Mapping the Hidden Streams of the Milky Way: Correcting Bias in Dark Matter Searches
Boone et al. (2025) develop a method to correct biases in stellar stream observations caused by uneven survey conditions in the Dark Energy Survey. Using synthetic stars from the Balrog tool, they refine measurements of stellar densities, demonstrating the method on the Phoenix stream. Their corrections remove false patterns and improve dark matter studies, offering an essential approach for future deep surveys like LSST.
Probing Hidden Galaxies: Tracing Dark Matter with the GD-1 Stellar Stream
Jacob Nibauer and collaborators analyzed the GD-1 stellar stream’s star motions to study invisible dark matter subhalos around the Milky Way. They found that the stream’s velocity dispersion is higher than expected, suggesting interactions with compact, dense dark matter clumps. Their models show that about 5% of the Milky Way’s mass is in these subhalos, possibly indicating self-interacting dark matter rather than the standard cold dark matter model.
How Binary Stars Complicate the Dark Matter Mystery in Tiny Galaxies
Gration and collaborators show that binary stars can skew measurements of ultrafaint dwarf galaxies by inflating their stellar velocity dispersions. Using simulations, they find unresolved binaries add significant “noise,” sometimes making globular clusters appear like galaxies. The effect is even stronger if the galaxies form fewer low-mass stars. Their work highlights the need to account for binaries when estimating galactic masses and testing dark matter theories.
A Pulsar Clue: Finding a Hidden Clump of Dark Matter Near the Sun
Chakrabarti et al. report the first detection of a dark matter sub-halo near the Sun using pulsar timing data. By analyzing excess acceleration in binary pulsars, they infer a compact dark object with a mass around 10 million solar masses. This finding supports ΛCDM predictions and opens a new method for probing dark matter in our Galaxy.
Unearthing the Dark Side: What Three Tiny Galaxies Reveal About Dark Matter
Hao Yang and colleagues studied the dark matter in three Milky Way dwarf galaxies using DESI data. They compared single- and two-population models, finding diverse inner dark matter profiles: Draco showed a cusp-like center, while Sextans and Ursa Minor leaned toward cores. Their results align with previous findings but also highlight uncertainties from data and modeling choices.
Haskap Pie: A Fresh Slice of Dark Matter Detection
Haskap Pie is a new halo-finding algorithm that combines several techniques to more accurately detect and track dark matter halos in simulations. It outperforms existing methods by better identifying subhalos, using efficient particle sampling, and tracking halos over time. This makes it a powerful tool for studying galaxy formation and cosmic structure.
Broken Expectations: How Modeling Assumptions Impact Our View of Dark Matter in Dwarf Galaxies
This study shows that common methods used to model dark matter in dwarf galaxies, like the Jeans equation, can underestimate central densities and J-factors due to simplifying assumptions. Using realistic simulations, the authors find that tidal forces and orbital dynamics can bias results, suggesting that more accurate modeling is needed for interpreting dark matter signals.