Provided by: neat_2.0-2build1_amd64 bug

NAME

       neat - nebular empirical analysis tool

SYNOPSIS

       neat [option1] [value1] ...

DESCRIPTION

       neat  carries  out  a  comprehensive empirical analysis on a list of nebular emission line
       fluxes. If uncertainties are required, it evaluates them using  a  Monte  Carlo  approach.
       neat's philosophy is that abundance determinations should be as objective as possible, and
       so user input should be minimised. A number of choices can be made by the  user,  but  the
       default options should yield meaningful results.

OPTIONS

       -i, --input [FILENAME]
              The  line  list  to  be  analysed.   Plain text files containing two, three or four
              columns of numbers can be understood by neat.  Full details of the input format are
              given in the "methodology" section below.

       -u, --uncertainties
              Calculate uncertainties, using 10,000 iterations.  If this option is specified, the
              -n option will be ignored

       -n, --n-iterations [VALUE]
              Number of iterations. Default: 1

       -e, --extinction-law [VALUE]
              Extinction law to use for dereddening.

              Valid values are:
               How: Galactic law of Howarth (1983, MNRAS, 203, 301)
               CCM: Galactic law of Cardelli, Clayton, Mathis (1989, ApJ, 345, 245)
               Fitz: Galactic law of Fitzpatrick & Massa (1990, ApJS, 72, 163)
               LMC: LMC law of Howarth (1983, MNRAS, 203, 301)
               SMC: SMC law of Prevot et al. (984, A&A, 132, 389)

              Default: How

       -c [VALUE]
              The logarithmic extinction at H beta.  By default,  this  is  calculated  from  the
              Balmer line ratios.

       -nelow, -nemed, -nehigh, -telow, -temed, -tehigh [VALUE]
              By  default,  electron densities and temperatures are calculated from the available
              diagnostics, but their values can be overridden with these commands.  The  required
              units are cm-3 for densities and K for temperatures.

       -he, --helium-data [VALUE]
              The atomic data to use for He I abundances

              Valid values are:
               S96: Smits, 1996, MNRAS, 278, 683
               P12: Porter et al., 2012, MNRAS, 425, 28

              Default: P12

       -icf, --ionisation-correction-scheme [VALUE]
              The ICF scheme to be used to correct for unseen ions

              Valid values are:
               KB94: Kingsburgh & Barlow (1994, MNRAS, 271, 257)
               PT92: Peimbert, Torres-Peimbert & Ruiz (1992, RMxAA, 24, 155)
               DI14: Delgado-Inglada, Morisset & Stasinska (2014, MNRAS, 440, 536)

              Default: DI14

       -v, --verbosity [VALUE]
              Amount  of  output  to  write  for each derived quantity. This option has no effect
              unless -n or -u is specified.

              Valid values are:
               1: write out summary files, binned results and complete results
               2: write out summary files and binned results
               3: write out summary files only

              Default: 3

       -id, --identify
              This option triggers an algorithm which attempts to  convert  observed  wavelengths
              into  rest  wavelengths.  If the option is not present, neat assumes that the input
              line list already has rest wavelengths in the first column

       -rp    When calculating Monte Carlo uncertainties, neat's default behaviour is  to  assume
              that  all  uncertainties are Gaussian.  If -rp is specified, it will compensate for
              the upward bias affecting weak lines described by Rola and Pelat  (1994),  assuming
              log normal probability distributions for weaker lines.

              Until  version  1.8, the default behaviour was the opposite; log normal probability
              distributions were assumed unless -norp was specified.  This was changed after  our
              discovery that the effect described by Rola and Pelat only occurred under extremely
              specific conditions: see Wesson et al. 2016 for details.

       -cf, --configuration-file [FILE]
              Since version 2.0, NEAT's analysis scheme is  specified  in  a  configuration  file
              which  is  read  in  at  run time, rather than being hard coded.  If this option is
              omitted the default configuration file is used, which is intended  to  be  suitable
              for  any line list and should only really need changing if particular lines need to
              be excluded from the analysis.  The configuration file contains a series of weights
              to  be  applied  when calculating diagnostics and abundances, and the format of the
              default file should be clear enough that editing it is straightforward.  A negative
              value  for a weight means that the line will be weighted by its observed intensity;
              a positive value means that the line will be weighted by the given value.

