Deep images of the Galactic center with GRAVITY

¹ Max Planck Institute for extraterrestrial Physics, Giessenbachstraße 1, 85748 Garching, Germany
² LESIA, Observatoire de Paris, Université PSL, CNRS, Sorbonne Université, Université de Paris, 5 place Jules Janssen, 92195 Meudon, France
³ Max Planck Institute for Astronomy, Königstuhl 17, 69117 Heidelberg, Germany
⁴ 1 st Institute of Physics, University of Cologne, Zülpicher Straße 77, 50937 Cologne, Germany
⁵ Univ. Grenoble Alpes, CNRS, IPAG, 38000 Grenoble, France
⁶ Universidade de Lisboa – Faculdade de Ciências, Campo Grande, 1749-016 Lisboa, Portugal
⁷ Faculdade de Engenharia, Universidade do Porto, rua Dr. Roberto Frias, 4200-465 Porto, Portugal
⁸ European Southern Observatory, Karl-Schwarzschild-Straße 2, 85748 Garching, Germany
⁹ European Southern Observatory, Casilla 19001, Santiago 19, Chile
¹⁰ Sterrewacht Leiden, Leiden University, Postbus 9513, 2300 RA Leiden, The Netherlands
¹¹ Departments of Physics and Astronomy, Le Conte Hall, University of California, Berkeley, CA 94720, USA
¹² CENTRA – Centro de Astrofísica e Gravitação, IST, Universidade de Lisboa, 1049-001 Lisboa, Portugal
¹³ Department of Astrophysical & Planetary Sciences, JILA, Duane Physics Bldg., 2000 Colorado Ave, University of Colorado, Boulder, CO 80309, USA
¹⁴ Department of Particle Physics & Astrophysics, Weizmann Institute of Science, Rehovot 76100, Israel
¹⁵ Institute of Astronomy, Madingley Road, Cambridge CB3 0HA, UK
¹⁶ Department of Physics, Technical University Munich, James-Franck-Straße 1, 85748 Garching, Germany
¹⁷ Max Planck Institute for Astrophysics, Karl-Schwarzschild-Str. 1, 85741 Garching, Germany
¹⁸ Department of Physics, University of Illinois, 1110 West Green Street, Urbana, IL 61801, USA
¹⁹ Hamburger Sternwarte, Universität Hamburg, Gojenbergsweg 112, 21029 Hamburg, Germany
²⁰ CERN, 1 Esplanade des Particules, Genève 23 1211, Switzerland
²¹ Department of Astrophysics, IMAPP, Radboud University, 6500 GL Nijmegen, The Netherlands

Received: 15 October 2021
Accepted: 29 November 2021

Abstract

Stellar orbits at the Galactic Center provide a very clean probe of the gravitational potential of the supermassive black hole. They can be studied with unique precision, beyond the confusion limit of a single telescope, with the near-infrared interferometer GRAVITY. Imaging is essential to search the field for faint, unknown stars on short orbits which potentially could constrain the black hole spin. Furthermore, it provides the starting point for astrometric fitting to derive highly accurate stellar positions. Here, we present G^R, a new imaging tool specifically designed for Galactic Center observations with GRAVITY. The algorithm is based on a Bayesian interpretation of the imaging problem, formulated in the framework of information field theory and building upon existing works in radio-interferometric imaging. Its application to GRAVITY observations from 2021 yields the deepest images to date of the Galactic Center on scales of a few milliarcseconds. The images reveal the complicated source structure within the central 100 mas around Sgr A*, where we detected the stars S29 and S55 and confirm S62 on its trajectory, slowly approaching Sgr A*. Furthermore, we were able to detect S38, S42, S60, and S63 in a series of exposures for which we offset the fiber from Sgr A*. We provide an update on the orbits of all aforementioned stars. In addition to these known sources, the images also reveal a faint star moving to the west at a high angular velocity. We cannot find any coincidence with any known source and, thus, we refer to the new star as S300. From the flux ratio with S29, we estimate its K-band magnitude as m_K(S300) ≃ 19.0 − 19.3. Images obtained with CLEAN confirm the detection. To assess the sensitivity of our images, we note that fiber damping reduces the apparent magnitude of S300 and the effect increases throughout the year as the star moves away from the field center. Furthermore, we performed a series of source injection tests. Under favorable circumstances, sources well below a magnitude of 20 can be recovered, while 19.7 is considered the more universal limit for a good data set.