Provided by: neat_2.2-1build1_amd64 
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
-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 file.
--citation
Prints out the bibliographic details of the paper to cite if you use neat in your research
-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
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/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 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/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).
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 (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 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 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.
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 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/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. If reporting a bug, please state which version of neat you were using, and include input
and any output files produced if possible.
AUTHORS
Roger Wesson, Dave Stock, Peter Scicluna