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