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 “ -p” to produce the physics model grid file “project_name_seds.grid.hd5”.
  2. Run “ -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.


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

pick_models_per_background: Uses a background map generated by the user to put a set of model SEDs at locations with similar background intensity. This way, it is ensured that different regimes of background emission are evenly sampled. The set of models generated by pick_models is reused for each background intensity bin. This function is not yet used in the standard examples.


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

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_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_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.


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.