Using post-selection to map physical noise to a weaker accepted logical channel and then applying order-K perturbative PEC reduces sampling overhead by 3-4 orders of magnitude for logical GHZ preparation on up to 200 qubits with the Iceberg code.
How to Factor 2048 Bit RSA Integers in 8 Hours Using 20 Million Noisy Qubits
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Pinnacle Architecture using QLDPC codes reduces physical qubits needed to factor RSA-2048 to under 100,000 at 10^{-3} error rate.
A closed-form resource estimation tool for concatenated quantum error correction reveals that magic-state operations rarely dominate qubit costs, with general optimizations providing orders-of-magnitude larger reductions than magic-specific ones.
Equivariant sp-QCNN encodes general symmetries with group theory, splits circuits at pooling layers to preserve symmetry while enabling parallel measurements, and shows improved efficiency and trainability over standard equivariant QCNNs in noisy quantum data classification.
The paper assesses quantum computing threats to cybersecurity across infrastructure layers and proposes a nine-component blueprint for quantum-resistant defenses.
citing papers explorer
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Zeno-Enhanced Probabilistic Error Cancellation with Quantum Error Detection Codes
Using post-selection to map physical noise to a weaker accepted logical channel and then applying order-K perturbative PEC reduces sampling overhead by 3-4 orders of magnitude for logical GHZ preparation on up to 200 qubits with the Iceberg code.
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The Pinnacle Architecture: Reducing the cost of breaking RSA-2048 to 100 000 physical qubits using quantum LDPC codes
Pinnacle Architecture using QLDPC codes reduces physical qubits needed to factor RSA-2048 to under 100,000 at 10^{-3} error rate.
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Magic states are rarely the best resource to optimize: An analytical tool for qubit resource estimation in concatenated codes
A closed-form resource estimation tool for concatenated quantum error correction reveals that magic-state operations rarely dominate qubit costs, with general optimizations providing orders-of-magnitude larger reductions than magic-specific ones.
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Resource-efficient equivariant quantum convolutional neural networks
Equivariant sp-QCNN encodes general symmetries with group theory, splits circuits at pooling layers to preserve symmetry while enabling parallel measurements, and shows improved efficiency and trainability over standard equivariant QCNNs in noisy quantum data classification.
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Cybersecurity in the Quantum Era: Assessing the Impact of Quantum Computing on Infrastructure
The paper assesses quantum computing threats to cybersecurity across infrastructure layers and proposes a nine-component blueprint for quantum-resistant defenses.