FIT3D, a tool for fitting stellar populations and emission lines in optical spectroscopy.


Index

* Basic description

FIT3D is a package for fitting optical spectra to deblend the underlying stellar population and the ionized gas, and extract physical information from each component. FIT3D is a tool developed focused on the analysis of Integral Field Spectroscopy data (but not restricted to it) and it is the basis of Pipe3D, a pipeline already used in the analysis of datasets like CALIFA, MaNGA, and SAMI. It can run iteratively or in an automatic way to derive the parameters of a large set of spectra.

FIT3D is distributed freely including its complete source code, the the only condition of give the proper credits to its developers, citing it properly and quoting the following article in any publication that uses it:

Pipe3D, a pipeline to analyze Integral Field Spectroscopy data: I. New fitting phylosophy of FIT3D, Sanchez et al., 2015, RevMexA&A, in press.



* Download, Requirements and Installation

The last stable version of FIT3D is version 2.0 (29/09/2015). It can be download from here:
* How to use it?

Most of the functionalities and descriptions of how to work with FIT3D included in the README_FIT3D.txt file for version 1.0 are valid for version 2.0, since we tried to follow the same scheme for input and output of files. However, the internal algorithms have changes sustantially. For a detailed description of these new algorithms we refer the user to the following articles and publications:

All the Perl and Python algorithms share the same inputs and output formats, and the same name (appart from the subfix .pl instead of .py).

* List of algorithms included in FIT3D:

  • 1) Algorithms for fitting the stellar population assuming a constant velocity dispersion in Amstrong, constant along the spectral range, that it is fitted by the algorithm. These algorithms are similar in this sense to version 1.0, and are useful for spectra dominated by the instrumental resolution or at short wavelength ranges:
    auto_ssp_elines_rnd.pl
    auto_ssp_elines_rnd_rss.pl
    auto_ssp_elines_rnd_cube.pl
    
    or
    auto_ssp_elines_rnd.py
    auto_ssp_elines_rnd_rss.py
    auto_ssp_elines_rnd_cube.py
    
    The inputs are similar to the corresponding ones in version 1.0, although the outputs have a slightly different format.
    Examples of its use:
    auto_ssp_elines_rnd.pl  NGC5947.spec_5.txt miles_2.fits auto_ssp.NGC5947.cen.only.out \\
    mask_elines.txt auto_ssp_V500_several_Hb.config 1 -1 40 3850 6800 emission_lines.txt \\
     0.02 0.0001 0.005 0.03  2.5 0.25 1.2 9.0 0.5 0.1 0.0 1.6
    
    or
    auto_ssp_elines_rnd.py NGC5947.spec_5.txt ssp_lib.fits,ssp_lib.3.fits auto_ssp.NGC5947.cen.only.out\\
    mask_elines.txt auto_ssp_V500_several_Hb.config 1 -1 40 3850 6800 emission_lines.txt 0.02 0.001 \\
    0.015 0.025 2 0.5 1 9 0.5 0.1 0.0 1.6
    
  • 2) Algorithms for fitting the stellar population assuming a constant velocity dispersion in Amstrong, that it is fixed, in addition to a velocity dispersion in km/s that it is fitted by the algorithm. These algorithms have the same inputs and output than the previous one. The main difference is that they require the instrumental velocity dispersion in AA as an extra input, and the guess, step and range of velocity dispersions are now in km/s:
    auto_ssp_elines_rnd_sigma_inst.pl
    auto_ssp_elines_rnd_rss_sigma_inst.pl
    auto_ssp_elines_rnd_cube_sigma_inst.pl
    
