1 citations · 1 across the 7 of their papers we have counts for
8 papers
Rapid mixing of quantum spin chains at any finite temperature
Leeseok Kim
We prove that a quasi-local quantum Gibbs sampler rapidly mixes to the Gibbs state of any 1D finite-range Hamiltonian at all finite temperatures in $\mathcal{O}\left(\log (n/\varep…
Randomized product formulas beyond optimal deterministic scaling
Leeseok Kim, Luis Pedro García-Pintos
Product formulas, also known as Trotter formulas, are among the most widely used and practical methods for simulating quantum systems on quantum computers. Here we introduce two ne…
Randomized Quantum Optimal Control
Leeseok Kim, Francisco Riberi, Kevin Baca +1
Quantum optimal control (QOC) aims to find control functions that optimally steer a quantum system toward a target operation. We introduce a \emph{randomized} QOC framework where o…
Robust high-order quantum simulation using finite-width pulses
Leeseok Kim, Milad Marvian
We present a general framework for promoting first-order pulse sequences in quantum simulation to higher-order sequences that maintain robustness in the presence of finite pulse-wi…
High-order dynamical decoupling in the weak-coupling regime
Leeseok Kim, Milad Marvian
We introduce a high-order dynamical decoupling (DD) scheme for arbitrary bounded system-bath interactions in the weak-coupling regime. Given any decoupling group that…
Higher-order Zeno sequences
Kasra Rajabzadeh Dizaji, Leeseok Kim, Milad Marvian +1
The quantum Zeno effect typically refers to freezing the dynamics of a quantum system through frequent observations. In general, quantum Zeno dynamics is obtained with an error of…
Faster Randomized Dynamical Decoupling
Changhao Yi, Leeseok Kim, Milad Marvian
We present a randomized dynamical decoupling (DD) protocol that can improve the performance of any given deterministic DD, by using no more than two additional pulses. Our construc…
Hamiltonian Quantum Generative Adversarial Networks
Leeseok Kim, Seth Lloyd, Milad Marvian
We propose Hamiltonian Quantum Generative Adversarial Networks (HQuGANs), to learn to generate unknown input quantum states using two competing quantum optimal controls. The game-t…