Reduced measurement cost speeds quantum circuit design for optimization
Measurement-Efficient Differentiable Quantum Architecture Search for Combinatorial Optimization
Machine Learning
Summary
Designing quantum circuits to solve complex problems usually requires many measurements, making it costly to run on real quantum computers. The authors show a way to cut these measurement needs by about 40% for a big group of optimization problems without changing the quality of the results. They tested their idea using two well-known problems and found their method lowers the workload on quantum hardware with minimal extra work on regular computers. This makes it more practical to use quantum computing in solving hard optimization tasks.
What this means in practice
- •For quantum computing engineers: Reduce quantum hardware runs needed to tune quantum algorithms for combinatorial optimization problems.
- •For optimization software developers: Create more efficient tools that integrate quantum circuit design with fewer resource demands for complex scheduling and routing problems.
Authors
Lukas Theißinger, Thore Gerlach, Christian Bauckhage
Abstract
Differentiable quantum architecture search (DQAS) is a promising framework for the automated design of quantum circuits, particularly for variational quantum optimization algorithms. However, its practical deployment on quantum hardware is limited by the large number of circuit measurements required during optimization, making hardware execution costly. In this work, we show that for a broad class of combinatorial optimization problems and commonly used rotational gate parameterizations, the measurement cost of DQAS can be significantly reduced without changing the optimization objective. We derive the proposed measurement reduction scheme theoretically and validate it experimentally on 3-SAT and MaxCut benchmark problems. Our approach reduces the requested gradient measurement cost by about 39 to 41% while introducing only negligible classical post-processing overhead, lowering the practical cost of executing DQAS on quantum hardware.