The Quantum Approximate Optimization Algorithm and spin chains
APA
Mbend, G. (2019). The Quantum Approximate Optimization Algorithm and spin chains. Perimeter Institute. https://pirsa.org/19070079
MLA
Mbend, Glen. The Quantum Approximate Optimization Algorithm and spin chains. Perimeter Institute, Jul. 09, 2019, https://pirsa.org/19070079
BibTex
@misc{ pirsa_PIRSA:19070079, doi = {10.48660/19070079}, url = {https://pirsa.org/19070079}, author = {Mbend, Glen}, keywords = {Condensed Matter}, language = {en}, title = {The Quantum Approximate Optimization Algorithm and spin chains}, publisher = {Perimeter Institute}, year = {2019}, month = {jul}, note = {PIRSA:19070079 see, \url{https://pirsa.org}} }
SISSA International School for Advanced Studies
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Talk Type
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Abstract
Various optimization problems that arise naturally in science are frequently solved by heuristic algorithms. Recently, multiple quantum enhanced algorithms have been proposed to speed up the optimization process, however a quantum speed up on practical problems has yet to be observed. One of the most promising candidates is the Quantum Approximate Optimization Algorithm (QAOA), introduced by Farhi et al. I will then discuss numerical and exact results we have obtained for the quantum Ising chain problem and compare the performance of the QAOA and the Quantum Annealing algorithm. I will also briefly describe the landscape that emerges from the optimization problem and how techniques borrowed from machine learning can be used to improve the optimization process.