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Ziteng Wang

Publications and source records attributed to Ziteng Wang.

At least 19 recordsLinked to original sources
arXiv2026

Evidence for the binary nature of the long-period radio transient ASKAP/DART J1832-0911

Long-period transients are a class of periodic pulsed radio source repeating on the minute to hour timescale. Recently, an increasing number of them are being identified as binary systems, specifically white dwarfs with low-mass main-sequence companions. In this work we analyse the most luminous long-period transient discovered to date, ASKAP/DART J1832-0911, with two years of radio data, and propose that it, too, may be a white dwarf system, although in a far more compact orbit than the aforementioned. The pulses are composed of quasi-periodic components which evolve in a systematic way over days and months. The source is highly linearly or elliptically polarised and its brightness enabled very high signal-to-noise measurement of the time-resolved Faraday rotation measure, which was found to vary across pulse phase. The linear polarisation position angle, circular polarised fraction, and spectral index also varied systematically in ways not typical of pulsars and magnetars. We show that an ultra-compact asynchronous polar explains much of the phenomenology of ASKAP/DART J1832-0911, in particular the evolution of the pulse morphology, rotation measure variation, and periodic X-ray emission, although we cannot conclusively prove a binary nature. However, our model makes testable predictions.

astro-ph.HE↗
arXiv2026

Two new highly scattered fast radio bursts: evidence for scatter broadening by the circumsource medium

We found two highly scattered Fast Radio Bursts (FRBs) during commissioning of the Commensal Realtime ASKAP Fast Transient COherent (CRACO) backend. FRB 240210D and FRB 240312D have scattering times of $34\pm6$ and $300\pm48$ ms, respectively, when scaled to 1 GHz. FRB 240312D originates near a spiral arm of a face-on galaxy at a redshift of only 0.05. Scintillation from a Milky Way screen constrains the distance of the scattering screen to $\sim 10$ pc from the source. FRB 240312D is therefore the first highly scattered FRB where scattering screens in the host galaxy centre, a background galaxy, or intervening structures can all be excluded, leaving only the circumsource medium. Integral field spectroscopy of the host reveals a Milky Way-like galaxy with a star-formation region at the FRB position. We find refractive scattering in a pulsar wind nebula as the most likely scattering origin. However, the explanation is not completely satisfactory as it requires a fine-tuned orientation. Hence, additional theoretical studies under different FRB progenitor models are needed. From the two FRBs, we calculate a total rate of $R_\mathrm{tot}=210^{+460}_{-180}\,\mathrm{events}\,\mathrm{sky}^{-1}\mathrm{day}^{-1}$ with durations between 55.2 ms and 1 s and above a fluence of 9 Jy ms consistent with the rate of shorter FRBs. This elevated rate suggests that the strong scattering seen in other FRBs likewise does not arise from chance-aligned sightlines, but is instead causally linked to the FRB sources.

astro-ph.HE↗
arXiv2026

H+ Embedding: Harmonizing Global and Token-Level Retrieval with Context-Dependent Phrases

Terminology-intensive retrieval, especially in medical settings, depends on preserving multi-word entities, abbreviations, numerical constraints, and compositional concepts. However, existing representations lie at two extremes: single-vector retrievers often over-compress local relevance signals, while token-level late interaction retains every tokenizer subword at substantial indexing, storage, and scoring cost. This mismatch raises a natural question: can context-dependent phrases provide a useful retrieval unit between global vectors and tokens? We introduce H+ Embedding, a unified multi-granularity retriever that predicts variable-length phrase partitions, preserves uncovered tokens as singletons, and applies importance-guided unit selection with weighted MaxSim interaction. Across 16 scientific, medical, and bilingual tasks, its phrase retrieval branch exceeds the global retrieval branch by 6.91 macro nDCG@10. It also nearly matches Token while using 13.7% fewer document vectors and outperforms content-independent grouping rules under moderate vector budgets. Context-dependent phrase interaction therefore provides an intermediate quality-cost point between global compression and token-level interaction for practical retrieval systems.

cs.AI↗
arXiv2026

FRB20250613A: a remarkable repeating FRB with apparent millisecond-timescale scattering variations

