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 Set CURRENT_DOC_BUILD = hcss-doc-14.0
 
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• To produce the highest quality maps, you should consider re-processing or fine-tuning the observations with the latest HIPE User Release. Maps available from the HSA are created within a bulk processing framework, and a reprocessing while fine-tuning the mapper parameters, according to the characteristics of the observed sky region, could enhance the quality of the final maps.

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      * These are due to a non-optimal estimate of background by the high-pass filter close to a bright source. The current masked high-pass filter pipeline is a trade-off, designed to get a good sensitivity on point-sources and preserve some extended emission up to a few arcmin scale. However due to the relatively large width in the second high-pass filtering, significant stripping from the 1/f noise is still present in the level 2 maps. On the other hand a large fraction of the extended emission is filtered out. The observer is advised to play with the threshold to define the mask and with the width of the high-pass filter to reduce these effects or move to MADmap scanamorphos to preserve extended emission at all scales. Level 2.5 MADmap maps, combining scans and crossed-scans on the other hands do preserve extended emission at all spatial scales.
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   * Calibration block transient in L2 maps*
       Several red (160um) scan maps are affected by a calibration block downwards transient when scheduled immediately before the science observation. This can be mitigated by running a high-pass filter with a smaller width, fitting the transient or just masking the affected frames at the start of the observation.
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<--      * Scan maps processed with SPG v4.1.0 were deglitched with "MMT deglitching", a temporal deglitching of the pixel timelines. This deglitching technique works very well for deep fields (e.g. cosmological fields) but fails at high scan speed (60"/s) or even medium scan speeds on bright (>~1Jy) sources, wrongly identified as glitches.
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   * Brightest sources core deglitched in the Level 2 map processed with old pipeline version (SPG v4.1.0)*
       This is due to the MMT deglitching at high speed (60"/s), which can wrongly identify bright sources as glitches. A possible solution in these cases is to use 2nd order deglitching in the interactive pipeline, now the default in the HCSS pipeline.

   * Glitches from Cosmic ray hits*
       Level 2 maps in the archive (HSA) processed with SPG 4.1.0 are affected by glitches as a side effect of disabling the deglitching on bright sources. This has been corrected in SPG version 6.1.0 and above. Interactive HIPE sessions shall get rid off of all these glitches by playing with the deglitching thresholds or using the 2nd order deglitching (memory consuming).
      * At 20"/s scan speed, the MMT deglitching does fine if there are no bright sources (>~1Jy), for instance for cosmological survey observations. For brighter sources (nearby galaxies or galactic fields) it is better to switch to second order deglitching. For more information see the PACS Data Reduction Guide (PDRG).
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The astrometry of several PACS scan maps acquired between ODs 320 and 761 has been reported to be off by 4 arcsec (solid offset of the whole map) or even above for a few fields where the tracking stars are not homogeneously distributed in the star-tracker field-of-view. It is intended to improve the a posteriori reconstructed pointing for all observations in the future.
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      * The absolute astrometry of Level 2 maps on Solar System Objects (SSO), projected in the SSO reference frame is not reliable and can be off up to 20 arcsec. This a data processing issue only (aberration & light travel time correction), while the observations themselves were correctly performed (uplink). This issue is under investigations at HSC and PACS ICC.
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   * Quality flags in the quality*

       Currently, the quality flags at the quality context inside the observation context are just meant for HSC/ICC internal evaluation of the quality of the products and not for the users. In case the data had some serious quality problem, the PI of the program has been contacted about it. Otherwise, only information in the quality summary, when available, should concern the observers.
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PACS Scan Map AOT release note: 23 Feb 2010

PACS Photometer - Point/Compact Source Observations: Mini Scan-Maps & Chop-Nod AOT release note: 12 Nov 2010
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• To produce the highest quality cubes possible, you should consider re-processing or fine-tuning the observations with the latest HIPE User Release. Cubes available from the HSA are created within a bulk processing framework, and a reprocessing while fine-tuning the important pipeline task parameters, according to the characteristics of the observation and source, could enhance the quality of the final results. The first two chapters of the PACS Data Reduction Guide for spectroscopy (HIPE 13) give information about the need to reprocess, and about what to do with HSA-obtained cubes before using them for science.

