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Table of Contents - Subject Index - Author Index - Search - PS reprint - PDF reprint Greisen, E. G., Valdes, F. G., Calabretta, M. R., & Allen, S. L. 2003, in ASP Conf. Ser., Vol. 295 Astronomical Data Analysis Software and Systems XII, eds. H. E. Payne, R. I. Jedrzejewski, & R. N. Hook (San Francisco: ASP), 403

Representations of Spectral Coordinates in FITS

Eric W. Greisen¹
National Radio Astronomy Observatory, P. O. Box O, Socorro, NM 87801 USA; Email: egreisen@nrao.edu

Francisco G. Valdes²
National Optical Astronomy Observatories, P. O. Box 26732, Tucson, AZ 85719 USA; Email: valdes@noao.edu

Mark R. Calabretta³
Australia Telescope National Facility, P. O. Box 76, Epping, NSW 1710 Australia; Email: Mark.Calabretta@atnf.csiro.au

Steven L. Allen⁴
UCO/Lick Observatory, University of California, Santa Cruz, CA 95064 USA; Email: sla@ucolick.org

Abstract:

In Paper I, Greisen & Calabretta (2003) describe a generalized method for specifying the coordinates of FITS data samples. Following that general method, Calabretta & Greisen (2003) in Paper II describe detailed conventions for defining celestial coordinates as they are projected onto a two-dimensional plane. The present paper extends the discussion to the spectral coordinates of wavelength, frequency, and velocity. World coordinate functions are defined for spectral axes sampled evenly in wavelength, frequency, or velocity, evenly in the logarithm of wavelength or frequency, as projected by ideal dispersing elements, and as specified by a lookup table. Papers I and II have been accepted into the FITS standard by the North American, Japanese and European FITS Committees; we expect the present work to be accepted as well. The full text of the proposed standards can be found at http://www.aoc.nrao.edu/~egreisen.

1. Introduction

Greisen & Calabretta (2003, ``Paper I'') describes the computation of the world or physical coordinates as a multi-step process. The vector of pixel offsets from the reference point is multiplied by a linear transformation matrix and then scaled to physical units. Mathematically, this is given by

$$x_i = s_i \,\, q_i = s_i \, \sum_{j=1}^N m_{ij} \,\, \left( p_j - r_j \right) \, ,$$ (1)

where $p_j$ are pixel coordinates, $r_j$ are pixel coordinates of the reference point given by CRPIX$\,j$, $m_{ij}$ is a linear transformation matrix given either by PC$\,i$_$j$ or CD$\,i$_$j$, $N$ is the dimensionality of the WCS representation given by WCSAXES, and $s_i$ is a scaling given either by CDELT$\,i$ or by 1.0. The final step in the computation is the conversion of these linear relative coordinates into the actual physical coordinates. The conventions to be applied to ideal spectral axes are described in ``Paper III'' (Greisen et al. 2003) and summarized here. A later work (Calabretta, et al. 2003, ``Paper IV'') will address the corrections needed to convert real astronomical data into the ideal axes assumed in the celestial coordinates (Calabretta & Greisen 2003, ``Paper II'') and present manuscripts.

2. Basic Coordinates

The basic ``spectral'' coordinates are frequency, wavelength, and Doppler relativistic velocity. There are several other coordinates which are proportional to one of these, including wavenumber, energy, and ``radio'' and ``optical'' conventional velocities. Let us consider the case in which an axis is linearly sampled in spectral variable $X$, but is to be expressed in terms of variable $S$. We may restrict $X$ to the basic types since all others are linearly proportional to one of them. Let us also introduce an intermediate variable $P$ which is the basic variable associated with $S$. The relationship between $X$ and $S$ is then $S(X) = S(P(X))$ with inverse $X(S) = X(P(S))$. The statement that an axis is linearly sampled in $X$ simply means that

$$X = X_{\mathrm{r}} + w \frac{\mathrm{d}X}{\mathrm{d}w}$$ (2)

where $w$ is the intermediate value $x_i$ for the spectral axis and ${\mathrm{d}X}/{\mathrm{d}w}$ is a constant. Since, to first order and very near the reference point, the axis is linear in $S$, i.e., $S \approx S_{\mathrm{r}} + w$, we may determine the derivative by

$$\frac{\mathrm{d}X}{\mathrm{d}w} = \left. \frac{\mathrm{d}P}... ...t. \frac{\mathrm{d}P}{\mathrm{d}X} \right\vert _{\rm r} \,\, .$$ (3)

A three-step algorithm chain is then indicated:

1. Compute once $X_{\rm r} = X(P(S_{\rm r}))$ and ${\mathrm{d}X}/{\mathrm{d}w}$ using Equation (3) and then compute $X$ at $w$ using Equation (2).
2. Compute $P$ from $X$ using the set of non-linear relationships between the basic spectral coordinates..
3. Compute $S$ from $P$ using the set of linear relationships between the basic and secondary spectral coordinates.

Dispersion coordinates for UV, optical, and IR spectra at $\lambda > 200$ nm are commonly given as wavelengths in air rather than in vacuum. The relationship between these is given by $\lambda = n(\lambda_a) \lambda_a$ and causes a relative difference of around 0.03%. The conversion between wavelengths in air and wavelengths in vacuum adds another step in the chain described above.