USING NEAT

   Input file format
       neat requires as input a plain text file containing a list of emission  line  fluxes.  The
       file  can  contain  two, three or four columns. If two columns are found, the code assumes
       they contain the the laboratory wavelength of the  line  (λ0)  and  its  flux  (F).  Three
       columns  are  assumed to be λ0, F, and the uncertainty on F (ΔF). Four columns are assumed
       to be the observed wavelength of the line, λobs, λ0,  F,  and  ΔF.  The  rest  wavelengths
       should  correspond exactly to those listed in the file /usr/share/neat/complete_line_list.
       The flux column can use any units, and the uncertainty on the flux should be given in  the
       same units. Examples can be found in the /usr/share/neat/example/ directory.

   Rest wavelengths
       neat  identifies lines by comparing the quoted wavelength to its list of rest wavelengths.
       However, rest wavelengths of lines can differ by  up  to  a  few  tenths  of  an  Angstrom
       depending  on  the  source.  Making  sure  that neat is identifying your lines properly is
       probably the most important step in using the code, and misidentifications are  the  first
       thing  to  suspect  if you get unexpected results. To assist with preparing the line list,
       the command line option -id can be used. This applies a very simple algorithm to the input
       line list to determine their rest wavelengths, which works as follows:

        1. A reference list of 10 rest wavelengths of common bright emission lines is compared to
       the wavelengths of the 20 brightest lines in the observed spectrum.
        2. Close matches are identified and the mean offset between observed and rest wavelengths
       is calculated.
        3.  The shift is applied, and then an RMS scatter between shifted and rest wavelengths is
       calculated.
        4. This RMS scatter is then used as a  tolerance  to  assign  line  IDs  based  on  close
       coincidences  between  shifted  observed  wavelengths  and  the  full  catalogue  of  rest
       wavelengths listed in utilities/complete_line_list

       The routine is not intended to provide 100% accuracy and  one  should  always  check  very
       carefully  whether  the  lines  are  properly identified, particularly in the case of high
       resolution spectra.

   Line blends
       In low resolution spectra, lines of comparable intensity may  be  blended  into  a  single
       feature. These can be indicated with an asterisk instead of a flux in the input line list.
       Currently, neat has only limited capabilities for dealing with  blends:  lines  marked  as
       blends  are not used in any abundance calculations, and apart from a few cases, it assumes
       that all other line fluxes represent unblended or deblended  intensities.  The  exceptions
       are  some  collisionally  excited  lines  which are frequently blended, such as the [O II]
       lines at 3727/3729Å. In these cases the blended flux can be given with the mean wavelength
       of  the  blend,  and the code will treat it properly. These instances are indicated in the
       utilities/complete_line_list file by a "b" after the ion name.

   Uncertainties
       The uncertainty column of the input file is of crucial importance if you want to  estimate
       uncertainties  on  the  results  you  derive.  Points  to  bear  in mind are that the more
       realistic your estimate of the line flux measurement uncertainties, the more realistic the
       estimate  of  the  uncertainties  on the results will be, and that in all cases, the final
       reported uncertainties are a lower limit to the actual uncertainty on the results, because
       they account only for the propagation of the statistical errors on the line fluxes and not
       on sources of systematic uncertainty.

       In some cases you may not need or wish to propagate uncertainties. In this  case  you  can
       run just one iteration of the code, and the uncertainty values are ignored if present.

RUNNING THE CODE

       Assuming  you  have  a line list prepared as above, you can now run the code. In line with
       our philosophy that neat should be as simple and objective as  possible,  this  should  be
       extremely  straightforward.  To  use  the  code in its simplest form on one of the example
       linelists, you would type

        % cp /usr/share/neat/example/ngc6543_3cols.dat .
        % neat -i ngc6543_3cols.dat

       This would run a single iteration of the code, not propagating uncertainties.  You'll  see
       some  logging output to the terminal, and the calculated results will have been written to
       the file ngc6543_3cols.dat_results. If this is all you need, then the job's done  and  you
       can write a paper now.

