12 citations · 18 across the 8 of their papers we have counts for
8 papers
Catalytic Stabilization of Ergotropy and Backflow Suppression in Open Many-Body Quantum Batteries
Liang Luo, Shun-Cai Zhao
Coherent energy backflow and non-Markovian oscillations limit energy retention and degrade extractable work (ergotropy) in open many-body quantum batteries. Here, we present a cata…
Coherent catalyst induced stabilization of ergotropy in open quantum batteries
Ni-Ya Zhuang, Shun-Cai Zhao
Environmental dissipation and thermal fluctuations fundamentally constrain the extractable work and long-time stability of open quantum batteries. To mitigate dissipation-induced e…
Lamb-shift-mediated energy transfer in open quantum batteries
Liang Luo, Shun-Cai Zhao
Open quantum batteries (QBs) operate under unavoidable system--environment interactions, where both dissipation and coherent frequency renormalization can affect their dynamics. Wh…
Non-Markovian N-spin chain quantum battery in thermal charging process
Shun-Cai Zhao, Zi-Ran Zhao, Ni-Ya Zhuang
Ergotropy serves as a key indicator for assessing the performance of quantum batteries(QBs). Using the Redfield master equation, we investigate ergotropy dynamics in a non-Markovia…
Multi-timescale time encoding for CNN prediction of Fenna-Matthews-Olson energy-transfer dynamics
Shun-Cai Zhao, Yi-Meng Huang, Yi-Fan Yang +1
Machine learning simulations of open quantum dynamics often rely on recursive predictors that accumulate error. We develop a non-recursive convolutional neural networks (CNNs) that…
Rapid and Stable Collective Charging and Discharge Suppression in Strongly Coupled Many-Body Quantum Batteries
Shun-Cai Zhao, Yi-Fan Yang, Ni-Ya Zhuang
Achieving rapid and stable energy storage in quantum batteries (QBs) remains a key challenge, particularly under strong system-environment coupling where non-Markovian effects beco…
Quantum dynamics evolution predicted by the long short-term memory network in the photosystem II reaction center
Zi-Ran Zhao, Shun-Cai Zhao, Yi-Meng Huang
Predicting future physical behavior from limited theoretical simulation data is an emerging research paradigm driven by the integration of artificial intelligence and quantum physi…
Predicting quantum evolutions of excitation energy transfer in a light-harvesting complex using multi-optimized recurrent neural networks
Shun-Cai Zhao, Yi-Meng Huang, Zi-Ran Zhao
Constructing models to discover physics underlying magnanimous data is a traditional strategy in data mining which has been proved to be powerful and successful. In this work, a mu…