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SUMMARY:The New Scientific Method - Will Handley
DTSTART:20260219T160000Z
DTEND:20260219T170000Z
UID:TALK244834@talks.cam.ac.uk
CONTACT:Matthew Grayling
DESCRIPTION:In the 1990s\, CCDs replaced photographic plates and transform
 ed observational astronomy. Today\, GPU hardware and large language models
  are driving a comparable shift in how we analyse data. Astronomy has inve
 sted enormously in the current generation of instruments such as JWST\, DE
 SI\, Euclid\, LSST and the SKA\, and many of the analyses needed to fully 
 exploit them have\, until now\, been computationally prohibitive.\n\nThis 
 is often framed as a job for neural networks. In fact\, classical\, interp
 retable statistical methods on the same GPU hardware can match or outperfo
 rm neural network approaches\, and the consequences go beyond speed. It ma
 rks a shift from fitting a single model to comparing hundreds\, from ignor
 ing systematics to marginalising over them\, and from waiting days to acti
 ng in real time.\n\nLarge language models are driving a separate revolutio
 n\, not replacing the scientist but transforming how researchers work: bui
 lding and verifying complex analyses\, interrogating legacy codebases\, an
 d synthesising research across large teams. In this talk I will illustrate
  both through results from our group\, including new results on dark energ
 y from DESI\, Type Ia supernova standardisation\, real-time gravitational-
 wave follow-up and 21-cm radio astronomy\, and argue that rigorous analysi
 s made routine\, combined with LLM-assisted development under robust verif
 ication\, is the start of a new scientific method.
LOCATION:Hoyle Lecture Theatre\, Institute of Astronomy
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