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20222026
most citedSimulating Non-Markovian Open Quantum Dynamics with Neural Quantum States

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

quant-ph2026

Error Propagation Theory for Variational Non-Markovian Open Quantum Dynamics

Long Cao, Daochi Zhang, Yao Wang +4

Variational approaches based on neural quantum states and physics-informed neural networks provide powerful paradigms for simulating non-Markovian open quantum dynamics. However, e…

quant-ph2026

Simulating non-Markovian open quantum dynamics by exploiting physics-informed neural network

Long Cao, Liwei Ge, Daochi Zhang +4

This work integrates the physics-informed neural network (PINN) approach into the neural quantum state framework to simulate open quantum system dynamics, to circumvent the computa…

quant-ph2026

Characterization-free classification and identification of the environment between two quantum players

Masahito Hayashi, Longyang Cao, Baichu Yu +1

Identifying the causal structure of quantum channels is essential for verifying quantum networks and certifying quantum resources. We introduce a characterization-free protocol ena…

quant-ph2024★ 1 cited

Simulating Non-Markovian Open Quantum Dynamics with Neural Quantum States

Long Cao, Liwei Ge, Daochi Zhang +5

Reducing computational scaling for simulating non-Markovian dissipative dynamics using artificial neural networks is both a major focus and formidable challenge in open quantum sys…

cond-mat.mes-hall2022

Kondo cooling in quantum impurity systems

Xiangzhong Zeng, Lyuzhou Ye, Long Cao +3

The Peltier effect is the reverse phenomenon of the Seebeck effect, and has been observed experimentally in nanoscale junctions. However, despite its promising applications in loca…