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Abstract
In the last decade, public and industrial research funding has moved quantum computing from the early promises of Shor’s algorithm through experiments to the era of noisy intermediate scale quantum devices (NISQ) for solving realworld problems. It is likely that quantum methods can efficiently solve certain (NP) hard optimization problems where classical approaches fail. In our perspective, we examine the field of quantum optimization, that is, solving optimization problems using quantum computers. We provide an entry point to quantum optimization for researchers from each topic, optimization or quantum computing, by demonstrating advances and obstacles with a suitable use case. We give an overview on problem formulation, available algorithms, and benchmarking. Although we show a proofofconcept rather than a full benchmark between classical and quantum methods, this gives an idea of the current quality and capabilities of quantum computers for optimization problems. All observations are incorporated in a discussion on some recent quantum optimization breakthroughs, current status, and future directions.
Original language  English 

Article number  1128576 
Number of pages  9 
Journal  Frontiers in Quantum Science and Technology 
Volume  2 
DOIs  
Publication status  Published  23 Feb 2023 
Keywords
 quantum computing (QC)
 quantum optimization
 perspecitves
 optimization algorithms
 problem modeling
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 1 Active

Quantum Enhanced and Verified Exascale Computing  QEVEC (Transfer)
Kendon, V. (Principal Investigator)
EPSRC (Engineering and Physical Sciences Research Council)
1/11/21 → 31/03/25
Project: Research