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Zinan Wang

Publications and source records attributed to Zinan Wang.

10 recordsLinked to original sources

SENTINEL: A Multi-Level Formal Framework for Safety Evaluation of Foundation Model-based Embodied Agents

We present SENTINEL, a framework for formally evaluating the physical safety of foundation model (FM)-based embodied agents. SENTINEL is the first to provide multi-level safety evaluation across semantic interpretation, plan generation, and physical execution within a unified formal framework. Unlike prior methods that rely on heuristic rules or subjective FM judgments, SENTINEL grounds practical safety requirements in formal temporal logic (TL) semantics that can precisely specify state invariants, temporal dependencies, and timing constraints. It employs a multi-level verification pipeline where (i) at the semantic level, intuitive natural language safety requirements are formalized into TL formulas and the agent's understanding of these requirements is probed for alignment with the TL formulas; (ii) at the plan level, high-level action plans and subgoals generated by the agent are verified against the TL formulas to detect unsafe plans before execution; and (iii) at the trajectory level, multiple execution trajectories are merged into a computation tree and efficiently verified against physically-detailed TL specifications for a final safety check. We apply SENTINEL in VirtualHome and AI2-THOR, and formally evaluate multiple FM-based embodied agents against diverse safety requirements. Our experiments show that by grounding physical safety in temporal logic and applying verification methods across multiple levels, SENTINEL provides a rigorous foundation for systematically evaluating the safety of FM-based embodied agents in simulation-based physical environments, and can effectively expose potential safety violations in interpreting, planning, and executing the tasks.

cs.AI

Bridging Photon Statistics and Phase Transitions in Random Fiber Lasers

Complex systems exhibit rich equilibrium states, yet the universal principles governing these systems remain unrevealed, motivating the search for novel experimental platforms. Random fiber lasers (RFLs), which generate partially-coherent light-wave through feedback from Rayleigh scattering, provide a photonic realization of such systems. Here we report a comprehensive theoretical and experimental investigation of photon statistics for RFLs based on classical second-order temporal correlation function \( g^{(2)}(τ) \), revealing unique statistical properties and introduce a two-dimensional framework for controlling photon statistics. Remarkably, we establish a unified landscape between photon correlation, intensity statistics governed by Levy statistics, and phase transitions with replica symmetry breaking. This multifaceted relationship, observed for the first time, bridges disordered photonics with statistical physics of complex system. Our results offer new pathways for engineering laser emission with controllable photon statistics, and more broadly, this work positions RFLs as a fertile land for exploring emergent behaviors in disordered systems.

physics.optics

Strategic Optimization and Challenges of Large Language Models in Object-Oriented Programming

In the area of code generation research, the emphasis has transitioned from crafting individual functions to developing class-level method code that integrates contextual information. This shift has brought several benchmarks such as ClassEval and CoderEval, which consider class-level contexts. Nevertheless, the influence of specific contextual factors at the method level remains less explored. This research focused on method-level code generation within the Object-Oriented Programming (OOP) framework. Based on CoderEval, we devised experiments that varied the extent of contextual information in the prompts, ranging from method-specific to project-wide details. We introduced the innovative metric of "Prompt-Token Cost-Effectiveness" to evaluate the economic viability of incorporating additional contextual layers. Our findings indicate that prompts enriched with method invocation details yield the highest cost-effectiveness. Additionally, our study revealed disparities among Large Language Models (LLMs) regarding error type distributions and the level of assistance they provide to developers. Notably, larger LLMs do not invariably perform better. We also observed that tasks with higher degrees of coupling present more substantial challenges, suggesting that the choice of LLM should be tailored to the task's coupling degree. For example, GPT-4 exhibited improved performance in low-coupling scenarios, whereas GPT-3.5 seemed better suited for tasks with high coupling. By meticulously curating prompt content and selecting the appropriate LLM, developers can optimize code quality while maximizing cost-efficiency during the development process.

cs.SE

Mid-infrared computational temporal ghost imaging

Ghost imaging in the time domain allows for reconstructing fast temporal objects using a slow photodetector. The technique involves correlating random or pre-programmed probing temporal intensity patterns with the integrated signal measured after modulation by the temporal object. However, the implementation of temporal ghost imaging necessitates ultrafast detectors or modulators for measuring or pre-programming the probing intensity patterns, which is not universally available in all spectral regions especially in the mid-infrared range. Here, we demonstrate a frequency downconversion temporal ghost imaging scheme that enables to extend the operation regime to arbitrary wavelengths regions where fast modulators and detectors are not available. The approach modulates a signal with temporal intensity patterns in the near-infrared and transfers the patterns to an idler via difference-frequency generation at the wavelength of the temporal object to be retrieved. As a proof-of-concept, we demonstrate temporal ghost imaging in the mid-infrared. The scheme is flexible and introduces new possibilities for scan-free pump-probe imaging and the study of ultrafast dynamics in spectral regions where ultrafast modulation or detection is challenging such as the mid-infrared and THz regions.

physics.optics

Replica symmetry breaking in 1D Rayleigh scattering system: theory and validations