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   * Off-subtraction for unchopped long-range scan observations*
       Range Spectroscopy unchopped observation require off-position scans observed in a separate AOR. The off-source observation need to be subtracted from the on-scan after producing Level 2 rebinned spectra, this results a Level 2.5 product. The pipeline only generates Level 2 data products for unchopped spectroscopy in SPG 8.0. You need to combine interactively the on and off positions using the dedicated multi-observation unchopped pipeline script under the PACS pipeline menu.
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   * Unchopped grating scan flux calibration*
       The absolute flux calibration of the PACS spectrometer is based on observations of flux calibration standards using chopped spectroscopy modes. There are hints of systematic differences in the response scaling between chopped and unchopped mode due to response transients within the chopping pattern. In SPG 8.0 the flux calibration of unchopped data relies on the system response derived chopped scheme, therefore absolute flux values need to be carefully interpreted. Please contact Helpdesk for guidelines on the specific observation you have to deal with.
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• • The order selection filters of the PACS spectrometer have a steep but not perfectly vertical transmission profile at the cut­off wavelengths of the spectral bands. PACS spectra near the band borders of bands R1, B3A and B2B are therefore affected by higher- or lower-order wavelengths leaking into the spectra -- both continuum and spectral lines! Consult the PACS Calibration Document for more information on the leakage regions.

• • A second pass in the optics of the PACS spectrometer can cause a ghost image to appear on most spaxels (but never in the central spaxel). If a source located in one of these "originating" spaxels shows a strong spectral line (typically an atomic fine-structure line), then a weak, broadened line can be seen at an offset wavelength in its corresponding "destination" spaxel affected by the 2nd-pass ghost. The peak flux of this line is typically ~5% of the peak of the originating line. The most prominent ghost is the 122 micron feature, which originates from the usually strong CII+ 157.7 micron line. A list of strong ghosts and an image showing the directions of the projected passes on the 5x5 IFU footprint can be found in the PACS Calibration Document.

• • To check for the presence of contamination from unwanted astronomical sources in the off positions of chopNod mode observations, you can use a Split On-Off pipeline script to produce an off-source and on-source cube. These cubes can then be compared to each other to check for contamination in spectral lines or by strong continuum emission, e.g. by over-plotting the respective spectra. Note that the on-source and off-source cubes produced by this task will not allow you to detect faint levels of contamination because wriggles from the RSRF are not removed by this process. For faint targets (line peak-to-continuum emission ~<5-10 Jy) you should also check the differential signal between the nodA and B on-source cubes. This is documented in the PACS Data Reduction Guide for spectroscopy. In this guide you can also find advice on checking for contamination in the unchopped mode observations, which is done either by comparing companion observations (unchopped range) or with a small script provided in the PDRG (unchopped line).

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   * RSRF at wavelengths below 53 microns*
       The relative spectral response function (used by the pipeline task rsrfCal) is an extrapolation at wavelengths below 53 microns. This will cause problems in the spectra from module 3 (=spaxel 3,0, i.e. in the cube image you see when you look at a PacsCube or PacsRebinnedCube with the Standard Cube Viewer or the Spectrum Explorer, it is the 4th up and on the very left): the extrapolation is too steep and makes the pixel-spectra similarly follow a very steep curve. This is being corrected.
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• • As for any slit-spectrograph, if the incoming light beam is neither homogeneously nor symmetrically illuminating a spaxel, then line profiles may be distorted from the ideal Gaussian shape. In case of a point-source observed with PACS, the spectral line profile develops a skew, increasing as the offset of the photocentre along the instrument Z-axis (perpendicular the slit direction) does. Examples of skewed line shapes are given in the PACS Observers Manual.

• • The PACS spectrometer flux calibration accuracy is limited by detector response drifts and slight pointing offsets arising from the standard 1.2" (1-sigma) pointing error occurring within each and every observation. These limit both the absolute flux accuracy and relative accuracy within a band. Various pipelines deal better with these than others (see the advice in the PACS Data Reduction Guide for spectroscopy) but they can never be entirely negated. Hence the calibration uncertainty for any particular observation is a combination of the general calibration uncertainties (given in the PACS Observers Manual), the noise on the spectrum (explained in more detail in the PDRG chp 7.6), and the "activity" during any single observation.

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   * Line flux correction due to strong wings in the instrumental profile (IP)*
       Pre-flight ground-based monochromatic measurements indicated the PACS spectrometer instrumental profile distributes measurable power in spectral line wings. The effect is below ~10% and only noticeable for wavelengths longer than ~150 micrometers. Future HIPE releases will provide a correction factor to apply on a Gaussian fit in order to compensate for line power lost in the IP wings.
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PACS chopped line scan and high sampling range scan AOT release note: 19 Jan 2010 

PACS Wavelength Switching AOT release note: 20 Jan 2009

PACS SED and large range scan AOT release note: 10 Mar 2010

PACS Unchopped Mode AOT Release Note: 20 Sep 2010
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• In order to obtain the best possible Level 2 SPIRE photometry data, the observations might have to be reprocessed with the latest HIPE User Release.

• • For the definitions of the new product levels, introduced with HIPE v11, see The SPIRE Data reduction Guide, sections 3.2.3 and 3.2.4
  • These new levels will be available in the Herschel Science Archive when the observations will be bullk-reprocessed with HIPE v11. The useful user script Photometer_MapMerge.py can be used to make level 2.5 (parallel mode) or level 3 (mosaic) maps, see Section 5.8.3 in the SPIRE Data Reduction Guide.

