Improved Stacking for Line-Intensity Mapping
Analysis
This paper explores methods to enhance the sensitivity of line-intensity mapping (LIM) stacking analyses, a technique used to detect faint signals in noisy data. The authors introduce and test 2D and 3D profile matching techniques, aiming to improve signal detection by incorporating assumptions about the expected signal shape. The study's significance lies in its potential to refine LIM observations, which are crucial for understanding the large-scale structure of the universe.
Key Takeaways
- •Introduces 2D and 3D profile matching techniques for improved LIM stacking.
- •Demonstrates up to 25% improvement in detection significance in simulations.
- •Highlights the importance of considering signal shape and clustering effects in LIM analysis.
Reference
“The fitting methods provide up to a 25% advantage in detection significance over the original stack method in realistic COMAP-like simulations.”