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Using APOGEE Spectra

Several different types of APOGEE spectra are available:

The construction of these files is described in other locations as linked above.

The combined spectra (apStar files) may be the most useful of these. These combine spectra from individual visits after resampling them onto a common, logarithmically-spaced wavelength scale, and after removing derived radial velocities of each visit; thus the resulting spectra are in rest, vacuum wavelengths. Data from the entire APOGEE wavelength range (which includes some gaps, see below ) are included in a single array. The wavelength scale is recorded in the header in standard FITS cards; thus, standard software should allow, e.g., straighforward plotting of flux vs. wavelength.

For all APOGEE spectra, there are several important things to be aware of and that you are likely to notice if you look at and use the spectra. Some of these are listed here and discussed in more detail below:

Data quality flags

Information about the data quality of APOGEE spectra is encoded in several different bitmasks that are included with the spectra.

Wavelength coverage and chip gaps

The APOGEE spectra are recorded onto three different detectors. While the overall coverage ranges from 1.514 to 1.696 microns, there are small gaps between the detectors, leading to gaps in the wavelength coverage. While all of the APOGEE spectra lie in the infrared H band, we sometimes refer to the chips as the "blue", "green", and "red" chips, going from the shorter wavelengths to longer wavelengths. Data products refer to the separate chips as chips "a", "b", and "c", in the order in which they are read out. As it turns out, the "red" chip is the first one to read out, so this nomenclature is in reverse wavelength order. The following table explains the terminology.

ChipName Start wavelength End wavelengthCentral dispersion
a "red" 1.647 μ 1.696 μ -0.236 A/pix
b "green" 1.585 μ 1.644 μ -0.283 A/pix
c "blue" 1.514 μ 1.581 μ -0.326 A/pix

Note that the starting and ending wavelengths vary slightly from fiber to fiber because of variations of their placement along the instrument pseudo-slit. The dispersion varies with wavelength, and, to a lesser extent, with fiber.

Imperfect subtraction of night sky lines

The night sky lines (i.e., "airglow"), primarily from OH emission in the Earth's atmosphere, can be extremely bright. In the current version of the pipeline the emission from sky fibers near the sky position of each target is subtracted from the spectra of the targets. However, this subtraction is almost always imperfect because (1) the sky spectra need to be shifted in wavelength to match the object spectra, because of variations of locations of the fibers along the pseudo-slit, and (2) the line spread function (LSF) of different fibers varies because of changes in image quality across the field-of-view. Because the night sky lines are so bright, even small fractional variations due to these issues can cause the subtraction to be very noticeably imperfect; thus most sky lines are either under- or over-subtracted.

We note that, even if the airglow subtraction were perfect, the area of the spectrum "under" the sky lines would be of significantly lower signal-to-noise, because of the large Poisson contribution from the bright lines. Partly because of this, we have not yet put significant effort into improving the sky subtraction. Additional work along these lines may be made for subsequent data releases.

The imperfect sky subraction does have the unfortunate result of making the APOGEE spectrum appear a bit "ugly" to a quick, casual inspection. The APOGEE data products (e.g., apVisit and apStar files) do have a record of the sky spectrum that was subtracted, and it is possible to use this as a guide to recognizing pixels that are likely to be affected by imperfect sky subtraction.

Error arrays

All APOGEE spectra include an array of uncertainties ("errors") for each pixel. These uncertainties are initially calculated from the raw pixel data based on the noise properties of the detectors (gain and readout noise). These raw errors are propagated into subsequent data products.

However, in downstream spectral products, data in any given pixel may have been derived from some combination of pixels in the raw data, and data from any individual raw pixel may contribute to more than one pixel in the combined spectra, leading to correlated errors between pixels. This can occur in visit spectra because these are combined from two separate dithered observations. If dithers are exactly spaced by 0.5 pixels, then the combined spectra just interleaves the two dithered exposures, but if the dithers are slightly imperfect (as they generally are), any pixel in the combined well-sampled spectrum will have contributions from multiple raw pixels. For the visit-combined apStar spectra, the pixels definitely have contributions from multiple raw pixels, because the apStar spectra are RV-corrected and resampled onto a common wavelength grid. Although the uncertainties are propagated into the apVisit and apStar spectra, this propagation ignores the correlation of uncertainties that results from having processed pixels that are derived from multiple raw pixels.

Multiple observations of selected targets have been used to estimate empirical uncertainties, and these demonstrate that, for most targets, the calculated uncertainties are reasonable, i.e., the scatter from observation to observation is comparable to the estimated uncertainty in each observation. However, for very bright targets the calculated uncertainties are almost certainly an underestimate, because the accuracy of these data are most likely limited by systematic errors in the data processing and calibration data products. We have not yet fully quantified these, but we think it is likely that there is an uncertainty "floor" around the 0.5% level, i.e., a maximum S/N of ~200. We have not set such a floor in the spectrum uncertainty arrays, so users need to beware that there is a likely maximum S/N~200.

Bad pixels/missing regions

The IR detectors are not cosmetically perfect, leading to small regions of the chip that are bad, as well as a significant number of bad or "hot" pixels. These are flagged during the data processing, and can lead to bad or missing regions in any given spectrum. Because visit spectra are combined from multiple individual dithered spectra, a single bad pixel can propagate into multiple pixels in the visit-combined spectra. These can have the effect, along with poorly subtracted sky lines, of making individual visit spectra look rather "ugly". The mask arrays can be used to identify the cause of most bad pixels.

Because any given star may not use the same fiber in different visits, combined spectra generally look somewhat cleaner, especially if a target happens to be observed on different fibers in different visits and/or if the observed radial velocity (including differences in barycentric RV) differs significantly from visit-to-visit. However, even if the combined spectra do not have regions with data missing, there may be regions where the noise level is elevated if that portion of the spectrum landed on a bad region in one or more of the visits.

Ghosts

The use of VPH gratings results in the production of some "ghosts" on the 2-D images. The most prominent of these is the "Littrow ghost", which for APOGEE falls somewhere in the wavelength region 1.624 to 1.626 microns, depending on the fiber.

The amplitude of the ghost depends on the brightness of other stars in the field, so it does not always contribute a significant amount of flux. Pixels possibly affected by the Littrow ghost are flagged with the LITTROW_GHOST bit in the APOGEE_PIXMASK bitmask.

Fiber cross talk

In order to pack as many stars as possible in the APOGEE detector, the spacing between adjacent spectra is relatively small, amounting to ~ 6.5 pixels between adjacent PSF peaks. Therefore, the wings of the PSF overlap slightly with adjacent spectra, in particular if a faint object is located adjacent to a much brighter object. To mitigate this, the targets on each plate are sorted into three brightness categories -- bright (B), medium (M), and faint (F) -- and these categories are placed along the pseudo-slit (and hence, on the detectors) in the order FMBBMF FMBBMF ..., so, in principle, a faint object (or sky) should never land next to a bright object. However, the magnitude ranges of these categories can be broad, so it is possible for objects of significantly different brightness to be adjacent to each other.

The extraction portion of the data reduction pipeline accounts for contributions of light from the two adjacent spectra for each object. However, the quality of this extraction depends on a high-quality knowledge of the amplitude of the wings of the light distribution. In cases where adjacent targets are significantly brighter than an object, small inaccuracies in the PSF model may lead to significant errors in the extraction of adjacent spectra.

For each visit, a bit is set in the APOGEE_STARFLAG bitmask if an adjacent object is more than 100 times brighter than the star (VERY_BRIGHT_NEIGHBOR) or more than 10 times brighter (BRIGHT_NEIGHBOR). The former case, which is rare, is automatically considered as a bad spectrum, i.e., not to be included in the combined spectrum.

Incomplete data acquisition

In DR10, we release all APOGEE data that have been obtained before July 2012. However, since most fields are visited multiple times, there are fields in DR10 that will be (or have been) revisited since the DR10 cutoff date. Both individual spectra taken before this date, as well as combined spectra from all visits before this date, are included in the DR10 release, but for stars that have not been completed, the S/N of the DR10 spectra will not be at the survey goal. Subsequent data releases will yield different, higher S/N, spectra.

Persistence in the "blue" chip

Some areas of the detectors used in the APOGEE instrument suffer from a problem that we refer to as "superpersistence". In these locations on the chip, previous exposure to light causes a glow in subsequent images that can be very significant and last for a significant amount of time. The problem is most severe on about 1/3 of the "blue" chip, i.e. the chip that records wavelengths between 1.514 and 1.581 microns. The orientation of the chip is such that this region affects essentially all of this wavelength region for the 1/3 of the fibers that put light into this area. There are also regions in the "green" chip that are affected by a lower level of superpersistence, but these are not so cleanly delineated by fiber or wavelength.

The effect of superpersistence depends on the prior exposure history, and likely on the brightness of the target being recorded. Some level of mitigation is provided by the fiber management system described above, since the grouping of fibers according to target brightness makes it relatively uncommon for a faint target to be observed through a fiber that was previously placed on a bright target. However, since the magnitude ranges that define these categories are broad, there can still be cases where faint targets follow bright ones. In addition, calibration flat field exposures are taken between every plate to map the distribution of light between fibers and to measure the fiber-to-fiber throughput variations, and these roughly evenly-illuminated frames give rise to some superpersistence.

Superpersistence is a complex phenomenon, and in DR10 we have made no effort to correct for it. Subsequent data releases may attempt to incorporate some kind of correction.

The effect of superpersistence can be very significant and easily noticed: the flux levels in the region of the spectrum affected can be enhanced by tens of percent or more. This enhancement is likely to have some wavelength dependence, so spectral features might be distorted. However, depending on the brightness of the target and preceding ones, it is not guaranteed that the spectra are significantly adversely affected, so we do not immediately call all data that falls in the persistence region bad.

In the data reduction pipeline, we flag all pixels in the APOGEE_PIXMASK bitmask where significant superperstence is known to occur, with three different flags corresponding to the level of the effect: PERSIST_HIGH, PERSIST_MED, and PERSIST_LOW. In addition, we have a visit level flag, APOGEE_STARFLAG, for each object, with bits that that get set when a significant number of pixels (>20%) of the spectrum is affected, again split into categories PERSIST_HIGH, PERSIST_MED, and PERSIST_LOW. In addition, we look for evidence in the spectra of a "jump" in flux between the "green" and the "blue" chips, and if this is present at a easily recognized level, we set a flag PERSIST_JUMP_HIGH or PERSIST_JUMP_LOW if the "blue" portion of the spectrum seems abnormally high or abnormally low (this latter could occur, e.g., if a sky fiber from a region affected by superpersistence is used for sky subtraction, although the pipeline takes some steps to try to avoid this occurance).

In the combined spectra, we provide star level flags that are bitwise AND and bitwise OR combinations of the visit APOGEE_STARFLAG flags, so you can tell if a given object was marked as having a significant number of pixels in the superpersistence region in all or any of the visit spectra that went into the combination.