A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Machine learning detects subhalos in lensed images with high accuracy and low false positives.
Paper uses machine learning to detect dark matter subhalos in simulated Gaia DR2 data.
New method uses neural networks to infer dark matter subhalo abundance from stellar streams.
The subtle and unique imprint of dark matter substructure on extended arcs in strong lensing systems contains a wealth of information about the properties and distribution of dark matter on small scales and, consequently, about the underlying particle physics. However, teasing out this effect poses a significant challe…