Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties

Using mock spectra based on Vazdekis/MILES library fitted within the wavelength region 3600-7350\AA, we analyze the bias and scatter on the resulting physical parameters induced by the choice of fitting algorithms and observational uncertainties, but avoid effects of those model uncertainties. We co...

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Principais autores: Ge, J, Yan, R, Cappellari, M, Mao, S, Li, H, Lu, Y
Formato: Journal article
Publicado em: Oxford University Press 2018
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author Ge, J
Yan, R
Cappellari, M
Mao, S
Li, H
Lu, Y
author_facet Ge, J
Yan, R
Cappellari, M
Mao, S
Li, H
Lu, Y
author_sort Ge, J
collection OXFORD
description Using mock spectra based on Vazdekis/MILES library fitted within the wavelength region 3600-7350\AA, we analyze the bias and scatter on the resulting physical parameters induced by the choice of fitting algorithms and observational uncertainties, but avoid effects of those model uncertainties. We consider two full-spectrum fitting codes: pPXF and STARLIGHT, in fitting for stellar population age, metallicity, mass-to-light ratio, and dust extinction. With pPXF we find that both the bias in the population parameters and the scatter in the recovered logarithmic values follows the expected trend. The bias increases for younger ages and systematically makes recovered ages older, M∗/Lr larger and metallicities lower than the true values. For reference, at S/N=30, and for the worst case (t=108yr), the bias is 0.06 dex in M∗/Lr, 0.03 dex in both age and [M/H]. There is no significant dependence on either E(B-V) or the shape of the error spectrum. Moreover, the results are consistent for both our 1-SSP and 2-SSP tests. With the STARLIGHT algorithm, we find trends similar to pPXF, when the input E(B-V)<0.2 mag. However, with larger input E(B-V), the biases of the output parameter do not converge to zero even at the highest S/N and are strongly affected by the shape of the error spectra. This effect is particularly dramatic for youngest age, for which all population parameters can be strongly different from the input values, with significantly underestimated dust extinction and [M/H], and larger ages and M∗/Lr. Results degrade when moving from our 1-SSP to the 2-SSP tests. The STARLIGHT convergence to the true values can be improved by increasing Markov Chains and annealing loops to the "slow mode". For the same input spectrum, pPXF is about two order of magnitudes faster than STARLIGHT's "default mode" and about three order of magnitude faster than STARLIGHT's "slow mode".
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spelling oxford-uuid:da00515c-828e-400d-985b-b9cb7a18a48c2022-03-27T09:00:09ZRecovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertaintiesJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:da00515c-828e-400d-985b-b9cb7a18a48cSymplectic Elements at OxfordOxford University Press2018Ge, JYan, RCappellari, MMao, SLi, HLu, YUsing mock spectra based on Vazdekis/MILES library fitted within the wavelength region 3600-7350\AA, we analyze the bias and scatter on the resulting physical parameters induced by the choice of fitting algorithms and observational uncertainties, but avoid effects of those model uncertainties. We consider two full-spectrum fitting codes: pPXF and STARLIGHT, in fitting for stellar population age, metallicity, mass-to-light ratio, and dust extinction. With pPXF we find that both the bias in the population parameters and the scatter in the recovered logarithmic values follows the expected trend. The bias increases for younger ages and systematically makes recovered ages older, M∗/Lr larger and metallicities lower than the true values. For reference, at S/N=30, and for the worst case (t=108yr), the bias is 0.06 dex in M∗/Lr, 0.03 dex in both age and [M/H]. There is no significant dependence on either E(B-V) or the shape of the error spectrum. Moreover, the results are consistent for both our 1-SSP and 2-SSP tests. With the STARLIGHT algorithm, we find trends similar to pPXF, when the input E(B-V)<0.2 mag. However, with larger input E(B-V), the biases of the output parameter do not converge to zero even at the highest S/N and are strongly affected by the shape of the error spectra. This effect is particularly dramatic for youngest age, for which all population parameters can be strongly different from the input values, with significantly underestimated dust extinction and [M/H], and larger ages and M∗/Lr. Results degrade when moving from our 1-SSP to the 2-SSP tests. The STARLIGHT convergence to the true values can be improved by increasing Markov Chains and annealing loops to the "slow mode". For the same input spectrum, pPXF is about two order of magnitudes faster than STARLIGHT's "default mode" and about three order of magnitude faster than STARLIGHT's "slow mode".
spellingShingle Ge, J
Yan, R
Cappellari, M
Mao, S
Li, H
Lu, Y
Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties
title Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties
title_full Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties
title_fullStr Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties
title_full_unstemmed Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties
title_short Recovering stellar population parameters via two full-spectrum fitting algorithms in the absence of model uncertainties
title_sort recovering stellar population parameters via two full spectrum fitting algorithms in the absence of model uncertainties
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AT yanr recoveringstellarpopulationparametersviatwofullspectrumfittingalgorithmsintheabsenceofmodeluncertainties
AT cappellarim recoveringstellarpopulationparametersviatwofullspectrumfittingalgorithmsintheabsenceofmodeluncertainties
AT maos recoveringstellarpopulationparametersviatwofullspectrumfittingalgorithmsintheabsenceofmodeluncertainties
AT lih recoveringstellarpopulationparametersviatwofullspectrumfittingalgorithmsintheabsenceofmodeluncertainties
AT luy recoveringstellarpopulationparametersviatwofullspectrumfittingalgorithmsintheabsenceofmodeluncertainties