Search Results for author:
Found 4 papers, 3 papers with code
Quantum diffusion map for nonlinear dimensionality reduction
Inspired by random walk on graphs, diffusion map (DM) is a class of unsupervised machine learning that offers automatic identification of low-dimensional data structure hidden in a high-dimensional dataset.
Robustness of Quantum-Enhanced Adaptive Phase Estimation
As all physical adaptive quantum-enhanced metrology schemes operate under noisy conditions with only partially understood noise characteristics, so a practical control policy must be robust even for unknown noise.
Single-shot Adaptive Measurement for Quantum-enhanced Metrology
We construct a formal framework for AQEM by modeling the procedure as a decision-making process, and we derive the imprecision and the Cram\'{e}r-Rao lower bound with explicit dependence on the feedback policy.
Learning in Quantum Control: High-Dimensional Global Optimization for Noisy Quantum Dynamics
Quantum control is valuable for various quantum technologies such as high-fidelity gates for universal quantum computing, adaptive quantum-enhanced metrology, and ultra-cold atom manipulation.
