The Circular Electron-Positron Collider (CEPC), a proposed next-generation Higgs factory, provides new opportunities to explore physics beyond the Standard Model (SM). With its clean electron-positron collision environment and the ability to collect large samples of Higgs, W, and Z bosons, the CEPC enables precision measurements and searches for new physics. This white paper outlines the CEPC's discovery potential, including studies of exotic decays of the Higgs, Z, and top quarks, dark matter and dark sector phenomena, long-lived particles, supersymmetry, and neutrino-related signatures. Advanced detector technologies and reconstruction techniques, such as one-to-one correspondence reconstruction and jet origin identification, significantly improve sensitivity to rare and weakly interacting processes. The CEPC is particularly well suited to probe the electroweak phase transition and test models of electroweak baryogenesis and dark sector interactions. In addition, global fit analyses highlight the CEPC's complementary role in constraining a wide range of new physics scenarios. These features position the CEPC as a powerful tool for exploring the next frontier in fundamental particle physics in the post-Higgs discovery era.

Most previous studies on relativistic quantum information have primarily focused on the vacuum state $|0\rangle$ and the first excited state $|1\rangle$ in two-mode entangled systems. In this work, we go beyond these limitations by considering arbitrary $q$-th excited states $|q\rangle$, aiming to investigate their role in preserving quantum resources. We analyze the influence of the Hawking effect on multipartite quantum states in the Schwarzschild spacetime, with particular attention to quantum entanglement and coherence. Our results show that, under the influence of the Hawking effect, increasing the excitation number $q$ leads to a reduction in quantum entanglement and mutual information, while enhancing quantum coherence. This indicates that the Hawking effect on excited multipartite states tends to degrade quantum correlations but simultaneously protects quantum coherence in curved spacetime. Therefore, when implementing quantum information protocols in gravitational settings, reducing the excitation number $q$ is favorable for maintaining entanglement, whereas increasing $q$ may be advantageous for tasks that rely on quantum coherence in relativistic quantum information processing.

The linear seesaw (LSS) model provides a natural framework for generating small neutrino masses at low energy scales, thereby offering promising testability prospects. However, in generic LSS models, the exact mass degeneracy (before the electroweak symmetry breaking) between the two sterile neutrinos that form a Dirac pair precludes the generation of CP asymmetries from their interplay, posing a significant challenge to explaining the observed baryon (or lepton) asymmetry of the Universe via the leptogenesis mechanism. In this work, we explore two well-motivated approaches to generate a suitable mass splitting for the two sterile neutrinos that form a Dirac pair, and consequently naturally realize a resonantly enhanced generation of baryon (and lepton) asymmetry. First, we demonstrate that the renormalization group evolution effects can naturally induce the desired mass splitting for the sterile neutrinos, resulting in a successful generation of the observed baryon asymmetry of the Universe. Second, motivated by the recent result from the EMPRESS collaboration that indicates the possible existence of a large lepton asymmetry of the Universe, we explore the possibility that a large lepton asymmetry might naturally follow from the electroweak symmetry breaking which automatically induces the desired mass splitting for the sterile neutrinos.

The $\Lambda$CDM model provides a good fit to a large span of cosmological data but harbors areas of phenomenology. With the improvement of the number and the accuracy of observations, discrepancies among key cosmological parameters of the model have emerged. The most statistically significant tension is the $4-6\sigma$ disagreement between predictions of the Hubble constant $H_0$ by early time probes with $\Lambda$CDM model, and a number of late time, model-independent determinations of $H_0$ from local measurements of distances and redshifts. The high precision and consistency of the data at both ends present strong challenges to the possible solution space and demand a hypothesis with enough rigor to explain multiple observations--whether these invoke new physics, unexpected large-scale structures or multiple, unrelated errors. We present a thorough review of the problem, including a discussion of recent Hubble constant estimates and a summary of the proposed theoretical solutions. Some of the models presented are formally successful, improving the fit to the data in light of their additional degrees of freedom, restoring agreement within $1-2\sigma$ between {\it Planck} 2018, using CMB power spectra data, BAO, Pantheon SN data, and R20, the latest SH0ES Team measurement of the Hubble constant ($H_0 = 73.2 \pm 1.3{\rm\,km\,s^{-1}\,Mpc^{-1}}$ at 68\% confidence level). Reduced tension might not simply come from a change in $H_0$ but also from an increase in its uncertainty due to degeneracy with additional physics, pointing to the need for additional probes. While no specific proposal makes a strong case for being highly likely or far better than all others, solutions involving early or dynamical dark energy, neutrino interactions, interacting cosmologies, primordial magnetic fields, and modified gravity provide the best options until a better alternative comes along.[Abridged]

