bionic (1) neat.1.gz

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