Contextuality as an External Bookkeeping Cost under Fixed Shared-State Semantics
📰 ArXiv cs.AI
Contextuality in quantum probability theories incurs an external bookkeeping cost for classical simulations under fixed shared-state semantics
Action Steps
- Define contextuality and its role in quantum probability theories
- Analyze the external bookkeeping cost for classical simulations under fixed shared-state semantics
- Evaluate the minimal external-label size required for a classical simulation to maintain a fixed internal description across contexts
- Apply the findings to optimize quantum simulation and information processing protocols
Who Needs to Know This
This research benefits AI researchers and quantum computing engineers who need to understand the fundamental differences between quantum and classical probability theories and their implications on simulation and information processing
Key Insight
💡 Classical simulations of quantum systems require additional contextual information, resulting in an external bookkeeping cost
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🤖 Contextuality incurs a bookkeeping cost in classical simulations of quantum systems #quantumcomputing #AI
Key Takeaways
Contextuality in quantum probability theories incurs an external bookkeeping cost for classical simulations under fixed shared-state semantics
Full Article
Title: Contextuality as an External Bookkeeping Cost under Fixed Shared-State Semantics
Abstract:
arXiv:2601.20167v2 Announce Type: cross Abstract: Contextuality is a central feature distinguishing quantum from classical probability theories, but its operational meaning is often stated only qualitatively. In this Letter, we study a simple information-theoretic question: how much additional contextual information must a classical simulation introduce when it tries to keep a shared internal description fixed across contexts? To make this question precise, we analyze a minimal external-label si
Abstract:
arXiv:2601.20167v2 Announce Type: cross Abstract: Contextuality is a central feature distinguishing quantum from classical probability theories, but its operational meaning is often stated only qualitatively. In this Letter, we study a simple information-theoretic question: how much additional contextual information must a classical simulation introduce when it tries to keep a shared internal description fixed across contexts? To make this question precise, we analyze a minimal external-label si
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