FRB Galaxies¶

A significant portion of FRB science will flow from studying galaxies related to these events.

This will include both the galaxy that hosted the event and galaxies foreground to the event which may imprint signatues in the signal itself.

We have thus far generated a class FRBGalaxy to hold, manipulate, and derive key observed and physical quantities.

Once a large enough sample exists, there will be other objects to generate a easy-to-access database (e.g. Table) of galaxy properties.

FRBGalaxy¶

This is the parent class and is not intended to be instantiated on its own, at least not often. Instead, instantiate one of its children. Nevertheless, it contains the majority of methods and attributes used by the children, described here.

Attributes¶

The FRBGalaxy class contains a set of attributes, listed in self.main_attr, that are a series of dict and are intended to hold the primary quantities of the object. To set a common structure, the allowed keys within each dict are defined in the frb.galaxies.defs module. For example, the morphology attribute may contain the entries listed in defs.valid_morphology which is reproduced here:

valid_morphology = [
    'reff_ang',   # Effective radius in arcsec; Galfit
    'reff_kpc',   # Effective radius in kpc; Galfit
    'n',          # Sersic index; Galfit
    'PA',         # Position angle (deg); Galfit
    'b/a',        # Ellipticity; Galfit
]

The uncertainty in each of these values is also permitted, e.g. reff_ang_err and n_err.

Methods¶

There are a number of methods used to modify the class and also to calculate quantities of interest from existing photometry and line flux measurements.

set_z¶

This sets the redshift of the galaxy and/or the related FRB, e.g.:

frbgalaxy.set_z(0.192, 'spec')

Here spec indicates the measurement is spectroscopic.

parse_galfit¶

There are a series of methods that will parse output files from standard galaxy analysis codes, e.g. CIGALE, GALFIT, pPXF. Here is the sample call for GALFIT:

frbgalaxy.parse_galfit('frb121102_galfit.log', 0.15)

The first item is the filename and second is the plate-scale of the image analyzed (arcsec per pixel). The values measured are ingested into the frbgalaxy.morphology dict.

calc_nebular_SFR¶

There are a few methods for deriving quantities of scientific interest for the galaxy. The example provided here is for the star-formation rate (SFR) using a nebular line flux. Here is an example call:

frbgalaxy.calc_nebular_SFR(method='Ha')

If successful, the ‘SFR_nebular’ key of the frbgalaxy.derived dict will be filled with the value (using units of Msun/yr). By default, an extinction correction will be applied to the measurement if the ‘AV_nebular’ was filled previously. This method also requires that the redshift have been set previously.

I/O¶

One can write the main contents of the FRBGalaxy object to disk with the write_to_json() method:

frbgalaxy.write_to_json()

If not outfile name is given (as above), one is auto-generated based on the class and FRB.

Similarly, one can instantiate the class with a JSON file:

frbgalaxy.from_json('name_of_file.json')

FRBHost¶

This is a child of FRBGalaxy and is intended to be used for the galaxy which hosts a given FRB.

by_name¶

One particulaly useful method is by_name() which lets you Instantiate the class by the FRB name:

host121102 = frbgalaxy.FRBHost.by_name('121102')

Of course, a previously generated JSON file must already have been archived.

PATH¶

A subset of the FRB Host galaxies have been analyzed using the Probabilistic Assignment of Transients to their Hosts (PATH) framework as described in Aggarawal et al. 2021. This relies on the `astropath <>`_ code base.

You can load up the PATH results using:

from frb.galaxies import utils
path_table = utils.load_PATH()

The standard file uses the adopted priors with results as given in the adopted.csv file under frb/data/Galaxies/PATH. See the README there for further details.

Developers can use frb_build to generate new PATH csv files.

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