Fermi/LAT

This service provides data analysis for Fermi Large Area Telescope (LAT) based on Fermi Science Tools provide by Fermi Science Support Center. The data analysis can be launched either using the MMODA fronend interface or through a Python API from e.g. a Jupyter notebook on a user laptop.

The main parameter panel generic for all analysis services allows to select the source of interest, based on its name or coordinates:

The start and end time limits also need to be specified in the main parameter panel.

Upon each data analysis request, Fermi/LAT photon lists and spacecraft file are downloaded using the astroquery.fermi service. The photons are selected within a circular region of the radius, to be specified separately for each data product type in the Fermi/LAT instrument specific panel. The instrument specific parameter panel allow to select one of the three available data product types: Image, Spectrum or Lightcurve.

Selecting one of the available data product types reveals additional parameters specific to this data product. Here is an example for the Image:

The image parameter panel allows to specify the energy range (Emin, Emax parameters), the image size (Radius parameter) and pixel size (pixsize parameter).

The image data product is a photon count map, produced using gtselect gtkmtime and gtbin commands (see "Exploring LAT data" for details). Photons from the event class 2048 and event type 3 are selected (see Fermi LAT event classes for explanations of the event classification).

The product display panel that appears upon the completion of data analysis shows the image together with a set of buttons that provide a possibility for further manipulations of the data product:

The "Qeury parameters" button provides the metadata with the analysis parameters. The "API code" button displays the Python API code that can be copy-pasted into a python code (e.g. on the user laptop) to request the data product. The same API code can also be launched in an online Jupyter lab environment on a collaborative data science platform renkulab.io, using the "View on Renku" button.

The lightcurves and spectra are produced using the "aperture photometry" method. Within this approach, the source and background counts are estimated using a circle of the radius $R_s$ and a ring $R_s<R<R_b$. Both the source circle and the background estimate ring contain the source and background counts in different proportions. If the backgorund count rate per square degree is $B$, the background counts collected within an expoture time $T$ scale proportionally to the area of the circle or the ring: $Cts_{b1}=B(\pi R_s^2)(A_{eff}T)$, $Cts_{b2}=B(\pi (R_b^2-R_s^2))(A_{eff}T)$, where $A_{eff}$ is the effective area of the telescope. The source counts from a source with the flux $F$ in the same regions scale scale in according to the Point Spread Function (PSF) $P[R]$, which is the probability density function to find a photon at an angular distance $R$ from the source position on the sky: $Cts_{s1}=F\ P[R_s]\ (A_{eff}T)$, $Cts_{s2}=F\ (P[R_b] - P[R_s])\ (A_{eff}T)$. Overall, the total counts in the circle and the ring are

$$Cts_1=\left(F\ P[R_s]+B(\pi R_s^2)\right)(A_{eff}T)\\ Cts_2=\left(F\ (P[R_b]-P[R_s])+B(\pi (R_b^2-R_s^2))\right)(A_{eff}T)$$

This system of equations can be resolved for $F$ and $B$ if counts in the source circle $Cts_1$ and in the ring surrounding the circle, $Cts_2$, are known. The tools generating the Lightcurve and Spectrum data products extract $Cts_1, Cts_2$ using a chain of gtselect, gtmktime, gtbin tools and calculate the exposure $(A_{eff}T)$ using the gtexposure tool, with appcorr='no' parameter (no apperture correction applied). The energy-dependent PSF fractions $P[R_s]$, $P[R_b]$ are calculated using the appcorr='yes' parameter.

The $R_s$ and $R_b$ parameters can be specified as parameters Source_region_radius and Background_region_radius in the Lightcurve and Spectrum parameters panels:

Similar to the Image data product display panel, there are additional buttons allowing to visualise the product metadata, the API code for requesting the product from a Python notebook and a button for the product inspection on the renkulab.io platform