arXiv subjects

Shen-Liang Yang

Publications and source records attributed to Shen-Liang Yang.

3 recordsLinked to original sources

arXiv2026

Noise-enhanced quantum kernels on analog quantum computers

The quantum kernel method, a promising quantum machine learning algorithm, possesses substantial potential for demonstrating quantum advantage. Although the majority of the quantum kernel is constructed in the context of gate-based quantum circuits, inspired by the idea of analog quantum computing, here we construct an analog quantum kernel and a hybrid quantum kernel, and show their competitiveness against other kernel methods in a benchmarking task and the practical problem of estimating non-Markovianity from sparse data. Additionally, we also incorporate operational noise into the quantum kernels. Our results reveal that the presence of operational noise can be beneficial to the performance of the developed quantum kernels. We attribute this counterintuitive noise-enhanced performance to the improved expressivity and higher model complexity induced by noise. These results pave the way for practical implementations of quantum kernel methods and provide an efficient approach for estimating non-Markovianity with reduced experimental demands.

quant-ph↗

arXiv2025

HierarchicalEOM.jl: An efficient Julia framework for hierarchical equations of motion in open quantum systems

The hierarchical equations of motion (HEOM) approach can describe the reduced dynamics of a system simultaneously coupled to multiple bosonic and fermionic environments. The complexity of exactly describing the system-environment interaction with the HEOM method usually results in time-consuming calculations and a large memory cost. Here, we introduce an open-source software package called HierarchicalEOM$.$jl: a Julia framework integrating the HEOM approach. HierarchicalEOM$.$jl features a collection of methods to compute bosonic and fermionic spectra, stationary states, and the full dynamics in the extended space of all auxiliary density operators (ADOs). The required handling of the ADOs multi-indexes is achieved through a user-friendly interface. We exemplify the functionalities of the package by analyzing a single impurity Anderson model, and an ultra-strongly coupled charge-cavity system interacting with bosonic and fermionic reservoirs. HierarchicalEOM$.$jl achieves a significant speedup with respect to the corresponding method in the Quantum Toolbox in Python (QuTiP), upon which this package is founded.

quant-ph↗

arXiv2024

Non-Markovian skin effect

The Liouvillian skin effect and the non-Hermitian skin effect have both been used to explain the localization of eigenmodes near system boundaries, though the former is arguably more accurate in some regimes due to its incorporation of quantum jumps. However, these frameworks predominantly focus on weak Markovian interactions, neglecting the potentially crucial role of memory effects. To address this, we investigate, utilizing the powerful hierarchical equations of motion method, how a non-Markovian environment can modify the Liouvillian skin effect. We demonstrate that a non-Markovian environment can induce a ``thick skin effect", where the skin mode broadens and shifts into the bulk. {We further identify that the skin-mode quantum coherence can only be generated when the coupling contains counter-rotating terms}, leading to the coherence-delocalization and oscillatory relaxation with a characteristic linear scaling with system size. Remarkably, both the skin-mode and steady-state coherence exhibit resistance to decoherence from additional environmental noise. These findings highlight the profound impact of system-bath correlations on relaxation and localization, revealing unique phenomena beyond conventional Markovian approximations.

quant-ph↗