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

arXiv: https://arxiv.org/abs/2312.00264 · HTML: https://mlsanity.com/paper/2312.00264/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 17 of its 108 references that are in the map.
- First posted on arXiv 1 Dec 2023.

## Builds on (most cited first, 17 of 17)

- [Epidemic processes in complex networks](https://mlsanity.com/paper/1408.2701/) (2014)
- [Scale-free networks are rare](https://mlsanity.com/paper/1801.03400/) (2018)
- [A practical heuristic for finding graph minors](https://mlsanity.com/paper/1406.2741/) (2014)
- [Nonnegative/binary matrix factorization with a D-Wave quantum annealer](https://mlsanity.com/paper/1704.01605/) (2017)
- [Noise-Adaptive Compiler Mappings for Noisy Intermediate-Scale Quantum Computers](https://mlsanity.com/paper/1901.11054/) (2019)
- [Fast clique minor generation in Chimera qubit connectivity graphs](https://mlsanity.com/paper/1507.04774/) (2015)
- [Extracting Success from IBM's 20-Qubit Machines Using Error-Aware Compilation](https://mlsanity.com/paper/1903.10963/) (2019)
- [Quantum Annealing Implementation of Job-Shop Scheduling](https://mlsanity.com/paper/1506.08479/) (2015)
- [A Survey on Compressive Sensing: Classical Results and Recent Advancements](https://mlsanity.com/paper/1908.01014/) (2019)
- [HAMMER: boosting fidelity of noisy Quantum circuits by exploiting Hamming behavior of erroneous outcomes](https://mlsanity.com/paper/2208.09371/) (2022)
- [An Ensemble Approach for Compressive Sensing with Quantum](https://mlsanity.com/paper/2006.04682/) (2020)
- [FrozenQubits: Boosting Fidelity of QAOA by Skipping Hotspot Nodes](https://mlsanity.com/paper/2210.17037/) (2022)
- [Algorithm engineering for a quantum annealing platform](https://mlsanity.com/paper/1410.2628/) (2014)
- [Super-blockers and the effect of network structure on information cascades](https://mlsanity.com/paper/1802.05039/) (2018)
- [EQUAL: Improving the Fidelity of Quantum Annealers by Injecting Controlled Perturbations](https://mlsanity.com/paper/2108.10964/) (2021)
- [Quantum computing cryptography: Finding cryptographic Boolean functions with quantum annealing by a 2000 qubit D-wave quantum computer](https://mlsanity.com/paper/1806.08706/) (2018)
- [Optimizing embedding-related quantum annealing parameters for reducing hardware bias](https://mlsanity.com/paper/2011.00719/) (2020)

## Abstract (arXiv)

Quantum Annealers (QAs) operate as single-instruction machines, lacking a SWAP operation to overcome limited qubit connectivity. Consequently, multiple physical qubits are chained to form a program qubit with higher connectivity, resulting in a drastically diminished effective QA capacity by up to 33x. We observe that in QAs: (a) chain lengths exhibit a power-law distribution, a few dominant chains holding substantially more qubits than others; and (b) about 25% of physical qubits remain unused, getting isolated between these chains. We propose Skipper, a software technique that enhances the capacity and fidelity of QAs by skipping dominant chains and substituting their program qubit with two readout results. Using a 5761-qubit QA, we demonstrate that Skipper can tackle up to 59% (Avg. 28%) larger problems when eleven chains are skipped. Additionally, Skipper can improve QA fidelity by up to 44% (Avg. 33%) when cutting five chains (32 runs). Users can specify up to eleven chain cuts in Skipper, necessitating about 2,000 distinct quantum executable runs. To mitigate this, we introduce Skipper-G, a greedy scheme that skips sub-problems less likely to hold the global optimum, executing a maximum of 23 quantum executables with eleven chain trims. Skipper-G can boost QA fidelity by up to 41% (Avg. 29%) when cutting five chains (11 runs).