31 citations · 49 across the 7 of their papers we have counts for
8 papers
Exponential separation in sensing continuous signals via squeezing
Francesco Anna Mele, Nadine Meister, Haimeng Zhao +2
Quantum sensing traditionally focuses on using quantum resources such as squeezing and entanglement to improve precision for sensing fixed signals. However, in many applications su…
Learning the closest Slater determinant
Nisarga Paul, Haimeng Zhao, David D. Dai
Learning compact, interpretable descriptions of quantum many-body states is an important task in quantum science. We study the task of learning the Slater determinant with maximum…
Exponential quantum advantage in processing massive classical data
Haimeng Zhao, Alexander Zlokapa, Hartmut Neven +4
Broadly applicable quantum advantage, particularly in classical data processing and machine learning, has been a fundamental open problem. In this work, we prove that a small quant…
Random Stinespring superchannel: converting channel queries into dilation isometry queries
Filippo Girardi, Francesco Anna Mele, Haimeng Zhao +2
The recently introduced random purification channel, which converts copies of an arbitrary mixed quantum state into copies of the same uniformly random purification, has em…
Statistical Gravity and entropy of spacetime
Riccardo Fantoni
We discuss the foundations of the statistical gravity theory we proposed in a recent publication [Riccardo Fantoni, Quantum Reports, 6, 706 (2024)].
Entanglement-induced provable and robust quantum learning advantages
Haimeng Zhao, Dong-Ling Deng
Quantum computing holds unparalleled potentials to enhance machine learning. However, a demonstration of quantum learning advantage has not been achieved so far. We make a step for…
Learning quantum states and unitaries of bounded gate complexity
Haimeng Zhao, Laura Lewis, Ishaan Kannan +3
While quantum state tomography is notoriously hard, most states hold little interest to practically-minded tomographers. Given that states and unitaries appearing in Nature are of…
MAGIC: Microlensing Analysis Guided by Intelligent Computation
Haimeng Zhao, Wei Zhu
The modeling of binary microlensing light curves via the standard sampling-based method can be challenging, because of the time-consuming light-curve computation and the pathologic…