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Machine Learning methods will play a fundamental role in our ability to optimize the science output from the next generation of large scale surveys. Given the peculiarities of astronomical data, it is crucial that algorithms are adapted to…

Instrumentation and Methods for Astrophysics · Physics 2019-08-08 Emille E. O. Ishida

In recent years, machine learning (ML) methods have remarkably improved how cosmologists can interpret data. The next decade will bring new opportunities for data-driven cosmological discovery, but will also present new challenges for…

Methods based on machine learning have recently made substantial inroads in many corners of cosmology. Through this process, new computational tools, new perspectives on data collection, model development, analysis, and discovery, as well…

Fuelled by increasing computer power and algorithmic advances, machine learning techniques have become powerful tools for finding patterns in data. Since quantum systems produce counter-intuitive patterns believed not to be efficiently…

Quantum Physics · Physics 2018-05-14 Jacob Biamonte , Peter Wittek , Nicola Pancotti , Patrick Rebentrost , Nathan Wiebe , Seth Lloyd

Could Machine Learning (ML) make fundamental discoveries and tackle unsolved problems in Cosmology? Detailed observations of the present contents of the universe are consistent with the Cosmological Constant Lambda and Cold Dark Matter…

Cosmology and Nongalactic Astrophysics · Physics 2023-02-10 Ofer Lahav

It is well known that the best way to understand astronomical data is through machine learning, where a "black box" is set up, inside which a kind of artificial intelligence learns how to interpret the features in the data. We suggest that…

Instrumentation and Methods for Astrophysics · Physics 2024-04-01 Douglas Scott , Ali Frolop

An array of large observational programs using ground-based and space-borne telescopes is planned in the next decade. The forthcoming wide-field sky surveys are expected to deliver a sheer volume of data exceeding an exabyte. Processing the…

Instrumentation and Methods for Astrophysics · Physics 2023-05-26 Kana Moriwaki , Takahiro Nishimichi , Naoki Yoshida

Machine Learning algorithms are good tools for both classification and prediction purposes. These algorithms can further be used for scientific discoveries from the enormous data being collected in our era. We present ways of discovering…

Instrumentation and Methods for Astrophysics · Physics 2021-02-26 Shraddha Surana , Yogesh Wadadekar , Divya Oberoi

While astrophysical and cosmological probes provide a remarkably precise and consistent picture of the quantity and general properties of dark matter, its fundamental nature remains one of the most significant open questions in physics.…

Astrophysics and cosmology are rich with data. The advent of wide-area digital cameras on large aperture telescopes has led to ever more ambitious surveys of the sky. Data volumes of entire surveys a decade ago can now be acquired in a…

Instrumentation and Methods for Astrophysics · Physics 2017-04-18 Jan Kremer , Kristoffer Stensbo-Smidt , Fabian Gieseke , Kim Steenstrup Pedersen , Christian Igel

Dark matter cannot be observed directly, but its weak gravitational lensing slightly distorts the apparent shapes of background galaxies, making weak lensing one of the most promising probes of cosmology. Several observational studies have…

Cosmology and Nongalactic Astrophysics · Physics 2018-12-18 Dezső Ribli , Bálint Ármin Pataki , István Csabai

With the volume and availability of astronomical data growing rapidly, astronomers will soon rely on the use of machine learning algorithms in their daily work. This proceeding aims to give an overview of what machine learning is and delve…

Instrumentation and Methods for Astrophysics · Physics 2025-08-06 Sara A. Webb , Simon R. Goode

This article reviews recent advances in the application of machine learning to weak-lensing cosmology. Weak gravitational lensing provides a unique and powerful probe of the total matter distribution in the Universe, independent of its…

Cosmology and Nongalactic Astrophysics · Physics 2026-05-14 Masato Shirasaki

Machine learning is a field that has been growing in importance since the early 2010s due to the increasing accuracy of classification models and hardware advances that have enabled faster training on large datasets. In the field of…

Instrumentation and Methods for Astrophysics · Physics 2025-12-15 Alexis Mathis , Daniel Yu , Nolan Faught , Tyrian Hobbs.

Here we will give a perspective on new possible interplays between Machine Learning and Quantum Physics, including also practical cases and applications. We will explore the ways in which machine learning could benefit from new quantum…

Quantum Physics · Physics 2021-08-24 Lorenzo Buffoni , Filippo Caruso

The ability to test the nature of dark mass-energy components in the universe through large-scale structure studies hinges on accurate predictions of sky survey expectations within a given world model. Numerical simulations predict key…

Machine learning and deep learning techniques are contributing much to the advancement of science. Their powerful predictive capabilities appear in numerous disciplines, including chaotic dynamics, but they miss understanding. The main…

General Literature · Computer Science 2021-09-15 Miguel A. F. Sanjuan

Revolutionary advances in both theory and technology have launched cosmology into its most exciting period of discovery yet. Unanticipated components of the universe have been identified, promising ideas for understanding the basic features…

Astrophysics · Physics 2008-11-26 Wendy L. Freedman , Michael S. Turner

The evidence for the dark matter of the hot big bang cosmology is about as good as it gets in natural science. The exploration of its nature is now led by direct and indirect detection experiments, to be complemented by advances in the full…

Cosmology and Nongalactic Astrophysics · Physics 2017-03-15 P. J. E. Peebles

Upcoming cosmological surveys will provide unprecedented amount of data, which will require innovative statistical methods to maximize the scientific exploitation. Standard cosmological analyses based on abundances, two-point and…

Cosmology and Nongalactic Astrophysics · Physics 2025-05-20 Farida Farsian , Federico Marulli , Lauro Moscardini , Carlo Giocoli
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