Ziyuan Zhu

Ziyuan Zhu, Keyu Hu, Zhifei Chen et al.

Reconstructing continuous physical fields from sparse measurements is a central inverse problem, but data-driven generative models can produce states that violate governing dynamics. We introduce a physics-informed generative solver that separates stable prior learning from inference-time enforcement of conservation laws. Martingale-Regularized Score Matching regularizes score pretraining with a Score Fokker-Planck constraint, yielding a dynamically stable prior. Physics-Informed Implicit Score Sampling then guides denoising trajectories by gradients of physical residuals, projecting samples toward admissible manifolds without retraining. In acoustics, the method co-generates pressure and particle velocity from sparse sensors, enabling dense virtual arrays that suppress spatial aliasing. The same framework generalizes to real-world ERA5 meteorological fields under extreme sparsity. Together, this work establishes a rigorous and generalizable paradigm for solving high-dimensional inverse problems, bridging the gap between generative artificial intelligence and first-principles science.

Yue Zhang, Ziyuan Zhu, Dan Meng

Different from the traditional software vulnerability, the microarchitecture side channel has three characteristics: extensive influence, potent threat, and tough defense. The main reason for the micro-architecture side channel is resource sharing. There are many reasons for resource sharing, one of which is SMT (Simultaneous Multi-Threading) technology. In this paper, we define the SMT Transient Channel, which uses the transient state of shared resources between threads to steal information. To mitigate it, we designed a security demand-based dynamic mitigation (DDM) to Mitigate the SMT transient channels. The DDM writes the processes' security requirements to the CPU register sets, and the operating system calls the HLT instruction to dynamically turn on and off the hyper-threading according to the register values to avoid the side channels caused by execution resource sharing. During the implementation of the scheme, we modified the Linux kernel and used the MSR register groups of Intel processor. The evaluation results show that DDM can effectively protect against the transient side-channel attacks such as PortsMash that rely on SMT, and the performance loss of DDM is less than 8%.