Based on the $(2712.4\pm14.4)\times 10^{6}$ $\psi(3686)$ events collected with the BESIII detector, we present a high-precision study of the $\pi^+\pi^-$ mass spectrum in $\psi(3686)\rightarrow\pi^{+}\pi^{-}J/\psi$ decays. A clear resonance-like structure is observed near the $\pi^+\pi^-$ mass threshold for the first time. A fit with a Breit-Wigner function yields a mass of $285.6\pm 2.5~{\rm MeV}/c^2$ and a width of $16.3\pm 0.9~{\rm MeV}$ with a statistical significance exceeding 10$\sigma$. To interpret the data, we incorporate final-state interactions (FSI) within two theoretical frameworks: chiral perturbation theory (ChPT) and QCD multipole expansion (QCDME). ChPT describes the spectrum above 0.3 GeV/$c^2$ but fails to reproduce the threshold enhancement. In contrast, the QCDME model, assuming the $\psi(3686)$ is an admixture of S- and D-wave charmonium, reproduces the data well. The pronounced dip near 0.3 GeV/$c^2$ offers new insight into the interplay between chiral dynamics and low-energy QCD.

Large Language Models (LLMs) have shown strong performance in automated source-to-target code translation through pretraining on extensive code corpora. However, mainstream LLM-based code translation methods suffer from two critical limitations. First, they are highly sensitive to language-specific features, which often introduce source-language syntax or lexicon into the output, leading to syntactic confusion. Second, they lack fine-grained semantic alignment due to an over-reliance on function-level parallel datasets, resulting in semantic misalignment between the translated code and the original source. To overcome these limitations, we propose TIT, a Tree-structured Instruction Tuning paradigm for LLM-based code translation. Specifically, TIT consists of three modules. First, to mitigate syntactic confusion, the syntactic information representation module integrates language-agnostic syntactic features via structured parsing. Then, to generate high-quality fine-grained parallel data, the fine-grained parallel dataset augmentation module aligns nodes with code segments through statement-level segmentation and contrastive matching. Finally, we leverage the dual-stage tree instruction tuning module to alleviate the contextual processing burden on the LLM caused by the introduction of syntactic information. The first stage employs syntax-aware fine-tuning to enable the LLM to autonomously comprehend structured syntactic information, while the second stage utilizes code generation fine-tuning to guide the model in generating accurate target code based on function-level syntactic dependencies. The experimental results demonstrate that the proposed method significantly outperforms existing approaches in multiple LLMs, achieving a success rate 1.22x-1.75x higher in code translation while markedly reducing syntactic confusion.

Multi-object editing aims to modify multiple objects or regions in complex scenes while preserving structural coherence. This task faces significant challenges in scenarios involving overlapping or interacting objects: (1) Inaccurate localization of target objects due to attention misalignment, leading to incomplete or misplaced edits; (2) Attribute-object mismatch, where color or texture changes fail to align with intended regions due to cross-attention leakage, creating semantic conflicts (\textit{e.g.}, color bleeding into non-target areas). Existing methods struggle with these challenges: approaches relying on global cross-attention mechanisms suffer from attention dilution and spatial interference between objects, while mask-based methods fail to bind attributes to geometrically accurate regions due to feature entanglement in multi-object scenarios. To address these limitations, we propose a training-free, inference-stage optimization approach that enables precise localized image manipulation in complex multi-object scenes, named MDE-Edit. MDE-Edit optimizes the noise latent feature in diffusion models via two key losses: Object Alignment Loss (OAL) aligns multi-layer cross-attention with segmentation masks for precise object positioning, and Color Consistency Loss (CCL) amplifies target attribute attention within masks while suppressing leakage to adjacent regions. This dual-loss design ensures localized and coherent multi-object edits. Extensive experiments demonstrate that MDE-Edit outperforms state-of-the-art methods in editing accuracy and visual quality, offering a robust solution for complex multi-object image manipulation tasks.

