dqc_simulator is a new Python toolkit for automating realistic simulations of both hardware and software in distributed quantum computing systems.
NetSquid, a NETwork Simulator for QUantum Information using Discrete events
5 Pith papers cite this work. Polarity classification is still indexing.
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Hybrid QFL cuts quantum transmissions from 3TNMP to {3t + 2(T-t)}NMP over T rounds while preserving near-centralized convergence and improving depolarizing-noise resilience via decentralized aggregation and Steane-code QEC.
New building block and protocol for all-photonic quantum repeaters using repeater graph states that reduces emissive memories at end nodes and integrates with memory-based systems.
Connected tree topology supports larger user capacity under decoherence than lattice for entanglement distribution and shows better QKD robustness.
Monte Carlo simulations map fidelity gains up to 0.07 and yield losses up to 0.55 for one round of DEJMPS purification across a grid of amplitude-damping and dephasing noise strengths in entangled photon systems.
citing papers explorer
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dqc_simulator: an easy-to-use distributed quantum computing simulator
dqc_simulator is a new Python toolkit for automating realistic simulations of both hardware and software in distributed quantum computing systems.
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Practical Quantum Federated Learning for Privacy-Sensitive Healthcare: Communication Efficiency and Noise Resilience
Hybrid QFL cuts quantum transmissions from 3TNMP to {3t + 2(T-t)}NMP over T rounds while preserving near-centralized convergence and improving depolarizing-noise resilience via decentralized aggregation and Steane-code QEC.
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Architecture and protocols for all-photonic quantum repeaters
New building block and protocol for all-photonic quantum repeaters using repeater graph states that reduces emissive memories at end nodes and integrates with memory-based systems.
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Scaling Network Topologies for Multi-User Entanglement Distribution
Connected tree topology supports larger user capacity under decoherence than lattice for entanglement distribution and shows better QKD robustness.
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Effectiveness of the DEJMPS purification protocol in noisy entangled photon systems, a Monte Carlo simulation
Monte Carlo simulations map fidelity gains up to 0.07 and yield losses up to 0.55 for one round of DEJMPS purification across a grid of amplitude-damping and dephasing noise strengths in entangled photon systems.