Artificial Star Input Lists

The BEAST requires artificial star tests (ASTs) to produce a noise model. The AST input list software generates lists of magnitudes and (if desired) positions for ASTs that can be injected into the observed imaging and then re-photometered to assess the photometric bias, uncertainty, and completeness as a function of the model grid. The output from this software must be run through the same photometry routine (typically DOLPHOT) as used for the photometry measurements themselves.

Once the input lists have been run through the user’s photometry program and each input magnitude has an associated output magnitude (or non-detection value), those results can be used as input ASTs for the building the BEAST noise model.

Generating BEAST-friendly lists of artificial star tests

  1. Run run_beast.py -p to produce the physics model grid file project_name_seds.grid.hd5.
  2. If you wish to repeat ASTs over multiple bins of stellar density or background brightness, run tools/create_background_density_map.py on your observed star catalog. See the help message for this script for the necessary arguments.
  3. Run run_beast.py -a. This will use the datamodel to find everything it needs to make ASTs (filters, limits, SED grid, etc.). It will produce a list of fake stars in all bands using the datamodel photometry catalog to trim the inputs at the proper magnitudes. Currently, this script generates fake stars uniformly sampling log(age) space and randomly drawing from the metallicities in the model grid. Alternatively, the user can modify the script to use any combination of one of the SED picking, plus one of the position picking functions described below.

Functions

Picking SEDs

These functions are found in beast.observationmodel.ast.make_ast_input_list.

mag_limits: Determines the magnitude limits for the models in each filter in the photometry file.

pick_models: Samples the model grid and outputs models that fit within the mag limits.

pick_models_toothpick_style: Tries to pick models in a way that evenly samples the range of fluxes in each band. Models will be picked until each magnitude bin for each band is covered by a given number of fake stars. (Not yet in example.)

Picking positions

These functions are found in beast.observationmodel.ast.make_ast_xy_list

pick_positions: Uses the observed stellar catalog to distribution the artificial stars in a similar spatial pattern to the observed catalog

pick_positions_from_map: Uses one of the maps generated by create_background_density_map to make sure that each of the different source density or background regimes in the image are properly sampled. The source density or background range is divided into bins, and the set of SEDs chosen by one of the pick_models functions above is then reused for each background intensity bin.

Parameters

ast_bands_above_maglimit : integer Number of filters that must be above the magnitude limit for an AST to be included in the list (Default = 3)

ast_realization_per_model : integer Number of Realizations of each included AST model to be put into the list. (Default = 20)

ast_maglimit : float (single value or array with one value per filter)

  1. option 1: [number] to change the number of mags fainter than the 90th percentile faintest star in the photometry catalog to be used for the mag cut. (Default = 1)
  2. option 2: [space-separated list of numbers] to set custom faint end limits (one value for each band).

ast_models_selected_per_age : integer Number of models to pick per age (if pick_models is used) (Default = 70).

ast_with_positions : (bool, optional) If True, the ast list is produced with X,Y positions. If False, the ast list is produced with only magnitudes.

ast_density_table : (string, optional) Name of the density table created by tools.create_background_density_map If supplied, pick_positions_from_map will be used to repeat the ASTs in the table for each source density or background density region. The source density and background maps are in the same format.

ast_N_bins : (int, optional) Number of source density or background bins that you want ASTs repeated over

Note that ast_density_table require ast_reference_image to be specified (see below).

ast_pixel_distribution : float (optional) (Used if ast_with_positions is True), minimum pixel separation between AST position and catalog star used to determine the AST spatial distribution.

ast_reference_image : string (optional, but required if ast_with_positions is True and no X and Y information is present in the photometry catalog) Name of the reference image used by DOLPHOT when running the measured photometry.

Returns

Table of fake star magnitudes for all bands in the datamodel photometry file. The file will be in ascii format in the project directory, and it will have the name: [project]/[project]_inputAST.txt

The table will have <number of ages> * ast_models_selected_per_age * ast_realization_per_model lines. If ast_with_positions is True then each line will start with 0 1 X Y, which are the first four columns required by DOLPHOT to define the input star position.

In case the new method is used, which samples by background density, this number will be multiplied by the number of background density bins chosen.

The code will also optionally output a fits file, [project]/[project]_ASTparams.fits, which has the physical parameters associated with each of the artificial stars. It has <number of ages> * ast_models_selected_per_age lines, and has the same columns as the main SED grid file.