10 citations · 25 across the 7 of their papers we have counts for
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Faster Stochastic First-Order Method for Maximum-Likelihood Quantum State Tomography
Chung-En Tsai, Hao-Chung Cheng, Yen-Huan Li
In maximum-likelihood quantum state tomography, both the sample size and dimension grow exponentially with the number of qubits. It is therefore desirable to develop a stochastic f…
Optimal Second-Order Rates for Quantum Soft Covering and Privacy Amplification
Yu-Chen Shen, Li Gao, Hao-Chung Cheng
We study quantum soft covering and privacy amplification against quantum side information. The former task aims to approximate a quantum state by sampling from a prior distribution…
Error Exponent and Strong Converse for Quantum Soft Covering
Hao-Chung Cheng, Li Gao
How well can we approximate a quantum channel output state using a random codebook with a certain size? In this work, we study the quantum soft covering problem. Namely, we use a r…
Strong Converse for Privacy Amplification against Quantum Side Information
Yu-Chen Shen, Li Gao, Hao-Chung Cheng
We establish a one-shot strong converse bound for privacy amplification against quantum side information using trace distance as a security criterion. This strong converse bound im…
Maximum-Likelihood Quantum State Tomography by Cover's Method with Non-Asymptotic Analysis
Chien-Ming Lin, Hao-Chung Cheng, Yen-Huan Li
We propose an iterative algorithm that computes the maximum-likelihood estimate in quantum state tomography. The optimization error of the algorithm converges to zero at an $O ( (…
Strong Converse for Classical-Quantum Degraded Broadcast Channels
Hao-Chung Cheng, Nilanjana Datta, Cambyse Rouzé
We consider the transmission of classical information through a degraded broadcast channel, whose outputs are two quantum systems, with the state of one being a degraded version of…