A proof-of-concept that maps circle packing for chromatography to a maximum independent set problem and runs QAOA on 18 qubits, with resource estimates for harder sphere packing variants.
Superstaq: Deep Optimization of Quantum Programs
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abstract
We describe Superstaq, a quantum software platform that optimizes the execution of quantum programs by tailoring to underlying hardware primitives. For benchmarks such as the Bernstein-Vazirani algorithm and the Qubit Coupled Cluster chemistry method, we find that deep optimization can improve program execution performance by at least 10x compared to prevailing state-of-the-art compilers. To highlight the versatility of our approach, we present results from several hardware platforms: superconducting qubits (AQT @ LBNL, IBM Quantum, Rigetti), trapped ions (QSCOUT), and neutral atoms (Infleqtion). Across all platforms, we demonstrate new levels of performance and new capabilities that are enabled by deeper integration between quantum programs and the device physics of hardware.
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quant-ph 1years
2024 1verdicts
CONDITIONAL 1representative citing papers
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Sphere Packing on a Quantum Computer for Chromatography Modeling
A proof-of-concept that maps circle packing for chromatography to a maximum independent set problem and runs QAOA on 18 qubits, with resource estimates for harder sphere packing variants.