SCREAM adapts the CATHODE method to treat stellar streams as feature-space over-densities, incorporates measurement uncertainties into neural network training, and achieves F1=0.745 on GD-1 while recovering faint members and a diffuse cocoon missed by prior methods.
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3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
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astro-ph.GA 3years
2026 3representative citing papers
DESI data on the GD-1 stream identifies a thin cold core and a hot cocoon with 30% of members whose dispersion is consistent with 11 Gyr of dark matter subhalo heating.
The MAGIC survey provides photometric metallicities for RGB stars over ~3000 deg² using CaHK narrow-band imaging plus DELVE g,r,i data, recovering 13/14 known ultra-faint dwarfs and confirming a distant Reticulum II member.
citing papers explorer
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Characterizing Stellar Streams with Error-Aware Machine Learning
SCREAM adapts the CATHODE method to treat stellar streams as feature-space over-densities, incorporates measurement uncertainties into neural network training, and achieves F1=0.745 on GD-1 while recovering faint members and a diffuse cocoon missed by prior methods.
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Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon
DESI data on the GD-1 stream identifies a thin cold core and a hot cocoon with 30% of members whose dispersion is consistent with 11 Gyr of dark matter subhalo heating.
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The DECam MAGIC Survey $-$ Mapping the Ancient Galaxy in CaHK: Overview and Summary of Early Science
The MAGIC survey provides photometric metallicities for RGB stars over ~3000 deg² using CaHK narrow-band imaging plus DELVE g,r,i data, recovering 13/14 known ultra-faint dwarfs and confirming a distant Reticulum II member.