arXiv subjects

Zhibo Liu

Publications and source records attributed to Zhibo Liu.

At least 19 recordsLinked to original sources

arXiv2026

Kaon gravitational form factors and mechanical structure in a three-flavor NJL model

We investigate the gravitational form factors (GFFs) of the kaon in a proper-time-regularized three-flavor Nambu--Jona-Lasinio model. We treat the kaon as a light--strange pseudoscalar bound state and evaluate its energy--momentum-tensor matrix element using a dressed quark--graviton vertex. By retaining the interaction-induced contact contribution alongside the quark triangle diagrams, we preserve the gravitational Ward--Takahashi identity and ensure the conservation of the total energy--momentum tensor. We determine the light- and strange-quark contributions to the kaon GFFs, contrast them with the corresponding pion results, and extract the associated pressure and shear-force distributions, together with the Breit-frame and transverse light-front mass radii. Explicit flavor-symmetry breaking dictates that the strange sector carries a larger share of the kaon momentum and mechanical response. Consequently, compared to the pion, the kaon exhibits a less negative $D$-term and more compact mechanical distributions, featuring enhanced central pressure and shear. We further show that a Ward--Takahashi-identity-preserving reduction of the $C$-term projection is essential for maintaining the pion low-energy theorem in proper-time regularization.

hep-ph↗

arXiv2026

Pion and kaon D terms from holographic QCD and coupled-channel dispersion relations

For a spin-zero meson, the exact trace identity relates the D term to the tensor gravitational form factor $A_M(t)$ and the total scalar trace $\Theta_M(t)$. We study the pion and kaon D terms by combining a holographic tensor form factor with a chiral-dispersive representation of the trace. Its normalization and slope at the origin are obtained from the forward Ward identity and curved-space SU(3) chiral perturbation theory. A two-channel $\pi\pi/K\bar K$ Muskhelishvili--Omn\`es solution constructed from empirical scattering amplitudes describes the continuation to spacelike momentum. Available lattice-QCD results are shown for comparison. In the chiral limit, saturation of the trace by the normalized explicit quark-mass response gives $D_\pi(0)=-1/3$, while the soft-pion theorem gives $D_\pi(0)=-1$. This comparison separates the explicit-mass contribution from the remaining chiral scalar response. At physical masses, SU(3) breaking in the chiral matching distinguishes the pion and kaon forward values, and coupled-channel rescattering governs their evolution away from the origin. The kaon D term is less negative than the pion result in the low-$Q^2$ spacelike region considered, with the separation decreasing as $Q^2$ increases. These form factors provide a low-energy reference for future lattice studies of the tensor and scalar channels.

hep-ph↗

arXiv2026

The Unseen Delta: Characterizing the Compiler Optimization Landscape via Top-Down Differential Analysis

Compiler optimizations are essential for achieving high performance in modern software. However, recent studies highlight the persistence of performance bugs, i.e., subtle defects where the compiler generates functionally correct but computationally inefficient code, leading to significant performance degradation. Existing detection and testing methods typically employ a bottom-up approach, focusing on specific low-level code properties and remaining confined to known optimization rules. Consequently, they struggle to quantify the holistic impact of identified issues and often overlook critical microarchitectural inefficiencies. We observe a key indicator of untapped potential: different compilers often produce binaries with significant performance differences for identical source code. However, the root causes of these discrepancies remain largely unexplored and difficult to pinpoint using current techniques. To bridge this gap, we introduce a top-down differential analysis methodology. This approach calibrates compiler optimization differences with fine-grained, hierarchical microarchitectural metrics, offering a comprehensive view of runtime behavior. Using a sampling-based approach, this method efficiently pinpoints the critical code snippets responsible for performance differences, enabling targeted root cause analysis. Our empirical evaluation uncovers substantial and often surprising performance differences between binaries generated by GCC and Clang. A categorization of root causes reveals systemic challenges in compiler optimizations. To quantitatively validate our findings and demonstrate practical impact, we developed a binary patching framework that fixes identified performance issues by transplanting superior code sequences from competing compilers. This work provides a novel lens for understanding and analyzing optimization defects.

