Instructions to Run Fermi Analysis Software Tools

Choosing Sources:

Our recommendation for choosing sources is as follows:

There are two types of catalogue for Gamma-Ray sources

• FAVA Catalogue: An all sky Gamma ray source catalogue published my Fermi LAT.
• TeV Catalogue: This is a catalogue for the TeV energy sources in extragalactic space.

We will follow the steps listed below:

1. We will mark all the sources in FAVA catalogue that shows high activity ( I choose a threshold of $N^f>35$ )
2. Match the FAVA sources against the TeV catalogue
3. From there we will preferably choose sources that are either FRSQ or BL Lac
4. We will then extract the data from Fermi Servers

Here is a table of all the sources

Name	RA	Dec	Date	Type
3C 279	194.05	-5.78	2007.08	FRSQ
4C +21.35	186.23	21.38	2010.06	FRSQ
PKS 1441+25	220.99	25.03	2015.04	FRSQ

Why High Activity Sources:

Higher activity implies more events. More events means the likelihood analysis giving more accurate results and also more scope to identify more correlation between events.

Extracting Data:

To extract data we have to first visit the client side web application of Fermi LAT server. There we will have to fill up the expected information. Like in the following form.

Object name or coordinates:
Coordinate system:	J2000B1950Galactic
Search radius (degrees):
Observation dates:
Time system:	GregorianMETMJD
Energy range (MeV):
LAT data type:	PhotonExtendedNone
Spacecraft data:

Explanation:

Here we can see different objects require different measurement system. J2000 refers to the celestial RA/Dec coordinate system for measuring position of the stars and astronomic/astrophysical objects modified after Gregorian calendar year 2000. B1950 is for the same but for the period of 1950-1999. Galactic refers to the galactic latitude and longitude positioning system. MJD is Modified Julian Dates, where Julian dates are converted to seconds. MET is Mission Elapse Time i.e. the time elapse since the Fermi LAT started it's orbit in seconds. MET is the standard time measurement unit for Fermi Analysis.

This tool called xTime can help convert between different time units.

N.B.- you should keep a record of your search query, like the following.

Query Data for 4C +21.35
Equatorial coordinates (degrees)	(186.23,21.83)
Time range (MET)	(239557417,346982402)
Time range (Gregorian)	(2008-08-04 15:43:36,2011-12-31 00:00:00)
Energy range (MeV)	(100, 500000)
Search radius (degrees)	15

Analysis:

To run the analysis, you obviously need the Fermi software tools. You can download it using conda. To install, run the following:

$ conda create -n fermi -c conda-forge -c fermi fermitools

To activate Fermitools use conda activate fermi And to exit Fermi use conda deactivate To work more efficiently you need a few more tools like

• To run in Jupyter notebooks, you will need the nb_conda package

  $ conda install -c conda-forge nb_conda

• To create XML files of your data for model likelihood analysis on Fermitools you will need make4FGLxml.py

• We should also install ds9 to view the fits files. To install the ds9 software first go to the SAOImageDS9 site and download the TAR file. As the version for Ubuntu 22 is not released yet, you can just download the file for version 20. For Fedora, it's only been updated till Fedora 33, let's try Fedora 37 when it's released. Extract the TAR file. In your command line go to the extracted directory and give sudo permission

  $ sudo -s
  $ mv ds9 /usr/local/bin
  $ chmod +x /usr/local/bin/ds9

  Then run the program from command line

  $ ds9

• If you want a more advanced likelihood option, you can also use Fermipy

  $ conda install -c conda-forge fermipy

Using CLI:

When we extract the data from Fermi LAT servers, we might get several photon files, in that case, we have to do the following:

$ ls *_PH* > events.txt

Choose the filename based on your preference and context. E.g.- for binned analysis it can be

$ ls *_PH* > binned_events.txt

or for unbinned analysis

$ ls *_PH* > unbinned_events.txt

When analyzing point sources, it is recommended that you include events with high probability of being photons. To do this, you should use gtselect to cut on the event class, keeping only the SOURCE class events. In addition, since we do not wish to cut on any of the three event types (conversion type, PSF, or EDISP), we will use evtype=3. Note that "INDEF" is the default for evtype in gtselect.

