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lc_generation [2022/02/10 15:54]
theoastro |
lc_generation [2023/06/02 17:05] (current)
theoastro |
| 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 = 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: |
| '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. |
| {{:injections_lightcurves.png}} | {{:injections_lightcurves.png}} |
| |
| === Gamma-ray burst afterglows (GRBs) === | === 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. |
| | 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) |
| |