    It is important to take into account that most SSP-templates have already an intrinsic resolution that should be subtracted to the one included as a parameter in these algorithms.
    Example of its use
    auto_ssp_elines_rnd_sigma_inst.pl NGC5947.spec_5.txt ssp_lib.fits,ssp_lib.3.fits,2.4 \\
    auto_ssp.NGC5947.cen.only.out mask_elines.txt auto_ssp_V500_several_Hb.config 1 -1 40 3850 6800 \\
    emission_lines.txt 0.02 0.001 0.015 0.025 10 10 5 400 0.5 0.1 0.0 1.6
    # TIME 30 39 17 28 8 115 1 270 1
    FIT_RED 1 0.001 22
    SIGMA_E = 0.208668634350491
    CUT = 12.8368625938892 0.00
    0.02,10
    REDSHIFT = 0.0198078150202248 +- 6.50263187872471e-08
    D_SIGMA = 10
    SIGMA = 118.233215401682+-7.03193614601974 86.6888529801223
    D_Av = 0.1
    AV = 0.0 +- 0.1
    Signal-to-Noise = 46.5296282650667
    Deriving SFH....
    CONF=Ha_SII_V500.config
    ----------------------------------------
    6 1.93595010783665
    eline 6562.68 0 125.53191274498 7.77648133656951 4.18372299245214 0.421670929803096 5930.4911034592 1.59191026528982 0 0 0 0 0 0 0 0 0 0 
    eline 6583.41 0 58.426777235727 5.16942234343316 4.18372299245214 0.421670929803096 5930.4911034592 1.59191026528982 0 0 0 0 0 0 0 0 0 0 
    eline 6548.08 0 19.4561168194971 3.98610007918904 4.18372299245214 0.421670929803096 5930.4911034592 1.59191026528982 0 0 0 0 0 0 0 0 0 0 
    eline 6730.74 0 18.9723258598184 4.10873881369962 4.18372299245214 0.421670929803096 5930.4911034592 1.59191026528982 0 0 0 0 0 0 0 0 0 0 
    eline 6716.39 0 21.0187746354738 4.03119227242443 4.18372299245214 0.421670929803096 5930.4911034592 1.59191026528982 0 0 0 0 0 0 0 0 0 0 
    poly1d -0.337361429983028 0.0328628861270606 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
    OUT_FILE = elines_auto_ssp.NGC5947.cen.only.out
    DONE FIT ELINES CONFIG 0
    CONF=OIII_only_V500.config
    ----------------------------------------
    3 2.7232339732112
    eline 5006.84 0 16.8964278478661 4.70714405385853 3.45035289537316 0.460843174739232 5890.71314664585 12.4657492326643 0 0 0 0 0 0 0 0 0 0 
    eline 4958.91 0 5.62651047333941 4.67393442703892 3.45035289537316 0.460843174739232 5890.71314664585 12.4657492326643 0 0 0 0 0 0 0 0 0 0 
    poly1d 0.213770265960871 0.0134287731675713 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
    OUT_FILE = elines_auto_ssp.NGC5947.cen.only.out
    DONE FIT ELINES CONFIG 1
    CONF=Hb_V500.config
    ----------------------------------------
    2 0.911212364681216
    eline 4861.32 0 39.2525747337526 3.45311114962433 4.61073641198046 0.515866409360188 5938.27803365537 10.129764879085 0 0 0 0 0 0 0 0 0 0 
    poly1d 0.0278218502453836 0.0223193157987596 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
    OUT_FILE = elines_auto_ssp.NGC5947.cen.only.out
    DONE FIT ELINES CONFIG 2
    CONF=Hg_V500.config
    ----------------------------------------
    2 1.04700606364783
    eline 4340.47 0 21.6643913253098 2.91227767082192 4.75878473267294 0.372131495521538 5895.54809290569 9.73893307403003 0 0 0 0 0 0 0 0 0 0 
    poly1d -0.031497691168201 0.0205312544990526 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
