Analysis Functions
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Bisector
 This tool deduces the bisector by evaluating the
midpoint between the two halves of the spectral line at an input number of flux
levels.  Since outliers can produce bothering effects, for
instance while calculating the peak position of the line, they must be removed. In order to solve this issue, you can select
between two options:  automatic bisector evaluation: VOSpec works
with a suitable smoothed version of the input spectral line. The smoothing
method depends on the input line with the aim to modify it at less as possible.
To select this option click on the “Previous automated line smoothing”
checkbox. if the automated line smoothing checkbox is not
selected, the bisector algorithm expects a suitable input spectral line. This
option allows the user to perform by him/herself any previous smoothing,
denoising, … method.
Bisector parameters
The distortion of the spectral
lines can be characterized by two conventionally used parameters:
 Velocity Span (or amplitude):
measures the velocity difference in the bisector at two flux levels. The
considered levels are the continuum and the line peak.
 Bisector Curvature: is defined
as the difference between bisector spans computed for the top and bottom halves
of a line. Three bisector points are considered to calculate the velocity span
values:
Equivalent Width
VOSpec allows
the interactive calculus of the equivalent width of a given spectral line.
The formula
used to evaluate the value of the equivalent width is:
_{}
where:
_{}is the
continuum flux. For the time being, a linear continuum is considered.
_{}is the
spectrum flux.
Statistics
The Statistics Window allows
you to calculate some statistical values of your spectra, wavelet transforms,
fits …
These are the formulas used
by VOSpec to calculate each statistical value:
Measures
of central tendency
Give us an idea of the
"middle" or "typical" value of the data.
Mean:
Note that the mean can
be drastically affected by outliers.
 Median:
The median is determined
sorting the data set from lowest to highest values and taking the middle one.
In the case of an even number of values, the median is the mean of the two
middle numbers.
The median is much less
affected by outliers than the mean. For this reason, the median often is used
when there are a few extreme values that could greatly influence the mean and
distort what might be considered typical.
Measures of dispersion
Characterize the
spread or variability of a data set.
 Variance:
_{}
 Standard Deviation:
It is just the square root
of the variance.
Restores the units of the
spread to the data units.
_{}
 Median absolute
deviation:

Very robust estimator

Highly insensitive to outliers
_{}
 Range: is the
difference between the largest and the smallest flux values.
Tuning
In the tuning window you can
find some useful tools to perform simple modifications in your spectra.
The currently available
tuning utilities are:
Multivalued Spectra Averaging
Replaces all flux values at
the same wavelength position by their mean value.
Rebinning
 Increase or decrease spectra resolution
 The output spectrum is evaluated at an input number
of evenly spaced wavelength positions selected by the user.
Reject zero and negative values
This utility allows you to remove zero and negative
flux values from your spectra
Mirroring
A simple way to
check the asymmetry of a spectrum section is the mirroring method. It works by
evaluating the mirrored image of a given spectrum line or region with respect
to an axis.
Currently there
are the following available options:
Line Mirroring
Given
a spectral line, this method evaluates automatically its axis (peak position)
and returns the mirrored line respect to this axis.
Spectrum Mirroring
Given a spectrum (or a spectrum selection),
this mirroring option evaluates the mirrored image of the input spectrum (or
the spectrum selection) with respect to the axis introduced by the user.
If no axis is introduced, the tool considers the
midpoint of the wavelength range where the input spectrum is defined.
Flux
The Flux window gives
access to Line Flux and Integrated Flux utilities. They both work by selecting
in the main VOSpec display window the region in which we are interested in
(drag right button of mouse over the spectrum region on which the fitting
algorithm shall be run) and then clicking in the "Calculate" button.
Line Flux
Measures the flux between a
spectral line and a linear continuum.
The spectral line must be
selected in the main VOSpec display window before clicking the “Calculate”
button.
Integrated Flux
Estimates the area under a region of a spectrum
using simple trapezoidal integration.
The region of the spectrum
we are interested in must be selected in the main VOSpec display window before
clicking the “Calculate” button.
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Filters
VOSpec offers many types of filtering or denoising
methods:
 Averaging FiltersAveraging_Filters
 Mean
 Median
 Kernel Filtersernel_Filters
 Constant width: Kernel
FiltersKernel_Filters
 Adaptive width: Adaptive
FiltersAdaptive_Filters
 Wavelet FiltersWavelet_Filters
Averaging Filters
The averaging filters offered by VOSpec are:
 Mean filter
 Median filter
For both types of filtering methods there are two
different options:
Defined by input number of
adjacent pointsDefined_by_input_number_of_adjacent_points
Defined by input number of
subintervals*Defined_by_input_number_of_subintervals
Defined by input number of adjacent points
These averaging filters
replace every flux value of the input spectrum by the mean/median value of the
set composed by such input flux value plus its N backward and N forward
adjacent flux values. N is the input number of adjacent points.
