Using PennyLane for Quantum Differentiable Programming




January 10, 2022 6:00 PM

We invite you to attend Episode XXXIV of the Warsaw Quantum Computing Group meetup, this time on 10.01.2022, 18:00 CET. Antal Szava will give a talk "Using PennyLane for Quantum Differentiable Programming".

If you are interested, please register by 9.01 EOD:

Abstract from Antal: Advances in deep learning have greatly affected quantum computation, allowing a plethora of previously intractable scientific problems to be within reach for investigation via scientific computing. A key factor behind this new field is the availability of quantum software and differentiable programming. PennyLane is a cross-platform Python library for differentiable programming of quantum computers. It allows coding up solutions to problems in quantum machine learning, quantum chemistry and quantum computation and allows training quantum computers the same way as classical neural networks. To achieve all this, PennyLane integrates with multiple machine learning libraries and is device-agnostic: it only takes a single line of code to be changed to run the same program on simulators or real quantum hardware. During this talk, we will cover how differentiable programming and quantum computation can go hand in hand and cover how PennyLane is used to solve specific problems in the domains of quantum machine learning and quantum computation.

BIO: Antal Száva works as a quantum software developer at the Toronto-based quantum computing startup Xanadu and leads the PennyLane core development subteam. In 2019, he obtained a double Master's degree at the Technical University of Berlin and the Delft University of Technology University in computer science. He completed his thesis at the QuTech research centre with the topic of quantum network routing.
You can find the details on the event's website:

We wish you a Happy 2022 Year and hope to see you soon!

Quantum AI Foundation

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