Provided by: neat_2.2-1_amd64 bug


       neat - nebular empirical analysis tool


       neat [option1] [value1] ...


       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.


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

       -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.   Any
              weights  not  specified  in  FILE  take their values from the default configuration

              Prints out the bibliographic details of the paper to cite if you use neat  in  your

       -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

       -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

       -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.

       -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.  The KB94 ICF implemented in neat additionally contains a correction
              for chlorine, from Liu et al., 2000, MNRAS, 312, 585.

       -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

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

       -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.

       -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.

       -sr, --subtract-recombination
              The  recombination  contribution to some important diagnostic collisionally excited
              lines is always calculated but, by default, is not subtracted. This  option  causes
              the  subtraction  to be carried out. Note that the code takes roughly twice as long
              to run if this is enabled, as the temperature and abundance calculations need to be
              repeated following the subtraction.

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

       -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


   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/examples/ 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
        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.

       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.


       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/examples/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).


   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
       (ionisation  potential  <20eV), medium (20eV<IP<45eV) and high excitation (IP>45eV) 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

        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
        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
       atomic  data  calculations  from  Storey  et  al.  (2017).  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. By default,
       the recombination contribution to CELs is reported but not subtracted.  The  command  line
       option --subtract-recombination can be used if the subtraction is required - this requires
       an additional loop within the code which makes it run roughly half as  fast  as  when  the
       subtraction is not carried out.

   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.


       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/, 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  examples/ngc6543_3cols.dat,  then  there
       will   now   be   roughly   150   files   in   the  example  directory,  with  names  like
       examples/ngc6543_3cols.dat_mean_cHb,  examples/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/ ngc6453.dat

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


       alfa, equib06, mocassin


       No known bugs. If reporting a bug, please state which version of neat you were using,  and
       include input and any output files produced if possible.


       Roger Wesson, Dave Stock, Peter Scicluna