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ARXIV:2605.03932 · QUANTUM COMPUTING · SUBMITTED 06 MAY · 20:27 UTC · FRESHNESS STALE
ARXIV:2605.03932QUANTUM COMPUTINGSUBMITTED 06 MAY · 20:27 UTCFRESHNESS STALEVincenzo Lipardi · Domenica Dibenedetto · Georgios Stamoulis · Mark H. M. Winands · arXiv
A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design.
Opportunity summary
Pain A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design.
Evidence 0 refs | 3 sources | 50% coverage
Blocker Evidence unverified
A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design. In this paper, we propose a magic-informed quantum architecture…
Nonstabilizerness, commonly referred to as magic, is a fundamental resource underpinning quantum advantage. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the…
ScienceToStartup currently rates this 3.0/10 on the public viability pass. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the general framework of…
Quantum Computing moved forward this cycle; last verified May 2026. Public score 3.0/10. Production flags indicate code availability.
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Score3.0Analysis summary
A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design.
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Paper Pack
10.48550/arXiv.2605.03932A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design.
Abstract
Nonstabilizerness, commonly referred to as magic, is a fundamental resource underpinning quantum advantage. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the general framework of circuit design. Inspired by the AlphaGo approach, we tackle the problem with a Monte Carlo Tree Search technique equipped with a Graph Neural Network (GNN) that estimates the magic of candidate quantum circuits. The GNN model induces a magic-based bias that steers the search toward either high- or low-magic regimes, depending on the target objective. We benchmark the proposed magic-informed QAS technique on both the structured ground-state energy problem and on the more general quantum state approximation problem, spanning different sizes and target magic levels. Experimental results show that the proposed technique effectively influences the magic across the search tree and notably also on the resulting final circuit, even in regimes where the GNN operates on out-of-distribution instances. Although introducing a problem-agnostic magic bias could, in principle, constrain the search dynamics, we observe consistent improvements in solution quality across all problems tested.
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Proof status
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Dimensions overall score 3.0
PROBLEM
A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over...
METHOD
Nonstabilizerness, commonly referred to as magic, is a fundamental resource underpinning quantum advantage. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the general framework of circuit...
RESULT
ScienceToStartup currently rates this 3.0/10 on the public viability pass. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the general framework of circuit design. Code availability is fla...
WHY NOW
Quantum Computing moved forward this cycle; last verified May 2026. Public score 3.0/10. Production flags indicate code availability.
Abstract-backed public claims while anchored extraction refreshes.
A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the general framework of circuit design.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Nonstabilizerness, commonly referred to as magic, is a fundamental resource underpinning quantum advantage. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the general framework of circuit design.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
ScienceToStartup currently rates this 3.0/10 on the public viability pass. In this paper, we propose a magic-informed quantum architecture search (QAS) technique that enables control over a quantum resource within the general framework of circuit design. Code availability is flagged in the production record; the public repository link still needs proof alignment.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
Quantum Computing moved forward this cycle; last verified May 2026. Public score 3.0/10. Production flags indicate code availability.
Abstract-backed fallback claim; anchored extraction has not materialized a public claim row yet.
partial
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A novel quantum architecture search technique uses Monte Carlo Tree Search and a Graph Neural Network to control quantum resource 'magic' for improved circuit design.
Segment
Quantum Computing
Adoption evidence
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Commercial read
3.0/10 public viability
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Build Passport
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reason
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proof status
unverified
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next verification path
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stale
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Build readiness
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passport absent
stale
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Artifact maturity
GitHub and Hugging Face maturity payloads
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stale
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Technical feasibility
partial
Current read
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Gaps
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Run minimal reproduction from the Build Passport prototype path.
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Buyer clarity
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missing
Current read
No public implementation surface observed.
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Write integration checklist from prototype path and target workflow.
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People
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ARTIFACTS
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DEFENSIBILITY
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