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Evaporating the Milky Way halo and its satellites with inelastic self-interacting dark matter

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arxiv 1805.03203 v2 pith:SRE7UEI2 submitted 2018-05-08 astro-ph.GA hep-ph

classification astro-ph.GAhep-ph
keywords inelasticdarkmattercrosshaloself-interactingdensityelastic
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Self-interacting dark matter provides a promising alternative for the cold dark matter paradigm to solve potential small-scale galaxy formation problems. Nearly all self-interacting dark matter simulations so far have considered only elastic collisions. Here we present simulations of a galactic halo within a generic inelastic model using a novel numerical implementation in the Arepo code to study arbitrary multi-state inelastic dark matter scenarios. For this model we find that inelastic self-interactions can: (i) create larger subhalo density cores compared to elastic models for the same cross section normalisation; (ii) lower the abundance of satellites without the need for a power spectrum cutoff; (iii) reduce the total halo mass by about 10%; (iv) inject the energy equivalent of O(100) million Type II supernovae in galactic haloes through level de-excitation; (v) avoid the gravothermal catastrophe due to removal of particles from halo centers. We conclude that a ~5 times larger elastic cross section is required to achieve the same central density reduction as the inelastic model. This implies that well-established constraints on self-interacting cross sections have to be revised if inelastic collisions are the dominant mode. In this case significantly smaller cross sections can achieve the same core density reduction thereby increasing the parameter space of allowed models considerably.

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Forward citations

Cited by 6 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. OpenAlex reports about 88 citations worldwide. Full citation record

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  2. Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning

    astro-ph.CO 2019-09 conditional novelty 7.0 of 10

    A neural likelihood ratio estimator trained on simulated strong lensing images can infer the abundance and mass slope of dark matter subhalos from an ensemble of lenses.

  3. A Novel Implementation of Self-Interacting Dark Matter in AREPO

    astro-ph.CO 2026-07 accept novelty 6.5 of 10

    A dedicated-tree Monte-Carlo SIDM module in AREPO-2 conserves energy/momentum under multiple scatters, supports velocity-dependent and inelastic models, and runs with only modest overhead versus CDM except in late cor...

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    SIDM halos accelerate bar formation and growth in disk galaxies through enhanced angular momentum exchange, independent of core formation.

  5. Numerical evolution of self-gravitating halos of self-interacting dark matter

    astro-ph.CO 2025-06 conditional novelty 6.0 of 10

    A new simulation method efficiently evolves spherical self-interacting dark matter halos, reproducing core flattening and gravothermal collapse with orders-of-magnitude less computing power.

  6. Evolution of self-gravitating spherical dark-matter halos with and without new physics

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    A spherical-symmetry N-body algorithm, NSphere, quickly evolves dark matter halos, and finds that after sudden tidal stripping a halo relaxes to a density profile falling as r^-10.

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