spectral analysis on faint extended sources: problems and strategies

Spectral analysis on faint extended

sources: problems and strategies.

Gamma-ray Large AreaGamma-ray Large AreaSpace TelescopeSpace Telescope

Omar TibollaPadova University

DC2 Closeout Workshop,Goddard Space Flight Center,

31 May – 2 June 2006

Vela FoV

Vela

PSR0904-5008 RXJ0852.0-4622 (Vela Jr)?

Vela Jr?

Is there really a source or is it only caused by Diffuse Galactic emission?

Yes, it’s a source

Is it extended? Is it Vela Jr?

It seems so...

Vela Jr? (2)

Yes, it is extended.

...and it seems also to have a structure...

Spectral analysis: directly

Let’s consider a ROI centered in Vela Jr center

ROI radius = 10o.

So at the same time we study all the 3 sources and the backgrounds directly.

Spectral analysis: directly (2)

Vela

PSR0904-5008

Galactic backgrounds

Extragalactic background

Residual components

Using the LAT source catalog?No

(Pulsars should have a Broken Power Law Spectrum)

Spectral analysis: directly (3)

Vela

PSR0904-5008



Residual components

Freeing scale parameters?No

The solution is trying to isolate sources and to study them separately...

But the 3 sources are very close among them, so we must use small ROI, much smaller than LAT PSF.Cut in energy!(and more attention to higher energies gammas)

Another exemplum

Extragalactic backgroundResidual components


This exemplum is more impressive; letting free too much the parameters (in this case scale parameters), we can get also non physical solutions!

So, after isolating sources and studying them separately...we should freeze their parameters as soon as possible...

Backgrounds

ROI of radius = 2o

Centered in: RA = 138o

dec = -43.5o

To know the backgrounds we consider a ROI near the sources we are studying but far enough to not be influenced by them

= 2o

Backgrounds (2)

Extragalactic background (fixed):constant diffuse emission

Pref = 1.6 ( x 10-7)Sp. Index= -2.1Galactic backgrounds: modeled with MapCube file GP_gamma.fitsThe scale factor is almost 1 never change very much(up to 1.037..)

Residual component:modeled with MapCube file residual.fitsThe scale factor is more than 3 times grater than we was expecting... 3.309

PSR0904-5008

Now we try to isolate PSR0904-5008.

ROI centered in the source: RA = 136.058o

dec = -50.1258o

ROI radius = 2o

(remember that now the backgrounds are totally fixed)

PSR0904-5008 (2)

So we ask python likelihood to fit PSR0904-5008 spectral behaviour with a Broken Power Law:

Pref. = 0.07026 ( x 10-9)Index 1 = -0.6664Index 2= -1.6589

EB = 4991.4

Extragalactic background Residual components


But we don’t like this fit... in particular if we look the behaviour at higher energies...

PSR0904-5008

PSR0904-5008 (3)

So we fix manually the Energy Break at 20 GeV and after we let

that EB run up to 25 GeV...

With EB = 20 GeV we obtain:

Pref. = 0.01374 + 0.00031 ( x 10-9)Index 1 = -0.924 + 0.012Index 2= -2.656 + 0.049 Residual components



PSR0904-5008 with EB = 20 GeV

EB : 20 GeV 25 GeV PSR0904-5008 with EB = 25 GeV


Residual components


With EB = 25 GeV we obtain:

Pref. = 0.00988 + 0.00023 ( x 10-9) Index 1 = -0.9776 + 0.011 Index 2= -2.989 + 0.064

For EB : 20 GeV 25 GeV, results

are very similar among them.

(log L increase for EB 5 GeV...

but for EB < 20 GeV the gap

between model and experimental data becomes relevant...

So we’ll use EB = 20 GeV )

PSR0904-5008 (4)

PSR0904-5008


Residual components


We tried (with Luis Reyes) to use a single Power Law with an exponential cut-off:

PSR0904-5008 (5)

1P

EE B

eand the this curve fits much better, with the following parameters:

Pref. = 1.46 + 0.31 ( x 10-9) Index = -0.832 + 0.073

EB = 7055 + 3884

P1= 26630 + 1744

It looks much better…

Vela

Now it’s Vela turn.

ROI centered in the source: RA = 128.842o

dec = -45.1687o

ROI radius = 2o

Vela



Residual components

Vela

Vela doesn’t create any problem. Its spectrum is fitted very well with a Broken Power Law:

Pref. = 0.0813 + 0.0049 ( x 10-9)Index 1 = -1.750 + 0.008Index 2= -3.441 + 0.078

EB = (4624 + 133) MeV

RXJ0852.0-4622

And what about Vela Jr model?We create a homogeneous disk fits file (MapSource)...and after we let that the radius of this circle runs

from 1o down to 0.8o.

