Researchers at the Swiss Federal Institute of Technology Lausanne (EPFL) in Switzerland and Columbia University have developed a method for using a traditional computer to simulate the Quantum Approximate Optimization Algorithm (QAOA).
The approach employs a classical machine learning algorithm that acts like near-term quantum computers.
The researchers used an artificial neural network previously co-developed by EPFL's Giuseppe Carleo to simulate QAOA, which is considered a promising candidate for "quantum advantage" in near-term quantum computers.
Said Carleo, "This does not mean that all useful quantum algorithms that can be run on near-term quantum processors can be emulated classically. In fact, we hope that our approach will serve as a guide to devise new quantum algorithms that are both useful and hard to simulate for classical computers."
From EPFL (Switzerland)
View Full Article
Abstracts Copyright © 2021 SmithBucklin, Washington, DC, USA
No entries found