Output Files

Fermipy ROI Snapshots

For each target, the pipeline will perform a baseline fit to the region of interest (ROI) and produce a snapshot in the standard fermipy ROI FITs file format These are producted by the AnalyzeROI link for data, and copied to directories used for simulations.

Fermipy SED Files

For each target, and for each spatial profile used to model the target the pipeline will produce a standard fermipy SED FITs file format These are producted by the AnalyzeSED link for data, or the SimulateROI link for simulations.

Dark Matter Likeihood ‘Castro’ Files

For each target, spatial profile and J-factor prior combination, the pipeline will produce DMCastroData fits file with the likelhoods as a function of DM interaction rate. These are produced by the ConvertCastro link for the individual targets, and by the StackLikelihood link for the stacked roster results.

Dark Matter Limits Files

For each target, spatial profile and J-factor prior combination, the pipeline will produce DMCastroData fits file with the upper limits on the DM interaction rate. These will also be produced for the stacked results from each roster and J-factor prior combination.

Expectation Band Files

For every target, simulation scenario and J-factor prior combination, the pipeline will also produce FITs files with summeries of the limits to capture the expected limits bands.

Bookkeeping and Generated Configuration Files

Several files needed for bookeeping are created by the PrepareTargets script.

• Target List Yaml Files

  These are dictionaries of all the targets and all the profiles to consider for each target. Here is an example from the simple test analysis:

  draco: [ack2016_point]
  segue_1: [ack2016_point]
  

• Roster List Yaml Files

  These are dictionaries of all the targets and target version that define each roster. Here is an example from teh simple test analysis:

  test_point: [‘segue_1:ack2016_point’, ‘draco:ack2016_point’]

• ROI configuration Yaml Files

This is simply the fermipy configuration file to be used for the baseline analysis and SED fitting in each ROI. Details of the syntax and options are here <https://fermipy.readthedocs.io/en/latest/config.html> _ These are copied from the template version to each of the analysis directories and updated to include the target name and direction.

• Spatial Profile Yaml Files

These file define the various spatial profiles used to fit each target. The syntax is basically what fermipy needs to create a new source.

name: ack2016_point
source_model: {DEC: 57.91528, RA: 260.05167, SpatialModel: PointSource, SpectrumType: PowerLaw}

• J-value Yaml Files

These file define the values of the J-factor for different profiles. They are needed to convert the analysis results to DM annihilation rate. Here is an example:

{j_integ: 2.188e+18, j_sigma: 0.6, type: NFW}

• Simulation Input Yaml Files

These file define the various spatial profiles used to fit each target. The syntax inside the ‘injected_source’ tag is exactly what fermipy needs to create a new source.

injected_source:
  name: dm
  source_model:
    SpatialModel: PointSource
    SpectrumType: DMFitFunction
    channel0: {value: 4}
    mass: {value: 100.0}
    norm: {value: 2.188e+18}
    sigmav: {value: 3.0e-26}

• Simulated Source Spectrum Yaml Files

  These files are created by the SimulateROI task, and contain some information about the simulated sources.

• Source Correlation Yaml Files

  These file are created by the AnalyzeSED (for data) or SimulateROI (for simulations) tasks, and contain the correlation factors between the target source and any other source in the ROI above the threshold for special treatment (typically 0.25).