On Post-Processing the Results of Quantum Optimizers

Borle, Ajinkya; McCarter, Josh

doi:10.48550/arxiv.1905.13107

Cited by 1 publication

(1 citation statement)

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“…These error mitigation strategies often rely on the pre-and post-processing of quantum results. Examples include qubit readout error mitigation [17], zero-limit noise extrapolation [23,40], and domain-specific purification schemes [6]. In addition to the core concepts we distill from variational quantum computing, we further require mechanisms for the integration of custom error mitigation strategies.…”

Section: Qcor Language Extension Scopementioning

confidence: 99%

QCOR: A Language Extension Specification for the Heterogeneous Quantum-Classical Model of Computation

Mintz,

Mccaskey,

Dumitrescu

et al. 2019

Preprint

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Quantum computing is an emerging computational paradigm that leverages the laws of quantum mechanics to perform elementary logic operations. Existing programming models for quantum computing were designed with fault-tolerant hardware in mind, envisioning standalone applications. However, near-term quantum computers are susceptible to noise which limits their standalone utility. To better leverage limited computational strengths of noisy quantum devices, hybrid algorithms have been suggested whereby quantum computers are used in tandem with their classical counterparts in a heterogeneous fashion. This modus operandi calls out for a programming model and a high-level programming language that natively and seamlessly supports heterogeneous quantum-classical hardware architectures in a single-source-code paradigm. Motivated by the lack of such a model, we introduce a language extension specification, called QCOR, that enables single-source quantum-classical programming. Programs written using the QCOR library and directives based language extensions can be compiled to produce functional hybrid binary executables. After defining the QCOR's programming model, memory model, and execution model, we discuss how QCOR enables variational, iterative, and feed forward quantum computing. QCOR approaches quantum-classical computation in a hardwareagnostic heterogeneous fashion and strives to build on best practices of high performance computing (HPC). The high level of abstraction in the developed language is intended to accelerate the adoption of quantum computing by researchers familiar with classical HPC.

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