
Jin Shanmu used an autonomous run on GPT-5.6-Sol to solve a long-standing mathematical problem while researching brain ultrasounds.
Beijing-based neurosurgeon Jin Shanmu has successfully proven Crouzeix’s conjecture in numerical linear algebra using a 16-hour autonomous run on GPT-5.6-Sol.
AI-generated summary
Crouzeix’s conjecture posits that the norm of applying any function to a matrix is no larger than twice the function’s maximum value on that matrix’s numerical range.
When Beijing-based neurosurgeon Jin Shanmu pulled up a chair at his computer, he was not looking to make mathematical history. He was simply trying to crack a problem related to brain ultrasounds.
Jin, a postdoctoral researcher and resident at the Peking Union Medical College Hospital, managed to prove Crouzeix’s conjecture, a problem in numerical linear algebra.
His tool? A 16-hour autonomous run on GPT-5.6-Sol, operating on the ChatGPT Work platform.
Proposed by French mathematician Michel Crouzeix, the conjecture posits that the norm of applying any function to a matrix is no larger than twice the function’s maximum value on that matrix’s numerical range.
While abstract, it has long been an intriguing problem in matrix analysis – a field Jin stumbled into while undertaking research on transcranial ultrasounds.

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