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SUMMARY:Promotionsvortrag Physik: Automated discovery of better quantu
 m machines
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 00000010000000162F2A31C90BD443BF85C506E05FD0F2
DESCRIPTION:Ankündigung des Promotionsvortrags von: Herrn Jonas Landg
 raf Human intelligence is associated with the ability to perform compl
 ex reasoning\, find creative solu-tions to problems\, and discover and
  generalize patterns. Ambitiously\, the field of artificial intelli-ge
 nce (AI) aims to enable computer systems to acquire such abilities and
  has experienced re-markable progress in recent years. Leveraging thes
 e advances for scientific research has the potential to accelerate pro
 gress and achieve milestones previously unreachable. In this thesis\, 
 we develop and adapt new tools based on AI and numerical optimization 
 to address several chal-lenges in quantum information processing. In p
 articular\, we implement a sub-microsecond-latency neural network for 
 the control of a super-conducting circuit experiment. This neural netw
 ork is capable of interacting with the quantum ex-periment in real-tim
 e\, so on time scales much shorter than the system&#8217\;s coherence 
 time. Using reinforcement learning\, we train the network exclusively 
 from measurements and show that it can efficiently initialize a superc
 onducting transmon. Furthermore\, we develop an algorithm to automatic
 ally discover new design schemes for signal-processing devices. Our al
 gorithm optimizes the discrete and continuous system parameters to ach
 ieve the desired target behavior with the minimum required resources. 
 By using an abstract graph representation\, the discovered setups can 
 be interpreted easily\, leading to multiple gener-alizations. Our desi
 gn concepts are transferable and can be implemented on a variety of ha
 rdware platforms\, including photonic\, microwave\, and optomechanical
  systems. In the last part of the talk\, we demonstrate how to extend 
 these concepts to discover lattice models comprising a periodic struct
 ure. (Vortrag auf Englisch) Dem Vortrag schließt sich eine Diskussion
  von 15 Minuten an. Vortrag und Diskussion sind öffentlich. Diesen Ve
 rfahrensteilen folgt ein nicht öffentliches Rigorosum v
DTSTART:20260204T130000Z
DTEND:20260204T143000Z
LOCATION:Leuchs-Russell-Auditorium\, MPI\, Staudtstr. 2\, Erlangen
DTSTAMP:20260411T092235Z
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