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JWST Lensed quasar dark matter survey II: Strongest gravitational lensing limit on the dark matter free streaming length to date

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arxiv 2405.01620 v1 pith:3IZTRBNJ submitted 2024-05-02 astro-ph.CO

JWST Lensed quasar dark matter survey II: Strongest gravitational lensing limit on the dark matter free streaming length to date

classification astro-ph.CO
keywords darkdustmatterwarmlimitmassmeasurementsmodel
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This is the second in a series of papers in which we use JWST MIRI multiband imaging to measure the warm dust emission in a sample of 31 multiply imaged quasars, to be used as a probe of the particle nature of dark matter. We present measurements of the relative magnifications of the strongly lensed warm dust emission in a sample of 9 systems. The warm dust region is compact and sensitive to perturbations by populations of halos down to masses $\sim 10^6$ M$_{\odot}$. Using these warm dust flux-ratio measurements in combination with 5 previous narrow-line flux-ratio measurements, we constrain the halo mass function. In our model, we allow for complex deflector macromodels with flexible third and fourth-order multipole deviations from ellipticity, and we introduce an improved model of the tidal evolution of subhalos. We constrain a WDM model and find an upper limit on the half-mode mass of $10^{7.6} M_\odot$ at posterior odds of 10:1. This corresponds to a lower limit on a thermally produced dark matter particle mass of 6.1 keV. This is the strongest gravitational lensing constraint to date, and comparable to those from independent probes such as the Ly$\alpha$ forest and Milky Way satellite galaxies.

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Cited by 4 Pith papers

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  2. The free-streaming length of dark matter from JWST observations of 28 strong gravitational lenses

    astro-ph.CO 2026-06 unverdicted novelty 6.0

    JWST lensing data on 28 systems constrain dark matter free-streaming length to below 6-7 kpc and thermal relic mass above 6.5-7.4 keV, consistent with cold dark matter predictions.

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