FRB20250613A is a repeating FRB discovered by the Australian SKA Pathfinder and localised to a low-metallicity dwarf galaxy at a redshift of $z = 0.0987 \pm 0.0001$. FRB 20250613A exhibits a plethora of exotic features that likely overlay the imprint of the circum-burst environment on some intrinsic features of the source. Here we perform a comprehensive analysis of bursts detected by ASKAP, MeerKAT, and the Murriyang Parkes radio telescopes. Bursts during the MeerKAT epoch show a large apparent variance in scattering on timescales of minutes to hours. Polarimetric analysis of the full sample shows spectral depolarisation with variability on timescales of days and changes in rotation measure of $\sim$ 300 rad m$^{-2}$ over days to months. This suggests a highly turbulent magneto-ionised environment. We find significant preference for separations of $\sim$6.8$\pm$0.8 ms in multi-component bursts that we suggest is likely intrinsic to the burst emission mechanism. Finally, we find that a subset of bursts exhibit variations in these propagation effects on burst components separated by just milliseconds, that are difficult to explain by changing sightlines, but plausibly due to non-linear plasma effects in the circum-burst environment caused by the high field strength of the FRB emission. These properties, which demand a nearby turbulent screen of material, are all consistent with the FRB progenitor being embedded in the dense stellar wind of a Be star binary companion, objects which are relatively plentiful in low-mass and low-metallicity galaxies like the FRB20250613A host.

astro-ph.HE↗
arXiv2026

Long-Period Transients as a new frontier in time-domain astronomy

Long-period radio transients (LPTs) are relatively new astrophysical objects occupying the observational gap between canonical pulsars and slowly varying radio variables. They emit coherent, highly polarised radio bursts with periods from minutes to hours, often exhibiting millisecond- to minute-scale substructure, short duty cycles, and broadband emission. Their radio luminosities typically exceed what rotational energy alone can power, necessitating alternative energy sources such as magnetic field decay, magnetospheric reconnection, or binary interactions. As multiwavelength counterparts in X-ray, optical, and infrared bands provide key constraints on progenitors and emission mechanisms, observational evidence points to a diverse progenitor population including ultra-long period magnetars and magnetic white dwarf binaries. Fast imaging surveys with SKAO and its precursors are opening a new discovery space, enabling systematic detection, high-cadence monitoring, and detailed follow-up. Despite the challenges of high extinction, intermittent emission, and computational demands for discovery, the expanding LPT population provides a new laboratory for studying coherent radio emission in a range of compact-object systems, from pulsars to white dwarf binaries. This diversity allows us to test how the emission processes depend on magnetic field strength, rotation, and binary interaction.

astro-ph.HE↗
arXiv2026

Periodic Radio and X-ray Emission from an Accreting White Dwarf Binary

Long period radio transients (LPTs) are coherent bursts of polarised radio emission that repeat periodically on timescales of minutes to hours. Little is known about the physical origins of these systems. Astronomers have proposed magnetars that rotate slowly and white dwarfs that rapidly orbit with a companion star as potential explanations. While several recent examples appear to support the latter hypothesis, the mechanism generating these bright radio pulses remains poorly understood. Here we report our discovery and classification of the LPT ASKAP J174508.9-505149 as an accreting white dwarf binary. This object has a ~1.3h spectroscopic orbital period and exhibits orbitally-modulated X-ray emission and radio bursts. These elliptically polarised radio bursts drift in emission frequency, potentially due to a longer beat period, and turn off for several hours at a time. Some long period radio transients have been associated with non-interacting white dwarf binaries. We have spectroscopically confirmed this system as an accreting cataclysmic variable, identified through characteristic optical emission lines and an ongoing X-ray outburst. Our results strengthen the link between at least some long period radio transients and white dwarf binaries.

astro-ph.HE↗
arXiv2026

Unlocking Multi-Site Clinical Data: A Federated Approach to Privacy-First Child Autism Behavior Analysis

Automated recognition of autistic behaviors in children is essential for early intervention and objective clinical assessment. However, the development of robust models is severely hindered by strict privacy regulations (e.g., HIPAA) and the sensitive nature of pediatric data, which prevents the centralized aggregation of clinical datasets. Furthermore, individual clinical sites often suffer from data scarcity, making it difficult to learn generalized behavior patterns or tailor models to site-specific patient distributions. To address these challenges, we observe that Federated Learning (FL) can decouple model training from raw data access, enabling multi-site collaboration while maintaining strict data residency. In this paper, we present the first study exploring Federated Learning for pose-based child autism behavior recognition. Our framework employs a two-layer privacy protection mechanism: utilizing human skeletal abstraction to remove identifiable visual information from the raw RGB videos and FL to ensure sensitive pose data remains within the clinic. This approach leverages distributed clinical data to learn generalized representations while providing the flexibility for site-specific personalization. Experimental results on the MMASD benchmark demonstrate that our framework achieves high recognition accuracy, outperforming traditional federated baselines and providing a robust, privacy-first solution for multi-site clinical analysis.