       Your  results  will  be  enhanced  greatly,  though,  if  you can estimate the uncertainty
       associated with them. To do this, invoke the code as follows:

        % neat -i ngc6543_3cols.dat -u

       The -u switch causes the code to run 10,000 times. In each iteration,  the  line  flux  is
       drawn  from  a normal distribution with a mean of the quoted flux and a standard deviation
       of the quoted uncertainty.  By repeating this randomisation process  lots  of  times,  you
       build  up a realistic picture of the uncertainties associated with the derived quantities.
       The more iterations you run, the more accurate the results; 10,000 is a sensible number to
       achieve  well  sampled probability distributions. If you want to run a different number of
       iterations for any reason, you can  use  the  -n  command  line  option  to  specify  your
       preferred value

       If  the  -rp option is specified, then for lines with a signal to noise ratio of less than
       6, the line flux is drawn from a log-normal distribution which  becomes  more  skewed  the
       lower the signal to noise ratio is. This corrects the low SNR lines for the upward bias in
       their measurement described by Rola & Pelat (1994). The full  procedure  is  described  in
       Wesson et al. (2012).  However, use of this option is no longer recommended as the bias is
       highly dependent on the fitting procedure - see Wesson et al. (2016).

METHODOLOGY

   Extinction correction
       The code corrects for interstellar reddening using the ratios of the Hα,  Hβ,  Hγ  and  Hδ
       lines.  Intrinsic  ratios  of  the  lines  are  first calculated assuming a temperature of
       10,000K and a density of 1000cm-3. The line list is then dereddened, and temperatures  and
       densities  are then calculated as described below. The temperatures and densities are then
       used to recalculate the intrinsic Balmer line ratios, and the original line list  is  then
       dereddened using this value.

   Temperatures and densities
       neat  determines  temperatures,  densities  and abundances by dividing emission lines into
       low, medium and high excitation lines. In each zone, the  diagnostics  are  calculated  as
       follows:

        1.  A temperature of 10000K is initially assumed, and the density is then calculated from
       the line ratios relevant to the zone.
        2. The temperature is then calculated from the temperature diagnostic line ratios,  using
       the derived density.
        3.  The  density  is  recalculated  using  the  appropriately  weighted  average  of  the
       temperature diagnostics.
        4. The temperature is recalculated using this density.

       This iterative procedure is carried out successively for low-, medium- and high-ionization
       zones,  and  in  each case if no diagnostics are available, the temperature and/or density
       will be taken to be that derived for the previous zone.  Temperatures  and  densities  for
       each  zone  can also be specified on the command line with the -telow, -temed, -tehigh and
       -nelow, -nemed, -nehigh options.

       neat also calculates a number of diagnostics from recombination  line  diagnostics.  These
       are:

        1. The Balmer jump temperature is calculated using equation 3 of Liu et al. (2001)
        2. The Paschen jump temperature is calculated using equation 7 of Fang et al. (2011)
        3.  A density is derived from the Balmer and Paschen decrements if any lines from H10-H25
       or P10-P25 are observed. Their ratios relative to Hβ are compared  to  theoretical  ratios
       from  Storey  &  Hummer  (1995),  and  a  density  for  each  line  calculated  by  linear
       interpolation. The final density  is  calculated  as  the  weighted  average  of  all  the
       densities.
        4.  Temperatures are estimated from helium line ratios, using equations derived from fits
       to tabulated values of 5876/4471 and 6678/4471. The tables are calculated  at  ne=5000cm-3
       only. We plan to improve this calculation in future releases.
        5.  OII recombination line ratios are used to derive a temperature and density, using the
       diagnostic diagram in Figure 1. of McNabb et al. (2013).  Values  are  found  by  linearly
       interpolating the logarithmic values.
        6.  Recomination  line  contributions  to  CELs  of  N+,  O+  and O2+ are estimated using
       equations 1-3 of Liu et al. (2000).

       These recombination line diagnostics are not used in abundance calculations. Nor  are  the
       temperature diagnostics corrected for the recombination line contributions. Whether or not
       to do so is an unfortunately subjective choice which we leave to the user.

   Ionic abundances
       Ionic abundances  are  calculated  from  collisionally  excited  lines  (CELs)  using  the
       temperature  and  density  appropriate  to their ionization potential. Where several lines
       from a given ion are present, the ionic abundance adopted is a  weighted  average  of  the
       abundances from each ion.