Standard Hierarchy for LAT Event Classes
Event Class	evclass	Photon File	Extended File	Description
P8R3_TRANSIENT020	16		X	Transient event class with background rate equal to two times the A10 IGRB reference spectrum.
P8R3_TRANSIENT010	64		X	Transient event class with background rate equal to one times the A10 IGRB reference spectrum.
P8R3_SOURCE	128	X	X	This event class has a residual background rate that is comparable to P7REP_SOURCE. This is the recommended class for most analyses and provides good sensitivity for analysis of point sources and moderately extended sources.
P8R3_CLEAN	256	X	X	This class is identical to SOURCE below 3 GeV. Above 3 GeV it has a 1.3-2 times lower background rate than SOURCE and is slightly more sensitive to hard spectrum sources at high galactic latitudes.
P8R3_ULTRACLEAN	512	X	X	This class has a background rate very similar to ULTRACLEANVETO.
P8R3_ULTRACLEANVETO	1024	X	X	This is the cleanest Pass 8 event class. Its background rate is 15-20% lower than the background rate of SOURCE class below 10 GeV, and 50% lower at 200 GeV. This class is recommended to check for CR-induced systematics as well as for studies of diffuse emission that require low levels of CR contamination.
P8R3_SOURCEVETO	2048	X	X	This class has the same background rate than the SOURCE class background rate up to 10 GeV but, above 50 GeV, its background rate is the same as the ULTRACLEANVETO one while having 15% more acceptance.
Extended Hierarchy
Event Class	evclass	Photon File	Extended File	Description
P8R3_TRANSIENT020E	8		X	Extended version of the P8R3_TRANSIENT020 event class with a less restrictive fiducial cut on projected track length through the Calorimeter.
P8R3_TRANSIENT010E	32		X	Extended version of the P8R3_TRANSIENT010 event class with a less restrictive fiducial cut on projected track length through the Calorimeter.
NON-ACD Hierarchy
Event Class	evclass	Photon File	Extended File	Description
P8R3_TRANSIENT015S	65536		X	Transient event class designed for analysis of prompt solar flares in which pileup activity may be present. This class has a background rate equal to 1.5 times the A10 reference spectrum.

Conversion Type Partition
Event Type	evtype	Description
FRONT	1	Events converting in the Front-section of the Tracker. Equivalent to convtype=0.
BACK	2	Events converting in the Back-section of the Tracker. Equivalent to convtype=1.
FRONT & BACK	3	Events converting in the Front-and-Back section of the Tracker.
PSF Type Partition
Event Type	evtype	Description
PSF0	4	First (worst) quartile in the quality of the reconstructed direction.
PSF1	8	Second quartile in the quality of the reconstructed direction.
PSF2	16	Third quartile in the quality of the reconstructed direction.
PSF3	32	Fourth (best) quartile in the quality of the reconstructed direction.
EDISP Type Partition
Event Type	evtype	Description
EDISP0	64	First (worst) quartile in the quality of the reconstructed energy.
EDISP1	128	Second quartile in the quality of the reconstructed energy.
EDISP2	256	Third quartile in the quality of the reconstructed energy.
EDISP3	512	Fourth (best) quartile in the quality of the reconstructed energy.

Check out this website for any kind of confusion.

Making cuts using the events file keywords

Applying selection cuts to the LAT data is typically performed using select, and is documented in detail within the data exploration analysis thread. Typically cuts are made to bound the dataset's time range, energy range, position, region of interest radius, and maximum zenith angle. The maximum zenith angle selection is designed to exclude time periods when any portion of the region of interest is too close to the Earth's limb, resulting in elevated background levels. The Earth's limb lies at a zenith angle of 113 degrees, so a suggested value of 90 provides protection against significant contamination by atmospheric gammas. (NOTE: This cut requires careful handling when calculating livetime, which is discussed in detail in the Likelihood Livetime and Exposure section.).