    OUT_FILE = elines_auto_ssp.NGC5947.cen.only.out
    DONE FIT ELINES CONFIG 3
    CONF=Hd_V500.config
    ----------------------------------------
    2 1.05777750504804
    eline 4101.74 0 21.9562167817658 3.48004109486228 4.71074971836506 0.305042217906204 5869.23781114215 5.80858552836387 0 0 0 0 0 0 0 0 0 0 
    poly1d -0.20198213830732 0.0216605972910519 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
    OUT_FILE = elines_auto_ssp.NGC5947.cen.only.out
    DONE FIT ELINES CONFIG 4
    CONF=OII_V500.config
    ----------------------------------------
    2 1.2424408623337
    eline 3727.4 0 20.6615486966124 3.25284452987767 3.42369606056702 0.301484877378336 5975.85373431992 15.3105228301958 0 0 0 0 0 0 0 0 0 0 
    poly1d 0.126080459347215 0.019954551778583 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
    OUT_FILE = elines_auto_ssp.NGC5947.cen.only.out
    DONE FIT ELINES CONFIG 5
    ------------------------------------------------------------------------------
    ID   AGE     MET    COEFF   Min.Coeff  log(M/L)   AV   N.Coeff   Err.Coeff
    ------------------------------------------------------------------------------
    0   0.0010  0.0080  0.0084  0.0083     2.6084    0.00   0.0084  0.0007  0.0081  0.0007 
    17  0.0060  0.0500  0.0085  0.0083     2.2890    0.00   0.0085  0.0010  0.0079  0.0010 
    20  0.0070  0.0500  0.0001  0.0001     2.4359    0.00   0.0001  0.0000  0.0001  0.0000 
    22  0.0080  0.0200  0.0036  0.0034     2.3642    0.00   0.0036  0.0007  0.0030  0.0007 
    28  0.0100  0.0200  0.0468  0.0473     2.5158    0.00   0.0468  0.0019  0.0482  0.0018 
    49  0.0800  0.0200  0.0000  0.0000     3.1632    0.00   0.0000  0.0000  0.0000  0.0000 
    60  0.3000  0.0080  0.0034  0.0033     3.4097    0.00   0.0034  0.0004  0.0031  0.0004 
    65  0.4000  0.0500  0.0084  0.0081     3.6525    0.00   0.0084  0.0012  0.0076  0.0012 
    70  0.6000  0.0200  0.0051  0.0049     3.6983    0.00   0.0051  0.0010  0.0043  0.0010 
    77  0.8000  0.0500  0.0176  0.0171     3.8928    0.00   0.0176  0.0025  0.0159  0.0025 
    82  10.0000 0.0200  0.0549  0.0521     4.7823    0.00   0.0549  0.0108  0.0462  0.0103 
    83  10.0000 0.0500  0.4292  0.4340     4.9401    0.00   0.4292  0.0159  0.4444  0.0150 
    84  12.5000 0.0080  0.0248  0.0244     4.7457    0.00   0.0248  0.0025  0.0236  0.0025 
    87  1.0000  0.0080  0.1015  0.1025     3.7970    0.00   0.1015  0.0040  0.1048  0.0038 
    93  3.0000  0.0080  0.0827  0.0829     4.2412    0.00   0.0827  0.0046  0.0835  0.0045 
    101  5.0000  0.0500  0.2052  0.2033     4.6780    0.00   0.2052  0.0178  0.1992  0.0177 
    ------------------------------------------------------------------------------
    I.Iter = 0 DONE
    --------------------------------------------------------------
    MSP CHISQ=0.796062040654125 AGE=3.47299923302586+-0.0494449926427294 
    MET=0.0301584129016329+-0.00129796283120835 AV=1.00000000000001e-12+-3.35731718423674e-13 
    REDSHIFT=0.0198078150202248+-6.50263187872471e-08 
    SIGMA_DISP_km_h=118.233215401682+-7.03193614601974 RMS=0.192702651612686 
    MED_FLUX=13.3951765492999 AGE_mass=8.2
    
