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      Detailed study of a rare hyperluminous rotating disk in an Einstein ring 10 billion years ago

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      Nature Astronomy
      Springer Science and Business Media LLC

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          Abstract

          Hyperluminous infrared galaxies (HyLIRGs) are the rarest and most extreme starbursts and found only in the distant Universe ( z ≳ 1). They have intrinsic infrared (IR) luminosities L IR ≥ 10 13 L and are commonly found to be major mergers. Recently, the Planck All-Sky Survey to Analyze Gravitationally-lensed Extreme Starbursts project (PASSAGES) searched ~10 4 deg 2 of the sky and found ~20 HyLIRGs. We describe a detailed study of PJ0116-24, the brightest ( μL IR ≈ 2.6 × 10 14 L , magnified with μ ≈ 17) Einstein-ring HyLIRG in the southern sky, at z = 2.125, with observations from the near-IR integral-field spectrograph VLT/ERIS and the submillimetre interferometer ALMA. We detected Hα, Hβ, [N ii] and [S ii] lines and obtained an extreme Balmer decrement (Hα/Hβ ≈ 8.73 ± 1.14). We modelled the molecular-gas and ionized-gas kinematics with CO(3–2) and Hα data at ~100–300 pc and (sub)kiloparsec delensed scales, respectively, finding consistent regular rotation. We found PJ0116-24 to be highly rotationally supported ( v rot/ σ 0, mol. gas ≈ 9.4) with a richer gaseous substructure than other known HyLIRGs. Our results imply that PJ0116-24 is an intrinsically massive ( M baryon ≈ 10 11.3 M ) and rare starbursty disk (star-formation rate, SFR = 1,490 M yr −1) probably undergoing secular evolution. This indicates that the maximal SFR (≳1,000 M yr −1) predicted by simulations could occur during a galaxy’s secular evolution, away from major mergers.

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          Matplotlib: A 2D Graphics Environment

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            Array programming with NumPy

            Array programming provides a powerful, compact and expressive syntax for accessing, manipulating and operating on data in vectors, matrices and higher-dimensional arrays. NumPy is the primary array programming library for the Python language. It has an essential role in research analysis pipelines in fields as diverse as physics, chemistry, astronomy, geoscience, biology, psychology, materials science, engineering, finance and economics. For example, in astronomy, NumPy was an important part of the software stack used in the discovery of gravitational waves 1 and in the first imaging of a black hole 2 . Here we review how a few fundamental array concepts lead to a simple and powerful programming paradigm for organizing, exploring and analysing scientific data. NumPy is the foundation upon which the scientific Python ecosystem is constructed. It is so pervasive that several projects, targeting audiences with specialized needs, have developed their own NumPy-like interfaces and array objects. Owing to its central position in the ecosystem, NumPy increasingly acts as an interoperability layer between such array computation libraries and, together with its application programming interface (API), provides a flexible framework to support the next decade of scientific and industrial analysis.
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              Astropy: A community Python package for astronomy

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                Journal
                Nature Astronomy
                Nat Astron
                Springer Science and Business Media LLC
                2397-3366
                July 15 2024
                Article
                10.1038/s41550-024-02296-7
                d7de6cc9-b645-42f0-940c-304fc2a25ef4
                © 2024

                https://creativecommons.org/licenses/by/4.0

                https://creativecommons.org/licenses/by/4.0

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