Discovery of Magnetospheric Interactions in the Doubly-Magnetic Hot Binary $ε$ Lupi
Bibliographic record
Abstract
Magnetic fields are extremely rare in close, hot binaries, with only 1.5\% of such systems known to contain a magnetic star. The eccentric $ε$ Lupi system stands out in this population as the only close binary in which both stars are known to be magnetic. We report the discovery of strong, variable radio emission from $ε$ Lupi using the upgraded Giant Metrewave Radio Telescope (uGMRT) and the MeerKAT radio telescope.The light curve exhibits striking, unique characteristics including sharp, high-amplitude pulses that repeat with the orbital period, with the brightest enhancement occurring near periastron. The characteristics of the light curve point to variable levels of magnetic reconnection throughout the orbital cycle, making $ε$ Lupi the first known high-mass, main sequence binary embedded in an interacting magnetosphere. We also present a previously unreported enhancement in the X-ray light curve obtained from archival XMM-Newton data. The stability of the components' fossil magnetic fields, the firm characterization of their relatively simple configurations, and the short orbital period of the system make $ε$ Lupi an ideal target to study the physics of magnetospheric interactions. This system may thus help us to illuminate the exotic plasma physics of other magnetically interacting systems such as moon-planet, planet-star, and star-star systems including T Tauri binaries, RS CVn systems, and neutron star binaries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".