  • 3) Algorithms to fit emission lines using a set of Gaussian functions. They have the same input and output files than the ones in version 1.0 of FIT3D (README_FIT3D.txt). However, they provide with more reliable errors for the derived parameters:
    fit_elines_rnd.pl
    kin_rss_elines_rnd.pl
    kin_cube_elines_rnd.pl
    
    Example of its use
    fit_elines_rnd.pl NGC5947.spec_5.txt Ha_V500.config none 6600 6800 0 120 5 1 0.15
    
    
    
    # TIME 58 33 17 28 8 115 1 270 1
    0 regions to mask
    4 models to fit
    10 free parameters
    ----------------------------------------
    4 71.5372696618876
    eline 6562.68 0 116.037682218271 14.827342175482 4.47712519559501 0.0698574094536745 5925.45252659664 4.77071045229235 0 0 0 0 0 0 0 0 0 0 
    eline 6583.41 0 69.5013658969098 14.8013933449347 4.47712519559501 0.0698574094536745 5925.45252659664 4.77071045229235 0 0 0 0 0 0 0 0 0 0 
    eline 6548.08 0 23.143954843671 14.7932344853836 4.47712519559501 0.0698574094536745 5925.45252659664 4.77071045229235 0 0 0 0 0 0 0 0 0 0 
    poly1d 13.3081620516717 0.00920191932726841 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 
    OUT_FILE = out.fit_spectra
    OUT_CONFIG = out_config.fit_spectra
    # TIME 5 34 17 28 8 115 1 270 1
    # SECONDS = 7
    

Publications Dozens of publications and several PhDs have used FIT3D in different versions. We list here just a few of those articles:

  • 2011, MNRAS, 415, 2439 "PPAK wide-field Integral Field Spectroscopy of NGC 628 - II. Emission line abundance analysis", Rosales-Ortega et al., 2011, MNRAS, 415, 2439
  • 2011, MNRAS, 410, 3135 "PPAK Wide-field Integral Field Spectroscopy of NGC 628 - I. The largest spectroscopic mosaic on a single galaxy", Sanchez et al., 2011, MNRAS, 410, 3135
  • 2012A&A...546A...2S "Integral field spectroscopy of a sample of nearby galaxies: II. Properties of the H ii regions", S.F.Sanchez et al., 2012, A&A, 546,2
  • 2012ApJ...756L..31R "A new scaling relation for HII regions in spiral galaxies: unveiling the true nature of the mass-metallicity relation", F.F. Rosales-Ortega et al., 2012,ApJL,756,31
  • 2012A&A...538A.144V "Spatially resolved properties of the grand-design spiral galaxy UGC 9837: a case for high-redshift 2D observations", K. Viironen et al., A&A, 2012, 538, 144
  • 2014, A&A, accepted (2014arXiv1405.5222B)A characteristic oxygen abundance gradient in galaxy disks unveiled with CALIFASanchez S.F., et al., A&A, 2013, accepted
  • 2013, A&A, accepted (2013arXiv1307.5316M) The O3N2 and N2 abundance indicators revisited: improved calibrations based on CALIFA and Te-based literature data , Marino et al., A&A, 2013, accepted.
  • 2014, A&A, 574, 47 Imprints of galaxy evolution on H ii regions Memory of the past uncovered by the CALIFA survey regionsSanchez et al., A&A, 2014, 574, 47
  • 2015, A&A, accepted Testing the Modern Merger Hypothesis via the Assembly of Massive Blue Elliptical Galaxies in the Local Universe, Haines et al, MNRAS, 2015, Accepted
  • 2015, A&A, accepted Central star formation and metallicity in CALIFA interacting galaxies, Barrera-Ballesteros, J.K., et al., A&A, 2015, Accepted
  • 2015, MNRAS, 451, 4397 The incidence of bar-like kinematic flows in CALIFA galaxies, Holmes, L., et al., 2015, MNRAS, 451, 4397
  • 2015, A&A, Accepted Outer-disk reddening and gas-phase metallicities: The CALIFA connection, Marino et al., 2015, A&A, accepted

S.F.Sanchez et al., 29/09/2015