Tangential Velocity of the Dark Matter in the Bullet Cluster from Precise Lensed Image Redshifts
Sandor M. Molnar (1), Tom Broadhurst (2,3), Keiichi Umetsu (4), Adi, Zitrin (5), Yoel Rephaeli (6,7), Meir Shimon (6) ((1) Leung Center for, Cosmology, Particle Astrophysics, National Taiwan University, Taiwan,, R.O.C. (2) Fisika Teorikoa, Zientzia eta Teknologia Fakultatea

TL;DR
This paper proposes a method to measure the tangential velocity of the dark matter in the Bullet Cluster through precise redshift differences in multiply-lensed images, potentially providing direct insights into cluster dynamics and dark matter behavior.
Contribution
It introduces a novel approach to measure the tangential velocity of galaxy clusters using lensing-induced redshift differences, supported by simulations and observational data.
Findings
Predicted redshift differences up to ~0.5 km/sec for specific lensed images.
Method feasible with ALMA and advanced optical-IR spectrographs.
Potential to directly measure cluster tangential velocities and resolve tensions with LCDM.
Abstract
We show that the fast moving component of the "bullet cluster" (1E0657-56) can induce potentially resolvable redshift differences between multiply-lensed images of background galaxies. The moving cluster effect can be expressed as the scalar product of the lensing deflection angle with the tangential velocity of the mass components, and it is maximal for clusters colliding in the plane of the sky with velocities boosted by their mutual gravity. The bullet cluster is likely to be the best candidate for the first measurement of this effect due to the large collision velocity and because the lensing deflection and the cluster fields can be calculated in advance. We derive the deflection field using multiply-lensed background galaxies detected with the Hubble Space Telescope. The velocity field is modeled using self-consistent N-body/hydrodynamical simulations constrained by the observed…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