Additionally, gtselect can be used to include/exclude events which have a higher/lower probability of being photons. The recommended class of events to use depends on the analysis in question. The LAT teams recommendations are listed in the "Event Selection Recommendations" table above. The instrument response functions used in the analysis tools must match the event classes selected.

The reconstruction and classification of LAT events is performed by the LAT instrument team as part of the Level 1 science data processing. The version of the event reconstruction algorithms used is referred to as Pass N. Currently, the LAT data pipeline uses Pass 8 (P8R3) algorithms. This processing is inherent in the science data, and cannot be changed. For a given reconstruction, the LAT team generates an accompanying set of parameterized instrument response functions (IRFs) that are designed for analysis of that particular dataset, these are labeled VN (where N is the version of the IRF). There may be several updates of IRFs for a given reconstruction, with one recommended for analysis (currently P8R3_CLASS_V3). The IRFs selected later in the analysis chain must match the data reconstruction version (currently Pass 8) and the event class selected at this stage, i.e. P8R3_SOURCE_V3 for a point source analysis. A more detailed discussion can be found in the LAT Response Functions section of the Cicerone.

The acceptance cone radius will vary with analysis type and source location. Performing a spectral analysis on a point source in the galactic plane will require a larger initial analysis region than for a source off the plane, to allow for fitting of multiple nearby sources. An acceptance cone radius of 10 deg is appropriate for spectral analysis of point sources off the Galactic plane, while 10-20 deg may be necessary for point sources located near the Galactic Plane. A timing analysis that does not use spectral modelling (for example, pulsar lightcurves) might select a smaller region to reduce background levels. These studies (timing analysis, GRB spectral analysis, extended source analysis, and others) require optimization of the acceptance cone on a case-by-case basis. Such optimization will need to consider the largest PSF of the LAT in the energy range of interest, as well as providing sufficient statistics to account for the surrounding sky structure. An all-sky analysis does not require this selection.

Event Selection Recommendations (P8R3)

Analysis Type	Minimum Energy (emin)	Maximum Energy (emax)	Max Zenith Angle (zmax)	Event Class (evclass)	IRF Name
Galactic Point Source Analysis	100 (MeV)	1000000 (MeV)	90 (degrees)	128	P8R3_SOURCE_V3
Off-plane Point Source Analysis	100 (MeV)	1000000 (MeV)	90 (degrees)	128	P8R3_SOURCE_V3
Burst and Transient Analysis (<200s)	100 (MeV)	1000000 (MeV)	100 (degrees)	16	P8R3_TRANSIENT020_V3
Galactic Diffuse Analysis	100 (MeV)	1000000 (MeV)	90 (degrees)	128	P8R3_SOURCE_V3
Extra-Galactic Diffuse Analysis	100 (MeV)	1000000 (MeV)	90 (degrees)	1024	P8R3_ULTRACLEANVETO_V3 or P8R3_SOURCEVETO_V3 (when interested in E>1 GeV energy range)
Impulsive Solar Flare Analysis	100 (MeV)	1000000 (MeV)	100 (degrees)	65536	P8R3_TRANSIENT015S_V3

We will now apply the gtselect tool to the data files.

$ gtselect evclass=128 evtype=3
Input FT1 file[] @binned_events.txt
Output FT1 file[] 3C279_binned_filtered.fits
RA for new search center (degrees) (0:360) [] INDEF
Dec for new search center (degrees) (-90:90) [] INDEF
radius of new search region (degrees) (0:180) [] INDEF
start time (MET in s) (0:) [] INDEF
end time (MET in s) (0:) [] INDEF
lower energy limit (MeV) (0:) [] 100
upper energy limit (MeV) (0:) [] 500000
maximum zenith angle value (degrees) (0:180) [] 90
Done.

