REVIEW 2 cited by
Constraints on Dark Matter from Dynamical Heating of Stars in Ultrafaint Dwarfs. Part 1: MACHOs and Primordial Black Holes
Not yet reviewed by Pith; the record is open.
This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.
SPECIMEN: schema-true, not a live event
T0 review · schema-true
One-sentence machine reading of the paper's core claim.
pith:XXXXXXXX · record.json · timestamp
abstract
We place limits on dark matter made up of compact objects significantly heavier than a solar mass, such as MACHOs or primordial black holes (PBHs). In galaxies, the gas of such objects is generally hotter than the gas of stars and will thus heat the gas of stars even through purely gravitational interactions. Ultrafaint dwarf galaxies (UFDs) maximize this effect. Observations of the half-light radius in UFDs thus place limits on MACHO dark matter. We build upon previous constraints with an improved heating rate calculation including both direct and tidal heating, and consideration of the heavier mass range above $10^4 \, M_\odot$. Additionally we find that MACHOs may lose energy and migrate in to the center of the UFD, increasing the heat transfer to the stars. UFDs can constrain MACHO dark matter with masses between about $10 M_\odot$ and $10^8 M_\odot$ and these are the strongest constraints over most of this range.
Forward citations
Cited by 2 Pith papers
-
Dynamical Evolutions in Globular Clusters and Dwarf Galaxies: Conduction Fluid Simulations
A two-fluid conduction model of stars plus collisionless dark matter predicts that most globular clusters have undergone mass segregation and core collapse on a Hubble time, whereas most dwarf galaxies have not.
-
DETONATE: A Benchmark for Text-to-Image Alignment and Kernelized Direct Preference Optimization
A kernel-based variant of direct preference optimization and a 100K-pair bias benchmark claim to improve text-to-image safety by separating safe and unsafe image representations during training.
Discussion (0). Continue with ORCID to comment.