Now we should know everything to face the study of RXJ0852.0-4622.

So we go back to the ROI shown in slide 5 and we put in the model all the fixed parameters we have obtained until now...

Using the model Vela Jr (using a Single Power Low Spectrum

hypothesis) with radius = 1o, we obtain:

Prefactor = 8.94 + 26.13 ( x 10-9)Spectral Index = -4.99 + 0.27

RXJ0852.0-4622 (2)

Vela

PSR0904-5008

Residual components



Note the 300% of uncertainity in the prefactor...

In fact, we can’t see Vela Jr in the plot...and, all in all, even if the result would be correct, I don’t like it (in particular for this SNR...)...

Something seems to be wrong...

Maybe having 2 source bright like Vela and PSR0904-5008 (almost one order of magnitude brighter than Vela Jr) make impossible the study of Vela Jr, amplifying too much its uncertainity..

PSR0904-5008


Vela


Residual components

Using the model Vela Jr with

radius = 0.8o, we obtain:

Prefactor > 10000 ( + 2 ) ( x 10-9) Spectral Index > -1 ( + 0.00002 )(Also in this case we can’t see Vela Jr in the plot...)There is really something wrong somewhere.

We could try to simplify the problem...

RXJ0852.0-4622 (3)

RXJ0852.0-4622 avoiding PSR0904-5008

In order to simplify the problem we could try to exclude PSR0904-5008 from the ROI.2 reasons: -it’s impossible to exclude Vela -at higher energies it’s the only relevant source (so there we can hope to see traces of Vela Jr)

ROI centered in : RA = 130o

dec = -45.5o

ROI radius = 4.3o


Vela

Residual components


PSR0904-5008

Vela Jr

RXJ0852.0-4622 avoiding PSR0904-5008 (2)

Using the model Vela Jr with

radius = 1o, we obtain:

Prefactor = 9813 + 986 ( x 10-9)Spectral Index = -2.165 + 0.042

And I like this result...

(Note that, even if PSR0904-5008 is not in the ROI, we should insert it in the model)


Vela

Vela Jr


Residual components

PSR0904-5008

And finally let’s do the check moving the radius of the model of

Vela Jr down to 0.8o...both Prefactor and Spectral Index decrease slowly.

With radius = 0.8o we obtain:

Prefactor = 5224 + 801 ( x 10-9) Spectral Index = -2.018 + 0.053

RXJ0852.0-4622 avoiding PSR0904-5008 (3)

This seems to be the correct way to follow, but we should know much better the geometrical shape (or structure) of RXJ0852.0-4622...

OK


Vela

Vela Jr


Residual components

PSR0904-5008

Let’s look if using the Power Law with the exponential cut-off for PSR0904-5008, we’ll get some improvements; using for Vela Jr,

radius = 1o, we have:


RXJ0852.0-4622 avoiding PSR0904-5008 (4)

(The same results we obtained with the Broken Power Low; but we could expect it, excluding that Pulsar from the ROI)


Vela

Vela Jr


Residual components

PSR0904-5008

For Vela Jr with radius = 0.8o we obtain:


again the same results we obtained before

RXJ0852.0-4622 avoiding PSR0904-5008 (5)

This seems to be the correct way to follow, but we should know much better the geometrical shape (or structure) of RXJ0852.0-4622...

OK

Next steps

In the last slide we end saying that the next step should be, having a better spatial resolution of RXJ0852.0-4622:

1- using better classes of gammas: using only gammas of class A could be very useful also for re-doing the spectral analysis we have just performed.

2- using higher cut in energy, in order to reduce the PSF

3- more detailed TS Maps

4- increase the observation time

5- try the new release of Science Tools (v7r2...here I used Science Tools v7r0p3)

6-in order to separate much better Vela and Vela Jr, it should be useful to have more cuts on CTB core (see Bill’s talk)

Acknowledgements

In alphabetic order:

-Bill Atwood; USFC, USA.

- Giovanni Busetto; Padova University, Italy.

- Seth Digel; SLAC, Stanford, USA.

- Francesco Longo; Trieste University , Italy.

- Elisa Mosconi; Padova University, Italy.

- Riccardo Rando; Padova University, Italy.

- Luis Reyes; GSFC, USA.

- Francesca Maria Toma; Padova University, Italy.

spectral analysis on faint extended sources: problems and strategies

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