The development of Internet technology has led to an increased prevalence of misinformation, causing severe negative effects across diverse domains. To mitigate this challenge, Misinformation Detection (MD), aiming to detect online misinformation automatically, emerges as a rapidly growing research topic in the community. In this paper, we propose a novel plug-and-play augmentation method for the MD task, namely Misinformation Detection with Potential Commonsense Conflict (MD-PCC). We take inspiration from the prior studies indicating that fake articles are more likely to involve commonsense conflict. Accordingly, we construct commonsense expressions for articles, serving to express potential commonsense conflicts inferred by the difference between extracted commonsense triplet and golden ones inferred by the well-established commonsense reasoning tool COMET. These expressions are then specified for each article as augmentation. Any specific MD methods can be then trained on those commonsense-augmented articles. Besides, we also collect a novel commonsense-oriented dataset named CoMis, whose all fake articles are caused by commonsense conflict. We integrate MD-PCC with various existing MD backbones and compare them across both 4 public benchmark datasets and CoMis. Empirical results demonstrate that MD-PCC can consistently outperform the existing MD baselines.

Nowadays, misinformation articles, especially multimodal ones, are widely spread on social media platforms and cause serious negative effects. To control their propagation, Multimodal Misinformation Detection (MMD) becomes an active topic in the community to automatically identify misinformation. Previous MMD methods focus on supervising detectors by collecting offline data. However, in real-world scenarios, new events always continually emerge, making MMD models trained on offline data consistently outdated and ineffective. To address this issue, training MMD models under online data streams is an alternative, inducing an emerging task named continual MMD. Unfortunately, it is hindered by two major challenges. First, training on new data consistently decreases the detection performance on past data, named past knowledge forgetting. Second, the social environment constantly evolves over time, affecting the generalization on future data. To alleviate these challenges, we propose to remember past knowledge by isolating interference between event-specific parameters with a Dirichlet process-based mixture-of-expert structure, and anticipate future environmental distributions by learning a continuous-time dynamics model. Accordingly, we induce a new continual MMD method DAEDCMD. Extensive experiments demonstrate that DAEDCMD can consistently and significantly outperform the compared methods, including six MMD baselines and three continual learning methods.

We investigate tripartite quantum-memory-assisted entropic uncertain and quantum coherence for GHZ and W states of a fermionic field in the background of a spherically symmetric black hole of Einstein-Gauss-Bonnet (EGB) gravity. Two distinct scenarios are analyzed: (i) the quantum memories (held by Bob and Charlie) are near the horizon while the measured particle (Alice) remains in the flat region, and (ii) the reverse configuration. Dimensional dependence is observed: in $d>5$ dimensions, the measurement uncertainty decreases monotonically with increasing horizon radius, while coherence increases; in $d=5$, both quantities exhibit non-monotonic behavior due to distinctive thermodynamic properties. Furthermore, comparative analysis reveals that the W state exhibits higher robustness in preserving coherence, whereas the GHZ state shows greater resistance to measurement uncertainty increase induced by Hawking radiation. Notably, the two scenarios yield qualitatively distinct behaviors: quantum coherence is consistently lower in Scenario 1 (quantum memory near horizon) than in Scenario 2 (measured particle near horizon), irrespective of the quantum state. For measurement uncertainty, the W state displays lower uncertainty in Scenario 1, while the GHZ state exhibits the opposite trend, with higher measurement uncertainty in Scenario 1. These results indicate that the characteristics of different quantum resources provide important insights into the selection and optimization of quantum states for information processing in curved spacetime.

The dark photon is a well motivated candidate for the dark matter which comprises most of the mass of our visible Universe, leading to worldwide experimental and observational efforts towards its discovery. A primary tool in this search is the cavity haloscope, which facilitates resonantly enhanced conversion to photons from both dark photons and axions. In this context, limits from axion search experiments are often directly converted into dark photon constraints, without re-analyzing the original data. However, this rescaling may not fully capture all of the relevant physics due to various reasons. By re-examining data taken by the Taiwan Axion Search Experiment with Haloscope (TASEH) experiment, we derive a world-leading constraint on the dark photon parameter space, excluding $|\epsilon|\gtrsim2\times10^{-14}$ in the $19.46 - 19.84\,\mu$eV mass range, which exceeds the naive `rescaling limit' by roughly one order of magnitude. In this data, we also identify a tentative signal with a local significance of 4.7$\sigma$, previously disregarded due to an axion-specific veto, corresponding to a dark photon with mass $m_X \simeq 19.5\,\mu$eV ($f_X\simeq 4.71$ GHz) and kinetic mixing $\epsilon \simeq 6.5\times10^{-15}$.

