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Register a new userMOSFiT: Modular Open-Source Fitter for Transients
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Authors
James Guillochon
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Much of the progress made in time-domain astronomy is accomplished by relating observational multi-wavelength time series data to models derived from our understanding of physical laws. This goal is typically accomplished by dividing the task in two: collecting data (observing), and constructing models to represent that data (theorizing). Owing to the natural tendency for specialization, a disconnect can develop between the best available theories and the best available data, potentially delaying advances in our understanding new classes of transients. We introduce MOSFiT: the Modular Open-Source Fitter for Transients, a Python-based package that downloads transient datasets from open online catalogs (e.g., the Open Supernova Catalog), generates Monte Carlo ensembles of semi-analytical light curve fits to those datasets and their associated Bayesian parameter posteriors, and optionally delivers the fitting results back to those same catalogs to make them available to the rest of the community. MOSFiT is designed to help bridge the gap between observations and theory in time-domain astronomy; in addition to making the application of existing models and creation of new models as simple as possible, MOSFiT yields statistically robust predictions for transient characteristics, with a standard output format that includes all the setup information necessary to reproduce a given result. As large-scale surveys such as LSST discover entirely new classes of transients, tools such as MOSFiT will be critical for enabling rapid comparison of models against data in statistically consistent, reproducible, and scientifically beneficial ways.
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Galaxy cluster analyses based on high-resolution observations of the Sunyaev-Zeldovich (SZ) effect have become common in the last decade. We present PreProFit, the first publicly available code designed to fit the pressure profile of galaxy clusters from SZ data. PreProFit is based on a Bayesian forward-modelling approach, allows the analysis of data coming from different sources, adopts a flexible parametrization for the pressure profile, and fits the model to the data accounting for Abel integral, beam smearing, and transfer function filtering. PreProFit is computationally efficient, is extensively documented, has been released as an open source Python project, and was developed to be part of a joint analysis of X-ray and SZ data on galaxy clusters. PreProFit returns $chi^2$, model parameters and uncertainties, marginal and joint probability contours, diagnostic plots, and surface brightness radial profiles. PreProFit also allows the use of analytic approximations for the beam and transfer functions useful for feasibility studies.
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A pioneering electromagnetic (EM) observation follow-up program of candidate gravitational wave (GW) triggers has been performed, Dec 17 2009 to Jan 8 2010 and Sep 4 to Oct 20 2010, during the recent LIGO/Virgo run. The follow-up program involved ground-based and space EM facilities observing the sky at optical, X-ray and radio wavelengths. The joint GW/EM observation study requires the development of specific image analysis procedures able to discriminate the possible EM counterpart of GW trigger from background events. The paper shows an overview of the EM follow-up program and the developing image analysis procedures as they are applied to data collected with TAROT and Zadko.
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