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We develop an optimization algorithm, using simulated annealing for the quantification of patterns in astronomical data based on techniques developed for robotic vision applications. The methodology falls in the category of cost…

Instrumentation and Methods for Astrophysics · Physics 2020-09-09 Maria Chira , Manolis Plionis

We train a machine learning algorithm to learn cosmological structure formation from N-body simulations. The algorithm infers the relationship between the initial conditions and the final dark matter haloes, without the need to introduce…

Cosmology and Nongalactic Astrophysics · Physics 2018-07-02 Luisa Lucie-Smith , Hiranya V. Peiris , Andrew Pontzen , Michelle Lochner

A review of the principles of observational testing of cosmological theories is given with a special emphasis on the distinction between observational facts and theoretical hypotheses. A classification of modern cosmological theories and…

The High Latitude Spectroscopic Survey (HLSS) is the reference baseline spectroscopic survey for NASA's Nancy Grace Roman space telescope, measuring redshifts of $\sim 10$M H$\alpha$ emission line galaxies over a $2000$ deg$^2$ footprint at…

Cosmology and Nongalactic Astrophysics · Physics 2023-05-31 Kevin S. McCarthy , Zhongxu Zhai , Yun Wang

One of the challenges in testing gravity with cosmology is the vast freedom opened when extending General Relativity. For linear perturbations, one solution consists in using the Effective Field Theory of Dark Energy (EFT of DE). Even then,…

Cosmology and Nongalactic Astrophysics · Physics 2017-09-20 Jérôme Gleyzes

This work develops a multivariate extension of the Fixed Rank Kriging (FRK) framework for spatial prediction in settings where multiple spatial processes may provide complementary information. The goal is to preserve the computational…

Methodology · Statistics 2026-03-24 Gaia Caringi , Piercesare Secchi

Existing deep learning methods for remote sensing image fusion often suffer from poor generalization when applied to unseen datasets due to the limited availability of real training data and the domain gap between different satellite…

Computer Vision and Pattern Recognition · Computer Science 2025-12-03 Yongchuan Cui , Peng Liu , Yi Zeng

With neutrino astronomy just beginning to burgeon, and the prospects of detecting the cosmic neutrino background closer than ever, we live in an era with the unique opportunity not only to investigate the universe with this novel probe, but…

High Energy Physics - Phenomenology · Physics 2021-09-06 Saul Hurwitz

The present thesis is devoted to the non-parametric reconstruction of some cosmological parameters using diverse observational datasets. The Universe is assumed to be spatially homogeneous and isotropic, thus described by the FLRW metric.…

Cosmology and Nongalactic Astrophysics · Physics 2022-07-19 Purba Mukherjee

Understanding neural representations will help open the black box of neural networks and advance our scientific understanding of modern AI systems. However, how complex, structured, and transferable representations emerge in modern neural…

Machine Learning · Computer Science 2025-02-28 Liu Ziyin , Isaac Chuang , Tomer Galanti , Tomaso Poggio

Large pre-trained models, or foundation models, have shown impressive performance when adapted to a variety of downstream tasks, often out-performing specialized models. Hypernetworks, neural networks that generate some or all of the…

Machine Learning · Computer Science 2025-03-04 Jeffrey Gu , Serena Yeung-Levy

Next generation surveys will observe the large-scale structure of the Universe with unprecedented accuracy. This will enable us to test the relationships between matter over-densities, the curvature perturbation and the Newtonian potential.…

Cosmology and Nongalactic Astrophysics · Physics 2012-06-22 Yong-Seon Song , Lukas Hollenstein , Gabriela Caldera-Cabral , Kazuya Koyama

In this essay, we immerse into the framework of normed division algebras as a suitable arena to accommodate the standard model of elementary particles, and we explore some applications to cosmology. Remarkably, they permit interesting…

Cosmology and Nongalactic Astrophysics · Physics 2022-08-11 Jose Beltrán Jiménez , Tomi S. Koivisto

We present a new method for inferring galaxy star formation histories (SFH) using machine learning methods coupled with two cosmological hydrodynamic simulations. We train Convolutional Neural Networks to learn the relationship between…

We compare a large suite of theoretical cosmological models to observational data from the cosmic microwave background, baryon acoustic oscillation measurements of expansion, Type Ia SNe measurements of expansion, redshift space distortion…

Cosmology and Nongalactic Astrophysics · Physics 2017-12-13 Zhongxu Zhai , Michael Blanton , Anže Slosar , Jeremy Tinker

Elucidating the connection between the properties of galaxies and the properties of their hosting haloes is a key element in galaxy formation. When the spatial distribution of objects is also taken under consideration, it becomes very…

The limits of available computing power have forced models for the structure of stellar halos to adopt one or both of the following simplifying assumptions: (1) stellar mass can be "painted" onto dark matter particles in progenitor…

Cosmology and Nongalactic Astrophysics · Physics 2015-06-18 Jeremy Bailin , Eric F. Bell , Monica Valluri , Greg S. Stinson , Victor P. Debattista , H. M. P. Couchman , James Wadsley

There is growing interest in using 3-dimensional neutral hydrogen mapping with the redshifted 21 cm line as a cosmological probe, as it has been argued to have a greater long-term potential than the cosmic microwave background. However, its…

Astrophysics · Physics 2008-11-26 Yi Mao , Max Tegmark , Matthew McQuinn , Matias Zaldarriaga , Oliver Zahn

We match the real Higgs triplet model (RHTM) onto HEFT under different parameter choices and power-counting schemes, thereby obtaining several representative HEFT formulations and clarifying their relations. We establish the primary HEFT…

High Energy Physics - Phenomenology · Physics 2026-02-17 Zizhou Ge , Huayang Song , Xia Wan

We use mock galaxy survey simulations designed to resemble the Dark Energy Survey Year 1 (DES Y1) data to validate and inform cosmological parameter estimation. When similar analysis tools are applied to both simulations and real survey…