When Streams Curve Away: a Test of Dark Matter from Extragalactic Stellar Stream Populations

N. Starkman, J. Nibauer, S. Pearson, S. Wu‡, L. Necib

The Astrophysical Journal·2026submitted

When Streams Curve Away: a Test of Dark Matter from Extragalactic Stellar Stream PopulationsWhen Streams Curve Awaysubmitted
Likelihood ratio between CDM and SIDM plotted against the observed fraction of streams with a convex segment, for catalogs of 100, 1,000 and 10,000 streams. The curves steepen with catalog size; at 10,000 streams, either predicted rate is strongly favored.

The Astrophysical JournalApJ·2026submitted·N. Starkman, J. Nibauer, et al.N. Starkman, J. Nibauer, S. Pearson, et al.N. Starkman, J. Nibauer, S. Pearson, S. Wu‡, L. Necib·The Astrophysical JournalApJ·2026submitted

The Astrophysical JournalApJ·2026submitted

How often stellar streams curve away from their host galaxy’s center can tell cold from self-interacting dark matter at up to 5σ, with catalogs the size Euclid, Rubin and Roman will provide.

How often stellar streams curve away from their host galaxy’s center can tell cold from self-interacting dark matter at up to 5σ, with catalogs the size Euclid, Rubin and Roman will provide. In a spherical halo a stream cannot curve this way in projection; in a triaxial halo, which cold dark matter predicts, it can. The test needs only the stream’s projected track and the host’s center: no distances, velocities or model of the stream’s progenitor.

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Paper Figure 6

Paper Figure 6. Likelihood-ratio comparison of CDM and SIDM from the observed rate , the streams containing a convex segment out of a catalog of , for (solid). The dashed curve is the streams projected for Euclid by Starkman et al. (2026). Curves use the predicted rates . The statistic measures relative model preference: positive values favor CDM (blue quadrant), negative values favor SIDM (green quadrant), and larger absolute values mean stronger preference. Shading marks the quadrant in which each model is favored; vertical lines mark the two predicted rates, from Figure 5. With streams, a rate near either prediction begins to favor its corresponding model; streams strongly distinguish between the two.