cs.SE↗

arXiv2026

Detecting and Understanding Vulnerabilities in Fully Homomorphic Encryption Frameworks

Fully homomorphic encryption (FHE) allows computations to be performed directly on encrypted data without decryption, offering strong privacy guarantees for sensitive data analysis. This capability is important for privacy-sensitive applications like secure cloud computing, finance, and healthcare. The complexity of FHE schemes, however, has hindered their practical adoption. To make FHE accessible to a broader range of developers, a new generation of specialized frameworks has emerged to translate high-level FHE programs into complex FHE operations, introducing a new programming paradigm. However, the inherent complexity of FHE frameworks makes them prone to incorrect implementation logic. Unlike mere crashes, logic bugs in these frameworks can silently corrupt encrypted computation, potentially leading to severe financial losses and security vulnerabilities in FHE-enhanced applications. In this work, we introduce HERTA, the first automated testing tool tailored for FHE frameworks. HERTA leverages metamorphic testing to uncover deep-seated implementation bugs and vulnerabilities across the multi-layered FHE software stack. To that end, we design a set of novel metamorphic relations (MRs) derived specifically from FHE semantics. These MRs stress the most challenging aspects of the pipeline, enabling automated correctness testing without the need for a manual ground truth. Our evaluation of HERTA on 3 leading industry frameworks discovered 21 previously unknown bugs, several of which have already been confirmed and fixed by developers. Furthermore, our hazard analysis reveals the critical security impact these bugs pose to the integrity and availability of FHE-based services.

cs.CR↗

arXiv2026

NAG: A Unified Native Architecture for Encoder-free Text-Graph Modeling in Language Models

Prevailing methods for integrating graphs into Language Models (LMs) typically rely on a segregated architecture: external Graph Neural Networks (GNNs) encode structural topology, while LMs process textual semantics. We argue this approach is suboptimal for text-graphs: it creates a conceptually disjointed interaction paradigm. By segregating structural encoding from semantic processing, these systems must perform a complex implicit alignment between abstract graph tokens and concrete textual elements. Challenging the necessity of external encoders, we propose NAG (Native Architecture for Graphs), a unified framework that internalizes graph processing within the LM's native manifold. Instead of bridging disparate embedding spaces, NAG repurposes the self-attention mechanism to enforce topological dependencies and recalibrates positional IDs to ensure structural equivalence. This allows the model to harness its intrinsic linguistic capability to simultaneously comprehend node and edge content alongside structural topology. We introduce two efficient implementations: NAG-Zero for absolute preservation of the base model's linguistic capabilities, and NAG-LoRA for enhanced structural adaptation. Experiments across diverse graph tasks validate that NAG achieves robust graph comprehension without the overhead of external encoders, offering a simpler, more coherent paradigm for text-graph modeling.

cs.CL↗

arXiv2025

Gravitational form factors of the baryon octet in holographic QCD

The gravitational form factors (GFFs) of the baryon octet, including hyperons, are investigated in a bottom-up holographic QCD model that explicitly incorporates the SU(3) flavor symmetry breaking through the strange quark mass. We fit the model parameters to reproduce the empirical masses of the baryon octet and examine the dependence of GFFs on the probe momentum. Our numerical results show distinct differences in the GFFs across the baryon octet. The computed GFFs are found to be in reasonable agreement with available lattice QCD results for the non-strange/nucleon sector. We also calculate the gravitational radii of the baryon octet and find that they decrease with increasing strangeness, indicating that heavier hyperons are more compact.

hep-ph↗

arXiv2025

Holographic description of the kaon gravitational form factor

We compute the kaon gravitational form factor (GFF) using a bottom-up holographic QCD approach that incorporates SU(3) flavor symmetry breaking through the strange quark mass. We present the resulting Q^2 dependence of the kaon GFF and compare it with that of the pion. In the high-energy limit, the kaon GFF exhibits a 1/Q^2 falloff, in agreement with perturbative QCD. Furthermore, we extract the gravitational radius of the kaon and find it to be almost the same as that of the pion, with a slightly smaller value.

