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Yao Yang

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Artificial Intelligence cond-mat.mes-hall cond-mat.mtrl-sci Numerical Analysis physics.optics

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preprint2026arXiv

QAROO: AI-Driven Online Task Offloading for Energy-Efficient and Sustainable MEC Networks

With the rapid advancement of artificial intelligence (AI) and intelligent science, intelligent edge computing has been widely adopted. However, the limitations of traditional methods, such as poor adaptability and the slow convergence of heuristic algorithms, are becoming increasingly evident. To enable sustainable and resource-efficient edge applications, this paper proposes an online task offloading framework for wireless powered mobile edge computing (MEC) networks, called Quantum Attention-based Reinforcement learning for Online Offloading (QAROO). The system employs a binary offloading strategy with the aim of co-optimizing computing and energy resources in dynamic channel environments. In response to the issues of poor adaptability in traditional approaches and the slow convergence of heuristic algorithms, the framework integrates quantum neural networks and attention mechanisms, introducing three key improvements: using recurrent neural networks to enhance temporal modeling capability, proposing an uncertainty-guided quantization method to improve exploration efficiency, and incorporating attention mechanisms into quantum networks to strengthen feature representation. Experiments demonstrate that the proposed method outperforms comparative schemes in terms of normalized computation speed and processing time, offering an efficient and stable solution for online task offloading in large-scale Internet of Things (IoT) dynamic environments.

preprint2022arXiv

Elucidating the Degradation Mechanism of Gd2Zr2O7 Waste Form under Multi-Energy He Ion Irradiation

We studied the microstructural and helium bubbling evolutions of Gd2Zr2O7 waste form with immobilized TRPO (50 wt%) under multi-energy He ion irradiation. Three structurally heterogeneous regions for the Gd2Zr2O7 waste form were found as a function of the depth from the He-irradiated surface. Specifically, at a depth less than 40 nm below the He-irradiated surface (Region I) the Gd2Zr2O7 waste form is completely amorphous with large spherical He bubbles (5-25 nm). In the intermediate region, Region II, (40-800 nm) partially amorphized Gd2Zr2O7 waste form accompanied with ribbon-like He bubbles that may lead to the formation of microcracks is observed. The crystallinity is not impacted in Region III for a depth of more than 800 nm. For the first time, we elucidated that the Gd2Zr2O7 waste form, which was considered to be structurally intact at 100 dpa, is completely amorphized at 6.5 dpa with the synergistic displacement damage, electronic energy loss, and He concentration enabled. This study leads to new physical insights into amorphization and He bubbles formation mechanisms of Gd2Zr2O7 waste form under multi-energy He irradiation, which is essential for the design and optimization of irradiation-resistant ceramic waste matrices.

preprint2016arXiv

Generation and Detection of Surface Plasmon Polaritons by Transition Metal Dichalcogenides for Chip-level Electronic-Photonic Integrated Circuits

The monolithic integration of electronics and photonics has attracted enormous attention due to its potential applications. However, the realization of such hybrid circuits has remained a challenge because it requires optical communication at nanometer scales. A major challenge to this integration is the identification of a suitable material. After discussing the material aspect of the challenge, we identified atomically thin transition metal dichalcogenides (TMDs) as a perfect material platform to implement the circuit. The selection of TMDs is based on their very distinct property: monolayer TMDs are able to emit and absorb light at the same wavelength determined by direct exciton transitions. To prove the concept, we fabricated simple devices consisting of silver nanowires as plasmonic waveguides and monolayer TMDs as active optoelectronic media. Using photoexcitation, direct optical imaging and spectral analysis, we demonstrated generation and detection of surface plasmon polaritons by monolayer TMDs. Regarded as novel materials for electronics and photonics, transition metal dichalcogenides are expected to find new applications in next generation integrated circuits.

preprint2015arXiv

Detecting Potential Instabilities of Numerical Algorithms

It has been the standard teaching of today that backward stability analysis is taught as absolute, just as in Newtonian physics time is taught absolute time. We will prove it is not true in general. It depends on algorithms. We will prove that forward and mixed stability anlaysis are absolutely invalid stability analysis in the sense that they have absolutely wrong reference points for detecting huge element growth of any algoritms(if any), even an "ideal" or "desirable" backward stability analysis is not so "ideal" or "desirable" in general. Any of forward stable, backward stable and mixed stable algorihms as in Demmel, Kahan , Parlett and other's papers and text books, see Demmel(6) and Higham(8)may not be really stable at all because they may fail to detect and expose any potential instabilities of the algorithm in corresponding stability analysis. Therefore, it is impossible to prove an algorithm is stable according to the standard teachin of today, just as it is impossible to prove a mathematical equuation(Maxwell's) is a law of physics according to the standard teaching in Newtonian physics.