Paper III presents a full set of codes to be used in keyword CTYPE$ia$ for spectral coordinate types and for the non-linear algorithms involved, including air wavelengths. Keywords RESTFRQ$a$ and RESTWAV$a$ are reserved to give the line rest frequency (in Hz) or wavelength (in m) needed for the conversion between frequency/wavelength and velocity.

3. Dispersed Spectra: -GRI Non-linear Algorithm

Figure 1: Geometry of gratings, prisms, and grisms. This simplified representation omits the collimation and focusing optics. Dashed lines mark ray paths in the plane of the figure - the ``dispersion plane''. The normal to the grating/exit prism face and the normal to the detector plane are each projected onto the dispersion plane, and angles $\alpha$, $\beta$, and $\theta$ are measured with respect to these projected normals. Usually the incident ray for a prism or grism is perpendicular to the entry face so that $\alpha$ is equal to the prism angle, $\rho$. Angle $\beta$ is wavelength-dependent, and consequently so is the offset $\xi$ in the dispersion direction on the detector. The intermediate spectral world coordinate, $w$, is proportional to $\xi$. Reference wavelength $\lambda_{\rm r}$ follows the reference ray defined by $\beta_{\rm r}$ and illuminates the reference point at $w = \xi = 0$. The normal to the detector plane is shown tilted by angle $\theta$ from the reference ray though typically this angle is zero. The grating spacing $G^{-1}$ is indicated.

One common form of spectral data is produced by imaging the light from a disperser, such as a prism, grating, or grism, as illustrated in Figure 1. Paper III presents the full mathematics by which the wavelength $\lambda$ and the spacing at the detector $\xi(\lambda)$ may be related. The basic grism equation is given by

$$\lambda = \frac{(n_{\rm r} - n'_{\rm r}\lambda_{\rm r}) \sin\alpha + \sin\beta}{Gm/cos\epsilon - n'_{\rm r}\sin\alpha} \, .$$ (4)

Despite numerous approximations made in the development of the mathematics, it is found that suitable parameters provide good fits to a variety of spectrometers in use at the KPNO.

4. Coordinates by Table Lookup: -TAB Algorithm

There are numerous instances in which a physical coordinate is well defined at each pixel along an image axis, but the relationship of the coordinate values between pixels cannot be described by a simple functional form. Observations of the same object made at an arbitrary set of frequencies or times are the simplest examples. In addition, the calibration of some spectrographs is represented best by a list of wavelengths for each pixel on the spectral axis.

Fully separable, one-dimensional axes of this type may be represented by an algorithm, -TAB, defined in Paper III. A FITS binary table containing only one row is used. The coordinates are given by a vector of values in a single cell, optionally accompanied by a second indexing vector in a second cell within the row. The parameters required by -TAB are the table extension name, the table version number, the table level number, the column name for the coordinate vector, and the column name for the optional indexing vector. The character-valued generic keyword PS$\,i$_$j$ is introduced to provide the three character-valued parameters of this algorithm. The coordinate value is found by first evaluating Equation (1) and adding the reference value. The result is used as a value to be looked up in the vector of values found in the indexing vector cell. The corresponding position in the vector of values in the coordinate vector cell then provides the actual coordinate. If the indexing vector is omitted, the value found with Equation (1) is used as a direct index for the coordinate vector.

The -TAB algorithm described above is then generalized to cases in which the coordinates on $N$ axes are dependent on each other, but the indexing vectors are independent. In this case, the values of the coordinates are contained in one column of the (one-row) table as an array of dimensions $(N, K_1, K_2, \ldots, K_N)$, where $K_i$ is the number of indexing values on axis $i$. The indexing vector for axis $i$, if present, will occupy a separate column and will contain $K_i$ values in a one-dimensional array. An additional parameter is required for each of the $N$ coordinates to give the axis number $i$ within the coordinate array.

5. Summary

Paper I has defined a general framework to describe world coordinates in the FITS format; Paper II has extended that framework to describe ideal celestial coordinate representations. Paper III, summarized here, extends the discussion to ideal spectral coordinates and introduces a general table lookup algorithm. All three papers are well on their way to becoming part of the IAU FITS Standard.

References

Calabretta, M. R. et al. 2003, Representations of distortions in FITS world coordinate systems, in preparation, (``Paper IV'')

Calabretta, M. R. & Greisen, E. W. 2003, A&A, accepted (``Paper II'')

Greisen, E. W. & Calabretta, M. R. 2003, A&A, accepted (``Paper I'')

Greisen, E. W., Valdes, F. G., Calabretta, M. R., & Allen, S. A. 2003, A&A, in preparation (``Paper III'')

Footnotes

... Greisen¹

The National Radio Astronomy Observatory is a facility of the (U.S.) National Science Foundation operated under cooperative agreement by Associated Universities, Inc.

... Valdes²

The National Optical Astronomy Observatory is a facility of the (U.S.) National Science Foundation operated under cooperative agreement by Associated Universities for Research in Astronomy, Inc.

... Calabretta³

The Australia Telescope is funded by the Commonwealth of Australia for operation as a National Facility managed by CSIRO.

... Allen⁴

UCO/Lick Observatory is operated by the University of California.

© Copyright 2003 Astronomical Society of the Pacific, 390 Ashton Avenue, San Francisco, California 94112, USA Next: Restoration of Digitized Astronomical Plates with the Pixon Method
Up: Algorithms
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