Study the discovery potential as a function of the energy cutoff:

- Modify ingredients for pex according to each flux model (Ecut)- Run pex for each Ecut using new ingredients- Calculate discovery power

Distributions used for fake signal injection during pex production

Dicovery power for different Ecut models

50% discovery power (in terms of the median n_s) as a function of the Ecut

Using Neyman truncated we would find a worst sensitivity.

But NIKHEF have presented the contrary?

Convoluting PSF with Morphology map

Modify the likelihood algorithm to treat the spectral index as a free parameter…

Performed measurements when the inter-line offsets used in the time calibration data base are not taken into account (miscalibrating lines)

Try to recover the official values calculated using calibration constants not corrected by the inter-line timing

This was done for different period or years…

2010

2010

2010

2008-2012

2008-2012

Try different philosophy:

Each ARS (OM) collects 1 single photon from the Cherenkov light cone induced by the muon (1 photon per event)

The influence of this single hit in the reconstruction should be sufficient small to be included in the track fit (forget about probe OMs or probe ARSs)

Read residuals from reconstructed tracks (using all hits) and then fill histograms with the residuals for each ARS

The mean value of the number of hits used to reconstruct a downgoing muon is around 35, which is the factor we could gain in data processing time!

One single physics data run could be enough! (300 thousand events, each having 30-40 hits)

With just the 10% of the hits read from file 046700 there is sufficient statistics to make some good fits:

Write code to find best range for fitting the tres distribution

New code for reading TVC params and make plots.

Start to write a guide for users …