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SUMMARY:The many faces of optical neural networks
DTSTART:20250314T150000Z
DTEND:20250314T160000Z
DTSTAMP:20260510T045700Z
UID:indico-event-45559@agenda.infn.it
DESCRIPTION:Speakers: Alex Ivovosky (Oxford University)\n\nOptical neural 
 networks (ONNs) harness the fundamental properties of light to enable ultr
 afast\, energy-efficient computation\, surpassing the limitations of digit
 al-electronic systems in tasks such as large-scale matrix multiplications.
  By exploiting interference\, diffraction\, and nonlinearity\, ONNs can pe
 rform parallel processing of high-dimensional data\, reducing latency and 
 power consumption. This talk explores three complementary perspectives on 
 ONNs. First\, we discuss ONN applications for machine learning and our rec
 ent results on training an ONN by propagating light backwards through its 
 layers. Second\, we show how an ONN can be applied for spatial mode decomp
 osition of an optical field\, enabling the extraction of spatial informati
 on beyond the classical diffraction limit by leveraging the quantum and cl
 assical correlations in the field. Finally\, we discuss coherent Ising mac
 hines\, in which an optical network with feedback finds minimum-energy gat
 es of interacting spin systems to solve nontrivial combinatorial optimizat
 ion problems. In particular\, we highlight our recent findings on polariza
 tion symmetry breaking\, offering a new mechanism for all-optical implemen
 tation of an Ising machine. Together\, these facets illustrate the versati
 lity and transformative potential of ONNs.\n\nhttps://agenda.infn.it/event
 /45559/
LOCATION:Aula 6 (Dipartimento di Fisica-Ed. Fermi)
URL:https://agenda.infn.it/event/45559/
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