Harvard John A. Paulson School of
Engineering and Applied Sciences
EE Seminars
Please join us at SEC 1.413 or
Zoom<https://urldefense.proofpoint.com/v2/url?u=https-3A__harvard.zoom.u…
Upcoming Seminar: Nikolai Matni What makes learning to control easy or hard?
11/04/22<https://events.seas.harvard.edu/event/what_makes_learning_to_co…
Friday, October 28th at 11am ET
Davi Geiger, Professor, Courant Institute of Mathematical Sciences and of Neural Science,
New York University. "Spin and Qubit
Entropy<https://events.seas.harvard.edu/event/spin_and_qubit_entropy>…
Abstract:
Quantum physics, in its current formulation, is time reversible.
We propose a definition of quantum entropy for the spin and the qubit variables,
accounting for the uncertainty in the specification of a quantum state and the
probabilistic nature of its observables. It is rooted in the geometric quantization of the
spin.
This entropy overcomes the limitations of previously-proposed entropies, such as von
Neumann entropy which is restricted to quantify the randomness of specifying the quantum
state. As an example of a limitation, previously-proposed entropies are higher for Bell
entangled spin states than for disentangled spin states, even though the spin observables
are less constrained for a disentangled pair of spins than for an entangled pair.
The proposed entropy accurately quantifies the randomness of a spin or a qubit state, it
is lower for entangled states than for disentangled states, and its minimum is positive.
We suggest that the proposed entropy must always increase over time, so that the
randomness of a closed physical system cannot be reduced, thus creating a time arrow for
quantum physics.
Speaker bio:
Davi Geiger is an Associate Professor of Computer Science at the Courant Institute of
Mathematical Sciences and of Neural Science, New York University.
He is also a CoFounder of Kooick.ai and
Nhega.com. He received the BS in Physics at PUC
Rio de Janeiro, Brasil the Ph.D in Physics and Artificial Intelligence at MIT with
Professor Tomaso Poggio. Before coming to NYU, he spent three years at Siemens Corporate
Research in Princeton. He has received an NSF Career award. His interests include Computer
Vision, Machine Learning, Artificial Intelligence, Quantum Physics and Quantum Field
Theory.
Host: Woodward Yang
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