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lc_generation [2022/02/10 16:09]
theoastro 		lc_generation [2023/06/02 17:05] (current)
theoastro
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 Note that the parameters vary from model to model - an overview can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/blob/c9f55663f27625ca7c3aa1b8d74dcb231ca060e7/nmma/em/model.py#L16|here]]. Some models such as ''Bu2019lm'' require to embed a SVD grid for light curve computation which can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/tree/main/svdmodels|here]]. With these, a light curve object can be instantiated as follows: Note that the parameters vary from model to model - an overview can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/blob/c9f55663f27625ca7c3aa1b8d74dcb231ca060e7/nmma/em/model.py#L16|here]]. Some models such as ''Bu2019lm'' require to embed a SVD grid for light curve computation which can be found [[https://github.com/nuclear-multimessenger-astronomy/nmma/tree/main/svdmodels|here]]. With these, a light curve object can be instantiated as follows:
  
-  model_key = 'Bu2019lm' +  tmin=0.1 
-  t = np.arange(tmin=0.1, tmax=20.0 ,deltat=0.1) +  tmax=20.0 
-  lc_model = nmma.em.model.SVDLightCurveModel(model=model_key, sample_times = t, svd_path = "nmma/svdmodels/", parameter_conversion=None, mag_ncoeff=None,  lbol_ncoeff=None)+  deltat=0.1 
 +  t = np.arange(tmin, tmax, deltat) 
 +  lc_model = nmma.em.model.SVDLightCurveModel(model='Bu2019lm', sample_times = t, svd_path = "nmma/svdmodels/", parameter_conversion=None, mag_ncoeff=None,  lbol_ncoeff=None)
  
 By providing input values for a chosen model, a kilonova light curve in different photometric bands can be generated using: By providing input values for a chosen model, a kilonova light curve in different photometric bands can be generated using:
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     'inclination_EM': 0,     'inclination_EM': 0,
     'luminosity_distance': 40}     'luminosity_distance': 40}
-  lbol, mag= lc_model.generate_lightcurve(t, params)+  lbol, mag= lc_model.generate_lightcurve(t, params_range)
  
 Through the filter keys such as u,g,r,i,z,y,J,H,K, the light curves in different photometric bands can be obtained, e.g., using ''mag['u']''. An example plot of kilonova light curves in different photometric bands is shown below for AT2017gfo. Through the filter keys such as u,g,r,i,z,y,J,H,K, the light curves in different photometric bands can be obtained, e.g., using ''mag['u']''. An example plot of kilonova light curves in different photometric bands is shown below for AT2017gfo.
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 === Gamma-ray burst afterglows  === === Gamma-ray burst afterglows  ===
 In order to compute GRB afterglow light curves, NMMA uses the model ''TrPi2018'' from [[https://afterglowpy.readthedocs.io/en/latest/#|afterglowpy]]  and enables a GRB afterglow light curve generation on a fixed time grid.  In order to compute GRB afterglow light curves, NMMA uses the model ''TrPi2018'' from [[https://afterglowpy.readthedocs.io/en/latest/#|afterglowpy]]  and enables a GRB afterglow light curve generation on a fixed time grid. 
 +  import nmma.em.model
 +  t_day = np.arange(1., 950., 1.)
 +  grb_model = nmma.em.model.GRBLightCurveModel(t_day, resolution=12, jetType=0) 
 +  params_range = {
 +    'inclination_EM': 0,
 +    'log10_E0': 50.,
 +    'thetaCore': 0.05,
 +    'thetaWing': 0.01,
 +    'log10_n0':-4.5,
 +    'p':2.160,
 +    'log10_epsilon_e':-1.6, 
 +    'log10_epsilon_B':-2.,
 +    'luminosity_distance': 40,}
  
 +  lbol, mag = grb_model.generate_lightcurve(t_day, params_range)
  
 +GRB afterglow light curves can be accessed with the filter keys ''X-ray-5keV'' and ''X-ray-1keV'', e.g. ''mag_abs['X-ray-5keV']''.
 +
 +=== Shock-cooling supernovae  ===
 +NMMA uses a model from [[https://arxiv.org/pdf/2007.08543|Piro et al. 2021]]. Following a shock breakout, the radiation of shock heated material expands and cools, known as shock cooling emission. The emission in different spectral regimes can be computed as follows: 
 +
 +  t = np.arange(tmin=0.1, tmax=10., deltat=0.1)
 +  sn_model = nmma.em.model.ShockCoolingLightCurveModel(sample_times = t, parameter_conversion=None, model="Piro2021")
 +  params_range = {
 +    'log10_Menv': 30,
 +    'log10_Renv': 20,
 +    'log10_Ee': 49.,
 +    'luminosity_distance': 1.234e+24,}
 +  lbol, mag = sn_model.generate_lightcurve(t, params_range)
  
Last modified: le 2022/02/10 16:09

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