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SUMMARY:From Shannon to Schrödinger: Quantum Information\, PET and AI
DTSTART;VALUE=DATE-TIME:20260908T131000Z
DTEND;VALUE=DATE-TIME:20260908T135000Z
DTSTAMP;VALUE=DATE-TIME:20260922T191401Z
UID:indico-contribution-2056@events.ncbj.gov.pl
DESCRIPTION:Speakers: Beatrix Hiesmayr (University of Vienna)\nAI now riva
 ls or surpasses humans on many well-defined tasks\, sharpening the need to
  clarify what "information" means across disciplines. This talk frames inf
 ormation operationally: Shannon entropy for classical systems and von Neum
 ann entropy for quantum states\, and shows how these measures structure\, 
 analyze\, and reduce uncertainty in machine learning and data-driven infer
 ence. We compare classical and quantum information—highlighting superpos
 ition\, entanglement\, measurement disturbance\, and no-cloning—and conn
 ect these principles to technologies ranging from Positron Emission Tomogr
 aphy (PET)\, where information limits govern reconstruction quality and do
 se–time trade-offs\, to quantum computing\, where information is encoded
 \, processed\, and\nprotected under fundamentally different constraints. W
 e conclude with a speculative platform that illuminates the interface of g
 ravity and quantum control: using the discrete gravitational bound states 
 of a single neutron as  a qudit. The discussion emphasizes the unifying ro
 le of information across disciplines.\n\nhttps://events.ncbj.gov.pl/event/
 468/contributions/2056/
LOCATION:
URL:https://events.ncbj.gov.pl/event/468/contributions/2056/
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