Practical Quantum CIM Empowerment via All-Domestic-Core Agentic Large Model
The paper discusses the integration of a Coherent Ising Machine (CIM) with a large language model (LLM) to enhance quantum computing capabilities. This approach aims to simplify the modeling process for non-specialists and improve efficiency for experts. The authors highlight the potential for domestic technologies to empower quantum CIM applications while addressing ongoing challenges in the field.
- ▪Quantum computing devices are powerful tools for solving NP-complete problems but are complex for non-specialists.
- ▪The study integrates a femtosecond laser-pumped CIM with an LLM-driven agentic system using LangGraph and LangChain frameworks.
- ▪The research demonstrates that LLMs can effectively assist in modeling tasks such as QUBO/Ising model calibration and constraint weight iteration.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.23934 |
| Publication time | Tue, 26 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-26T04:07:43.013Z |
| Last seen | 2026-05-26T04:07:43.013Z |
| Headline source | Publisher (no WeSearch rewrite) |
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| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | vRI35SbkfFla |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Artificial Intelligence arXiv:2605.23934 (cs) [Submitted on 24 Apr 2026] Title:Practical Quantum CIM Empowerment via All-Domestic-Core Agentic Large Model Authors:Wang Rui, Lu Diannan View a PDF of the paper titled Practical Quantum CIM Empowerment via All-Domestic-Core Agentic Large Model, by Wang Rui and Lu Diannan View PDF HTML (experimental) Abstract:Quantum computing devices are recognized as powerful tools for solving NP-complete problems. However, the intricacy of their modeling presents notable barriers for non-specialists, while the tedious iteration of constraint weights and modeling methodologies also consumes substantial effort on the part of experts.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.
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