Making cuts using the spacecraft file keywords

The spacecraft files are used to select the good time intervals (GTIs) for data analysis by using gtmktime. Selecting times when the data quality is good (DATA_QUAL>0) will exclude time periods when some spacecraft event has affected the quality of the data. gtmktime can be used to generate and combine GTIs for any logical expression of keywords in the spacecraft file. Contamination from albedo gamma rays from the Earth is reduced by applying an additional timing selection to the maximum zenith angle cut made with gtselect. Excluding time intervals when the Earth's limb intersects the selected region of interest is one method of correcting the exposure for the zenith cut. This is accomplished by using the ROIcut=yes option in gtmktime. For other exposure correction options, see the Likelihood Livetime and Exposure section.

Some possible quantities for filtering data are:

• DATA_QUAL - quality flag set by the LAT instrument team (1 = ok, 2 = waiting review, 3 = good with bad parts, 0 = bad)
• LAT_CONFIG - instrument configuration (0 = not recommended for analysis, 1 = science configuration)
• ROCK_ANGLE - can be used to eliminate pointed observations from the dataset.

Time Selection Recommendations

Analysis Type	ROI-Based Zenith Angle Cut (roicut)	Relational Filter Expression (filter)
Galactic Point Source Analysis	no	(DATA_QUAL>0)&&(LAT_CONFIG==1)
Off-plane Point Source Analysis	no	(DATA_QUAL>0)&&(LAT_CONFIG==1)
Burst and Transient Analysis	yes	(DATA_QUAL>0)&&(LAT_CONFIG==1)
Galactic Diffuse Analysis	no	(DATA_QUAL>0)&&(LAT_CONFIG==1)
Extra-Galactic Diffuse Analysis	no	(DATA_QUAL>0)&&(LAT_CONFIG==1)
Burst and Transient Analysis	yes	(DATA_QUAL>0||DATA_QUAL==-1)&&(LAT_CONFIG==1)

Now we will perform the the good time interval using gtmktime tool.

$ gtmktime
Spacecraft data file[] L181126210218F4F0ED2738_SC00.fits
Filter expression[] (DATA_QUAL>0)&&(LAT_CONFIG==1)
Apply ROI-based zenith angle cut[] no
Event data file[] 3C279_binned_filtered.fits
Output event file name[] 3C279_binned_gti.fits

To view the DSS keyword, you can use the gtvcut tool and review the datacuts.

$ gtvcut 3C279_binned_gti.fits
Extension name[EVENTS]
DSTYP1: BIT_MASK(EVENT_CLASS,128,P8R3)
DSUNI1: DIMENSIONLESS
DSVAL1: 1:1

DSTYP2: POS(RA,DEC)
DSUNI2: deg
DSVAL2: CIRCLE(193.98,-5.82,15)

DSTYP3: TIME
DSUNI3: s
DSVAL3: TABLE
DSREF3: :GTI

GTIs: (suppressed)

DSTYP4: BIT_MASK(EVENT_TYPE,3,P8R3)
DSUNI4: DIMENSIONLESS
DSVAL4: 1:1

DSTYP4: ENERGY
DSUNI4: MeV
DSVAL4: 100:500000

DSTYP5: ZENITH_ANGLE
DSUNI5: deg
DSVAL5: 0:90

We will now make a counts map using gtbin

$ gtbin
Type of output file (CCUBE|CMAP|LC|PHA1|PHA2|HEALPIX) [PHA2] CMAP
Event data file name[] 3C279_binned_gti.fits
Output file name[] 3C279_binned_cmap.fits
Spacecraft data file name[] NONE
Size of the X axis in pixels[] 150
Size of the Y axis in pixels[] 150
Image scale (in degrees/pixel)[] 0.2
Coordinate system (CEL - celestial, GAL -galactic)[] CEL
First coordinate of image center in degrees (RA or galactic l)[] 193.98
Second coordinate of image center in degrees (DEC or galactic b)[] -5.82
Rotation angle of image axis, in degrees[] 0.0
Projection method Projection method e.g. AIT|ARC|CAR|GLS|MER|NCP|SIN|STG|TAN:[] AIT
gtbin: WARNING: No spacecraft file: EXPOSURE keyword will be set equal to ontime.

$ ds9 3C279_binned_cmap.fits

With this we can view the fits file in a GUI.

Using Python Library

(Work in progress.....)