A new LLM-guided search method called structured concept evolution discovers competitive lifted-product qLDPC code families including non-abelian constructions.
Discov- ering highly efficient low-weight quantum error-correcting codes with reinforcement learning
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Resource estimates show Shor's algorithm can break 256-bit ECDLP with fewer than 1450 logical qubits and 90 million Toffoli gates on fast-clock quantum hardware, enabling on-spend attacks on cryptocurrency mempools.
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.
citing papers explorer
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Large-Language-Model Discovery of Quantum LDPC Codes through Structured Concept Evolution
A new LLM-guided search method called structured concept evolution discovers competitive lifted-product qLDPC code families including non-abelian constructions.
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Securing Elliptic Curve Cryptocurrencies against Quantum Vulnerabilities: Resource Estimates and Mitigations
Resource estimates show Shor's algorithm can break 256-bit ECDLP with fewer than 1450 logical qubits and 90 million Toffoli gates on fast-clock quantum hardware, enabling on-spend attacks on cryptocurrency mempools.
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Learning Encodings by Maximizing State Distinguishability: Variational Quantum Error Correction
VarQEC uses a distinguishability loss as a machine-learning objective to variationally discover resource-efficient encoding circuits optimized for given noise models.