37 citations · 77 across the 8 of their papers we have counts for
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Theory of the Edge-of-Chaos Advantage in Quantum Reservoir Computing
Shuaifan Cao, Wei Xia, Xiaopeng Li
Numerical studies suggest that quantum reservoir computing performs optimally near the edge of chaos, a behavior commonly attributed to a balance between memory retention and nonli…
Quantum magic and non-commutativity as computational resources in quantum reservoir computing
Wei Xia, Shuaifan Cao, Xingze Qiu +1
Quantum reservoir computing (QRC) provides a hardware-efficient paradigm for temporal information processing on near-term quantum devices. Despite rapid experimental progress, a ri…
High-Accuracy Temporal Prediction via Experimental Quantum Reservoir Computing in Correlated Spins
Yanjun Hou, Juncheng Hua, Ze Wu +6
Physical reservoir computing provides a powerful machine learning paradigm that exploits nonlinear physical dynamics for efficient information processing. By incorporating quantum…
Quantum complexity phase transition in fermionic quantum circuits
Wei Xia, Yijia Zhou, Xingze Qiu +1
Understanding the complexity of quantum many-body systems has been attracting much attention recently for its fundamental importance in characterizing complex quantum phases beyond…
Complexity enriched dynamical phases for fermions on graphs
Wei Xia, Jie Zou, Xiaopeng Li
Dynamical quantum phase transitions, encompassing phenomena like many-body localization transitions and measurement-induced phase transitions, are often characterized and identifie…
Configured Quantum Reservoir Computing for Multi-Task Machine Learning
Wei Xia, Jie Zou, Xingze Qiu +5
Amidst the rapid advancements in experimental technology, noise-intermediate-scale quantum (NISQ) devices have become increasingly programmable, offering versatile opportunities to…
The Reservoir Learning Power across Quantum Many-Boby Localization Transition
Wei Xia, Jie Zou, Xingze Qiu +1
Harnessing the quantum computation power of the present noisy-intermediate-size-quantum devices has received tremendous interest in the last few years. Here we study the learning p…