GFM_StellarPhotometrics and model A in Nelson+ (2018a)

Furen Deng

5 Aug '21

Is GFM_StellarPhotometrics in stars/wind calculated in exact the same way as model A in Nelson+ (2018a)? I have tried the four SDSS filters, but I cannot reproduce GFM_StellarPhotometrics within 0.1 mag using python wrapper of FSPS. It seems like that there are lots of star particles with metallicity out of metallicity range of Padova isochrone, how do you extrapolate the table?

Dylan Nelson

5 Aug '21

The Model A of Nelson+18 is made with FSPS, as described in that paper.

The GFM_StellarPhotometrics in the snapshot are from a different, older method, based on BC03. The following code snippet will produce the interpolation table used to make GFM_StellarPhotometrics, so if you do a simple interpolation using it you should be able to reproduce those snapshot values.

def makeStellarPhotometricsHDF5_BC03():
""" Create stellar_photometrics.hdf5 file using BC03 models, as used for Illustris and IllustrisTNG runs.
Bands: UBVK (Buser U,B3,V,IR K filter + Palomar200 IR detectors + atmosphere.57) in Vega, griz (sdss) in AB
Requires: http://www.bruzual.org/bc03/Original_version_2003/bc03.models.padova_1994_chabrier_imf.tar.gz
Produces: 87f665fe5cdac109b229973a2b48f848 stellar_photometrics.hdf5
Original: f4bcd628b35036f346b4e47f4997d55e stellar_photometrics.hdf5
(all datasets between the two satisfy np.allclose(rtol=1e-8,atol=8e-4))
"""
import numpy as np
import h5py
import glob
filenames1 = sorted(glob.glob("bc2003_hr_m*_chab_ssp.1color")) # m22-m72
filenames2 = sorted(glob.glob("bc2003_hr_m*_chab_ssp.1ABmag")) # m22-m72
# linear metallicities (mass_metals/mass_total), not in solar!
Zvals = [0.0001, 0.0004, 0.004, 0.008, 0.02, 0.05]
bandNames = ['U','B','V','K','g','r','i','z']
nAgeVals = 220
assert len(Zvals) == len(filenames1) == len(filenames2)
# allocate
ages = np.zeros(nAgeVals)
mags = {}
for bandName in bandNames:
mags[bandName] = np.zeros( [len(Zvals),nAgeVals] )
# load BC03 model files
for i in range(len(Zvals)):
data1 = np.loadtxt(filenames1[i])
data2 = np.loadtxt(filenames2[i])
# verify expected number of rows/ages, and that we process the correct metallicity files
assert data1.shape[0] == data2.shape[0] == nAgeVals
with open(filenames1[i], 'r') as f:
assert "Z=%g" % Zvals[i] in f.read()
with open(filenames2[i], 'r') as f:
assert "Z=%g" % Zvals[i] in f.read()
ages = data1[:,0] - 9.0 # log yr -> log Gyr, same in all files
mags['U'][i,:] = data1[:,2]
mags['B'][i,:] = data1[:,3]
mags['V'][i,:] = data1[:,4]
mags['K'][i,:] = data1[:,5]
mags['g'][i,:] = data2[:,2]
mags['r'][i,:] = data2[:,2] - data2[:,4]
mags['i'][i,:] = data2[:,2] - data2[:,5]
mags['z'][i,:] = data2[:,2] - data2[:,6]
# write output
with h5py.File('stellar_photometrics.hdf5', 'w') as f:
f["N_LogMetallicity"] = np.array([len(Zvals)], dtype='int32')
f["N_LogAgeInGyr"] = np.array([nAgeVals], dtype='int32')
f["LogMetallicity_bins"] = np.log10(np.array(Zvals, dtype='float64'))
f["LogAgeInGyr_bins"] = ages
for bandName in bandNames:
f["Magnitude_"+bandName] = mags[bandName]

Is GFM_StellarPhotometrics in stars/wind calculated in exact the same way as model A in Nelson+ (2018a)? I have tried the four SDSS filters, but I cannot reproduce GFM_StellarPhotometrics within 0.1 mag using python wrapper of FSPS. It seems like that there are lots of star particles with metallicity out of metallicity range of Padova isochrone, how do you extrapolate the table?

The Model A of Nelson+18 is made with FSPS, as described in that paper.

The

`GFM_StellarPhotometrics`

in the snapshot are from a different, older method, based on BC03. The following code snippet will produce the interpolation table used to make`GFM_StellarPhotometrics`

, so if you do a simple interpolation using it you should be able to reproduce those snapshot values.Thank you!