An online Riemannian gradient descent method for MPO-based quantum state tomography achieves linear convergence with quadratically scaling sample complexity and connects the problem to low TT-rank tensor completion.
Quantum supremacy using a programmable superconducting processor
4 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 4verdicts
UNVERDICTED 4representative citing papers
HyFuHAD fuses classical Einstein fuzzy detection from multiple membership functions with quantum fuzzy detection to achieve claimed state-of-the-art performance in unsupervised hyperspectral anomaly detection.
O3LS reduces space overhead by up to 46.7% and time overhead by up to 36% in lattice surgery while suppressing logical error rates by up to an order of magnitude compared with prior layout and scheduling approaches.
The paper presents a systematic Q-EDA architecture and data flow from GDSII to wafer manufacturing for superconducting quantum chips, including nine quantum-specific DRC rules and tool benchmarks.
citing papers explorer
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Online Riemannian Gradient Descent for Quantum State Tomography with Matrix Product Operators
An online Riemannian gradient descent method for MPO-based quantum state tomography achieves linear convergence with quadratically scaling sample complexity and connects the problem to low TT-rank tensor completion.
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O3LS: Optimizing Lattice Surgery via Automatic Layout Searching and Loose Scheduling
O3LS reduces space overhead by up to 46.7% and time overhead by up to 36% in lattice surgery while suppressing logical error rates by up to an order of magnitude compared with prior layout and scheduling approaches.
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From GDSII to Wafer: EDA Design Flow and Data Conversion for Wafer-Scale Manufacturing of Superconducting Quantum Chips
The paper presents a systematic Q-EDA architecture and data flow from GDSII to wafer manufacturing for superconducting quantum chips, including nine quantum-specific DRC rules and tool benchmarks.