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Physics World

D-Wave rides high

Published Jun 1, 2011• 0 citations
Publisher
DOI
10.1088/2058-7058/24/06/6

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Quantum computers are noisy; without quantum error correction (QEC), deep programs fail as qubits lose information due to decoherence. Among QEC approaches, bivariate bicycle (BB) codes offer low overhead and constant-depth syndrome extraction, while neutral-atom arrays provide scalable, reconfigurable qubit layouts. However, executing BB-code primitives on neutral-atom systems requires a hardware-aware mapping that respects movement, zoning, and interaction constraints. We present Park-n-Ride, a system for compiling and executing the BB code on neutral-atom processors. Park-n-Ride introduces a module layout and movement model aligned with neutral-atom constraints, exposes a compact BB-native logical interface for compilation, and integrates scheduling mechanisms that enable efficient execution on zoned architectures. By co-designing BB-code abstractions with hardware execution, Park-n-Ride provides a practical path from qLDPC primitives to resource-efficient, high-throughput execution on reconfigurable neutral-atom arrays.
The Dial-a-Ride Problem (DARP) is a variant of the NP-hard vehicle routing problem with significant practical relevance in modern transportation systems. In this work, we introduce a novel Quadratic Unconstrained Binary Optimization formulation of the DARP that explicitly incorporates routing and time window constraints without requiring continuous variables, thereby making it compatible with quantum optimization approaches. We employ quantum annealing on D-Wave hardware to solve the resulting instances. As the hardware alone cannot identify the ground states for instances with 196 qubits, we enhance the obtained solutions using the Quantum-Guided Cluster Algorithm, a post-processing heuristic that leverages two-point correlations between sampled states. Our numerical results demonstrate that the proposed hybrid quantum-classical framework yields close-to-optimal solutions quickly for instances of up to 14 requests.