Instrument Science Reports (ISRs)

WFC3/UVIS image headers contain time-dependent inverse sensitivity values that may be used to properly convert detector count rates into physical units as the detector sensitivity changes over time. In-flight monitoring of CALSPEC standard stars is used to define these inverse sensitivity values for UVIS1 and UVIS2. With additional data from 2019 to 2026, we compute new linear best-fit solutions to the ratio of observed count rates to synthetic effective fluxes (obs/syn) derived using SEDs from CALSPEC. In addition, we incorporate revised encircled energy (EE) values from O’Connor et al. (2026), which introduce a scalar offset to the inverse sensitivity values for several filters. Errors in the linear fit coefficients are significantly improved with additional data, especially for UVIS2. We observe a wavelength dependence in the loss rates between 2011 and 2026, with UV filters losing sensitivity at roughly twice the rate of red filters (e.g. 0.2%/year in F225W, 0.1%/year in F814W). For a given dataset, the new solutions improve the agreement in the observed count rates (and the calculated effective fluxes) across the two detectors by 1-2% for some filters. Using the new linear fits to correct the observed photometry, we find the RMS scatter of the mean obs/syn flux ratio improves from 0.5% on each detector to 0.3% for UVIS1 and 0.2% for UVIS2. These updates may be important for high-precision photometry—such as stellar SED modeling—where the target spans both detectors, or for observations of a target acquired over several years. An updated photometry reference file will be delivered later in 2026 for reprocessing all archival UVIS images. Until then, we provide a workflow for manually correcting the observed count rates in calibrated images.

We present updated encircled energy (EE) curves for a subset of UVIS filters. These are derived from a reanalysis of the drizzled Point Spread Function (PSF) data underlying the current EE calibration together with new measurements from deep observations of the PSF wings. Improved centroiding and analysis techniques applied to the drizzled PSFs produce more accurate EE values at small radii (r ≤ 10 pixels), bringing the results into closer agreement with a large archival PSF study (Huynh et al. 2025). At large radii, we leverage deep observations of the PSF wings in six filters and compare the fraction of light between 2′′ and 6′′ with predictions from an optical model of the PSF (Hartig 2009). For filters with pivot wavelengths ≳ 4000 Å, the model agrees with the empirical data, but over-estimates the EE for UV filters by ∼ 0.5% at 2′′. The revised EE solutions affect the UVIS zeropoints, which are derived from aperture photometry in a 0.4′′ (10 pixel) radius and corrected to 6′′ using EE tables (Calamida et al. 2022). Overall, the impact is small; the EE at 0.4′′ is larger by ≳ 0.5% (0.005 mag) for several filters (F218W, F225W, F275W, F775W, F814W, F845M), especially for UVIS2. In contrast, the EE value is generally smaller at 0.4′′ for long-pass filters (F200LP, F350LP, F850LP), with F850LP differing by ∼ 2% (0.02 mag). Updated EE tables will be delivered together with a revised set of UVIS inverse sensitivity tables and zeropoints later in 2026. In the interim, we provide EE tables for commonly used filters in Appendix A.

The WFC3/IR channel has been shown to lose sensitivity over time. The sensitivity loss rate has been quantified in past works and we extend those measurements into 2026 using photometry of uncrowded regions of star clusters 47 Tucanae and Messier 4 in the F110W and F160W filters. This study adds 4–7 additional visits since Bajaj et al. (2022) for each target/filter combination. Using F160W data of 47Tuc, we find that the IR channel continues to lose sensitivity at a rate of -0.07% ± 0.01% per year using the full dataset, and -0.06% ± 0.02% per year using only the first exposure of every visit. Using M4 data observed in F110W, we find a sensitivity loss rate of -0.13% ± 0.02% per year using the full dataset, and -0.07% ± 0.03% per year using just the first exposure of every visit. We find that the rate of sensitivity loss has decreased since the previous study. This likely stems from the inclusion of more recent visits that were designed to mitigate persistence effects. These results suggest that earlier observations, which were not intended for sensitivity measurements, may have overestimated the IR channel’s sensitivity due to the effects of persistence from bright sources. The IMPHTTAB reference file that contains the correction to the time-dependent sensitivity remains unchanged from the sensitivity measurements of this report.

