Goal To consider sources which are spatially extended (wrt PSF).

Motivation Correctly account for the correct source extension will enhance our chance for discovery

Implementation Convolute PSF with source extension:

As we model our PSF as a 2D Gaussian the convolution results in a broader Gaussian*.

* We assume Gaussian sources of extension

We assume our PSF is a two dimensional Gaussian on the form:

3sigmas discovery

5sigmas discovery

5sigmas discovery

Reference paper: Kappes et al. (2007b)

Procedure:

1)Simulate signal neutrinos with next energy spectrum (i.e. according to each model):

To create 3D-Histogram with (ψ,σ,ε);Angular resolution, Error estimate, Energy Convolute PSF with morphology maps

Neutrino flux models and model dependent upper limit:

Use optimal discovery source extension ?

Use optimal discovery source extension ?

Calculate upper limit using pex where the source extension which maximises the discovery power is used in the likelihood…

Problems at positive declinations

Feldman-Cousins and first bin in the only background test statistic distribution.

Feldman-Cousins and first bin in the only background test statistic distribution

Goal Calibrate Oms (ARSs) using muon time residuals.

Idea Use all (in opposite to unbiased*) hit time residuals distributions to calculate OM offsets.

Motivation The processing time can be reduced by one order of magnitude.

* These are, for inter-line offsete calculation, the so-called probe hits.

How do these distributions look like?

How do these distributions look like?

Test: Add offsets to hit times (for each Omid), reconstruct tracks, and then try to calibrate back the Oms by finding the time offstes we have introduced by fitting the time residuals distributions with a Gaussian function.

Results does not reflect the offsets we have introduced

Lambda distributions worsen by intruducing the offsets

Macros produced and more than 20 runs processed to extract TVC parameters.

Evolution of the TVC distributions (mean value) per line

All ARS (all runs) TVC distributions

Fitting with 2D Gaussian