The output spectrum is
defined at the same wavelength positions than the input spectrum.
Defined by input number of subintervals
This option returns an output spectrum that is
defined at N+1 evenly spaced wavelength positions:
_{}
where N is the input
number of subintervals.
The flux values of the output spectrum at these
wavelength positions are the mean/median value of all input flux values lying
within the following interval:
_{}
Kernel Filters
These filters replace each flux value by a weighted
average of its adjacent flux values:
_{}
_{}is the input spectrum
evaluated at the kth position
_{}is the weighting function
(kernel) evaluated at the jth position
Available weighting functions (kernels) are:
Gaussian
Lorentzian
Voight
any spectrum: you can use any spectrum as kernel
filter. You just have to select the spectrum that you want to use as kernel
from the spectra list.
The width of the Gausian, Lorentzian and Voight
functions:
is constant at every position
can be introduced as input by two different ways:
real width
The algorithm uses the width
value introduced by the user without modifications.
fitted to range width
If the user doesn't know a
suitable value for the width, the input value introduced by him/her is fitted
to the range where the spectra are defined.
The value of the fitted width is proportional to
the input value.
Adaptive IDS Filters
These are convolution filters where the width of
the weighting functions at each wavelength position is adapted to the shape of
the spectrum.
The width is narrower close to the peaks of the
spectrum and wider close to the continuum.
The aim of these filters is to preserve all the
spectral lines, even the smoothest ones.
Wavelet Filters
These filters use the properties of the wavelet
transform to smooth the spectra.
The technique works in the following way: when a
data set is decomposed using wavelets, some of the resulting wavelet
coefficients correspond to details (high freq.) in the data set. If those
details are sufficiently small (smaller than a given threshold) , they might be
omitted without substantially affecting the main features of the data set.
The result is a cleanedup spectrum that still
preserves the important details.
Available wavelet functions are:
Daubechies
Coiflets
Symlets
The threshold used is the Donoho's threshold.
Allowed hard and soft thresholding methods.
Notes:
 In order to not extrapolate and to not
decrease resolution, the operations are performed at all wavelength
positions of every involved spectra lying within the ranges where such spectra
are defined.
 Spectra rebinning is done using simple linear
interpolation when necessary.
 If the spectra are defined in disjoint intervals
the arithmetic operations are not performed.
 Multivalued flux values (more than one flux
value at the same wavelength position) are replaced by their mean value.
Normalization
Normalization can be applied to both Theoretical and not calibrated
spectra in order to be adapted to real and calibrated flux.
De_Reddening
Interstellar reddening is a phenomenon associated
with interstellar extinction where the spectrum of electromagnetic
radiation from a radiation source changes characteristics from
that which was emitted.
Reddening occurs due to the light scattering off dust and other
matter in the interstellar medium. It preferentially removes
shorter wavelength photons from a radiated spectrum while leaving
behind the longer wavelength photons (in the optical, light
that is redder), leaving the spectroscopic lines unchanged
VOSpec provides support to this phenomenon allowing to apply
the Calzetti, Cardelli O’Donnel or LMC formula, depending
by the case.
Download the Video
Please see the video of
VOSpec De_Reddening (presented in Moscow Sept. 2006)
Luminosity Viewer
Tool to calculate the luminosity difference
RedShift
Select the checkbox and apply the proper redhift
VOSpec Calculator
VOSpec Calculator is the tool of VOSpec to
perform arithmetic operations among spectra or between a spectrum and a
constant.
To perform an arithmetic operation you just need
to:
 Select first operand: drag a spectrum from the
Spectra List and drop it on the operational area of the VOSpec Calculator
 Select the operation you want to perform
 Select second operand:
 drag a spectrum from the
Spectra List and drop it on the operational area of the VOSpec Calculator
or
 insert a constant in the
constant text field and click the “Add” button. The input constant should
appear now in the Operational Area.
 Click on the “Equals” button
 The resulting spectra will appear in the Spectra
List of VOSpec and in the History track of the VOSpec Calculator
 Click the “Reset” button before performing
a new arithmetic operation
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