• • Please note that there was a bug in the destriper task included in HIPE 9.0 that may affect your final map, especially if there are bright objects in the observed field. This has been corrected since HIPE 9.1. If your observation falls in the mentioned category, you are strongly advised to update your HIPE installation.
  • In HIPE 10.0 the flagging of thermistor jumps in the level 0.5 to 1 data reduction is not set properly. This induces the destriper to work improperly and to leave stripes in the final map. It has been solved starting with HIPE 10.1.

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      * Most of the stripes that are present in the final maps are due to a combination of thermal drifts (which in few cases are not efficiently removed) and median baseline subtraction. A similar effect is caused by very bright sources: in this case, the problem resides in the median baseline subtraction only. Suggested solutions:
         * switch to a baseline subtraction using a polynomial fitting using the optional task baselineRemovalPolynomial. If there are no jumps in the timelines, you may also try to run the baseline removal on the entire timeline;
         * in the case of bright sources, you may try to mask them before running the baseline removal (either median or polynomial): you can use this script as a template
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<--   * Thermistor jumps*
       As of HIPE 6.0.3, a new module together called signalJumpDetector in place to identify the jump and to exclude the affected thermistor(s). 
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• • The cooler temperature variations, as explained in greater details in the SPIRE Data Reduction Guide, section 6.4, can affect observations performed soon after the cooler recycle. The steep rise of the sub-K detector temperature is also known as the cooler burp and there is a quality flag coolerBurpDetected in HIPE v11 or later that indicates if the observation was performed during this period.
    The current list of observations known to have cooler temperature effects is here. Note that not all observations in this list raised the coolerBurpDetected flag.

<--   * WCS in 3-colour images*
       In all observation reduced with HIPE 8, the task createRgbImage puts wrong WCS in the output. Instead of using the WCS provided by the WCS input parameter, this task uses the WCS of one of the input images. This has been fixed in HIPE 9
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• • The extended calibrated maps (extdPxW in level-2, 2.5 or 3) incorporate zero level offsets derived from Planck-HFI. For small size SPIRE maps, smaller than ~30 arcmin, the zero-offset can be rather uncertain, due to the large Planck beam (8 arcmin). In such cases the interpretation of the zero offset as the absolute zero level must to be treated with extreme caution.

• For more information check the SPIRE Wiki page, SPIRE User's Manuals and/or contact the HSC helpdesk.

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SPIRE Point Source Mode release note: 30 Apr 2010 
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• In order to obtain the best possible Level 2 SPIRE FTS data, the observations should be reprocessed with the latest HIPE User Release.

• Extended calibrated spectra and spectral cubes: all extended calibrated spectra, including the spectral cubes as these are built by extended calibrated spectra, are affected by a missing correction for the far-field feedhorn efficiency. This correction is significant - a factor of 1.3-1.5 in SSW and 1.3-2.2 in SLW, as shown in the figure. More details on this critical problem will be available in a dedicated paper (Valtchanov et al, in preparation).

• Faint point source observations: if the SSW and SLW bands do not match up for a source that is known to be a point source, observers are recommended to run the background subtraction script in HIPE - more details are in the SPIRE Data Reduction Guide. If this doesn't solve the problem, the observer is encouraged to contact the HSC helpdesk or the FTS User Support Group.

• • Very small repetition numbers (e.g. 2 or 4) make 2nd level deglitching, which is based on a statistical outlier criterion, more challenging. The deglitching module may either not identify a glitch at all or it may not remove it completely. In cases where the glitch is located within the double-sided portion of the interferogram, the additional energy from the glitch will translate into artefacts of the continuum level. This kind of problem can be identified by inspecting all detectors from all scans in the level-1 spectral products. For some detectors, one or several scans may appear to be outliers. As a work-around, it is recommended to reprocess the data with a lower thresholdFactor when calling deglitchIfgm(). If the problem persists, the identified detector should be removed from the applicable scan in the SDI product.
    (NB: This affects HIPE 6 and higher)

• • If you know that the line you wish to measure is unresolved then you may want to fix the line width to the instrumental line width. For the Sinc model, implemented in the SpectrumFitterGUI you should put the Sinc width equal to resolution/π, which, for HR is 1.2/π = 0.382 GHz.

• • If your level-2 spectra show characteristic jumps at ~1250 GHz and ~750 GHz, and the spectra from the two bands SSW and SLW do not match, then your target is extended or semi-extended in the SPIRE beam. You need to use the semi-extended correction tool (SECT) available since HIPE v10. Check the the SPIRE Data Reduction Guide (SDRG).

