The Role of Machine Learning in the Next Decade of Cosmology

TL;DR

This paper discusses how machine learning is revolutionizing cosmology by enhancing data interpretation, outlining future opportunities and challenges, and emphasizing the need for interdisciplinary collaboration to fully realize ML's potential in the field.

Contribution

It highlights the transformative potential of ML in cosmology and advocates for increased interdisciplinary efforts to address upcoming challenges.

Findings

ML improves data interpretation in cosmology

Future opportunities for ML-driven discoveries are identified

Challenges include methodological adoption and understanding results

Abstract

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 adopting ML methodologies and understanding the results. ML could transform our field, but this transformation will require the astronomy community to both foster and promote interdisciplinary research endeavors.