Various social media platforms, e.g., Twitter and Reddit, allow people to disseminate a plethora of information more efficiently and conveniently. However, they are inevitably full of misinformation, causing damage to diverse aspects of our daily lives. To reduce the negative impact, timely identification of misinformation, namely Misinformation Detection (MD), has become an active research topic receiving widespread attention. As a complex phenomenon, the veracity of an article is influenced by various aspects. In this paper, we are inspired by the opposition of intents between misinformation and real information. Accordingly, we propose to reason the intent of articles and form the corresponding intent features to promote the veracity discrimination of article features. To achieve this, we build a hierarchy of a set of intents for both misinformation and real information by referring to the existing psychological theories, and we apply it to reason the intent of articles by progressively generating binary answers with an encoder-decoder structure. We form the corresponding intent features and integrate it with the token features to achieve more discriminative article features for MD. Upon these ideas, we suggest a novel MD method, namely Detecting Misinformation by Integrating Intent featuRes (DM-INTER). To evaluate the performance of DM-INTER, we conduct extensive experiments on benchmark MD datasets. The experimental results validate that DM-INTER can outperform the existing baseline MD methods.

The Super $\tau$-Charm facility (STCF) is an electron-positron collider proposed by the Chinese particle physics community. It is designed to operate in a center-of-mass energy range from 2 to 7 GeV with a peak luminosity of $0.5\times 10^{35}{\rm cm}^{-2}{\rm s}^{-1}$ or higher. The STCF will produce a data sample about a factor of 100 larger than that by the present $\tau$-Charm factory -- the BEPCII, providing a unique platform for exploring the asymmetry of matter-antimatter (charge-parity violation), in-depth studies of the internal structure of hadrons and the nature of non-perturbative strong interactions, as well as searching for exotic hadrons and physics beyond the Standard Model. The STCF project in China is under development with an extensive R\&D program. This document presents the physics opportunities at the STCF, describes conceptual designs of the STCF detector system, and discusses future plans for detector R\&D and physics case studies.

This study explores the possibility of a time-varying dark energy (DE) equation of state (EoS) deviating from -1. We employ a comprehensive dataset of usual astronomical probes (Type Ia supernovae, baryon acoustic oscillations, Big Bang nucleosynthesis, Hubble data, and Planck 2018 CMB) alongside future mock gravitational wave (GW) distance measurements from the Einstein Telescope. We utilize the Pad'e approximation, a versatile framework encompassing well-known DE models like constant EoS, Chevallier-Polarski-Linder parametrization and other time-evolving DE parametrizations. Within Pad'e parametrization, we examine three specific forms (Pad'e-I, SPad'e-I, Pad'e-II) applied to both spatially flat and non-flat universes. Pad'e-II exhibits particularly interesting features in terms of the evidence of dynamical DE at many standard deviations. Our results can be summarized as follows. Flat Universe: When analyzing the combined dataset of standard probes (including CMB) with Pad'e-II in a flat universe, we find a strong preference (6.4{\sigma}) for a dynamical (time-varying) DE EoS. This preference remains significant (4.7{\sigma}) even when incorporating future GW data. Non-Flat Universe: In a non-flat universe, the combined standard datasets (without or with CMB) also indicate dynamical DE EoS at a high confidence level (6.2{\sigma} and 6.4{\sigma}, respectively). The addition of GW data slightly reduces the evidence (3.8{\sigma} and 5.1{\sigma}, respectively), but the preference persists. These results collectively suggest a robust case for dynamical DE in the dark sector. While a non-flat universe is not strongly favored, Pad'e-II hints at a possible closed universe when CMB data is included (with or without GW data).

