STONKS: How XMM-Newton is Finding Faint Transients

In this episode, we explore the dynamic and violent universe revealed by the STONKS pipeline (Search for Transient Object in New observations using Known Sources). While the name might remind you of internet finance memes, this system is a serious tool for the XMM-Newton space telescope. We discuss how researchers are using STONKS to detect long-term X-ray transients in the Galactic plane that are too faint for standard wide-field survey instruments to see.

Join us as we break down the first results from a multi-year survey of the Galaxy, identifying 70 astrophysical sources that change in brightness over time. From waking magnetars to flaring stars, we look at what these faint signals tell us about the most extreme physical environments in the cosmos.

Key Topics Discussed:

• What is STONKS? A near-real-time detection system that compares new XMM-Newton observations against archival data to spot variability.
• The Advantage: Unlike survey missions (like Swift or eROSITA), STONKS utilizes long exposure times to find variable sources at fluxes several orders of magnitude lower than other systems.

Major Discoveries:

• A Magnetar Candidate: The detection of a potential magnetar (4XMM J175136.9-275858) caught at the onset of a massive outburst, increasing in brightness by nearly two orders of magnitude.
• Exotic Stars: The identification of a $\gamma$-Cas analogue (HD 162718) and new candidates for Cataclysmic Variables (CVs).
• New Detections: Of the 70 sources analyzed, 23 were detected in X-rays for the very first time.
• The Future: How systematic analysis of archival data is opening a new window into stellar evolution and compact objects like black holes and neutron stars.

Reference Material

"STONKS first results: Long-term transients in the XMM-Newton Galactic plane survey", Robbie Webbe, E. Quintin, N. A. Webb, Gabriele Ponti, Tong Bao, Chandreyee Maitra, Shifra Mandel, Samaresh Mondal, Astronomy & Astrophysics manuscript no. aa57789-25, January 28, 2026.

Acknowledements: Podcast prepared with Google/NotebookLM. Illustration credits: ESA