The WFC3/IR channel has an innate non-linear response to incident photons, which is corrected for in the calwf3 pipeline with the NLINFILE reference file. The 2009 solution is based on an average polynomial correction for each IR quadrant and is found to be poorly constrained at high fluence levels (e⁻) approaching the saturation limit. Using a variety of image types, sources, and sample sequences, we test a new pixel-based linearity correction developed by Shenoy et al. (2025). In nearly all cases, the new correction improves the linearity at fluence levels higher than ∼50,000 e⁻, with improvements up to 7% for pixels with fluences approaching the saturation limit (∼80,000 e⁻) in the last ima reads. The pixel-based solution also significantly decreases the number of cosmic rays erroneously flagged (due to nonlinearity correction errors) during ramp fitting in calwf3, leading to improved photometric accuracy in the calibrated flt data and higher signal-to-noise ratios, particularly in Quad 1 (upper-left detector quadrant). Because the new solution tends to make sources brighter, we recalibrate the five HST flux standards used to compute the IR zeropoints and find a negligible impact (∼0.1–0.2%) on the published values by Calamida et al. (2024), smaller than the RMS dispersion (∼0.5%) in the observed to synthetic flux ratios for all five flux standards. The new NLINFILE 9au15283i_lin.fits was delivered to CRDS in October 2025 and will be used to reprocess all WFC3/IR imaging and grism observations in the MAST archive. An updated reference file a2412448i_lin.fits was delivered in February 2026, improving the results at the highest fluence levels by a few tenths of a percent. Please consult the Addendum for details.

The current non-linearity correction for the Wide Field Camera 3 Infrared (WFC3/IR) channel is based on ground-based data acquired during WFC3’s Thermal Vacuum 3 (TV3) testing campaign. In the current reference file, the correction coefficients derived for each pixel are averaged over each of the four detector quadrants. In this work, we compute a new pixel-based non-linearity correction using in-flight calibration observations with the internal tungsten lamp flats acquired between 2011 and 2013. We derive the new correction coefficients by fitting a third-order polynomial to the accumulated signal “up-the-ramp” for each pixel. Approximately 2% of IR detector pixels are flagged as bad, and a solution cannot be computed. For these, we use the quadrant averages of the new correction coefficients. An accompanying report (Huynh et al. 2025) provides detailed testing results using both internal flats and external science targets acquired in a variety of observing modes. The report highlights improvements in photometry derived from “ flt.fits” data products calibrated using the new reference file, with the largest improvement for pixels with fluence levels approaching the full well limit of ∼80,000 e⁻. A new NLINFILE reference file was delivered in October 2025 and will be used to reprocess all WFC3/IR imaging and grism observations in the MAST archive.

HST is designed to use two guide stars in the fine-guidance sensors (FGSs) to maintain its pointing and tracking during exposures. The primary guide star (GS) holds the boresight fixed and the secondary star keeps the orientation fixed. However, HST is also able to track using only a single GS by fixing the boresite on one star and maintaining the orientation using the available gyro(s). We evaluate the pointing quality achieved in this latter case, when one GS and one gyro (RGM, a.k.a., reduced gyro mode) are used. We find that in 1GS-RGM, there is indeed more drift during the course of an orbit than when two guide stars are used, but the drift is much smaller than was seen in previous times of failing gyros. We quantify the 1GS-RGM drift seen in available archival GO data and in images from a test calibration program and find that (a) for exposures < 500 sec, the PSF quality in 1GS is indistinguishable from that of 2GS and (b) over the course of full orbits (~2500 sec), the drift in four of five cases was ≲ 0.2 pixel and ~0.4 pix in the other case. Such a drift is marginally detectable in observations, but it should have a marginal impact on most science programs, since the variation in the PSF caused by drift is smaller than the PSF variations with focus and with location on the detector. For observers who wish to correct drift effects, we show that use of a perturbed PSF during post-acquisition data analysis removes essentially all astrometric residuals, even for drift levels up to ~0.5 pix, as well as most of the photometric residuals.

