BEGIN:VCALENDAR VERSION:2.0 PRODID:IEEE vTools.Events//EN CALSCALE:GREGORIAN BEGIN:VTIMEZONE TZID:America/New_York BEGIN:DAYLIGHT DTSTART:20260308T030000 TZOFFSETFROM:-0500 TZOFFSETTO:-0400 RRULE:FREQ=YEARLY;BYDAY=2SU;BYMONTH=3 TZNAME:EDT END:DAYLIGHT BEGIN:STANDARD DTSTART:20261101T010000 TZOFFSETFROM:-0400 TZOFFSETTO:-0500 RRULE:FREQ=YEARLY;BYDAY=1SU;BYMONTH=11 TZNAME:EST END:STANDARD END:VTIMEZONE BEGIN:VEVENT DTSTAMP:20260427T230032Z UID:1E8FD837-D69D-4D2B-8478-F34B067C5CB5 DTSTART;TZID=America/New_York:20260424T103000 DTEND;TZID=America/New_York:20260424T113000 DESCRIPTION:Abstract:\nArtificial intelligence and combinatorial optimizati on problems—such as drug discovery and prime factorization—remain chal lenging even for advanced computers. We are attempting to address these li mitations by building photonic processors inspired by the brain—photonic neural networks—which utilize light for faster and more energy-efficien t processing [1]. We will discuss photonic networks\, including Ising mach ines enabled by thin-film lithium niobate photonics [2]\, highlighting the ir applications in number partitioning\, protein folding\, wireless commun ications\, and deep learning. Time permitting\, we will briefly introduce a quantum photonic neural network that can learn to act as near-perfect co mponents of quantum technologies and discuss the role of weak nonlineariti es [3].\n\n[1] Shastri\, B.J. et al. Photonics for artificial intelligence and neuromorphic computing. Nature Photonics 15 (2021)\n[2] Al-Kayed\, N. et al. Programmable 200 GOPS Hopfield-inspired photonic Ising machine. Na ture 648 (2025)\n[3] Ewaniuk\, J et al. Imperfect quantum photonic neural networks. Advanced Quantum Technologies (2023) .\n\nCo-sponsored by: Prof. Nicolas Quesada\n\nSpeaker(s): Bhavin J. Shastri\n\nJ. Armand Bombardier J-1035\, Polytechnique Montréal\, Montréal\, Quebec\, Canada\, H3T 1J4 LOCATION:J. Armand Bombardier J-1035\, Polytechnique Montréal\, Montréal\ , Quebec\, Canada\, H3T 1J4 ORGANIZER:nicolas.quesada@polymtl.ca SEQUENCE:104 SUMMARY:Photonic Ising machines and quantum neural networks URL;VALUE=URI:https://events.vtools.ieee.org/m/538645 X-ALT-DESC:Description: <br /><div><img src="https://events.vtools.ieee.org /vtools_ui/media/display/75a584d4-d76d-4b6e-a686-ff2555abf321" width="888" height="519"></div>\n<div>&nbsp\;</div>\n<div><span style="font-family: ' times new roman'\, times\, serif\;"><strong>Abstract:&nbsp\;</strong></spa n>\n<div data-olk-copy-source="MessageBody"><span style="font-family: 'tim es new roman'\, times\, serif\;">Artificial intelligence and combinatorial optimization problems&mdash\;such as drug discovery and prime factorizati on&mdash\;remain challenging even for advanced computers. We are attemptin g to address these limitations by building photonic processors inspired by the brain&mdash\;photonic neural networks&mdash\;which utilize light for faster and more energy-efficient processing [1]. We will discuss photonic networks\, including Ising machines enabled by thin-film lithium niobate p hotonics [2]\, highlighting their applications in number partitioning\, pr otein folding\, wireless communications\, and deep learning. Time permitti ng\, we will briefly introduce a quantum photonic neural network that can learn to act as near-perfect components of quantum technologies and discus s the role of weak nonlinearities [3].</span></div>\n<div>&nbsp\;</div>\n< div><span style="font-family: 'times new roman'\, times\, serif\;">[1] Sha stri\, B.J. et al. Photonics for artificial intelligence and neuromorphic computing. Nature Photonics 15 (2021)</span></div>\n<div><span style="font -family: 'times new roman'\, times\, serif\;">[2] Al-Kayed\, N. et al. Pro grammable 200 GOPS Hopfield-inspired photonic Ising machine. Nature 648 (2 025)</span></div>\n<div><span style="font-family: 'times new roman'\, time s\, serif\;">[3] Ewaniuk\, J et al. Imperfect quantum photonic neural netw orks. Advanced Quantum Technologies (2023)</span></div>\n.</div> END:VEVENT END:VCALENDAR