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      Spectropolarimetric variability in the repeating fast radio burst source FRB 20180301A

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          ABSTRACT

          As the sample size of repeating fast radio bursts (FRBs) has grown, an increasing diversity of phenomenology has emerged. Through long-term multi-epoch studies of repeating FRBs, it is possible to assess which phenomena are common to the population and which are unique to individual sources. We present a multi-epoch monitoring campaign of the repeating FRB source 20180301A using the ultra-wideband low (UWL) receiver observations with Murriyang, the Parkes 64-m radio telescope. The observations covered a wide frequency band spanning approximately 0.7–4 GHz, and yielded the detection of 46 bursts. None of the repeat bursts displayed radio emission in the range of 1.8–4 GHz, while the burst emission peaked at 1.1 GHz. We discover evidence for secular trends in the burst dispersion measure, indicating a decline at a rate of $-2.7\pm 0.2\, {\rm pc\, cm^{-3}\, yr^{-1}}$. We also found significant variation in the Faraday rotation measure of the bursts across the follow-up period, including evidence of a sign reversal. While a majority of bursts did not exhibit any polarization, those that did show a decrease in the linear polarization fraction as a function of frequency, consistent with spectral depolarization due to scattering, as observed in other repeating FRB sources. Surprisingly, no significant variation in the polarization position angles was found, which is in contrast with earlier measurements reported for the FRB source. We measure the burst rate and sub-pulse drift rate variation and compare them with the previous results. These novel observations, along with the extreme polarization properties observed in other repeating FRBs, suggest that a sub-sample of FRB progenitors possess highly dynamic magneto-ionic environments.

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          Matplotlib: A 2D Graphics Environment

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            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.
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              Astropy: A community Python package for astronomy

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                Author and article information

                Contributors
                Journal
                Monthly Notices of the Royal Astronomical Society
                Oxford University Press (OUP)
                0035-8711
                1365-2966
                December 2023
                October 10 2023
                December 2023
                October 10 2023
                September 28 2023
                : 526
                : 3
                : 3652-3672
                Article
                10.1093/mnras/stad2969
                f8781d94-2dc3-4a67-b910-88463a3813be
                © 2023

                https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model

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