4 papers
Generative Learning for Quantum Measurement Design
Jun Dai, Olivier Nahman-Lévesque, Guillaume Rabusseau +2
Extracting quantum information from a quantum state is a fundamental task of quantum computation, often requiring the estimation of many non-commuting observables under a finite me…
An SU(2)-symmetric Semidefinite Programming Hierarchy for Quantum Max Cut
Jun Takahashi, Chaithanya Rayudu, Cunlu Zhou +3
Understanding and approximating extremal energy states of local Hamiltonians is a central problem in quantum physics and complexity theory. Recent work has focused on developing ap…
A Symmetry-Enabled Direct Quantum Protocol for Many-Body Green's Functions
Changhao Yi, Cunlu Zhou
We present a symmetry-enabled direct quantum protocol for computing many-body Green's functions, a central tool for studying strongly correlated quantum systems. Our protocol relie…
Quantum Phase Estimation by Compressed Sensing
Changhao Yi, Cunlu Zhou, Jun Takahashi
As a signal recovery algorithm, compressed sensing is particularly useful when the data has low-complexity and samples are rare, which matches perfectly with the task of quantum ph…