Graph Neural Networks Learn the Noise of Real Quantum Chips to Rescue Failing Computations
Researchers in Zhengzhou have built a graph neural network that encodes the measured noise of superconducting quantum processors to correct ...
Researchers in Zhengzhou have built a graph neural network that encodes the measured noise of superconducting quantum processors to correct ...
A new hybrid quantum-classical operator splitting method solves nonlinear parabolic PDEs up to 100 dimensions with provably faster convergence, promising ...
Researchers in Florence have built generative diffusion models in which quantum coherence and the intrinsic noise of a real IBM ...
A new theoretical study shows that gate teleportation fidelity degrades in state-dependent ways under bit-flip, phase-flip, depolarizing, and amplitude-damping noise, ...
Researchers have built a federated hybrid quantum-classical neural network that classifies Alzheimer's disease from MRI scans with benchmark accuracies above ...
Researchers at Purdue University have developed a bidirectional multi-solution Grover search algorithm that dramatically cuts the iterations and circuit depth ...
Researchers have developed DDQAOA, a quantum optimization algorithm that automatically grows its own circuit depth and matches deep fixed-depth QAOA ...
A comprehensive new review finds that quantum graph neural networks deliver real parameter efficiency and task-specific utility, but definitive quantum ...
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© 2025 Scienmag - Science Magazine