Yu-Ching Shen

activity

20202026

collaborators

4 papers

quant-ph2026

Fine-Grained Complexity for Quantum Problems from Size-Preserving Circuit-to-Hamiltonian Constructions

Nai-Hui Chia, Atsuya Hasegawa, François Le Gall +1

The local Hamiltonian (LH) problem is the canonical $QMA$ -complete problem introduced by Kitaev. In this paper, we show its hardness in a very strong sense: we show that t…

quant-ph2025

Shadow Tomography Against Adversaries

Maryam Aliakbarpour, Vladimir Braverman, Nai-Hui Chia +4

We study single-copy shadow tomography in the adversarial robust setting, where the goal is to learn the expectation values of $M$ observables $O_{1}, \dots, O_{M}$ with $ε$ …

quant-ph2025

3-Local Hamiltonian Problem and Constant Relative Error Quantum Partition Function Approximation: $O (2^{\frac{n}{2}})$ Algorithm Is Nearly Optimal under QSETH

Nai-Hui Chia, Yu-Ching Shen

We investigate the computational complexity of the Local Hamiltonian (LH) problem and the approximation of the Quantum Partition Function (QPF), two central problems in quantum man…

math.PR2020

Large and Moderate Deviation Principles for the SIR Epidemic in a Random Environment

Xiaofeng Xue, Yumeng Shen

In this paper, we are concerned with SIR epidemics in a random environment on complete graphs, where every edges are assigned with i.i.d. weights. Our main results give large and m…

Fine-Grained Complexity for Quantum Problems from Size-Preserving Circuit-to-Hamiltonian Constructions

Shadow Tomography Against Adversaries

3-Local Hamiltonian Problem and Constant Relative Error Quantum Partition Function Approximation: O(22n​) Algorithm Is Nearly Optimal under QSETH

Large and Moderate Deviation Principles for the SIR Epidemic in a Random Environment

3-Local Hamiltonian Problem and Constant Relative Error Quantum Partition Function Approximation: $O (2^{\frac{n}{2}})$ Algorithm Is Nearly Optimal under QSETH