Multi-tasking through quantum annealing

TL;DR

This paper introduces multi-tasking quantum annealing (MTQA), enabling parallel processing of multiple optimization problems on quantum hardware, improving resource utilization and reducing solution time.

Contribution

The study presents MTQA, a novel method for embedding multiple problems into quantum annealing hardware, maintaining solution quality while enhancing efficiency and throughput.

Findings

MTQA achieves comparable solution quality to single-problem quantum annealing.

MTQA reduces time-to-solution (TTS) compared to classical methods.

Parallel embedding preserves quantum coherence without increasing complexity.

Abstract

Quantum annealing approximately solves combinatorial optimization problems by leveraging the principles of adiabatic quantum systems. In this approach, the system's Hamiltonian evolves from an initial general state to a problem-specific state. This study introduces multi-tasking quantum annealing (MTQA), a method that enables the parallel processing of multiple optimization problems by embedding them into spatially distinct regions on quantum hardware. MTQA is evaluated using two NP-hard problems: the minimum vertex cover problem (MVCP) and the graph partitioning problem (GPP). This parallel approach optimizes quantum resource utilization by concurrently utilizing idle qubits. The findings demonstrate that MTQA achieves a solution quality comparable to single-problem quantum annealing and classical simulated annealing (SA), while notably reducing the time-to-solution (TTS) metrics. Eigenspectrum analysis further theoretically supports the hypothesis that parallel embedding preserves quantum coherence and does not increase computational complexity by efficiently utilizing available quantum hardware (e.g., qubits and couplers). MTQA enables efficient multitasking in quantum annealing, optimizing hardware utilization and improving throughput for concurrent tasks and demonstrating performance for problems up to 100 nodes in real-world applications.