arXiv (All)
open access
Detection of metal absorption lines in quasar spectra: a neural network approach using U-Net
Current and future large spectroscopic surveys are significantly enhancing the volume and resolution of quasar spectra that are observed, which requires the creation of efficient and precise automated techniques to detect absorption features. This study focuses on the detection of metal absorption f
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Multi-wavelength Emission Modeling from Accretion Flows around Isolated Black Holes Including Magnetic Flux Transport#1036735
- The DESI Survey Validation: Results from Visual Inspection of the Quasar Survey Spectra#1065548
- Nitrogen-Loud Quasars from the Dark Energy Spectroscopic Instrument. II. Broad-Line Region Metallicity and Relative Nitrogen Enrichment#1083892
- Efficient reduction of stellar contamination and noise in planetary transmission spectra using neural networks#798771
- Efficient reduction of stellar contamination and noise in planetary transmission spectra using neural networks#797357
Record · ID 1064616
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive