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NASA software strips glare from simulated Roman images

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A galaxy’s faint outer edge can be hidden by a bright glint created inside the telescope that is supposed to observe it. NASA Ames’ ROSALIA software is designed to predict and remove that unwanted light from images made by the Nancy Grace Roman Space Telescope, which is set to launch on Aug. 30.

The problem is not a single kind of glare. Photons scattering inside Roman’s optical system can create artifacts that resemble real planets or nebulae, while a diffuse background can mask the darkest regions of the universe. Zodiacal light — sunlight scattered by interplanetary dust in our solar system — adds another layer of contamination.

ROSALIA, short for Roman Sky Analyst for Low Surface Brightness Imaging and Astronomy, will process images from Roman’s Wide Field Instrument, its camera for wide, high-resolution views in optical and near-infrared light. The software can also help astronomers adjust observation plans to limit glints before they contaminate a science target.

In NASA simulations, the team processed views of two interacting galaxies by removing four types of glare: zodiacal light, thermal background, stray light and stellar emission. The resulting images show sharper, cleaner structures and faint emissions at galaxy edges, where clues to cosmic history may be found. The images remain simulations, not observations from the telescope in space.

So what changes in practice? If ROSALIA performs as intended once Roman begins observing, the cleaner images could help astronomers characterize low-surface-brightness structures, including dim outskirts and diffuse regions. That could improve Roman’s ability to study how galaxies formed and grew, alongside its investigations of dark energy, dark matter and planets beyond the solar system. The software was developed by NASA Ames with NASA’s Goddard Space Flight Center and IPAC/Caltech; its performance on real data is still ahead.

four types of glareContaminants removed in NASA’s simulated Roman image processing

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