cs.CV↗
arXiv2026

Fractal hierarchy enables exponential scaling of topological boundary states

Exponential growth describes an extremely rapid process ubiquitous across mathematics and diverse physical, biological, and technological systems. Here, we introduce a class of fractal-inspired lattices that combine long-range periodic order with self-similar hierarchy, establishing a structural motif that enables exponential scaling of topological boundary states. We demonstrate this phenomenon in (i) a quasi-one-dimensional lattice chain constructed from Koch-curve unit cells and (ii) a two-dimensional periodic tiling lattice composed of Sierpinski-gasket unit cells. We show that, for suitable coupling parameters, both the number of topological boundary states $N_{\ell}$ and the number of topological minigaps $M_{\ell}$ grow exponentially with the fractal generation index $\ell$. We find that $N_{\ell}$ is an integer multiple of $M_{\ell}$, with the integer determined by the underlying symmetry. This hierarchical scaling law is captured by multi-topological-phase theory and confirmed experimentally in laser-written photonic lattices. Our results identify fractal hierarchy as a materials architecture principle for controlling boundary-state multiplicity, revealing an interplay between topology, self-similar geometry, and periodic order. More broadly, this work suggests a route to synthetic materials and integrated photonic platforms in which large numbers of robust boundary modes can be engineered within compact architectures.

physics.optics↗
arXiv2026

A Non-Abelian Route to Z2 Non-Hermitian Skin Effects

The non-Hermitian skin effect (NHSE), characterized by extensive boundary accumulation of eigenstates under open boundary conditions, has emerged as a central phenomenon in non-Hermitian physics. Conventionally, the NHSE arises from either non-reciprocal couplings or onsite gain and loss combined with synthetic gauge fields. Existing studies, however, have been largely confined to frameworks with Abelian-coupling, leaving the role of non-Abelian couplings essentially unexplored. Here, we demonstrate that non-Abelian-couplings can generate the NHSE, giving rise to a time-reversal-symmetry-protected Z2 skin effect with pseudospin-dependent boundary localization and dynamical pseudospin separation. Experimentally, we implement a representative four-level model using a programmable topolectrical circuit and directly observe both the predicted NHSE and the boundary-induced pseudospin-inversion reflection. Our work establishes a fundamental link between non-Abelian coupling and non-Hermitian topology, opening new avenues for realizing non-reciprocity-free topological materials and devices.

physics.optics↗
arXiv2026

DEAF: A Benchmark for Diagnostic Evaluation of Acoustic Faithfulness in Audio Language Models

Recent Audio Multimodal Large Language Models (Audio MLLMs) demonstrate impressive performance on speech benchmarks, yet it remains unclear whether these models genuinely process acoustic signals or rely on text-based semantic inference. To systematically study this question, we introduce DEAF (Diagnostic Evaluation of Acoustic Faithfulness), a benchmark of over 2,700 conflict stimuli spanning three acoustic dimensions: emotional prosody, background sounds, and speaker identity. Then, we design a controlled multi-level evaluation framework that progressively increases textual influence, ranging from semantic conflicts in the content to misleading prompts and their combination, allowing us to disentangle content-driven bias from prompt-induced sycophancy. We further introduce diagnostic metrics to quantify model reliance on textual cues over acoustic signals. Our evaluation of seven Audio MLLMs reveals a consistent pattern of text dominance: models are sensitive to acoustic variations, yet predictions are predominantly driven by textual inputs, revealing a gap between high performance on standard speech benchmarks and genuine acoustic understanding.

cs.AI↗
arXiv2026

Discovery of a 36-minute long-period transient ASKAP J142431.2-612611

We report the discovery of a new long-period radio transient, ASKAP J142431.2-612611, with a 36 minute period, identified in the Australian SKA Pathfinder Evolutionary Map of the Universe survey. We detected pulsed emission from ASKAP J142431.2-612611 over a period of eight days during follow-up observations with the Australia Telescope Compact Array, after which the source appears to have switched off. No optical or near-infrared counterpart is detected in archival surveys or in targeted Gemini South FLAMINGOS-2 observations. During its active state, the source exhibits a stable pulse profile with fractional polarisation consistent with 100%, evolving from elliptically to linearly polarised and tracing a well-defined great-circle trajectory on the Poincar\'e sphere. We show that this behaviour is consistent with fully linearly polarised intrinsic emission modified by propagation through a linearly polarised birefringent medium. This discovery expands the known population of long-period transients and highlights the intermittent nature of their activity. We discuss the implications for proposed models of long-period transients and outline future observations needed to constrain the origin of their intermittency and polarisation properties.

