Pith. sign in

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

1 Pith paper cite this work. Polarity classification is still indexing.

1 Pith paper citing it
abstract

Upcoming deep optical surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time 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 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 $\Delta\Sigma$ 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.

fields

astro-ph.CO 1

years

2024 1

verdicts

CONDITIONAL 1

representative citing papers

Galaxy Clustering with LSST: Effects of Number Count Bias from Blending

astro-ph.CO · 2024-11-21 · conditional · novelty 6.0

Blending in LSST-like image simulations biases galaxy redshift distributions and suppresses small-scale clustering beyond 3 sigma, yet leaves inferred Omega_m and galaxy bias on fiducial linear scales statistically unchanged.

citing papers explorer

Showing 1 of 1 citing paper.

  • Galaxy Clustering with LSST: Effects of Number Count Bias from Blending astro-ph.CO · 2024-11-21 · conditional · none · ref 45 · internal anchor

    Blending in LSST-like image simulations biases galaxy redshift distributions and suppresses small-scale clustering beyond 3 sigma, yet leaves inferred Omega_m and galaxy bias on fiducial linear scales statistically unchanged.