activity
20192026
most citedManipulating phonons of a trapped-ion system using optical tweezers

25 citations · 40 across the 6 of their papers we have counts for

collaborators

7 papers

quant-ph2026

Taming multiparty entanglement at measurement-induced phase transitions

Liuke Lyu, James Allen, Yi Hong Teoh +2

Measurement-induced phase transitions (MIPT) give rise to novel dynamical states of quantum matter realized by balancing unitary evolution and measurements. We present large-scale…

quant-ph2025★ 1 cited

Neural network enhanced cross entropy benchmark for monitored circuits

Yangrui Hu, Yi Hong Teoh, William Witczak-Krempa +1

We explore the interplay of quantum computing and machine learning to advance experimental protocols for observing measurement-induced phase transitions (MIPT) in quantum devices.…

cs.LG2024★ 1 cited

Autoregressive model path dependence near Ising criticality

Yi Hong Teoh, Roger G. Melko

Autoregressive models are a class of generative model that probabilistically predict the next output of a sequence based on previous inputs. The autoregressive sequence is by defin…

quant-ph2023

Investigations of 2D ion crystals in a hybrid optical cavity trap for quantum information processing

Zewen Sun, Yi Hong Teoh, Fereshteh Rajabi +1

We numerically investigate a hybrid trapping architecture for 2D ion crystals using static electrode voltages and optical cavity fields for in-plane and out-of-plane confinements,…

quant-ph2022★ 13 cited

Ion Trap Long-Range XY Model for Quantum State Transfer and Optimal Spatial Search

Dylan Lewis, Leonardo Banchi, Yi Hong Teoh +2

Linear ion trap chains are a promising platform for quantum computation and simulation. The XY model with long-range interactions can be implemented with a single side-band Molmer-…

quant-ph2021★ 25 cited

Manipulating phonons of a trapped-ion system using optical tweezers

Yi Hong Teoh, Manas Sajjan, Zewen Sun +2

We propose an experimental architecture where an array of optical tweezers affords site-dependent control over the confining potential of a conventional radio-frequency ion trap. T…

quant-ph2019

Machine learning design of a trapped-ion quantum spin simulator

Yi Hong Teoh, Marina Drygala, Roger G. Melko +1

Trapped ions have emerged as one of the highest quality platforms for the quantum simulation of interacting spin models of interest to various fields of physics. In such simulators…