       Recombination  lines (RLs) are also used to derive ionic abundances for helium and heavier
       elements. The method by which the helium abundance is determined  depends  on  the  atomic
       data  set  being  used; neat includes atomic data from Smits (1996) and from Porter et al.
       (2012, 2013). The Smits data is given for seven temperatures between  312.5K  and  20000K,
       and  for  densities  of  1e2,  1e4 and 1e6 cm-3; we fitted fourth order polynomials to the
       coefficient for each line at each density. neat then calculates the emissivities for  each
       density using these equations, and interpolates logarithmically to the correct density.

       For  the  Porter  et al. data, the emissivities are tabulated between 5000 and 25000K, and
       for densities up to 1e14cm-3. neat interpolates logarithmically in temperature and density
       between the tabulated values to determine the appropriate emissivity.

       In  deep  spectra, many more RLs may be available than CELs. The code calculates the ionic
       abundance from each individual RL intensity using the atomic data listed  in  Table  1  of
       Wesson et al. (2012). Then, to determine the ionic abundance to adopt, it first derives an
       ionic abundance for each individual multiplet from the multiplet’s co-added intensity, and
       then averages the abundances derived for each multiplet to obtain the ionic abundance used
       in subsequent calculations.

   Total abundances
       Total elemental abundances are estimated using the ionisation correction  scheme  selected
       from  Kingsburgh and Barlow (1994), Peimbert, Torres-Peimbert and Ruiz (1992), or Delgado-
       Inglada et al. (2014). Total oxygen abundances estimated from several strong line  methods
       are also reported.

       Where  ionic  or  total abundances are available from both collisionally excited lines and
       recombination lines, the code calculates the measured discrepancy between the two values.

OUTPUTS

       The code prints some logging messages to the terminal, so that you can see which iteration
       it is on, and if anything has gone wrong. The results are written to a summary file, and a
       linelist file, the paths to which are indicated in the terminal output. In the case  of  a
       single iteration, these files are the only output.

       If  you  have  run multiple iterations, you can also use the -v option to tell the code to
       create additional results files for each quantity calculated:  -v  1  tells  the  code  to
       write  out  for  each  quantity  all  the  individual  results,  and  a binned probability
       distribution file; with -v 2, only the binned distributions are written out, and with -v 3
       - the default - no additional results files are created.

   Normality test
       The  code  now applies a simple test to the probability distributions to determine whether
       they are well described by a normal,  log-normal  or  exp-normal  distribution.  The  test
       applied  is  that  the  code  calculates  the  mean and standard deviation of the measured
       values, their logarithm and their exponent, and calculates in each case  the  fraction  of
       values  lying  within  1, 2 and 3σ of the mean. If the fractions are close to the expected
       values of 68.3%, 95.5% and 99.7%, then the relevant distribution is considered  to  apply.
       In  these  cases,  the  summary file contains the calculated mean and reports the standard
       deviation as the 1σ uncertainty.

       If the file is not well described by a normal-type distribution, then the code reports the
       median  of the distribution and takes the values at 15.9% and 84.1% of the distribution as
       the lower and upper limits.

   Inspecting the output
       It is often useful to directly inspect the probability  distributions.  In  the  utilities
       directory  there is a small shell script, utilities/plot.sh, which will plot the histogram
       of results together with a bar showing the value and its uncertainty as derived above.  It
       will create PNG graphics files for easy inspection.

       The  script  requires  that  you ran the code with -v 1 or -v 2, and that you have gnuplot
       installed. It takes one optional parameter, the prefix of the files generated by neat. So,
       for example, if you've run 10,000 iterations on example/ngc6543_3cols.dat, then there will
       now   be   roughly   150   files   in   the   example   directory,   with    names    like
       example/ngc6543_3cols.dat_mean_cHb,  example/ngc6543_3cols.dat_Oii_abund_CEL, etc. You can
       then generate plots of the probability distributions for the results by typing:

        % /usr/share/neat/utilities/plot.sh ngc6453.dat

       Running the code without the optional parameter will generate plots  for  all  files  with
       names ending in "binned" in the working directory.

SEE ALSO

       alfa, equib06, mocassin

BUGS

       No known bugs.

AUTHOR

       Roger Wesson, Dave Stock, Peter Scicluna