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Nabila Aghanim

Researcher at Université Paris-Saclay

Publications -  450
Citations -  110271

Nabila Aghanim is an academic researcher from Université Paris-Saclay. The author has contributed to research in topics: Planck & Cosmic microwave background. The author has an hindex of 137, co-authored 416 publications receiving 100914 citations. Previous affiliations of Nabila Aghanim include University of Paris-Sud & University of Paris.

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Star formation rates and stellar masses from machine learning

TL;DR: In this article, the authors proposed a method based on the machine learning algorithm Random Forest to estimate the star formation rate (SFR) and the stellar mass (M ⋆ ), both of which, but especially the SFR, are very complex to estimate.
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Characterization of the non-Gaussianity of radio and IR point sources at CMB frequencies

TL;DR: In this paper, a simple prescription to infer the angular bispectrum from the power spectrum of point sources considering independent populations of sources, with or without clustering, was proposed.
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Planck intermediate results. LIII. Detection of velocity dispersion from the kinetic Sunyaev-Zeldovich effect

Nabila Aghanim, +142 more
TL;DR: In this paper, the authors present a detection of the temperature (and therefore velocity) dispersion due to the kinetic Sunyaev-Zeldovich (kSZ) effect from clusters of galaxies.
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Mass bias evolution in tSZ cluster cosmology.

TL;DR: In this paper, a power-law parametrisation was applied to the combination of tSZ number counts and power spectrum, finding a hint of redshift dependence that leads to a decreasing value of the mass bias for higher redshift.
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Planck intermediate results XL. The Sunyaev-Zeldovich signal from the Virgo cluster

Peter A. R. Ade, +270 more
TL;DR: In this article, the authors study the Sunyaev-Zeldovich (SZ) signal in the outskirts of the Virgo cluster and compare it with analytical models and a constrained simulation of the environment of Virgo, finding that a prolate model is favored by the combination of SZ and X-ray data, in agreement with predictions.