hep-ph↗

arXiv2025

Diverse polymorphs and phase transitions in van der Waals In$_2$Se$_3$

Van der Waals In$_2$Se$_3$ has garnered significant attention due to its unique properties and wide applications associated with its rich polymorphs and polymorphic phase transitions. Despite extensive studies, the vast complex polymorphic phase space remains largely unexplored, and the underlying microscopic mechanism for their phase transformations remains elusive. Here, we develop a highly accurate, efficient, and reliable machine-learning potential (MLP), which not only facilitates accurate exploration of the intricate potential energy surface (PES), but also enables us to conduct large-scale molecular dynamics (MD) simulations with first-principles accuracy. We identify the accurate structure of the $β''$ polymorph and uncover several previously unreported $β'$ polymorph variants exhibiting dynamic stability and competing energies, which are elucidated by characteristic flat imaginary phonon bands and the distinctive Mexican-hat-like PES in the $β$ polymorph. Through the MLP-accelerated MD simulations, we directly observe the polymorphic phase transformations among the $α$, $β$, $β'$, and $β''$ polymorphs under varying temperature and pressure conditions, and build for the first time an ab initio temperature-pressure phase diagram, showing good agreement with experiments. Furthermore, our MD simulations reveal a novel strain-induced reversible phase transition between the $β'$ and $β''$ polymorphs. This work not only unveils diverse polymorphs in van der Waals In$_2$Se$_3$, but also provides crucial atomic insights into their phase transitions, opening new avenues for the design of novel functional electronic devices.

cond-mat.mtrl-sci↗

arXiv2025

Gravitational form factor of the kaon in holographic QCD

The gravitational form factor (GFF) of the kaon is investigated in a bottom-up holographic QCD model, in which the strange quark mass breaks the SU(3) flavor symmetry. The probe energy ($Q^2$) dependence of the kaon GFF is explicitly shown and compared to that of the pion. It is presented that our result shows the $1/Q^2$ behavior in the high energy region, which is consistent with the perturbative QCD prediction. The gravitational radius of the kaon is also calculated, and it is found that the result is quite close to that of the pion but slightly smaller.

hep-ph↗

arXiv2024

Preserving Privacy in Software Composition Analysis: A Study of Technical Solutions and Enhancements

Software composition analysis (SCA) denotes the process of identifying open-source software components in an input software application. SCA has been extensively developed and adopted by academia and industry. However, we notice that the modern SCA techniques in industry scenarios still need to be improved due to privacy concerns. Overall, SCA requires the users to upload their applications' source code to a remote SCA server, which then inspects the applications and reports the component usage to users. This process is privacy-sensitive since the applications may contain sensitive information, such as proprietary source code, algorithms, trade secrets, and user data. Privacy concerns have prevented the SCA technology from being used in real-world scenarios. Therefore, academia and the industry demand privacy-preserving SCA solutions. For the first time, we analyze the privacy requirements of SCA and provide a landscape depicting possible technical solutions with varying privacy gains and overheads. In particular, given that de facto SCA frameworks are primarily driven by code similarity-based techniques, we explore combining several privacy-preserving protocols to encapsulate the similarity-based SCA framework. Among all viable solutions, we find that multi-party computation (MPC) offers the strongest privacy guarantee and plausible accuracy; it, however, incurs high overhead (184 times). We optimize the MPC-based SCA framework by reducing the amount of crypto protocol transactions using program analysis techniques. The evaluation results show that our proposed optimizations can reduce the MPC-based SCA overhead to only 8.5% without sacrificing SCA's privacy guarantee or accuracy.

cs.SE↗

arXiv2024

Compiled Models, Built-In Exploits: Uncovering Pervasive Bit-Flip Attack Surfaces in DNN Executables