In a relativistic framework, it is generally accepted that quantum steering of maximally entangled states provide greater advantages in practical applications compared to non-maximally entangled states. In this paper, we investigate quantum steering for four different types of Bell-like states of fermionic modes near the event horizon of a Schwarzschild black hole. In some parameter spaces, the peak of steering asymmetry corresponds to a transition from two-way to one-way steerability for Bell-like states under the influence of the Hawking effect. It is intriguing to find that the fermionic steerability of the maximally entangled states experiences sudden death with the Hawking temperature, while the fermionic steerability of the non-maximally entangled states maintains indefinite persistence at infinite Hawking temperature. In contrast to prior research, this finding suggests that quantum steering of non-maximally entangled states is more advantageous than that of maximally entangled states for processing quantum tasks in the gravitational background. This surprising result overturns the traditional idea of ``the advantage of maximally entangled steering in the relativistic framework" and provides a new perspective for understanding the Hawking effect of the black hole.

Charged lepton flavor violation is forbidden in the Standard Model but possible in several new physics scenarios. In many of these models, the radiative decays $\tau^{\pm}\rightarrow\ell^{\pm}\gamma$ ($\ell=e,\mu$) are predicted to have a sizeable probability, making them particularly interesting channels to search at various experiments. An updated search via $\tau^{\pm}\rightarrow\ell^{\pm}\gamma$ using full data of the Belle experiment, corresponding to an integrated luminosity of 988 fb$^{-1}$, is reported for charged lepton flavor violation. No significant excess over background predictions from the Standard Model is observed, and the upper limits on the branching fractions, $\mathcal{B}(\tau^{\pm}\rightarrow \mu^{\pm}\gamma)$ $\leq$ $4.2\times10^{-8}$ and $\mathcal{B}(\tau^{\pm}\rightarrow e^{\pm}\gamma)$ $\leq$ $5.6\times10^{-8}$, are set at 90\% confidence level.

We systematically investigate the directional dependence of Gaussian quadripartite quantum steering and its redistribution among different modes in the background of a Schwarzschild black hole. For physically accessible sectors, we identify three distinct behaviors: (i) steering from non-gravitational to gravitational observers undergoes sudden death at maximal asymmetry with the Hawking temperature, marking the crossover from two-way to one-way steerability; (ii) steering in the opposite direction decays monotonically and vanishes only in the extreme black hole limit, highlighting its directional sensitivity to spacetime curvature; (iii) steering from hybrid gravitational-non-gravitational partitions to non-gravitational mode persists at a finite asymptotic value set by the initial squeezing parameter. Moreover, all inaccessible steerings generated by the Hawking effect exhibit an intrinsic asymmetry, with their specific behavior being strongly dependent on the steering direction.

In this work, we investigate the velocity effects on information degradation due to the Unruh effect in accelerated quantum systems (with finite interaction time). We consider a detector moving along a spatial trajectory within a two-dimensional plane. The quantum systems studied were: accelerated single-qubit, quantum interferometric circuit, and which-path distinguishability circuit. Thus, for non-relativistic velocity regime, we obtained analytical expressions such as transition rates, quantum coherence, visibility, distinguishability, and the complementarity relation. On the other hand, for the ultra-relativistic velocity regime, we saw that the Unruh effect is suppressed and therefore the detector does not respond in this case. Our findings revealed that velocity effects imply mitigation of information degradation, this interesting behaviors happen because of the composite effect of both velocity and acceleration. The results obtained show that the addition of the non-relativistic, transverse and constant motion of an accelerated detector can play a protective role in quantumness in systems at high accelerations, although the effects are very small.

Zero-shot event-relational reasoning is an important task in natural language processing, and existing methods jointly learn a variety of event-relational prefixes and inference-form prefixes to achieve such tasks. However, training prefixes consumes large computational resources and lacks interpretability. Additionally, learning various relational and inferential knowledge inefficiently exploits the connections between tasks. Therefore, we first propose a method for Reasoning-Oriented Locating and Editing (ROLE), which locates and edits the key modules of the language model for reasoning about event relations, enhancing interpretability and also resource-efficiently optimizing the reasoning ability. Subsequently, we propose a method for Analogy-Based Locating and Editing (ABLE), which efficiently exploits the similarities and differences between tasks to optimize the zero-shot reasoning capability. Experimental results show that ROLE improves interpretability and reasoning performance with reduced computational cost. ABLE achieves SOTA results in zero-shot reasoning.