256,238,223,221,199,934,464,292,255,227,209,221,182,208,188],
   [948,611,401,329,269,255,251,226,209,197,945,508,319,263,224,219,225,206,203,210],
   [935,605,382,345,229,224,221,203,227,214,946,512,339,248,226,228,186,213,203,190],
   [944,646,496,379,289,265,291,272,267,240,927,609,381,332,279,283,245,242,243,232],
   [921,698,474,402,342,313,272,291,246,277,934,627,399,291,265,250,253,257,251,249],
   [941,686,549,398,322,272,271,230,243,233,939,617,454,296,261,276,245,250,244,251],
   [951,682,540,367,327,284,264,267,267,264,950,566,419,308,275,251,281,250,267,247],
   [922,661,512,369,304,293,245,258,266,247,923,510,404,331,304,250,252,236,249,245],
   [955,652,394,301,270,231,250,217,255,220,926,530,384,282,253,225,200,225,207,233],
   [926,630,411,324,257,244,228,226,225,230,924,519,326,270,217,228,215,202,206,200],
   [896,601,443,377,267,233,218,209,254,227,908,542,340,290,225,212,212,201,231,232],
   [945,616,423,326,278,254,251,231,223,213,923,487,313,267,241,221,194,218,224,211],
   [921,564,453,354,306,272,245,241,206,231,917,538,393,268,242,236,234,221,220,241]])