Freezing in, heating up, and freezing out: predictive nonthermal dark matter and low-mass direct detection View Full Text


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Article Info

DATE

2018-10

AUTHORS

Gordan Krnjaic

ABSTRACT

Freeze-in dark matter (DM) mediated by a light (≪ keV) weakly-coupled dark-photon is an important benchmark for the emerging low-mass direct detection program. Since this is one of the only predictive, detectable freeze-in models, we investigate how robustly such testability extends to other scenarios. For concreteness, we perform a detailed study of models in which DM couples to a light scalar mediator and acquires a freeze-in abundance through Higgs-mediator mixing. Unlike dark-photons, whose thermal properties weaken stellar cooling bounds, the scalar coupling to Standard Model (SM) particles is subject to strong astrophysical constraints, which severely limit the fraction of DM that can be produced via freeze-in. While it seems naively possible to compensate for this reduction by increasing the mediator-DM coupling, sufficiently large values eventually thermalize the dark sector with itself and yield efficient DM annihilation to mediators, which depletes the freeze-in population; only a small window of DM candidate masses near the ∼ GeV scale can accommodate the total observed abundance. Since many qualitatively similar issues arise for other light mediators, we find it generically difficult to realize a viable freeze-in scenario in which production arises only from renormalizable interactions with SM particles. We also comment on several model variations that may evade these conclusions. More... »

PAGES

136

References to SciGraph publications

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URI

http://scigraph.springernature.com/pub.10.1007/jhep10(2018)136

DOI

http://dx.doi.org/10.1007/jhep10(2018)136

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https://app.dimensions.ai/details/publication/pub.1107798865


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    "description": "Freeze-in dark matter (DM) mediated by a light (\u226a keV) weakly-coupled dark-photon is an important benchmark for the emerging low-mass direct detection program. Since this is one of the only predictive, detectable freeze-in models, we investigate how robustly such testability extends to other scenarios. For concreteness, we perform a detailed study of models in which DM couples to a light scalar mediator and acquires a freeze-in abundance through Higgs-mediator mixing. Unlike dark-photons, whose thermal properties weaken stellar cooling bounds, the scalar coupling to Standard Model (SM) particles is subject to strong astrophysical constraints, which severely limit the fraction of DM that can be produced via freeze-in. While it seems naively possible to compensate for this reduction by increasing the mediator-DM coupling, sufficiently large values eventually thermalize the dark sector with itself and yield efficient DM annihilation to mediators, which depletes the freeze-in population; only a small window of DM candidate masses near the \u223c GeV scale can accommodate the total observed abundance. Since many qualitatively similar issues arise for other light mediators, we find it generically difficult to realize a viable freeze-in scenario in which production arises only from renormalizable interactions with SM particles. We also comment on several model variations that may evade these conclusions.", 
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Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1007/jhep10(2018)136'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1007/jhep10(2018)136'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1007/jhep10(2018)136'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1007/jhep10(2018)136'


 

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