Is there a upper limit for specific SFR?

[tjtakys]

Hello,

I am using Prospector to fit SEDs with a parametric SFH model, and I have noticed that the resulting specific SFR (sSFR) does not go beyond ~1e-8 yr⁻¹ in my fits (see the attached figure). I would like to confirm whether this is an expected behavior or a limitation in the model.

I am using the following model configuration:

model_params = {}
# common parameters
model_params["imf_type"] = {'N':1, 'isfree':False, 'init':1} # 0:Salpeter, 1:Chabrier, 2:Kroupa
model_params["logzsol"] = {'N':1, 'isfree':True, 'init':-0.5, 'units':'log (Z/Zsun)', 'prior':priors.TopHat(mini=-2, maxi=0.2)}
model_params["zred"] = {'N':1, 'isfree':False, 'init':5, 'units':'redshift'}

# Parametric SFH 
model_params["sfh"] = {'N':1, 'isfree':False, 'init': 4, 'units': 'FSPS index'}
model_params["tau"] = {'N':1, 'isfree':True, 'init':1, 'units':'Gyr^{-1}', 'prior':priors.LogUniform(mini=1e-1, maxi=30)} # 100Myr-
model_params["tage"] = {'N':1, 'isfree':True, 'init':1, 'units':'Gyr', 'prior':priors.LogUniform(mini=1e-2, maxi=cosmo.age(5).to('Gyr').value)} # 1Myr-
model_params["mass"] = {'N':1, 'isfree':True, 'init':1e10, 'units':'Solar masses formed', 'prior':priors.LogUniform(mini=1e5, maxi=1e12)}

model_params["dust_type"] = {'N':1, 'isfree':False, 'init':4, 'units':'FSPS index'} # Kriek & Conroy 2013
model_params["dust_tesc"] = {'N':1, 'isfree':False, 'init':7.0, 'units':'log(yr)'} # dust1を追加で受ける星の年齢
model_params["dust1"] = {'N':1, 'isfree':False, 'init':0.0}
model_params["dust2"] = {'N':1, 'isfree':True, 'init':0.2, 'units':'optical depth for all stars at 5500AA', 'prior':priors.TopHat(mini=0.0, maxi=4.0)}
model_params["dust_index"] = {'N':1, 'isfree':True, 'init':0.0, 'units':'power-law multiplication of Calzetti', 'prior':priors.TopHat(mini=-1.0, maxi=0.4)}

# nebular
model_params.update(TemplateLibrary["nebular"]) 
model_params["nebemlineinspec"] = {'N':1, 'isfree':False, 'init':False} 
model_params['eline_sigma'] = {'N': 1, 'isfree':True, 'init':100.0, 'units':'km/s', 'prior':priors.TopHat(mini=99, maxi=101)}
model_params["gas_logz"] = {'N':1, 'isfree':True, 'init':0.0, 'units':'log Z/Zsun', 'prior':priors.TopHat(mini=-2, maxi=0.5)}
model_params["gas_logu"] = {'N':1, 'isfree':True, 'init':-2.0, 'units':'Q_H/N_H', 'prior':priors.TopHat(mini=-4, maxi=-1)}

# smoothing (Instrumental)
model_params.update(TemplateLibrary["spectral_smoothing"])
model_params['fftsmooth'] = {'N': 1, 'isfree': False, 'init': True}
model_params['sigma_smooth'] = {'N':1, 'isfree':True, 'init':200, 'units':'km/s', 'prior':priors.TopHat(mini=50, maxi=200)} # sigma, NOT FWHM

model_params["linespec_scaling"] = {'N':1, 'isfree': False, 'init':1.0}
model = LineSpecModel(model_params)

And I use the following code to calculate the SFR:
sfr100 = plotting.sfh.parametric_sfr(times=0, tavg=0.1, sfh=4, tage=tage, tau=tau, mass=mass)

Thank you in advance!

[bd-j]

Hi @tjtakys This can be a limitation of some parametric forms. You can check by computing the ratio of the SFR to the integral of the SFR for a delay tau model, and plug in your prior ranges for tau and tage.

So, you can widen the priors, or choose a different form. Note for the binned sfhs you'll never get a sSFR higher than 1/(t1-t0) for the youngest bin.