solutions.md (1378B)
1 # Findings 2 3 ## Code 4 The code is structured as follows: 5 6 * Construct statistical covariance matrix 7 * Construct Jacobi matrix of model function in terms of the parameters 8 * Guess parameters p0 9 10 Then we iterate the following: 11 12 * Construct System covariance matrix with the guess p0 13 * Fill Jacobi matrix with p0 = Design Matrix 14 * Claculate dp 15 * p0 = p0 + alpha*dp; alpha \in [0, 1] 16 * (calculate the chi^2 function) 17 18 Additionally we can calculate the chi^2 function at each iteration. 19 20 The guess used for all fits was determined by standard least-square fit 21 provided by 'scipy'. p0 = [0.9, 0.2, 0.81, 0.04, 0.02, -1, 0.84, 1.55] # in GeV 22 First let us look at results of single experiments fitted separately: 23 24 SND -------> Pictures 25 CMD2 26 KLOE 27 BABAR 28 29 Table with fits and chisq, pvalue 30 31 Then we can fit multiple experiments togehter if we align the given data and 32 construct block diagonal system covariance matricies. 4 experiments fited with 33 2 together gives 6 combinations. 34 35 SND-CMD2 36 SND-KLOE 37 SND-BABAR 38 CMD2-KLOE 39 CMD2-BABAR 40 KLOE-BABAR 41 6 Picturs 42 43 Table with fits and chisq, pvalue 44 45 46 Here we fitted all experiments together. 47 48 ALL EXPERIMENTS 49 1 Picture 50 51 Table with fits and chisq, pvalue 52 53 54 Discussion schau ma mal was rauskommt 55 56 Reference code git://popovic.xyz/tprak.git