Quantum
EigenOrbit Study Compares 12 Quantum Computing Backends
Publication: The Quantum Insider
Author: Mohib Ur Rehman
Source published: 03/11/2026, 14:33:10 UTC
Briefing created: 03/11/2026, 14:36:37 UTC
Based on a feed excerpt; full article content has not been acquired. Source evidence retrieved 03/11/2026, 14:34:25 UTC.
Briefings
The EigenOrbit study released in November 2026 introduced eigenkit, an open-source Python library designed to run quantum algorithms across 12 different execution providers including IBM Heron and IQM Emerald. The research evaluated 12 execution providers and found that no single backend performs best across all workloads. Simulator performance varies with circuit size and structure, while hardware performance depends on circuit topology matching physical connectivity. The study highlights a broader challenge for quantum software as the ecosystem grows, requiring provider-neutral approaches to evaluate workloads before deployment.
Key points
- The EigenOrbit study released in November 2026 introduced eigenkit, an open-source Python library designed to run quantum algorithms across 12 different execution providers including IBM Heron and IQM Emerald.
- The research evaluated 12 execution providers and found that no single backend performs best across all workloads, with simulator performance varying significantly based on circuit size and structure.
Context
This research addresses the growing challenge in quantum computing where developers need to evaluate a workload across different simulators and hardware platforms without rebuilding the software workflow for each provider. The study evaluates quantum workloads across 12 execution providers, spanning simulators and quantum hardware, and includes experiments on IBM Heron and IQM Emerald quantum processors.
Limitations
The evidence is limited to the EigenOrbit study published in November 2026. The research paper is preprint status (arxiv.org/abs/2611.02979) and the findings represent experimental evaluations rather than definitive conclusions. The library supports eight simulator backends and four hardware execution routes, but specific performance metrics for each workload are not provided in the evidence.
Generated by Bittrees-hosted qwen35-2b sha256:aaf42c8b7c3c on 03/11/2026, 14:36:37 UTC. Based on publisher-provided feed evidence; may not cover the full original article. Check the source for details.
View archived briefing on IPFS
bafybeiaalxworyxzaqnhmhnrdrkjspd3oqducmisfhiw2l56bcuxyimxzu