5 papers
Improved sample complexity bound for sample-based Lindbladian simulation
Siheon Park, Youngjin Seo, Byeongseon Go +3
We establish improved sample-complexity bounds for sample-based Lindbladian simulation based on the Wave Matrix Lindbladization (WML) algorithm. For a jump operator with dimens…
Code-agnostic bosonic noise suppression with hybrid rotations
Saurabh U. Shringarpure, Siheon Park, Sungjoo Cho +4
Physical-level noise on traveling bosonic modes remains a critical bottleneck for scalable quantum information processing. We show that for any single-mode bosonic code (qumode) co…
Ballistic bosonic noise suppression with hybrid qumode-qubit rotation gates
Saurabh U. Shringarpure, Siheon Park, Sungjoo Cho +4
Noise suppression is of paramount importance for reliable quantum information processing and computation. We show that for any single-mode bosonic code (qumode) corrupted by therma…
Sample-based Hamiltonian and Lindbladian simulation: Non-asymptotic analysis of sample complexity
Byeongseon Go, Hyukjoon Kwon, Siheon Park +2
Density matrix exponentiation (DME) is a quantum algorithm that processes multiple copies of a program state to realize the Hamiltonian evolution . Wave matrix Lin…
Variational Quantum Approximated Spectral Clustering
Hyeong-Gyu Kim, Siheon Park, June-Koo Kevin Rhee
Clustering is a fundamental task for analyzing unlabeled data based solely on its underlying distribution. Spectral clustering is a clustering method that represents a dataset as a…