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Quantum Annealers (QAs) operate as single-instruction machines, lacking aSWAP operation to overcome limited qubit connectivity. Consequently, multiplephysical qubits are chained to form a program qubit with higher connectivity,resulting in a drastically diminished effective QA capacity by up to 33x. Weobserve that in QAs: (a) chain lengths exhibit a power-law distribution, a fewdominant chains holding substantially more qubits than others; and (b) about25% of physical qubits remain unused, getting isolated between these chains. Wepropose Skipper, a software technique that enhances the capacity and fidelityof QAs by skipping dominant chains and substituting their program qubit withtwo readout results. Using a 5761-qubit QA, we demonstrate that Skipper cantackle up to 59% (Avg. 28%) larger problems when eleven chains are skipped.Additionally, Skipper can improve QA fidelity by up to 44% (Avg. 33%) whencutting five chains (32 runs). Users can specify up to eleven chain cuts inSkipper, necessitating about 2,000 distinct quantum executable runs. Tomitigate this, we introduce Skipper-G, a greedy scheme that skips sub-problemsless likely to hold the global optimum, executing a maximum of 23 quantumexecutables with eleven chain trims. Skipper-G can boost QA fidelity by up to41% (Avg. 29%) when cutting five chains (11 runs).

Skipper: Improving the Reach and Fidelity of Quantum Annealers by Skipping Long Chains