Starlight-polarization-based tomography of the magnetized ISM: PASIPHAE's line-of-sight inversion method

Creators: Pelgrims, V.; Panopoulou, G. V.; Tassis, K.; Pavlidou, V.; Basyrov, A.; Blinov, D.; Gjerl∅w, E.; Kiehlmann, S.; Mandarakas, N.; Papadaki, A.; Skalidis, R.; Tsouros, A.; Anche, R. M.; Eriksen, H. K.; Ghosh, T.; Kypriotakis, J. A.; Maharana, S.; Ntormousi, E.; Pearson, T. J.; Potter, S. B.; Ramaprakash, A. N.; Readhead, A. C. S.; Wehus, I. K.

Abstract

We present the first Bayesian method for tomographic decomposition of the plane-of-sky orientation of the magnetic field with the use of stellar polarimetry and distance. This standalone tomographic inversion method presents an important step forward in reconstructing the magnetized interstellar medium (ISM) in three dimensions within dusty regions. We develop a model in which the polarization signal from the magnetized and dusty ISM is described by thin layers at various distances, a working assumption which should be satisfied in small-angular circular apertures. Our modeling makes it possible to infer the mean polarization (amplitude and orientation) induced by individual dusty clouds and to account for the turbulence-induced scatter in a generic way. We present a likelihood function that explicitly accounts for uncertainties in polarization and parallax. We develop a framework for reconstructing the magnetized ISM through the maximization of the log-likelihood using a nested sampling method. We test our Bayesian inversion method on mock data, representative of the high Galactic latitude sky, taking into account realistic uncertainties from Gaia and as expected for the optical polarization survey PASIPHAE according to the currently planned observing strategy. We demonstrate that our method is effective at recovering the cloud properties as soon as the polarization induced by a cloud to its background stars is higher than ~0.1% for the adopted survey exposure time and level of systematic uncertainty. The larger the induced polarization is, the better the method's performance, and the lower the number of required stars. Our method makes it possible to recover not only the mean polarization properties but also to characterize the intrinsic scatter, thus creating new ways to characterize ISM turbulence and the magnetic field strength. Finally, we apply our method to an existing data set of starlight polarization with known line-of-sight decomposition, demonstrating agreement with previous results and an improved quantification of uncertainties in cloud properties.

Additional Information

© The Authors 2023. Open Access article, published by EDP Sciences, under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. This article is published in open access under the Subscribe to Open model. Subscribe to A&A to support open access publication. We are grateful to our anonymous referee who provided us with a detailed and constructive report that helped us improve this paper. The PASIPHAE program is supported by grants from the European Research Council (ERC) under grant agreements nos. 771282 and 772253; by the National Science Foundation (NSF) award AST-2109127; by the National Research Foundation of South Africa under the National Equipment Programme; by the Stavros Niarchos Foundation under grant PASIPHAE; and by the Infosys Foundation. G.V.P. acknowledges support by NASA through the NASA Hubble Fellowship grant #HST-HF2-51444.001-A awarded by the Space Telescope Science Institute, which is operated by the Association of Universities for Research in Astronomy, Incorporated, under NASA contract NAS5-26555. V.Pa. acknowledges support by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the "First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant" (Project 1552 CIRCE). V.Pa. and A.T. acknowledge support from the Foundation of Research and Technology – Hellas Synergy Grants Program through project MagMASim, jointly implemented by the Institute of Astrophysics and the Institute of Applied and Computational Mathematics. E.N. has received funding from the HFRI's 2nd Call for H.F.R.I. Research Projects to Support Post-Doctoral Researchers (Project number 224). K.T. and A.P. acknowledge support from the Foundation of Research and Technology – Hellas Synergy Grants Program through project POLAR, jointly implemented by the Institute of Astrophysics and the Institute of Computer Science. T.G. is grateful to the Inter-University Centre for Astronomy and Astrophysics (IUCAA), Pune, India for providing the Associateship programme under which a part of this work was carried out. G.V.P. would like to thank C. Zucker for helpful discussions in the early stages of this project.

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