Bulletin of the American Physical Society
APS March Meeting 2021
Volume 66, Number 1
Monday–Friday, March 15–19, 2021; Virtual; Time Zone: Central Daylight Time, USA
Session Y09: Quantum Machine Learning
11:30 AM–2:30 PM,
Friday, March 19, 2021
Sponsoring Unit: DQI
Chair: Yariv Yanay, Laboratory for Physical Sciences
Abstract: Y09.00004 : Classical simulation of quantum circuits with neural-network states
1:18 PM–1:54 PM
In this talk I will discuss advances in the classical variational representations of many-qubit states based on artificial neural networks.
First I will present results concerning the expressive power of neural-network quantum states, rewiewing representation theorems and arguing that these representations are not limited by the amount of entanglement they can encode.In this context, I will also show a new explicit and polynomially efficient mapping from contractible tensor-network states.
Then, I will show several applications of these variational representations, with a focus on quantum computing applications. Most notably, I will discuss machine-learning-based techniques useful to simulate large structured quantum circuits, beyond what is currently accessible with other classical approaches.
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