Seminaria

"Variability as a tool to map the accretion structure in AGN and prospects for NewAthena"

Scott Hagen (SISSA Trieste)

Active galactic nuclei (AGN) are powered by accretion onto a supermassive black hole (SMBH). Observations show that these vary on week-year timescales in the optical/UV and day-weeks in the X-ray. This is in stark contrast to standard accretion theory which predicts that they can only vary on ~10^5 year timescales, suggesting significant limitations in our understanding of accretion onto SMBHs. In this talk I will discuss how AGN variability provide an opportunity to study the physical conditions and structure of the accretion flow; from the central flow near the SMBH to outer large scale height structures such as the broad line region (BLR) and winds. I will show how modelling assuming a modified, intrinsically variable, disc structure can qualitatively match the observed variability properties; albeit with some limitations. I will further show results from a number of recent monitoring campaigns that highlight not only intrinsic variability, but also extrinsic variations caused by obscuring winds and variations in the BLR. Finally, I will briefly discuss the prospects for the upcoming ESA flagship mission NewAthena to probe the link between the inner flow and large scale structures (e.g. winds, the BLR) through a subset of sources displaying extreme variations in their inner structure.

"Cognitive outsourcing: Gain or loss in Astronomy?"

Sudhagar Suyamprakasam (NCAC, Warsaw)

Brief summary from the papers.

• What understanding means in AI-laden astronomy.  Yuan-Sen Ting, André Curtis-Trudel & Siyu Yao. Nature: s41550-026-02809-6
• Outsourcing thinking to AI? Focused immersion, AI dependency, and the double-edged impact on critical thinking. Jinrui Tian & Ronghua Zhan. Nature April 2026 
• How AI Impacts Skill Formation. Judy Hanwen Shen, Alex Tamkin. ArXiv:2601
• The last astronomers Amid a flood of AI advances, astrophysicists are questioning the soul of their field. Joshua Sokol Science. Science: 04 Jun 2026

The discussion points are here.   [1] In your view, to what extent are AI tools becoming essential for learning and knowledge acquisition, and how reliable are they as information sources?

[2] What are the potential benefits and drawbacks of AI-assisted research in astronomy, particularly in terms of its impact on human cognitive abilities, critical thinking, and scientific reasoning?

[3] What steps can academic and research institutions take to identify, assess, and monitor gradual changes in cognitive abilities, critical thinking, and independent reasoning associated with the increasing use of AI?

[4] Does insufficient research funding, limited human resources, and increasing pressure to publish in academia drive researchers to rely more heavily on AI tools to maintain research productivity and publication output?

[5] Academic and research organisations provide journals, library, internet access and specialist software. Should access to paid AI tools be seen as an equally valid component of research infrastructure?