Sample-size-reduction of quantum states for the noisy linear problem

K Jeong - Annals of Physics, 2023 - Elsevier
Quantum supremacy poses that a realistic quantum computer can perform a calculation that
classical computers cannot in any reasonable amount of time. It has become a topic of …

Assessing the feasibility of quantum learning algorithms for noisy linear problems

M Kim, P Kim - Scientific Reports, 2024 - nature.com
Quantum algorithms for solving noisy linear problems are reexamined, under the same
assumptions taken from the existing literature. The findings of this work include on the one …

Polynomial T-depth quantum solvability of noisy binary linear problem: from quantum-sample preparation to main computation

W Song, Y Lim, K Jeong, J Lee, JJ Park… - New Journal of …, 2022 - iopscience.iop.org
The noisy binary linear problem (NBLP) is known as a computationally hard problem, and
therefore, it offers primitives for post-quantum cryptography. An efficient quantum NBLP …

A quantum-classical hybrid algorithm with Ising model for the learning with errors problem

M Zheng, J Zeng, W Yang, PJ Chang, B Yan… - arXiv preprint arXiv …, 2024 - arxiv.org
The Learning-With-Errors (LWE) problem is a crucial computational challenge with
significant implications for post-quantum cryptography and computational learning theory …

Divide-and-conquer embedding for QUBO quantum annealing

M Jo, M Hanks, MS Kim - arXiv preprint arXiv:2211.02184, 2022 - arxiv.org
Quantum annealing promises to be an effective heuristic for complex NP-hard problems.
However, clear demonstrations of quantum advantage are wanting, primarily constrained by …