A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

The Hidden Potential of the “Gamma’’ Data.

•The Milagro Gamma-Hadron separation is bases on simple collective variables (no topology).

•The optimization of the core/angle fitters is for the typical event.

It may be possible to re-optimize the gamma/hadron separation and reconstruction for the “best” events (large, high energy).

We have archived ~50TB of raw data from Summer 2005-Present -->Future

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

VERITAS spent 10hrs looking at J2019+37.

Reported at APS that they don’t see it, but can’t rule out Milagro.

There is a population of sources for which Milagro, largely due to our HE response is more sensitive than VERITAS.

If we can improve our sensitivity at HE we can do some really important science.

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

HESS Galactic Source Spectra

Milagro Sensitivity

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Motivation for this work

10TeV in Milagro

Better core locator?Better curvature/sampling?Better angle fitter?Optimize on big showers >10 TeV. Don’t let CPU be a limitation -> Minuit OK -> Max Likelihood.--> Take a systematic approach.

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Gamma-Hadron Separation

Gamma-Hadron Variables:

X2 = nB2/mxPE

A4 = (fOR+fAS)nFit/mxPE

Interpretation:

nFit ~ nB2 ~ nAS ~ N

X2 = N/mxPE

A4 ~ N2/mxPE + OR term

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

“Idealized” Gamma-Hadron Separation

S = Shower Size = Integral under core fitPi = Amplitude of ith non-correlated hit in bottom layerRi = Distance of ith bottom layer hit to core

P(S,Pi,Ri) = Probability of observing a hit of amplitude Pi at radius Ri from a shower with size S.

Size should be something like GeV at ground level.

Likelihood (/h) = ∏ Pgamma(S,Pi,Ri)/Phadron(S,Pi,Ri)

Take care to make sure that bottom layer hits are independent. Smoothing? Local maxima.

Similar to A4? More hits => bigger S. Larger R => more OR’s hit.

Get P’s from gamma MC and hadron data/MC.

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Gaussian Core Fitter

The limitations of the Gaussian core fitter.

Amplitude computed, but not saves. I fixed that.

Fitter includes lots of black magic:•Different starting positions•Levenberg-Marquardt Method•Several passes.•Starting points from on AS/OR COM.•OR/AS not normalized.•No Zeros•Variable width

Output not suitable for amplitude measurement

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Gaussian Core Fitter

•Generated a sample of 10 TeV showers thrown from zenith.

•Fluctuations in the depth of the first interaction dominate the PE fluctuations at observation level.

•Fixed the energy on the ground level ( 400-600 GeV ).

•PE distributions are log-normal.

•Plotted log10(PEs) vs. Rcore for three PMT types (AS,MU,OR)

•Fit log10(PE) slices for fixed R to Gaussian to get mean,sigma.

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Gaussian Core Fitter

Mean - AS Mean - MU Mean - OT

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Sigma -AS Sigma -MU Sigma -OR

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Max. Likelihood Core Fitter

Do fits in log(amp) space.

Fix width. Sure it varies, but not much and not for the big events at large R.

Minuit fit: 3 parameters x,y,A

A (in GeV) is natural parameter.

Get predicted amp’s and sigmas from fits to distributions on previous page.

Result: Can fit cores out to ~180m!

Poorer fits for shorter distances.

Subtle point: Pond PMTs are makingredundant measurements. Re-samplingthe same blobs of energy. Played with 2

contribution from pond PMTs.

Still no zeros.

Potential to double collection area!

Code is functional and in Milinda (Beta).

Red = GaussianBlue = Likelihood

Red = GaussianBlue = Likelihood

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

New Estimate of Sampling and Curvature Correction

•Use same 10 TeV sample thrown from zenith.

•MC now includes time offset between Corsika injection times and time of FI

•Can now get “absolute” shower from time.

T=0

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

Curvature/Sampling

time time time

R = 5 m R = 75 m R = 140 m

•These plots are for 5PE pulses.

•Sampling and curvature both depend on R.

•Not surprising, Tony taught us this.

•Fits to Gaussian with different sigma to the left and right of the mean.

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

1 PE 2.5 PE 5 PE 9 PE

19 PE 37 PE 75 PE >100 PE

Curvature/Sampling

•Curvature is not linear -- more parabolic

•Curvature depends on amplitude.

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

1 PE 2.5 PE 5 PE 9 PE

19 PE 37 PE 75 PE >100 PE

Curvature/Sampling

•These are sigmas.

A. Smith UMD, April 20-21, 2007 Milagro collaboration meeting

New Likelihood Angle Fitter

•Fitter is not there yet.

•Must account for noise.

•Some time distributions don’t fit well.

•First test is an idealized --> How well can we do test.

•How much improvement can we expect (hope for?)

•2x (?) from core fitter.

•Angle improvement ? Time will tell.

•Milagro is the most sensitive instrument at E>20 TeV.

•Most of the code is in place, but not ready yet.