Radiation damage to the Hubble Space Telescope during two Solar cycles, and correction of Charge Transfer Inefficiency using ArCTIc

TL;DR

This work addresses Charge Transfer Inefficiency (CTI) in the Hubble Space Telescope’s ACS/WFC caused by radiation damage in low-Earth orbit. It develops ArCTIc v7, a fast, physically grounded CTI-correction framework that models instantaneous capture and homogeneous release across trap species with a volume-driven CCD description, and calibrates it using warm-pixel EPER trails collected across 178 epochs from 2002–2025. The authors demonstrate near-complete CTI correction, removing about 99.5% of lifetime trailing (and 99.9% in the worst recent data), and reveal that trap-density growth tracks solar activity with an 18.5% modulation peaking about 430 days after solar minimum. They further analyze limitations, propose improvements (e.g., low-n_e well-filling), and provide open-source software to separate CTI calibration from correction, with implications for future missions such as Euclid.

Abstract

From 2002 to 2025, the Hubble Space Telescope's Advanced Camera for Surveys has suffered in the harsh radiation environment above the protection of the Earth's atmosphere. We track the degradation of its image quality, as Solar protons and galactic cosmic rays have damaged its photosensitive charge-coupled device (CCD) imaging sensors. The rate of damage in low Earth orbit is modulated by $18.5^{+4.5}_{-0.5}$ per cent during an 11 year Solar cycle, peaking $430^{+11}_{-5}$ days after Solar minimum as recorded in the number of sunspots. The type of damage is consistent with defects in the silicon lattice that have all stabilised into one of three configurations. We also present the open-source Algorithm for Charge Transfer Inefficiency correction (ArCTIc) v7. This models the (instantaneous or gradual) capture of photoelectrons into lattice defects, and their release after (a discrete set or continuum of) characteristic time delays, which creates spurious trailing in an image. Calibrated using the trailing of hot pixels, and applied during post-processing of astronomical images, ArCTIc can correct 99.5% of Charge Transfer Inefficiency trailing averaged over the camera's lifetime, and 99.9% of trailing in the worst-affected recent data.

Figures (8)

• Figure 1: An example HSTACS/WFC image to illustrate our typical data and the effects of CTI (quadrant D of an image taken on 2021 January 3, approximately 19 years after ACS was launched). The readout register is at the top of this image, above row 0. Electrons from the first rows of pixels undergo few transfers, encounter not many charge traps, and thus do not suffer much CTI trailing. Electrons from pixels further down the page undergo many transfers, so significant charge can be captured and later released by traps. This effect creates visible CTI trails in the upper zoom region and even worse trails in the lower zoom. The edge regions of low flux at the left and bottom of the image are the serial prescan and parallel overscan. That these virtual pixels should contain zero electrons in an image is a convenient validation and verification test for successful CTI correction.
• Figure 2: The same HST ACS image zoom regions of \ref{['fig:example_image_zooms']} after CTI correction with ArCTIc to remove the trails. The right panels show the difference between the original and corrected fluxes.
• Figure 3: An example of identified warm pixels, from the same ACS/WFC image as \ref{['fig:example_image_zooms']}, further zoomed in to the top-middle of the two regions shown in \ref{['fig:example_image_zooms']}, near and far from the readout register that is above row 0. Orange squares indicate candidate warm pixels, identified in this image alone. Red squares above white rectangles show the warm pixels that were identified consistently at the same location in at least 2/3 of the images from this epoch. White rectangles confirm the pixels extracted and averaged as CTI trails.
• Figure 4: Measured CTI trails $n_{\rm e}^\mathrm{trail}(\Delta y)$ in one example epoch on 2024 July 26; we have similar data in each of 178 epochs throughout the lifetime of ACS. Red points in each panel show the mean value of 12 pixels behind a warm pixel, minus 12 pixels in front; dotted red lines show an ArCTIc model simultaneously fitted to all panels (to be conservative, we here show a fit with most parameters fixed to values in \ref{['tab:arctic_params']} and only $\rho_{\mathrm{total}}$ free; see §\ref{['sec:calibrate_time_evol_physical']}). Open circles indicate negative points. Each panel averages trails from warm pixels of different brightness $n_{\rm e}^\mathrm{wp}$ (increasing left to right, starting at the $\sim$50 electron sky background and separated by values shown at the top) and distance from the readout register $y$ (increasing bottom to top, separated by values shown on the right). Black data points and dotted lines show measurements and the absolute value of the best-fit model (\ref{['eqn:exponential_model_rhotot']}) after correction.
• Figure 5: Selected data points from \ref{['fig:stacked_trails']}, rearranged to check that the functional form of (the first line of) \ref{['eqn:exponential_model']} is a good fit. Green/blue/black points show the value of the first/second/all pixels in a CTI trail, from trails in the top row of \ref{['fig:stacked_trails']} (in panel a) and in its ninth column (in panel b). The tenth column is similar but more noisy, and accounts for the upturn at the end of the black points in panel a.