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1 Statistics David Forrest University of Glasgow.

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Presentation on theme: "1 Statistics David Forrest University of Glasgow."— Presentation transcript:

1 1 Statistics David Forrest University of Glasgow

2 2 The Problem - We don't know the statistical error on the measurement we want to make in the MICE - But our aim is to show 10% emittance drop with an error of 1%.... - We need to know the statistical error on the fractional change of emittance

3 3 Trackers We calculate 4D emittance from the fourth root of a determinant of a matrix of covariances...The problem is compounded because our data is highly correlated between two trackers.

4 4 How We Mean To Proceed W e assume that we will discover a formula that takes the form Sigma=K*(1/sqrt(N)) where K is some constant or parameter to be determined. How do we determine K? 1) First Principles: do full error propagation of cov matrices → difficult calculation 2) Run a large number of G4MICE simulations, using the Grid, to find the standard deviation for every element in the covariance matrix → Toy Monte Carlo 3) Empirical approach: large number of simulations to plot   versus 1/sqrt(N), identifying K (started)

5 5 Empirical approach For N= 1000 then:   = 0.0074 (with  = -0.210) For N= 10,000 then   = 0.0021(with  = -0.210) 500 1k event runs 50 10k event runs

6 6 8 pi K=0.47

7 7 10pi K=0.3115 K=0.31

8 8 Future Work Simulations have been done for 4, 6 and 8 pi beams at higher statistics Problems with accessing Grid storage in the last two weeks have frustrated my being able to access some of these. But they are all done. I hope to have full access tomorrow. I expect to see similar results for the 6pi beam and will produce a 4pi plot also.


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