Finally I am successful in calculating pi value — less than 0.3% error, by using random number generation. Although my computer needs some fixation on its compiler or path definition etc, there are very good online compilers which helps in testing and running c++ codes: try the given link.
Computing the value of pi using std::rand()
Enter number of trials: 10000
Enter number of random (x,y) points per trial: 10
pi = 3.14376 +- 0.00519107
average – exact = 0.00216735
CPU time = 0.004027 secs
Here is the code I found by searching a good deal on the web. Yes I did tinker around but only because my own compiler (Turbo C++ on windows 10, 64 bits) was throwing some exceptions on the included headers.
using namespace std;
double pi_estimate(const unsigned long points) More…
Experience and Plan of Action
The author has already spent a period of 14 months doing such research at the laboratory in Japan acquiring adequate amount of skill and orientation required for such a research goal.
The technique for this particular study is already at hand and has already been tested for other decay modes by the author himself. More…
The experimental high-energy physics processes are a brilliant case of application of the rules and methodologies of statistics. It comprises of multitude of processes each having a unique topography and physical kinematics. Some of the processes are called the signal for their specific treatment for extraction of a physical quantity. The other processes are mainly categorized as a bunch of background processes each contaminating the signal processes. The signals and background processes can crossfeed each other in the measurement of the yield for each of the process. There are errors associated with yield measurements and these propagate through the estimation of the yield and the efficiencies of the cross-feed associated with each yield [signal and background]. [Ref 1, Ref 2] More…