Conventional quantum algorithms are not feasible for solving combinatorial optimization problems (COPs) with constraints in the operation time of quantum computers. To address this issue, researchers have developed a novel algorithm called post-processing variationally scheduled quantum algorithm.
Conventional quantum algorithms are not feasible for solving combinatorial optimization problems with constraints in the operation time of quantum computers. To address this issue, researchers have developed a novel algorithm called post-processing variationally scheduled quantum algorithm. The novelty of this innovative algorithm lies in the use of a post-processing technique combined with variational scheduling to achieve high-quality solutions to COPs in a short time.
Quantum computers take advantage of the quantum property of superposition, using specialized qubits, that can exist in an infinite yet contained number of states of 0 or 1 or any combination of the two, to quickly solve large problems. However, when COPs involve constraints, conventional quantum algorithms like adiabatic quantum annealing struggle to obtain a near-optimal solution within the operation time of quantum computers.
The researchers analyzed the performance of this algorithm using both a simulator and real quantum devices such as a quantum annealer and a gate-type quantum device. The experiments revealed that pVSQA achieves a near-optimal performance within a predetermined time on the simulator and outperforms conventional quantum algorithms without post-processing on real quantum devices.
Tatsuhiko Shirai is currently an Assistant Professor at the Department of Computer and Communications Engineering at Waseda University in Japan. He obtained his master's and Ph.D. in Physics from the University of Tokyo in 2013 and 2016 respectively. In 2022, he obtained the SLDM Research Group Excellent Paper Award. His research interests include quantum algorithms, quantum open systems, and quantum computing. He is a member of The Physical Society of Japan.
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