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20222026
most citedLearning quantum states and unitaries of bounded gate complexity

31 citations · 49 across the 7 of their papers we have counts for

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6 papers · 1 filter

quant-ph2026

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…

quant-ph2026

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…

quant-ph2026

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…

quant-ph2025

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…

quant-ph2024★ 11 cited

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…

quant-ph2023★ 31 cited

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…