0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      CMB power spectra and cosmological parameters from Planck PR4 with CamSpec

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          ABSTRACT

          We present angular power spectra and cosmological parameter constraints derived from the Planck PR4 (NPIPE) maps of the cosmic microwave background. NPIPE, released by the Planck Collaboration in 2020, is a new processing pipeline for producing calibrated frequency maps from Planck data. We have created new versions of the CamSpec likelihood using these maps and applied them to constrain the lambda cold dark matter (ΛCDM) model and single-parameter extensions. We find excellent consistency between NPIPE and the Planck 2018 maps at the parameter level, showing that the Planck cosmology is robust to substantial changes in the mapmaking. The lower noise of NPIPE leads to ~10 per cent tighter constraints, and we see both smaller error bars and a shift towards the ΛCDM values for beyond-ΛCDM parameters including ΩK and AL.

          Related collections

          Most cited references38

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          SciPy 1.0: fundamental algorithms for scientific computing in Python

          SciPy is an open-source scientific computing library for the Python programming language. Since its initial release in 2001, SciPy has become a de facto standard for leveraging scientific algorithms in Python, with over 600 unique code contributors, thousands of dependent packages, over 100,000 dependent repositories and millions of downloads per year. In this work, we provide an overview of the capabilities and development practices of SciPy 1.0 and highlight some recent technical developments.
            Bookmark
            • Record: found
            • Abstract: not found
            • Article: not found

            Matplotlib: A 2D Graphics Environment

              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              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.
                Bookmark

                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Monthly Notices of the Royal Astronomical Society
                Oxford University Press (OUP)
                0035-8711
                1365-2966
                December 2022
                November 03 2022
                December 2022
                November 03 2022
                September 26 2022
                : 517
                : 3
                : 4620-4636
                Article
                10.1093/mnras/stac2744
                dab824d3-8ab7-4426-bba8-81268b7c1ef2
                © 2022

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

                History

                Comments

                Comment on this article