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Determining the Hubble constant through the analysis of Abell clusters

Lee et al. | Sep 28, 2026

Determining the Hubble constant through the analysis of  Abell clusters
Image credit: NASA Hubble Space Telescope

Galaxy clusters offer several advantages for measuring H0 compared to traditional methods, such as Cepheid variables or Type Ia supernovae. Unlike individual stars or supernovae, clusters are less affected by local variations in stellar population or interstellar medium properties, providing a more stable and consistent measure over large cosmological distances. This work proposes using galaxy clusters as an alternative method for determining the H0. It provides an independent perspective on the H0 debate and contribute to ongoing efforts to reconcile the differing values obtained from the other two measurements.

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Groundwater prediction using artificial intelligence: Case study for Texas aquifers

Sharma et al. | Apr 19, 2024

Groundwater prediction using artificial intelligence: Case study for Texas aquifers

Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.

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