PIQC proposes a distributed FTQC architecture based on molecular quantum nodes with photonic integration, nuclear registers, loss-tolerant entanglement, and Floquetified qLDPC codes.
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Pith papers citing it
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quant-ph 3years
2026 3verdicts
UNVERDICTED 3representative citing papers
Entanglement improves classification accuracy in distributed quantum ML tasks across datasets, but excessive amounts degrade performance by reducing effective parameter dimension.
Experimental demonstration of non-Markovian death, revival, and asymmetric structures in tripartite quantum steering.
citing papers explorer
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PIQC: Scalable Distributed Quantum Computing via Photonic Integration of Designed Molecular Quantum Nodes
PIQC proposes a distributed FTQC architecture based on molecular quantum nodes with photonic integration, nuclear registers, loss-tolerant entanglement, and Floquetified qLDPC codes.
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The power of entanglement in distributed quantum machine learning
Entanglement improves classification accuracy in distributed quantum ML tasks across datasets, but excessive amounts degrade performance by reducing effective parameter dimension.
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Observation of Non-Markovian Evolution of Tripartite Quantum Steering
Experimental demonstration of non-Markovian death, revival, and asymmetric structures in tripartite quantum steering.