Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published September 2021 | Published + Accepted Version
Journal Article Open

Detection of coherent low-frequency radio bursts from weak-line T Tauri stars

Abstract

In recent years, thanks to new facilities such as LOFAR that are capable of sensitive observations, much work has been done on the detection of stellar radio emission at low frequencies. Such emission has commonly been shown to be coherent emission, generally attributed to electron-cyclotron maser (ECM) emission, and has usually been detected from main-sequence M dwarfs. Here we report the first detection of coherent emission at low frequencies from T Tauri stars, which are known to be associated with high levels of stellar activity. Using LOFAR, we detect several bright radio bursts at 150 MHz from two weak-line T Tauri stars: KPNO-Tau 14 and LkCa 4. All of the bursts have high brightness temperatures (10¹³ − 10¹⁴ K) and high circular polarisation fractions (60–90%), indicating that they must be due to a coherent emission mechanism. This could be either plasma emission or ECM emission. Due to the exceptionally high brightness temperatures seen in at least one of the bursts (≥10¹⁴ K), as well as the high circular polarisation levels, it seems unlikely that plasma emission could be the source; as such, ECM is favoured as the most likely emission mechanism. Assuming this is the case, the required magnetic field in the emission regions would be 40–70 G. We determine that the most likely method of generating ECM emission is plasma co-rotation breakdown in the stellar magnetosphere. There remains the possibility, however, that it could be due to an interaction with an orbiting exoplanet.

Additional Information

© ESO 2021. Article published by EDP Sciences. Received 22 March 2021; Accepted 27 June 2021; Published online 15 September 2021. A.F.J., S.J.D.P. and T.P.R. acknowledge funding from the European Research Council (ERC) under Advanced Grant No. 743029. A.A.V. acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 817540, ASTROFLOW). This paper is based on data obtained with the International LOFAR Telescope (ILT) under project codes LC1_001 and LC12_015. LOFAR (Van Haarlem et al. 2013) is the Low Frequency Array designed and constructed by ASTRON. It has observing, data processing, and data storage facilities in several countries, that are owned by various parties (each with their own funding sources), and that are collectively operated by the ILT foundation under a joint scientific policy. The ILT resources have benefitted from the following recent major funding sources: CNRS-INSU, Observatoire de Paris and Université d'Orléans, France; BMBF, MIWF-NRW, MPG, Germany; Science Foundation Ireland (SFI), Department of Business, Enterprise and Innovation (DBEI), Ireland; NWO, The Netherlands; The Science and Technology Facilities Council, UK. This research made use of the Dutch national e-infrastructure with support of the SURF Cooperative (e-infra 180169) and the LOFAR e-infra group. The Jülich LOFAR Long Term Archive and the German LOFAR network are both coordinated and operated by the Jülich Supercomputing Centre (JSC), and computing resources on the supercomputer JUWELS at JSC were provided by the Gauss Centre for Supercomputing e.V. (grant CHTB00) through the John von Neumann Institute for Computing (NIC). This research made use of the University of Hertfordshire high-performance computing facility and the LOFAR-UK computing facility located at the University of Hertfordshire and supported by STFC [ST/P000096/1], and of the Italian LOFAR IT computing infrastructure supported and operated by INAF, and by the Physics Department of Turin university (under an agreement with Consorzio Interuniversitario per la Fisica Spaziale) at the C3S Supercomputing Centre, Italy. This research made use of Matplotlib (Hunter 2007), Scipy (Virtanen et al. 2020), and of APLpy, an open-source plotting package for Python (Robitaille & Bressert 2012).

Attached Files

Published - aa40849-21.pdf

Accepted Version - 2106.15445.pdf

Files

aa40849-21.pdf
Files (1.7 MB)
Name Size Download all
md5:c6760f389cb7c39f350a8b9a8a518e5a
856.5 kB Preview Download
md5:bff5432e65eb96c5f482b6841c44ea94
802.8 kB Preview Download

Additional details

Created:
August 20, 2023
Modified:
October 23, 2023