Bit-flip attacks (BFAs) can manipulate deep neural networks (DNNs). For high-level DNN models running on deep learning (DL) frameworks like PyTorch, extensive BFAs have been used to flip bits in model weights and shown effective. Defenses have also been proposed to guard model weights. However, DNNs are increasingly compiled into DNN executables by DL compilers to leverage hardware primitives. These executables manifest distinct computation paradigms; existing research fails to accurately capture and expose the BFA surfaces on DNN executables. To this end, we launch the first systematic study of BFAs on DNN executables. Prior BFAs are limited to attacking model weights and assume a strong whitebox attacker with full knowledge of victim model weights, which is unrealistic as weights are often confidential. In contrast, we find that BFAs on DNN executables can achieve high effectiveness by exploiting the model structure (usually stored in the executable code), which only requires knowing the (often public) model structure. Importantly, such structure-based BFAs are pervasive, transferable, and more severe in DNN executables. They also slip past existing defenses. To demonstrate the new attack surfaces, we assume a weak and more realistic attacker with no knowledge of victim model weights. We design an automated tool to identify vulnerable bits in victim executables with high confidence (70% vs. baseline 2%). We show on DDR4 DRAM that only 1.4 flips on average are needed to fully downgrade the accuracy of victim models, including quantized ones which could require 23x more flips previously, to random guesses. We comprehensively evaluate 16 DNN executables, covering large-scale models trained on commonly-used datasets compiled by the two most popular DL compilers. Our finding calls for incorporating security mechanisms in future DNN compilation toolchains.

cs.CR↗

arXiv2024

Observation of Rydberg excitons in monolayer MoS2 at room temperature by Imbert-Fedorov shift spectroscopy

Rydberg excitons in transition metal dichalcogenides (TMDs) have emerged as a promising platform for investigating the properties of open quantum systems, thanks to their large binding energies(hundreds of meV). However, the study of Rydberg excitons in TMDs has been hindered by sample quality limitations, strong background signals from ground excitons, and broadening at room temperature. In this work, we report the first observation of multiple Rydberg exciton states in monolayer MoS2 at room temperature using Imbert-Fedorov (IF) shift spectroscopy. By numerically solving the Schrodinger equation, we extracted the quasiparticle band gaps for A and B excitons, confirming the temperature-induced redshift of the band gap, in excellent agreement with previous results. Our findings establish IF shift spectroscopy as a powerful tool for characterizing Rydberg excitons in TMDs, paving the way for potential applications in quantum manipulation and control.

physics.optics↗

arXiv2024

Holographic description of elastic photon-proton and photon-photon scattering

We investigate the elastic photon-proton and photon-photon scattering in a holographic QCD model, focusing on the Regge regime. Considering contributions of the Pomeron and Reggeon exchange, the total and differential cross sections are calculated. While our model involves several parameters, by virtue of the universality of the Pomeron and Reggeon, for most of them the values determined in the preceding study on the proton-proton and proton-antiproton scattering can be employed. Once the two adjustable parameters, the Pomeron-photon and Reggeon-photon coupling constant, are determined with the experimental data of the total cross sections, predicting the both cross sections in a wide kinematic region, from the GeV to TeV scale, becomes possible. We show that the total cross section data can be well described within the model, and our predictions for the photon-proton differential cross section are consistent with the data.

hep-ph↗

arXiv2024

Elastic proton-neutron and antiproton-neutron scattering in holographic QCD

The total and differential cross sections of the elastic proton-neutron and antiproton-neutron scattering are studied in a holographic QCD model, focusing on the Regge regime. Taking into account the Pomeron and Reggeon exchange, which are described by the Reggeized spin-2 glueball and vector meson propagator respectively, those cross sections are obtained. It is presented that the currently available experimental data of the total cross sections can be well described within the model. Once a single adjustable parameter is determined with the total cross section data, the differential cross sections can be calculated without any additional parameters. Although the available differential cross section data are limited, it is found that our predictions are consistent with those.

hep-ph↗

arXiv2024

Elastic pion-proton and pion-pion scattering via the holographic Pomeron and Reggeon exchange

