How Galaxies Give Themselves Away express

Original: "Extracting intrinsic alignments in the Dark Energy Survey's year 1 data, using the self-calibration method and LSST-DESC tools"
arXiv:2601.10314 · 2026-01-15 · CC BY 4.0 · 1 min
Subtle distortions in the light from distant galaxies help reveal invisible dark matter, but the galaxies themselves can muddy the picture.

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When light from a distant galaxy travels toward us, dark matter along the way bends the rays slightly, like imperfect glass. Astronomers measure these distortions to understand where the invisible mass lurks. But galaxies also have their own, "intrinsic" distortions: they align not randomly but along the invisible threads of the cosmic web. It's like trying to gauge the curvature of a window pane when the panes themselves are slightly warped to begin with.

Scientists from the Dark Energy Survey collaboration tested a "self-calibration" method designed to separate intrinsic distortions from those caused by dark matter. They applied it to real telescope data from the first year of observations. For distant galaxies, a signal emerged, but for nearby ones, the results were ambiguous. The likely culprit: errors in estimating galaxy distances, because the self-calibration method is highly demanding on the accuracy of those estimates.

To look billions of light-years away, astronomers gauge distance by a galaxy's color. Even a slight error in color can place a galaxy in the wrong "layer" of the universe.

The authors showed how different ways of reconstructing the distance distribution affect the outcome. The same set of galaxies can yield either a faint hint of a signal or none at all. This is an important step for future sky surveys that will gather hundreds of times more data.

Intrinsic galaxy distortions were first noticed back in 2000, yet they remain one of the main obstacles to accurately mapping dark matter.

Scientists
Fritz ZwickyVera RubinChristian DopplerTheodore LymanDavid CharbonneauNancy Grace Roman
Concepts
vera rubin observatory lsst desi lz binning