1. GLAST and pulsars: models and simulations
Gamma-ray Large Area Space Telescope
Massimiliano Razzano
(INFN-Pisa)
Astrofisica gamma dallo spazio in Italia
AGILE e GLAST
ESRIN, Frascati, 3 luglio 2007
06/02/2006
M.Razzano

2. PulsarSpectrum, simulating pulsars for GLAST
PulsarSpectrum simulator
Flexible architecture to allow creation of pulsar sources;
Pulsar parameters easy to implement;
PSRPhenom: Phenomenological model;
PSRShape: Simulation of arbitrary energy-phase photon distribution;
Simulation of timing effects;
Full Interface with with LAT software (Gleam, observationSim);

3. Creating the f-E histogram
Photons from simulated pulsars are extracted according to a phase-energy distribution that is specified in a 2D ROOT histrogram (Nv)
Nv histogram, that depend on the energy E and on the phase f, or equivalently time t Є [0,P]).
2 simulation schemes/models can be used for creating it.
PSRPhenom
-Spectrum S(E) modeled with an analytical formula
-Lightcurve L(f) independently created;
Nv (E,f) = k x L(f) x S(E);
Normalization k is specified by the user (Flux above 100 MeV);
 Simple but some limitations
PSRShape
-Nv dependence on E and f is modeled using available data (EGRET) or prediction from theoretical models;
More complex models and also phase-dependence of spectrum

4. PSRPhenom: simulating lightcurves
Lightcurves can be random generated or read from a profile
Random curves (Lorentz peaks);
Existing TimeProfiles are useful for simulating known pulsars
Random peaks
Vela EGRET lightcurve (100 bins)
Simulation model Lightcurve
(2000 bins44us time bin width)

5. PSRPhenom: simulating spectra
I choose this analytical spectral shape:
(Nel and De Jager,1995):
Description of the high energy cutoff;
Parameters are obtained from fits on the known g ray pulsars (Nel, De Jager 1995);
Flux normalisation in a similar way to 3rdEGRET catalog (ph/cm2/s, E>100MeV);
Example for Vela-like PSR
F(E>100) ~9*10-6 ph/cm2/s,
En=1GeV,E0=8GeV;
g=1.62
b=1.7
Data from (N&DJ95)
b=1
Different scenarios
b=2

6. PSRShape:simulating arbitrary models A new model has been implemented
The base phenomenological model (power law + exp cutoff) cannot be used for more detailed phase-energy distribution of photons.
A new model has been implemented
PSRShape features
External ROOT 2D histogram files can be used
Flux normalization can be adjusted;
Resulting phase-dependent Vela (data from EGRET)
Phase-dependent spectrum model based on EGRET data

7. Timing effects
According to energy-phase distribution interval between photons are calculated, but the arrival times are processed for including timing effects.
Timing analysis of pulsars is based on analysis steps for applying timing corrections (e.g. barycentering), and phase-assignment. Timing is affected by several effects. These effects must be considered in order to have a realistic list of photons arrival times.
Motion of GLAST in Solar System, relativistic effects (barycentering)
Period change with time;
Ephemerides and timing solutions;
Timing noise;
Modulation in case of binary pulsars;

8. Barycentric decorretions
The analysis procedure on pulsars starts by perfoming the barycentering, i.e. transform the photon arrival times at the spacecraft to the Solar System Barycenter, located near the surface of the Sun
Several effects that contribute to the barycentering, mainly:
Geometrical delays (due to light propagation);
Relativistic effects (i.e “Shapiro delay” due to gravitational wall of Sun)
Time [days]
In order to be more realistic for the simulations we then must de-correct

9. Cordes Activity parameter A:
Adding Timing Noise
Timing noise is an important issue since it affect lightcurves and pulsar blind searches. A basic model of timing noise is includes
Several studies and modeling have been proposed for timing noise;
For our purposes we choose the model based on Random Walk (Cordes 1980);
Example of PN timing noise residuals for simulated pulsar called PSR J
Cordes Activity parameter A:
Noise events occurr at times ti
with mean rate R=1day-1
k=0->Phase Noise,
k=1=Frequency Noise,
k=2,Slow down Noise

10. Pulsars in binary systems
Emission from pulsars in binary systems could be much complicate. Since at this stage our purposes are mainly tests of SAE pulsar tools, we paid more attention to orbital motion than to pulsar emission processes
First stage implement Keplerian motions, including only:
Solution of Kepler’s equation;
Roemer delay;
Einstein and Shapiro delay already implemented, but no PPN parameters (e.g. g,r parameters) internally computed;
The Roemer delay can be seen, in this example of 6 months of sim. PSR J (Porb≈5.7 d)

11. Filling the D4 file with simulated pulsars
PulsarSpectrum is able to take both spin and orbital data of simulated pulsars for creating a D4 database
gtpulsardb
PulsarSpectrum
With simulations a summary file is created with names of files containing spin parameters and orbital parameters of the simulated pulsars;
These ASCII files can be converted into a single D4 fits file using gtpulsarb
SimPulsars_summary.txt
SimPulsars_spin.txt
SimPulsars_bin.txt
SimPulsars_names.txt
D4 fits file

12. Example of simulations
Lightcurve E>100 MeV
PSR B , 1 months simulation
Lightcurve E> 10 GeV, 15 photons
Lightcurve E>100 MeV

13. Simulation of PSR B1951+32 Model Lightcurve 30 days Count map
Spectrum
30 days
Sim. observation

14. DC2: Pulsar population EGRET pulsars (6); 3EG-coincident pulsars (39);
Credits:Seth Digel
EGRET pulsars (6);
3EG-coincident pulsars (39);
Isolated “Normal” pulsars RL or RQ, based on Slot Gap emission (140);
Millisecond pulsars RL or RQ based on Polar Cap (229);

15. EGRET pulsars: lightcurves
Vela,30d
Vela,55d
Seeing that pulsars does pulse….
Geminga,55d
Crab,55d

16. How many pulsars? Estimates from DC2
Classe
LATCoinc
LATCoinc 1year
AllRadioPsr
AllRadioPsr 1 year
No detection 13 32 14 34
Low confid. 51
125
High confid. 22 54 78
EGRET: 6 High Confidence, 3 Low Confidence
Low confidence
High confidence
LogN-LogS
(see D.J.Thompson ’03)
Flux 10-8 ph(>100 MeV) /cm2 s
counts

17. LAT studying high-energy cutoff
Using XSpec the spectra have been recontructed for Vela pulsar
using 2 different emission scenarios.

18. Conclusions
GLAST LAT will be a powerful instrument for studying g-ray pulsars;
Only 7 pulsars are known to emit in gamma-rays then statistics is poor;
Simulations are a powerful tools for several goals: help development of analysis tools and test new analysis techniques;
Study and design focused analyses (e.g. sensitivity);
Give rough estimates of LAT capabilities on pulsars;
Pulsar simulations reached a good level of detail;
DC2 and SCs contain large population of full-detail pulsars;
Ancillary tools have been developed for producing realistic population and sent to PulsarSpectrum;
Using PulsarSpectrum, new simulated pulsars will be added in the next simulation runs;
Help and support LAT SWG on pulsars with production of focused simulations