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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…
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…
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…
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…