Spin glass theory, as a paradigm for describing disordered magnetic systems, constitutes a prominent subject of study within statistical physics. Replica symmetry breaking (RSB), as one of the pivotal concepts for the understanding of spin glass theory, means that, under identical conditions disordered systems can yield distinct states with nontrivial correlations. Random fiber laser (RFL) based on Rayleigh scattering (RS) is a complex disordered system, owing to the disorder and stochasticity of RS. In this work, for the first time, we elaborate a precise theoretical model for studying the photonic phase transition via the platform of RS-based RFL, in which we clearly reveal that, apart from the pump power, the photon phase variation in RFL is also an analogy to the temperature term in spin glass phase transition, leading to a novel insight into the intrinsic mechanisms of photonic phase transition. In addition, based on this model and real-time high-fidelity detection spectral evolution, we theoretically predict and experimentally observe the mode-asymmetric characteristics of photonic phase transition in RS-based RFL. This finding contributes to a deeper understanding of the photonic RSB regime and the dynamics of RS-based RFL.

cond-mat.dis-nn

Characterization and regulation of statistical properties in Er-doped random fiber laser

Er-doped random fiber laser (ERFL) is a complex physical system, and understanding its intrinsic physical mechanisms is crucial for promoting applications. In this paper, we experimentally investigate the time-domain statistical properties of ERFL under full-bandwidth condition for the first time. We also analyze the effects of the transmission process and amplification process on the output characteristics of ERFL, on the basis of which we realize its regulation. This study guides RFL systems requiring transmission and amplification, offering fresh insights for regulating the time-domain stability.

physics.optics

Radiation build-up and dissipation in random fiber laser

Random fiber laser (RFL) is a complex physical system that arises from the distributed amplification and the intrinsic stochasticity of the fiber scattering. There has been widespread interest in analyzing the underlying lightwave kinetics at steady state. However, the transient state, such as the RFL build-up and dissipation, is also particularly important for unfolding lightwave interaction process. Here, we investigate for the first time the RFL dynamics at transient state, and track the RFL temporal and spectral evolution theoretically and experimentally. Particularly, with the contribution of randomly distributed feedback, the build-up of RFL shows continuous Verhulst logistic growth curves without cavity-related features, which is significantly different from the step-like growth curve of conventional fiber lasers. Furthermore, the radiation build-up duration is inversely related to the pump power, and the spectral evolution of RFL undergoes two phases from spectral density increase to spectral broadening. From steady-state to pump switch-off state, the RFL output power dissipates immediately, and the remaining Stokes lightwave from the Rayleigh scattering will gradually disappear after one round-trip. This work provides new insights into the transient dynamics features of the RFL.

physics.optics

The maximum likelihood degree of sparse polynomial systems

We consider statistical models arising from the common set of solutions to a sparse polynomial system with general coefficients. The maximum likelihood degree counts the number of critical points of the likelihood function restricted to the model. We prove the maximum likelihood degree of a sparse polynomial system is determined by its Newton polytopes and equals the mixed volume of a related Lagrange system of equations.

math.AG

Optimized Feedforward Neural Network Training for Efficient Brillouin Frequency Shift Retrieval in Fiber

Artificial neural networks (ANNs) can be used to replace traditional methods in various fields, making signal processing more efficient and meeting the real-time processing requirements of the Internet of Things (IoT). As a special type of ANN, recently the feedforward neural network (FNN) has been used to replace the time-consuming Lorentzian curve fitting (LCF) method in Brillouin optical time-domain analysis (BOTDA) to retrieve the Brillouin frequency shift (BFS), which could be used as the indicator in temperature/strain sensing, etc. However, FNN needs to be re-trained if the generalization ability is not satisfactory, or the frequency scanning step is changing in the experiment. This is a cumbersome and inefficient process. In this paper, FNN only needs to be trained once with the proposed method. 150.62 km BOTDA is built to verify the performance of the trained FNN. Simulation and experimental results show that the proposed method is promising in BOTDA because of its high computational efficiency and wide adaptability.

eess.SP

Rayleigh fading suppression in one-dimension optical scatters

Highly coherent wave is favorable for applications in which phase retrieval is necessary, yet a high coherent wave is prone to encounter Rayleigh fading phenomenon as it passes through a medium of random scatters. As an exemplary case, phase-sensitive optical time-domain reflectometry (Φ-OTDR) utilizes coherent interference of backscattering light along a fiber to achieve ultra-sensitive acoustic sensing, but sensing locations with fading won't be functional. Apart from the sensing domain, fading is also ubiquitous in optical imaging and wireless telecommunication, therefore it is of great interest. In this paper, we theoretically describe and experimentally verify how the fading phenomena in one-dimension optical scatters will be suppressed with arbitrary number of independent probing channels. We initially theoretically explained why fading would cause severe noise in the demodulated phase of Φ-OTDR; then M-degree summation of incoherent scattered light-waves is studied for the purpose of eliminating fading. Finally, the gain of the retrieved phase signal-to-noise-ratio and its fluctuations were analytically derived and experimentally verified. This work provides a guideline for fading elimination in one-dimension optical scatters, and it also provides insight for optical imaging and wireless telecommunication.

eess.SP