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MilkyWay-FRBs

There are two codes:

galactic_frbs.py -- which creates a database of FRB sources in X,Y,Z around the Milky Way, with DMs from an ISM model, and a width based on the Bhat curve (relates DM to pulse width / scattering)

analyze_frbs.py -- which plots the results of such a database.

To run:

python galactic_frbs.py ymw16 0.05 1.4 frbsample_ymw16_0.05_1.4.csv

This uses YMW16 as the ISM mode, a scaleheight of 0.05 kpc in Z, a survey frequency of 1.4 GHz (for the Bhat law), and writes the results to the CSV file.

Example output:

#x,y,z,dist,DM,width 3.5220033845868617,1.0918745087119022,0.04382651599596037,5.096524404861009,634.9056396484375,273.9694149697946 -5.745411513317328,8.956414266633045,-0.0342995714854575,16.827069922000856,2351.2783203125,5348.314650032203 -8.29202207043251,9.698977288811717,0.09359871688225069,19.392032549028478,2277.095458984375,277399.1958871533

X,Y,Z coordinates are in kpc, dist is the distance from the Sun (kpc), DM is in pc/cc (derived from ISM model) and the width is derived from the Bhat relation (ms)

Some widths can be very large -- no width larger than 100 ms has significance as it is essentially undetectible in any present or planned survey.

They are set up to produce around 350,000 sources. This can be controlled with Nfrbs -- this is the number simulated in order, after appropriate spatial selections are applied, that results in around 350,000 sources.

To analyse the FRBs:

python analyze_frbs.py frbsample_ymw16_0.05_1.4_.csv 1e25 -1.5

This reads in the sources in the CSV file, assigns a luminosity to each from a power law LF with E0=1E25 erg and powerlaw-slope -1.5.

All sources then have a S/N computed at Earth, and S/N>10 implies a detection.

It will produce a plot which is a comparison of the FRBs detectible in STARE2 and GReX, and plots of the various observational and other parameters of each FRB as seen by STARE2.

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