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17.12.2020 - 17.12.2020 | Virtual lecture

Programming Complexity: Large-Scale Photonics for Quantum Information and Machine Learning

Dirk Englund from the Massachussetts Institute of Technology will talk about "Programming Complexity: Large-Scale Photonics for Quantum Information and Machine Learning".
The lecture is part of the Distinguished Lecturer Series (DLS) at the Max Planck Institute for the Science of Light.

As part of the Distinguished Lecturer Series (DLS) at the Max Planck Institute for the Science of Light, Dirk Englund from the Massachussetts Institute of Technology will talk about "Programming Complexity: Large-Scale Photonics for Quantum Information and Machine Learning". Due to the circumstances, the lecture will be held virtually via Zoom.

Abstract:

After several decades of intensive theoretical and experimental efforts, the field of quantum information processing at a critical moment: special-purpose quantum information processors are at or past the “quantum complexity frontier” where classical computers can no longer predict their outputs: we can “program complexity”, unable to predict the outcome. Meanwhile, new technologies to connect quantum processors by photons give rise to quantum networks with functions impossible on today’s “classical-physics” internet. However, to harness the power of quantum complexity in “noisy intermediate-scale” quantum computers and networks requires advanced methods in quantum control and noise mitigation - perhaps to the ultimate goal of fault tolerant computing. This talk discusses one approach in that direction: large-scale programmable photonic integrated circuits (PICs) designed to control photons and atomic or atom-like quantum memories. The second part of the talk considers another “complexity frontier”: that encountered in machine learning and signal processing when trying to process exponentially growing quantities of data. These problems present new opportunities at the intersection with quantum information technologies - specifically, we will consider new directions for processing classical and quantum information in deep learning neural networks architectures.

Biography:

Dirk Englund received his BS in Physics from Caltech in 2002. After a Fulbright fellowship at T.U. Eindhoven, he completed an MS in Electrical Engineering and a PhD in Applied Physics at Stanford University in 2008. After a postdoctoral fellowship at Harvard University, he joined Columbia University as Assistant Professor of E.E. and of Applied Physics. He joined the MIT EECS faculty in 2013. Major recognitions include the 2011 Presidential Early Career Award in Science and Engineering, the 2011 Sloan Fellowship in Physics, the OSA's 2017 Adolph Lomb Medal, the Bose Research Fellowship in 2018, and a Humboldt Research Fellowship in 2020.

Hinweise zur Teilnahme:
Due to the circumstances, the lecture will be held via Zoom. To get the login credentials, please subscribe for the DLS Newsletter at https://mpl.mpg.de/newsletter. The Zoom link is sent to the subscribers some hours before the lecture.

Termin:

17.12.2020 15:00 - 16:00

Veranstaltungsort:

Online lecture via Zoom
Virtual lecture
Bayern
Deutschland

Zielgruppe:

Studierende, Wissenschaftler

E-Mail-Adresse:

Relevanz:

international

Sachgebiete:

Informationstechnik, Physik / Astronomie

Arten:

Vortrag / Kolloquium / Vorlesung

Eintrag:

08.12.2020

Absender:

Clarissa Grygier

Abteilung:

Kommunikation und Marketing

Veranstaltung ist kostenlos:

ja

Textsprache:

Englisch

URL dieser Veranstaltung: http://idw-online.de/de/event67532

Anhang
attachment icon Plakat DLS Dirk Englund

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