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Related papers: Predicting galaxy bias using machine learning

200 papers

We investigate the clustering of galaxy groups and clusters in the SDSS using the Berlind et al. (2006) group sample, which is designed to identify galaxy systems that each occupy a single dark matter halo. We estimate group masses from…

CMB lensing reconstructions are a sensitive probe of the growth of structure across cosmic time and a key tool to sharpen investigations of the very early Universe via delensing. At present, a large fraction of this information is drawn…

Cosmology and Nongalactic Astrophysics · Physics 2026-03-02 A. Baleato Lizancos , W. Coulton , A. Challinor , B. D. Sherwin , Y. Mehta

I describe a general formalism for galaxy biasing (Dekel & Lahav 1998) and its application to measurements of beta (=Omega^0.6/b), e.g. via direct comparisons of light and mass and via redshift distortions. The linear and deterministic…

Astrophysics · Physics 2007-05-23 Avishai Dekel

Machine learning techniques are utilised in several areas of astrophysical research today. This dissertation addresses the application of ML techniques to two classes of problems in astrophysics, namely, the analysis of individual…

Astrophysics · Physics 2009-01-06 N. Daniel Kumar

We present a machine learning (ML) pipeline to identify star clusters in the multi{color images of nearby galaxies, from observations obtained with the Hubble Space Telescope as part of the Treasury Project LEGUS (Legacy ExtraGalactic…

Astrophysics of Galaxies · Physics 2021-02-10 Gustavo Perez , Matteo Messa , Daniela Calzetti , Subhransu Maji , Dooseok Jung , Angela Adamo , Mattia Siressi

Machine learning has been successfully applied in varied field but whether it is a viable tool for determining the distance to molecular clouds in the Galaxy is an open question. In the Galaxy, the kinematic distance is commonly employed as…

The abundance of dark matter (DM) subhalos orbiting a host galaxy is a generic prediction of the cosmological framework, and is a promising way to constrain the nature of DM. In this paper, we investigate the use of machine learning-based…

Astrophysics of Galaxies · Physics 2023-01-02 Abdullah Bazarov , María Benito , Gert Hütsi , Rain Kipper , Joosep Pata , Sven Põder

Most existing star-galaxy classifiers use the reduced summary information from catalogs, requiring careful feature extraction and selection. The latest advances in machine learning that use deep convolutional neural networks allow a machine…

Instrumentation and Methods for Astrophysics · Physics 2016-10-20 Edward J. Kim , Robert J. Brunner

The world of 2D materials is rapidly expanding with new discoveries of stackable and twistable layered systems composed of lattices of different symmetries, orbital character, and structural motifs. Often, however, it is not clear a priori…

Mesoscale and Nanoscale Physics · Physics 2025-12-19 Daniel Kaplan , Alexander C. Tyner , Eva Y. Andrei , J. H. Pixley

Parametric modeling of galaxy cluster density profiles from weak lensing observations leads to a mass bias, whose detailed understanding is critical in deriving accurate mass-observable relations for constraining cosmological models.…

Cosmology and Nongalactic Astrophysics · Physics 2021-11-17 Martin W. Sommer , Tim Schrabback , Douglas E. Applegate , Stefan Hilbert , Behzad Ansarinejad , Benjamin Floyd , Sebastian Grandis

Significant galaxy mergers throughout cosmic time play a fundamental role in theories of galaxy evolution. The widespread usage of human classifiers to visually assess whether galaxies are in merging systems remains a fundamental component…

Distinguishing active galaxies from star-forming galaxies is essential for understanding galaxy evolution. Diagnostic methods like the BPT (Baldwin, Phillips, and Terlevich) diagram use optical emission-line ratios to separate galaxies.…

Astrophysics of Galaxies · Physics 2026-03-26 Farideh Mazoochi , Reihaneh Karimi , Mohammad Hossein Zhoolideh Haghighi , Fatemeh Tabatabaei

Measurements of the shear induced by weak gravitational lensing around galaxy cluster lines of sight are the gold standard for calibrating cluster observable-mass relations, thereby enabling a robust and precise inference of cosmological…

Cosmology and Nongalactic Astrophysics · Physics 2026-03-26 S. Bocquet , A. Fumagalli , C. T. Davies , K. Dolag , S. Grandis , J. J. Mohr

Gravitational lensing magnification modifies the observed spatial distribution of galaxies and can severely bias cosmological probes of large-scale structure if not accurately modelled. Standard approaches to modelling this magnification…

Properties of massive galaxy clusters, such as mass abundance and concentration, are sensitive to cosmology, making cluster statistics a powerful tool for cosmological studies. However, favoring a more simplified, spherically symmetric…

Galaxies are biased tracers of the underlying cosmic web, which is dominated by dark matter components that cannot be directly observed. The relationship between dark matter density fields and galaxy distributions can be sensitive to…

Cosmology and Nongalactic Astrophysics · Physics 2023-11-16 Core Francisco Park , Victoria Ono , Nayantara Mudur , Yueying Ni , Carolina Cuesta-Lazaro

We present a method to reconstruct the initial conditions of the universe using observed galaxy positions and luminosities under the assumption that the luminosities can be calibrated with weak lensing to give the mean halo mass. Our method…

Cosmology and Nongalactic Astrophysics · Physics 2018-10-24 Chirag Modi , Yu Feng , Uros Seljak

The connections among galaxies, the dark matter halos where they form and the properties of the large-scale Cosmic Web still need to be completely disentangled. We use the cosmological hydrodynamical simulation TNG100 of the IllustrisTNG…