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      Magnetic characterization of the SPB/β Cep hybrid pulsator HD 43317

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      Astronomy & Astrophysics
      EDP Sciences

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          emcee: The MCMC Hammer

          We introduce a stable, well tested Python implementation of the affine-invariant ensemble sampler for Markov chain Monte Carlo (MCMC) proposed by Goodman & Weare (2010). The code is open source and has already been used in several published projects in the astrophysics literature. The algorithm behind emcee has several advantages over traditional MCMC sampling methods and it has excellent performance as measured by the autocorrelation time (or function calls per independent sample). One major advantage of the algorithm is that it requires hand-tuning of only 1 or 2 parameters compared to \(\sim N^2\) for a traditional algorithm in an N-dimensional parameter space. In this document, we describe the algorithm and the details of our implementation and API. Exploiting the parallelism of the ensemble method, emcee permits any user to take advantage of multiple CPU cores without extra effort. The code is available online at http://dan.iel.fm/emcee under the MIT License.
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            A major upgrade of the VALD database

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              Modeling of solar oscillation power spectra

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                Author and article information

                Journal
                Astronomy & Astrophysics
                A&A
                EDP Sciences
                0004-6361
                1432-0746
                September 2017
                September 18 2017
                September 2017
                : 605
                : A104
                Article
                10.1051/0004-6361/201731012
                67755e41-6d66-4298-8135-3c964626423c
                © 2017
                History

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