Showing 1–20 of 24 results
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Feb 21, 2025Machine learning meets $\mathfrak{su}(n)$ Lie algebra: Enhancing quantum dynamics learning with exact trace conservationApr 22, 2024Physics-Informed Neural Networks and Beyond: Enforcing Physical Constraints in Quantum Dissipative DynamicsApr 3, 2025From short-sighted to far-sighted: A comparative study of recursive machine learning approaches for open quantum systemsJan 7, 2026Toward Quantum-Aware Machine Learning: Improved Prediction of Quantum Dissipative Dynamics via Complex Valued Neural NetworksJan 28, 2023QD3SET-1: A Database with Quantum Dissipative Dynamics Data SetsDec 15, 2025Quantum-inspired Chemical Rule for Discovering Topological MaterialsMar 1, 2023MLQD: A package for machine learning-based quantum dissipative dynamicsAug 22, 2024Molecular Quantum Chemical Data Sets and Databases for Machine Learning PotentialsApr 7, 2026A Physics-Informed Chemical Rule for Topological Materials DiscoveryApr 27, 2022One-shot trajectory learning of open quantum systems dynamicsNov 6, 2025TXL Fusion: A Hybrid Machine Learning Framework Integrating Chemical Heuristics and Large Language Models for Topological Materials DiscoveryAug 22, 2023Four-Dimensional-Spacetime Atomistic Artificial Intelligence ModelsJul 23, 2021Probing multipartite entanglement, coherence and quantum information preservation under classical Ornstein-Uhlenbeck noiseAug 29, 2024Digital stabilization of an IQ modulator in the carrier suppressed single side-band (CS-SSB) mode for atom interferometryDec 11, 2019Stochastic Equation of Motion Approach to Fermionic Dissipative Dynamics. II. Numerical ImplementationJul 23, 2021Effects of classical fluctuating environments on decoherence and bipartite quantum correlations dynamicsJul 23, 2021Probing tripartite entanglement and coherence dynamics in pure and mixed independent classical environmentsJan 15, 2024AI-enhanced on-the-fly simulation of nonlinear time-resolved spectraDec 11, 2019Stochastic Equation of Motion Approach to Fermionic Dissipative Dynamics. I. FormalismJul 6, 2022A comparative study of different machine learning methods for dissipative quantum dynamics