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May 20, 20260 citationsOpen Access

Exploring Magnetic Star-Planet Interactions in CARMENES targets Using Radio Observations

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LPL. Peña-MoñinoMPM. Pérez-Torres

Key Points

  • This research investigates how magnetic interactions between stars and planets can influence radio emissions from nearby star systems. The aim is to understand the relationship between these emissions and stellar properties.
  • Multi-epoch observations using uGMRT Band 4 to detect SPI-driven emission from CARMENES systems.
  • Extended analysis of GJ 486 incorporating various efficiencies for Poynting flux to radio emission conversion and different stellar wind models.
  • Developed exclusion maps to delineate constraints on stellar mass-loss rates and conversion efficiencies.
  • Non-detections from GJ 806, GJ 436, and CD Cet indicate no observable SPI-driven emission.
  • Analysis of GJ 486 highlights how the choice of interaction models influences emission predictions.
  • Exclusion maps reveal critical combinations of mass-loss rates and conversion efficiencies that can be ruled out based on observations.

Abstract

Magnetic star–planet interaction (SPI) in the sub-Alfvénic regime can channel Poynting flux back to the host star and potentially power highly circularly polarised, time-variable electron–cyclotron maser (ECM) emission. Here we present multi-epoch uGMRT Band 4 observations aimed at searching for SPI-driven emission from nearby CARMENES systems (GJ 806, GJ 436, and CD Cet). Our preliminary results show non-detections for all of these CARMENES systems. We then revisit GJ 486 using the latest public release of our SIRIO code, extending our published uGMRT analysis by (i) exploring a large range of efficiencies in the conversion of Poynting flux into radio emission, β, and stellar mass-loss rates; and (ii) incorporating additional interaction prescriptions and wind/magnetic geometries. The resulting exclusion maps directly show how uGMRT non-detections constrain the allowed combinations of stellar mass-loss rate and β, and highlight which modelling assumptions dominate the inference.

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Cite This Study

Peña-Moñino et al. (2026) studied this question.

synapsesocial.com/papers/6a0d5098f03e14405aa9c83fhttps://doi.org/10.25935/prex-llh6
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