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From the 1 of 6 linked papers with an AI index.

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6 papers

quant-ph2026

The log log jam in Gaussian state tomography

Sitan Chen, Weiyuan Gong, Qi Ye +1

The paper proves that any tomography protocol using Gaussian measurements on continuous‑variable systems inevitably incurs a sample complexity that scales as log log E with the sys…

cs.AR2026

Embedded Arena: Iterative Optimization via Hardware Feedback

Zhihan Zhang, Alexander Le Metzger, Jiuyang Lyu +10

Embedded devices from wildlife monitoring stations to clinical wearables require local AI inference due to latency, communication, or privacy constraints. Optimizing models for het…

quant-ph2024

Adaptivity can help exponentially for shadow tomography

Sitan Chen, Weiyuan Gong, Zhihan Zhang

In recent years there has been significant interest in understanding the statistical complexity of learning from quantum data under the constraint that one can only make unentangle…

quant-ph2024

Stabilizer bootstrapping: A recipe for efficient agnostic tomography and magic estimation

Sitan Chen, Weiyuan Gong, Qi Ye +1

We study the task of agnostic tomography: given copies of an unknown -qubit state which has fidelity with some state in a given class , find a state which has fidel…

quant-ph2024

On the sample complexity of purity and inner product estimation

Weiyuan Gong, Jonas Haferkamp, Qi Ye +1

We study the sample complexity of the prototypical tasks quantum purity estimation and quantum inner product estimation. In purity estimation, we are to estimate of an u…

quant-ph2024

Quantum-Classical Separations in Shallow-Circuit-Based Learning with and without Noises

Zhihan Zhang, Weiyuan Gong, Weikang Li +1

We study quantum-classical separations between classical and quantum supervised learning models based on constant depth (i.e., shallow) circuits, in scenarios with and without nois…