06/02/2006 M.Razzano - DC II Closeout Meeting Pulsars in DC2 preliminary results from an “optimized” analysis Gamma-ray Large Area Space Telescope Massimiliano Razzano (INFN - Pisa) LAT Collaboration Meeting 2006 (Stockholm, Aug )

Analysis overview At the DC2 closeout I presented an analysis on pulsars with radio counterparts with fixed cuts (E>100MeV, r= 3.0° & E>1GeV,r=0.5) and a single periodicity test; Now we know the DC2 truth so we can extend our analysis procedures to all simulated pulsars in order to have better population statistics A new automatic analysis on RL pulsar have been started and here are shown some of the preliminary results (still work in progress) from this optimized analysis. Optimized analysis: This new analysis is an improvement of the basic analysis presented at DC2 Closeout No fixed cuts in energy or ROI, but search for the “optimal” cuts that maximize the detection chance probability; More robust and organized Python scripts and classes; Not only the  2 test but also Z 2n and H test; Change analysis strategy;

The 3 ingredients of the analysis 1.Science Tools: Basic for pulsar data analysis ; (gtselect, gtbary, gtpphase, gtpsearch, gtephcomp; 2.The pyPulsar suite: Python classes and scripts for interfacing ScienceTools; File I/O and results organization; Extension (with FITS, ROOT, etc..) Plotting 3.The SLAC Computing Farm: 1.Set of bash and python scripts for running analysis; 2.Much more operations on a single pulsar in order to find optimal cuts  Parallel analysis on each pulsar (instead of serial)

Python scripting: pyPulsar pyGtTools (classes for interfacing with LAT Pulsar Science Tools) pyGtBary pyGtPsearch pyGtEphcomp pyGtPhase pyGtSelect LAT Pulsar Tools pyPulsar (class for managing data and analysis of a pulsar) pyAnScripts (scripts for various pulsar-related analysis) pyPulsar is a set of Python classes and scripts for doing pulsar analysis Analysis results

PyPulsar mini-tutorial pyPulsar can be found in the CVS under /users/razzano/pyPulsar (compatibility with latest ST release is under test…); Create a List of pulsars to be analyzed, i.e. using FindCoincPulsars.py (it can create a list of pulsar coincident with LAT catalog sources of from the whole D4 database): 2 analysis mode: standard and optimized. Run the script SingleRadioAnalysis.py, giving in input the pulsar parameters Optional, you can run a multiple analysis (MultipleRadioAnalysis.py) on a pulsar list. At the end you will have a summary that contains list of pulsars analyzed together with analysis results

Thresholds and Optimized Cuts Instead of fixed minimum energy E min and radius of the ROI r ROI for the analysis, we span a range of trial energies and radii, and for every couple E min and r ROI we compute the chance probability CP, in order to find the optimal couple E min,r ROI that minimize P in the periodicity test E min (MeV) = {20,100,300,500,1000,5000,10000,20000} 0.5° < r ROI < 3.5° What is the threshold for pulsar detection? After some tests and some discussions I decided to use a more “conservative” detection limits, according to the EGRET pulsars papers Energy  2 test H-testReference No detectionP > 2 x10 -3 The same as below Low-confidence5 x < P <2.7 x x < P< 6.8 x10 -3 Limit of B ,B (Ramanamurthy et al. 1996,Kaspi et. Al 2000) High-confidenceP < 5 x P < 2 x Limit of B (Ramanamurthy et al. 1995)

Pulsars in the LAT source catalog? As first step a search for coincidence between LAT sources and pulsars in D4 Radius dependent on energy (LAT_Cat_v2)  50 pulsars found

Example: List of Pulsars coincident with LAT Catalog This list have been obtained by scanning D4 with LAT Catalog (FindPulsarCoinc.py) Input are the LAT Catalog and the pulsar database…

The Chance Probability Map For each pulsar a “Chance Probability Map” is computed and the minimum is found, Corresponding to this minimum there are the “optimal” E min and r ROI e.g. here E min =10 GeV and r ROI =1.5° More fine cuts can be tried to better find the optimal cuts. Here only an example is shown

The Probability profile In the same way it is possible to show the chance probability change with energy for different r ROI. Here are shown profiles for r ROI =0.5 (dotted), r ROI =3.0 (dashed) and r ROI =1.5 (solid), where the minimum is For some bright pulsars optimal cuts are for high E min,but this is not too realistic since the DC2 pulsars are “ideal” and does not include timing noise. A more careful search excluding high E min should be more realistic

The final reports For every pulsar a summary report with the optimized cuts is written, then a Python script creates a general report of all analyzed pulsars This contains pulsar position, potential LAT counterpart, f0,f1, optimal cuts and informations about periodicity test

Pulsars in the LAT catalog:  2 -Test The analysis with Chi2 shows an increment with respect to the previous method Standard analysisOptimized cuts +old thresholds Optimized cuts + new thresholds No detection1444 Low confid High confid Chi-2 detections of pulsars coincident with the LAT Catalog Δ High Confidence □ Low Confidence

Pulsars in the LAT catalog: DC fluxes Distribution of pulsar DC flux (from the LAT Catalog) with optimized analysis compared with normal analysis (left) Low confidence High confidence

Work in progress… From the preliminary results the optimized cut analysis seems to provide better results than the basic analysis: many “discovered” pulsars and lower fluxes. The Python scripts have been upgraded and refined to be more robust; The parallel analysis approach is much more efficient than the serial one (at least 50 analyses for every pulsars must be done for the optimized cut analysis) Unfortunately some problems in accessing fits data files from different parallel processes give some conflicts, so a definitive analysis is not yet complete. This have been solved and new analysis runs go to run. Such type of analysis will be performed also on the whole DC2 pulsar population, in order to refine our pulsar studies with known ephemerides (i.e. use the RQ as RL);