The calwf3 software for WFC3/UVIS utilizes a reference file to flag pixels that are saturated beyond their full-well depth. Previously, this was accomplished using a constant threshold of 65,500 e- across the entire detector. In this study, we retrieved ∼1 million stars from the Mikulski Archive for Space Telescopes (MAST) to determine the flux level at which the Point Spread Function begins to flatten, which occurs as the central pixel saturates. We quantified the saturation limit as a function of position on the detector in 1,024 discrete regions, and interpolated to a pixel-by-pixel saturation map to construct a spatially-variable saturation map reference file that is now implemented in the calwf3 calibration pipeline. We find the saturation varies by 13% across the UVIS detectors, from 63,465 e- to 72,356 e-. These values agree well with earlier studies using sparser datasets, with the current analysis leading to improved characterization on small scales. Critically, the revised saturation values are larger than the previous constant threshold over 87% of the UVIS detector, leading to the recovery of usable science pixels near bright sources. This update greatly improves the robustness of saturation flags in the Data Quality arrays of observations obtained with WFC3/UVIS, and users are encouraged to redownload their data from MAST to benefit from the improved flags.

In crowded fields, small-aperture photometry can reduce contamination errors from neighboring sources compared to larger aperture photometry. However, the UVIS encircled energy (EE) varies with detector position and focus variations on orbital timescales for aperture radii less than 10 pixels (∼0.4''). Using a set of focus-diverse empirical PSFs by Anderson (2018), we compute 2D spatial maps of the aperture correction between 5–10 pixels and find a maximum change of ∼0.01 mag over all focus levels for a given detector position. The upper-left and lower-right corners of the UVIS detector are more focus-sensitive than the rest of the field of view, where the mean correction is systematically ∼0.01 mag higher in Amp A for bluer filters (F275W, F336W, F438W) and ∼0.01 mag higher in Amp D for redder filters (F606W, F814W) at all focus levels. We test the new aperture correction maps in globular clusters, and we find reduced scatter, better agreement between the two CCDs, and a small shift in the absolute photometry when compared to a single (constant) aperture correction per image. These improvements are specific to photometry with apertures < 10 pixels in radius; results from larger apertures are not affected. Using published EE tables can introduce systematic uncertainties in absolute photometry due to its tendency to vary with detector position and focus level, with larger errors for smaller apertures. Users requiring photometric accuracy better than ∼1% for small apertures can use isolated stars in the individual FLT/FLC frames (or PSF cutouts at a similar detector position and focus level) to compute encircled energy corrections and accurately account for the amount of flux at radii larger than their photometric apertures.

We examine the relative offsets of the linear terms in the geometric distortion between WFC3/IR and the Gaia DR3 catalog using the Mikulski Archive for Space Telescopes (MAST) pipeline WFC3/IR to Gaia DR3 alignment solutions to assess temporal stability over the lifetime of the WFC3 instrument (2009-2024). We find a period of increased uncertainty and offsets in the rotation term between 2018 and 2021, as seen in a previous analysis of WFC3/UVIS linear geometric distortion (O’Connor et al., 2024), corresponding with a period of increased jitter. We find a similar pattern of increased uncertainty between 2018 and 2021 in the skew offsets to Gaia DR3, as well. We find no significant linear temporal evolution in the rotation, skew, or scale offsets between the WFC3/IR IDCTAB distortion solution and Gaia DR3 over the 16-year lifetime of the WFC3 instrument; however, we do see temporal evolution in the shift offsets (the difference -in pixels- between the IDCTAB and Gaia WCS positions), which are dominated by telescope pointing inaccuracy external to the WFC3/IR geometric distortion solution. For observers requiring high-precision astrometry, we continue to recommend that observers verify or improve image alignment using the tweakreg routine.

In this starter guide, we provide a high-level overview of analysis of WFC3/IR data available from the Mikulski Archive for Space Telescopes (MAST). We intend this guide as a starting point for users examining WFC3/IR data for the first time, or for those refreshing their memory on WFC3/IR data analysis. Therefore, we focus on the analysis of archival data, not preparing new observations. Three appendices include A) a summary of the instrument and an optical schematic, B) examples from the Exposure Time Calculator, and C) a glossary of uncommon acronyms. This report addresses only data from WFC3’s IR channel; not the UVIS channel.

