Kinfit

From PrimExWiki

Often in nuclear and high energy physics one is faced with a chi-squared minimization problem involving several measured variables from a single event where there are known relations or constraints among the variables. It usually turns out that these constraints can be more easily expressed by introducing new variables to the problem, so-called unmeasured variables. The introduction of a new unmeasured variable will always require introduction of a new constraint equation, relating its value to the measured variables. The new problem is merely a mathematical restatement of the original problem. It may also turn out that the value of an unmeasured variable is of physical interest and so a best-fit value, its uncertainty and its statistical correlations with the other variables are desired.

The program KINFIT solves this problem. The method of Lagrange multipliers is used to avoid having to algebraically eliminate unmeasured variables from the problem using the constraints. In addition, the constraints are linearized so that the resulting approximation to the problem can be solved using matrix methods. The procedure is iterated until satisfactory convergence is obtained.

• Documentation (PostScript)
• Source code: /group/primex/kinfit/kinfit.f