Commentary on Chan <i>et al</i>. (2018): Cannabis use and educational level—which is the chicken and which is the egg?

Melchior, Maria; Silva, Marine Azevedo Da

doi:10.1111/add.14099

Cited by 1 publication

(1 citation statement)

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“…This definition depends therefore on the detection pipeline. Deblenders such as Scarlet [8] can be used to deblend recognized blended groups of galaxies, provided galaxy centers are properly identified. The fraction of recognized blends for LSST is estimated to be around 40 %.…”

Section: Blendingmentioning

confidence: 99%

Impact of blending on weak lensing measurements with the Vera C. Rubin Observatory

Ramel,

Doux,

Kuna

2024

EPJ Web Conf.

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Upcoming deep optical surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST) will scan the sky to unprecedented depths and detect billions of galaxies. This amount of detections will however cause the apparent superposition of galaxies on the images, called blending, and generate a new systematic error due to the confusion of sources. As consequences, the measurements of individual galaxies properties such as their redshifts or shapes will be impacted, and some galaxies will not be detected. However, galaxy shapes are key quantities, used to estimate masses of large scale structures, such as galaxy clusters, through weak gravitational lensing. This work presents a new catalog matching algorithm, called friendly, for the detection and characterization of blends in simulated LSST data for the Dark Energy Science Collaboration (DESC) Data Challenge 2. By identifying a specific type of blends, we show that removing them from the data may partially correct the amplitude of the excess surface mass density ΔΣ weak lensing profile that could be biased low by around 20% due to blending. This would result in impacting clusters weak lensing mass estimate and cosmology.

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Section: Blendingmentioning

confidence: 99%