In this report, we examine the behavior of Charge Transfer Efficiency (CTE) on the WFC3/UVIS detector over time as computed by the Extended Pixel Edge Response (EPER) technique, using internal calibration data acquired from 2009 through 2025. We find that the CTE has continued to decline as expected, with a steeper loss rate for lower signal levels. The lowest signal level (160 e-) has continued to decline at a rate of 0.0001 per year, with a total overall decline of 0.0015. Analyses from 2016 and 2020 found that the rate of decline was not well fit by a linear function. This report verifies the rate of decline is instead better fit by a quadratic function (which results in the smallest min. and max. residuals, on average) or a cubic function (which has the best “goodness of fit” χ² and R² values). We continue to see periodic oscillations of the residuals around all three fit lines (linear, quadratic, and cubic) on which we perform a Lomb-Scargle periodogram analysis of the residuals. We find a periodicity of about 8 years for the residuals around the linear fit lines and about 9 years for the quadratic and cubic fit lines.

Here we describe a Jupyter notebook demonstrating methods for the reduction and analysis of exoplanet transit observations taken with the WFC3/UVIS G280 grism. Released on Space Telescope’s hst notebooks GitHub repository, this notebook presents an example workflow for processing time-series observations taken with the G280 grism – from the calibrated flat-fielded spectra to transit light curves ready for fitting. The specific routines presented in the notebook are explained here, and are meant to highlight data reduction steps that users will typically apply to extract transit light curves. The steps include background subtraction, spatial and temporal cosmic ray correction, spectral trace fitting, spectral extraction, and light curve generation. The end products of the routines in the Jupyter notebook are the raw broadband and spectroscopic light curves, which can be ingested into publicly available light curve fitting tools to extract planetary transmission spectra.

We present new superdark calibration files for use with IR channel data from Wide Field Camera 3 (WFC3/IR) for HST Cycles 26-30, with all allowed observing modes. These superdarks incorporate five years’ worth of new IR dark exposures, and make use of updated bad pixel tables to more accurately represent the dark current in time-dependent hot pixel populations for data taken during those cycles. The files are available through the Calibration Reference Data System (CRDS) and have been used to reprocess affected datasets for new downloads from the Mikulski Archive for Space Telescopes (MAST).

We align more than 7,400 WFC3/UVIS exposures to the Gaia DR3 catalog to examine the time evolution of the linear terms (shift, rotation, scale and skew) of the geometric distortion solution between 2009 and 2022. We find small linear temporal changes in the scale and skew terms (less than 0.2 pixels in 13 years) which are generally dominated by intrinsic scatter (up to ±0.3 pixels). Concurrently, a larger filter-dependent offset in the scale term is observed, with a maximum difference of 0.3 pixels between F275W and F814W images at all epochs. A small rotation offset to Gaia of 0.003 ± 0.004 degrees is measured from 2009 to mid-2017, after which the offsets are as large as 0.01 degrees, with a large scatter. MAST pipeline processing includes an additional alignment step which corrects UVIS images for any residual linear terms with respect to Gaia DR3 when there are at least 10 matched sources. In addition to any pointing offsets, this step accounts for any evolution in the distortion linear terms described here. For observers requiring high-precision astrometry, we recommend using the tweakreg routine to realign images using a 4-parameter fit (x−shift, y−shift, rotation, and scale) or a 6-parameter fit (x−shift, y−shift, x−rotation, y−rotation, x−scale, and y−scale) depending on the number of matched sources. We provide links to DrizzlePac tutorials for improving both absolute and relative astrometry in WFC3 images.

We present a process for designing and training a convolutional neural network to classify detections from star finding algorithms in the exposure (FLT/FLC) frame for WFC3/UVIS images. This network can be used to filter out common spurious detections (cosmic rays or diffraction spikes), which are often present in imaging data where the point spread function is under or critically sampled (FWHM = 2 pix). The neural network achieved high accuracy for correctly identifying stars (96%). Falsely detected sources in catalogs (a common side effect of DAOFind-like algorithms) can cause incorrect matches and resulting astrometric transforms. Eliminating false detections can provide significant improvements to image alignment workflows and clean photometric catalogs. We also present caveats of this method, as well as general considerations for building neural networks for use in astronomical data analyses.