About This Article
In this STAN, the STIS Team presents a new CCD cosmic ray monitor, as well as updates to the latest version of the STIS Data Handbook, a new Jupyter notebook on Low Count Uncertainties in STIS, and an instrument science report on Updating the Sensitivity Curves of the STIS Echelles (Post-SM4).
New STIS CCD Cosmic Ray Monitor
The STIS team has developed a new monitor for identifying STIS CCD spectroscopic datasets that are potentially impacted by a specific cosmic ray removal failure. As described in section four of STIS ISR 1998-22, an assumption of the cosmic ray removal algorithm is that sub-exposures set to be combined for cosmic ray removal (CR-SPLITS) are well registered. However, if the position of the spectrum on the CCD varies by more than ~0.1 pixels (~5 mas in unbinned pixels) between CR-SPLITS, the algorithm may flag valid data as cosmic rays in one or more CR-SPLIT subexposures.
This overflagging issue is independent of the slit width, as movement in the spatial direction alone has been found to trigger the failure. Furthermore, the exact way in which the cosmic ray algorithm responds to misaligned CR-SPLITS is dependent on the unique properties of each dataset, such as the SNR and number of CR-SPLITS, as well as the detailed behavior of the telescope position variations during and between exposures. It was therefore more appropriate to implement a monitor that can identify potentially affected datasets from the CR flagging statistics alone.
The landing page for the resulting monitor can be found at https://www.stsci.edu/~STIS/monitors/cosmic_rays/. The data for the monitor is organized in subpages by year. Once daily, the page for the current year is updated to include the results of any new spectroscopic CCD data that is associated with 1D spectra. As described in the methodology below, the monitor only displays (1) statistics and locations of pixels flagged as cosmic rays, and (2) information publicly available from the program’s Phase II file. Therefore, datasets under proprietary access are included as no information on collected counts is used or released by the monitor.
The methodology used by the monitor was described in section three of STIS ISR 2019-02, where the fraction of pixels within the spectral extraction region of a dataset flagged as cosmic rays is compared with the fraction of pixels flagged as cosmic rays outside the extraction region. The ratio of these values is a simple metric to test if spectroscopic data was preferentially rejected, with values greater than ~2 being considered over-flagged. The monitor allows for easy access to this ratio, alongside interactive plots of the pixel locations of cosmic rays, and the frequency each pixel was flagged across a set of CR-SPLITS.
Some guidelines on how to correct for this behavior are given in STIS ISR 2019-02, but mitigations generally involve re-reducing the data with custom cosmic ray rejection thresholds using the stistools Python package function stistools.ocrreject(). Datasets affected by this issue are generally not eligible for repeats unless the misalignment is so severe that even custom-reduced data do not meet the science needs of the program. In these cases, a Hubble Observation Problem Report (HOPR) can be submitted detailing the issue and justifying why the data do not meet the science goals of the program.
The functionality used in the monitor will be implemented in the stistools Python package in the near future as stistools.ocrreject_exam(). An ISR with more detail on the internal workings of the monitor alongside specific examples of correcting for cosmic ray over rejection will also be published. If you require more assistance with custom cosmic ray rejections for data that is affected by this issue, contact the STIS help desk via hsthelp.stsci.edu.
STIS Data Handbook Updates
The STIS team has published a new version of the STIS Data Handbook that can be found here: STIS Data Handbook Version 8.0 .
The updates include the following:
- Added a number of more recent milestones in STIS operations/calibrations (post 2017).
- Removed references to IRAF/PyRAF throughout, and updated where necessary to analysis like removing fringes using the new Python
stistoolsand new Jupyter notebooks developed by the STIS team: https://github.com/spacetelescope/hst_notebooks/tree/main/notebooks/STIS. - A new section on Hubble Advanced Spectral Products (HASP) and notebooks in Section 3.7.
Recent STIS Documentation
New Jupyter Notebook on Low Count Uncertainties in STIS
We are pleased to announce a new Jupyter Notebook describing how to address measurement uncertainties in the very low count-rate regime. At low count rates, e.g., very faint UV continua with the MAMA detectors, the normal “root-N” approximation for the Poisson error breaks down. In the Notebook, we look at where and why the root-N approximation breaks down, how to calculate appropriate Poisson confidence intervals using Astropy, and how to apply these confidence intervals to HST/STIS observations. We also include a discussion of a known software bug currently being fixed caused by Poisson confidence interval calculations in the stistools inttag routine, used to split TIME-TAG observations into sub-exposures.
In addition, a new STIS Instrument Science Report presents updates on the sensitivity curves of the STIS echelles, found below:
ISR 2024-04: Updating the Sensitivity Curves of the STIS Echelles (Post-SM4)
Svea Hernandez, TalaWanda Monroe, Joleen K. Carlberg
The STIS team re-derived on-orbit sensitivity curves for the echelle modes for post-servicing mission 4 observations using the standard DA white dwarf G191-B2B. These new updates relied on the recent CALSPECv11 models, which introduced improvements in the fluxes of the primary standard stars of the order of ~1-3% depending on the wavelength of interest. As part of this effort, the team also released new blaze shift coefficients and echelle ripple tables. We present a detailed description of the procedures followed in the derivation of these new throughputs and the accompanying updates.