The elastic pion-proton and pion-pion scattering are studied in a holographic QCD model, focusing on the Regge regime. Taking into account the Pomeron and Reggeon exchange, which are described by the Reggeized $2^{++}$ glueball and vector meson propagator respectively, the total and differential cross sections are calculated. The adjustable parameters involved in the model are determined with the experimental data of the pion-proton total cross sections. The differential cross sections can be predicted without any additional parameters, and it is shown that our predictions are consistent with the data. The energy dependence of the Pomeron and Reggeon contribution is also discussed.

hep-ph↗

arXiv2024

Pomeron and Reggeon contributions to elastic proton-proton and proton-antiproton scattering in holographic QCD

The total and differential cross sections of elastic proton-proton and proton-antiproton scattering are studied in a holographic QCD model, considering the Pomeron and Reggeon exchanges in the Regge regime. In our model setup, the Pomeron and Reggeon exchanges are described by the Reggeized spin-2 glueball and vector meson propagators, respectively. How those contributions change with the energy is explicitly shown, focusing on the contribution ratios. The adjustable parameters included in the model are determined with the experimental data, and it is presented that the resulting total and differential cross sections are consistent with the data in a wide kinematic region.

hep-ph↗

arXiv2023

Refining Decompiled C Code with Large Language Models

A C decompiler converts an executable into source code. The recovered C source code, once re-compiled, is expected to produce an executable with the same functionality as the original executable. With over twenty years of development, C decompilers have been widely used in production to support reverse engineering applications. Despite the prosperous development of C decompilers, it is widely acknowledged that decompiler outputs are mainly used for human consumption, and are not suitable for automatic recompilation. Often, a substantial amount of manual effort is required to fix the decompiler outputs before they can be recompiled and executed properly. This paper is motived by the recent success of large language models (LLMs) in comprehending dense corpus of natural language. To alleviate the tedious, costly and often error-prone manual effort in fixing decompiler outputs, we investigate the feasibility of using LLMs to augment decompiler outputs, thus delivering recompilable decompilation. Note that different from previous efforts that focus on augmenting decompiler outputs with higher readability (e.g., recovering type/variable names), we focus on augmenting decompiler outputs with recompilability, meaning to generate code that can be recompiled into an executable with the same functionality as the original executable. We conduct a pilot study to characterize the obstacles in recompiling the outputs of the de facto commercial C decompiler -- IDA-Pro. We then propose a two-step, hybrid approach to augmenting decompiler outputs with LLMs. We evaluate our approach on a set of popular C test cases, and show that our approach can deliver a high recompilation success rate to over 75% with moderate effort, whereas none of the IDA-Pro's original outputs can be recompiled. We conclude with a discussion on the limitations of our approach and promising future research directions.

cs.SE↗

arXiv2023

PHYFU: Fuzzing Modern Physics Simulation Engines

A physical simulation engine (PSE) is a software system that simulates physical environments and objects. Modern PSEs feature both forward and backward simulations, where the forward phase predicts the behavior of a simulated system, and the backward phase provides gradients (guidance) for learning-based control tasks, such as a robot arm learning to fetch items. This way, modern PSEs show promising support for learning-based control methods. To date, PSEs have been largely used in various high-profitable, commercial applications, such as games, movies, virtual reality (VR), and robotics. Despite the prosperous development and usage of PSEs by academia and industrial manufacturers such as Google and NVIDIA, PSEs may produce incorrect simulations, which may lead to negative results, from poor user experience in entertainment to accidents in robotics-involved manufacturing and surgical operations. This paper introduces PHYFU, a fuzzing framework designed specifically for PSEs to uncover errors in both forward and backward simulation phases. PHYFU mutates initial states and asserts if the PSE under test behaves consistently with respect to basic Physics Laws (PLs). We further use feedback-driven test input scheduling to guide and accelerate the search for errors. Our study of four PSEs covers mainstream industrial vendors (Google and NVIDIA) as well as academic products. We successfully uncover over 5K error-triggering inputs that generate incorrect simulation results spanning across the whole software stack of PSEs.

cs.SE↗