A cross-platform execution engine for the quantum intermediate representation

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

Authors

Institutions

Publication Details

Journal
The Journal of Supercomputing
Published
2025-11-05
DOI
https://doi.org/10.1007/s11227-025-07969-2
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A cross-platform execution engine for the quantum intermediate representation

Anthony M. Cabrera, Elaine Wong, S. R. Johnson, Daniel Claudino et al.
The Journal of Supercomputing
Quantum Computing Algorithms and Architecture
article

A cross-platform execution engine for the quantum intermediate representation

Anthony M. Cabrera, Elaine Wong, S. R. Johnson, Daniel Claudino, Vicente Leyton‐Ortega, Sharmin Afrose, Meenambika Gowrishankar, Travis S. Humble, Austin J. Adams
article en

Abstract

Hybrid languages like the quantum intermediate representation (QIR) are essential for programming systems that mix quantum and conventional computing models, while execution of these programs is often deferred to a system-specific implementation. Here, we develop the QIR Execution Engine (QIR-EE) for parsing, interpreting, and executing QIR across multiple hardware platforms. QIR-EE uses LLVM to execute hybrid instructions specifying quantum programs and, by design, presents extension points that support customized runtime and hardware environments. We demonstrate an implementation that uses the XACC quantum hardware-accelerator library to dispatch prototypical quantum programs on different commercial quantum platforms and numerical simulators, and we validate execution of QIR-EE on IonQ, Quantinuum, and IBM hardware. Our results highlight the efficiency of hybrid executable architectures for handling mixed instructions, managing mixed data, and integrating with quantum computing frameworks to realize cross-platform execution.

The Journal of SupercomputingVol. 81(16)
Oak Ridge National Laboratory (US), Georgia Institute of Technology (US), Knoxville College (US), Quantum Science Center (US), University of Tennessee at Knoxville (US)
U.S. Department of Energy, Office of Science
Openalex Percentile: Top 83%
Quantum Computing Algorithms and Architecture
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A cross-platform execution engine for the quantum intermediate representation — Anthony M. Cabrera, Elaine Wong, et al. · The Journal of Supercomputing (2025) | TGRS Research Map | TGRS