• • For observations before OD1000 there could be an erroneously raised or a missing flag RADECACC. This flag is calculated as the difference between the observer requested target coordinates (kept in a metadata raNominal, decNominal) and the average pointing of the telescope during the observation (excluding the slew). This is an indicator of the pointing accuracy of the observation. If greater than 2.2" then RADECACC is raised in the QC context. The calculation of the average (ra, dec) during the observation does not take into account the known offset of 1.7" of the BSM home position for OD < 1000 and consequently observations with better pointing than 2.2" may be flagged and vice versa, observations at more than 2.2" may not be flagged. If you want to check the pointing offset with respect to the requested target coordinates then you should use the pointing information for the central detector SSWD4 in the level-2 context.
    A new quality parameter raDecOffset is introduced in HIPE v13, in level-2 products, which contains the correct offset between the raNominal, decNominal and ra,dec for the FTS central detector.

• • During the first few hours after the cooler was recycled the bolometers' temperature (the sub-K temperature) undergoes a steep rise before it reaches a stable plateau. Observations during this period suffer overcorrection of the instrument/telescope emission. This is more significant for faint targets and can be identified as an unphysical slope of the SLW spectrum, with an important negative gap in the region that overlaps with SSW (see the Figure). One way to check if your observation is within this problematic category is to get the median sub-K temperature for the first building block: print MEDIAN(obs.level0_5.get(0xA1060001).nhkt['signal']['SUBKTEMP'].data), where obs is the pre-loaded observational context. If the result is less than 0.2869 K then the observation is affected by this.
    This effect is fixed in HIPE v13.

<--  * FTS Array footprint user script*
       For very large area maps the script produces wrong overlay (offset from the real position) if the default map projections (tangential) is used. The workaround is to use smaller map where the tangential projection centre is near the FTS target position.
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• • For more information check the SPIRE Manuals and/or contact the HSC helpdesk.

• • From HIPE 13 onwards, automatic estimates of the spectra noise rms are provided to the users in the trendAnalysis > Statistisc context - these are based on an upgraded version of the task mkRms (see also the HIFI pipeline specficication document). Those estimates are in particular used to raise, or not, flags informing about whether the data are under-performing in terms of radiometric noise with respect to the theoretical predictions used at the time of the proposal. Because the noise estimate relies on the efficiency of automatically masking lines that may be present in the data, there can exist circumstances in which this masking in sub-optimally performed, therefore leading to inaccurate noise estimate, and possible false positives in the raised flags. Users should be aware of this limitation and, if necessary, cross-check the reliability of certain flags related to those noise figures through their own estimates.

• • The doGridding task in the HIFI pipeline is responsible for convolving the spectral datasets acquired in an OTF or DBS Raster mapping observation into a spectral cube with a specified pixel scale, which by default should match how the scan lines and readout points within each line were spaced during the observation. The scheme of signal filtering and interpolation to put the data on the specified grid may affect the overall flux conservation, at a level which is low but you should be aware of. For example, the total signal summed from a spectral cube produced using a Gaussian filter over the datasets of a Nyquist-sampled OTF map is generally < 1% lower than the sum of the signal taken directly from the input datasets (the Level 2 HTP datasets) before convolution. A part or all of this slight mismatch may be on the assumed versus actual beam shape at the observed frequency. If you wish to put the map on a coarser grid, effectively reducing the spatial resolution to a wider beam in order to match another observation, then the flux losses become more noticeable. Doubling the pixels sizes from their default (native map point spacing) can reduce the total flux by as much as 10%, accompanied by an increase in baseline RMS noise. The effect is more prevalent in OTF maps than DBS Raster, and in addition to deviations from ideal beam shape characteristics becoming more important, the filtering and interpolation method, and parameter values can be influential. No changes to the doGridding algorithm are planned, and this issue applies to all HIPE versions.

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PACS Spectroscopy AOR Update Guide for Routine Phase Observations: 10 Mar 2010
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<-- PACS Spectroscopy Performance and Calibration: 11 Mar 2010 

PACS Photometer Point Spread Function (PSF): 03 Nov 2010 
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*  Set ALLOWTOPICCHANGE = DpMgGroup, HscCommunitySupportGroup
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Temporary messages

Temporary messages

• • The PACS spectrometer flux calibration accuracy is limited by detector response drifts and slight pointing offsets arising from the standard 1.2" (1-sigma) pointing error occurring within each and every observation. These limit both the absolute flux accuracy and relative accuracy within a band. Various pipelines deal better with these than others (see the advice in the PACS Data Reduction Guide for spectroscopy) but they can never be entirely negated. Hence the calibration uncertainty for any particular observation is a combination of the general calibration uncertainties (given in the PACS Observers Manual), the noise on the spectrum (explained in more detail in the PDRG chp 7.6), and the "activity" during any single observation.