Zobrazeno 1 - 10
of 4 162
pro vyhledávání: '"ZHOU, TIAN"'
Autor:
Li, Yuchen, Zhou, Tian-Gang, Wu, Ze, Peng, Pai, Zhang, Shengyu, Fu, Riqiang, Zhang, Ren, Zheng, Wei, Zhang, Pengfei, Zhai, Hui, Peng, Xinhua, Du, Jiangfeng
Universality often emerges in low-energy equilibrium physics of quantum many-body systems, despite their microscopic complexity and variety. Recently, there has been a growing interest in studying far-from-equilibrium dynamics of quantum many-body sy
Externí odkaz:
http://arxiv.org/abs/2406.07625
Motivated by the abundance of functional data such as time series and images, there has been a growing interest in integrating such data into neural networks and learning maps from function spaces to R (i.e., functionals). In this paper, we study the
Externí odkaz:
http://arxiv.org/abs/2403.12187
Time series analysis is vital for numerous applications, and transformers have become increasingly prominent in this domain. Leading methods customize the transformer architecture from NLP and CV, utilizing a patching technique to convert continuous
Externí odkaz:
http://arxiv.org/abs/2402.05830
Accurate solar power forecasting is crucial to integrate photovoltaic plants into the electric grid, schedule and secure the power grid safety. This problem becomes more demanding for those newly installed solar plants which lack sufficient data. Cur
Externí odkaz:
http://arxiv.org/abs/2402.05823
Time series forecasting is essential for many practical applications, with the adoption of transformer-based models on the rise due to their impressive performance in NLP and CV. Transformers' key feature, the attention mechanism, dynamically fusing
Externí odkaz:
http://arxiv.org/abs/2402.05370
The concept of information scrambling elucidates the dispersion of local information in quantum many-body systems, offering insights into various physical phenomena such as wormhole teleportation. This phenomenon has spurred extensive theoretical and
Externí odkaz:
http://arxiv.org/abs/2401.09524
Measuring physical observables requires averaging experimental outcomes over numerous identical measurements. The complete distribution function of possible outcomes or its Fourier transform, known as the full counting statistics, provides a more det
Externí odkaz:
http://arxiv.org/abs/2312.11191
Spatio-temporal forecasting, pivotal in numerous fields, hinges on the delicate equilibrium between isolating nuanced patterns and sifting out noise. To tackle this, we introduce Sparse Regression-based Vector Quantization (SVQ), a novel technique th
Externí odkaz:
http://arxiv.org/abs/2312.03406
Autor:
Zhou, Tian
Soybean is an important source of protein in animal feed, and growing demand for meat consumption worldwide has led to increased soybean production. Over 120 million metric tons of soybean were harvested in the United States in 2018, approximately on
Externí odkaz:
http://hdl.handle.net/10919/102925
Autor:
Zhou, Tian-Gang, Zhang, Pengfei
Classical shadow tomography serves as a potent tool for extracting numerous properties from quantum many-body systems with minimal measurements. Nevertheless, prevailing methods yielding optimal performance for few-body operators necessitate the appl
Externí odkaz:
http://arxiv.org/abs/2309.01258