astro-ph.HE↗
arXiv2026

TrustMH-Bench: A Comprehensive Benchmark for Evaluating the Trustworthiness of Large Language Models in Mental Health

While Large Language Models (LLMs) demonstrate significant potential in providing accessible mental health support, their practical deployment raises critical trustworthiness concerns due to the domains high-stakes and safety-sensitive nature. Existing evaluation paradigms for general-purpose LLMs fail to capture mental health-specific requirements, highlighting an urgent need to prioritize and enhance their trustworthiness. To address this, we propose TrustMH-Bench, a holistic framework designed to systematically quantify the trustworthiness of mental health LLMs. By establishing a deep mapping from domain-specific norms to quantitative evaluation metrics, TrustMH-Bench evaluates models across eight core pillars: Reliability, Crisis Identification and Escalation, Safety, Fairness, Privacy, Robustness, Anti-sycophancy, and Ethics. We conduct extensive experiments across six general-purpose LLMs and six specialized mental health models. Experimental results indicate that the evaluated models underperform across various trustworthiness dimensions in mental health scenarios, revealing significant deficiencies. Notably, even generally powerful models (e.g., GPT-5.1) fail to maintain consistently high performance across all dimensions. Consequently, systematically improving the trustworthiness of LLMs has become a critical task. Our data and code are released.

cs.CL↗
arXiv2026

Beta Ensembles in the Freezing Regime and Finite Free Convolutions

In the freezing regime where the system size N is fixed and the inverse temperature beta tends to infinity, the eigenvalues of Gaussian beta ensembles converge to zeros of the Nth Hermite polynomial. That law of large numbers has been proved by analyzing the joint density or reading off the random matrix model. This paper studies its dynamical version of this phenomenon. We show that in the freezing regime the eigenvalue processes called beta Dyson Brownian motions converge to deterministic limiting processes which can be written as the finite free convolution of the initial data and the zeros of Hermite polynomials. This result is a counterpart of those in the random matrix regime where N tends to infinity with fixed beta, as well as to the high temperature regime where N tends to infinity while beta N remains bounded. We also establish Gaussian fluctuations around the limit and deal with the Laguerre case.

math.PR↗
arXiv2026

The ASKAP Variables and Slow Transients (VAST) Extragalactic Survey - Data Release 1

The Variables and Slow Transients (VAST) Survey on the Australian SKA Pathfinder (ASKAP) is designed to systematically explore the dynamic radio sky, detecting sources that vary on timescales from minutes to several years. In this paper, we present Data Release 1 of the VAST Extragalactic Survey, which targets slowly evolving synchrotron transients in the southern sky. The observations were carried out between June 2023 and May 2025, comprising 2945 images of 276 fields spanning $\sim 12300\ \mathrm{deg}^2$, observed at 888 MHz with a typical rms sensitivity of 0.24 mJy $\rm{beam}^{-1}$ and 12-20 arcsec resolution. Each field was revisited approximately every two months, yielding 10 or 11 observations per field. The VAST pipeline extracts the light curves for all the observed sources, and additional filters are implemented to improve the reliability of the resulting light curve database. The light curve database contains 0.5 million sources and 6.4 million individual measurements, publicly available through the CSIRO data access portal. An untargeted variability search yields 117 astrophysical variables, including 27 pulsars, 40 radio stars (10 newly detected at radio wavelengths), 44 active galactic nuclei, two optically identified supernovae, one supernova candidate, one brown dwarf, and two sources without multi-wavelength counterparts that are yet to be identified. This data release provides the first large-scale, high-cadence, uniform view of long-term radio variability in the extragalactic sky and lays the groundwork for future population studies of radio transients with ASKAP.

astro-ph.CO↗
arXiv2026

ASKAP J005512.2-255834: A Luminous, Long-Lived Radio Transient at z = 0.1 -- an Orphan Afterglow or an off-nuclear TDE from an IMBH?

We report the discovery of a slowly evolving, extragalactic radio transient, ASKAP J005512.2--255834 (hereafter ASKAP J0055-2558), identified using the Australian SKA Pathfinder in a search for orphan afterglows associated with archival gravitational wave events. Although discovered in this context, there is no evidence that the transient is associated with any known gravitational wave event. Nonetheless, this source exhibits a 20-fold increase in flux density over $<250$ days, and it remains in a declining, detectable state more than 1000 days after the initial detection. Follow-up observations from 0.3 to 9 GHz reveal an evolving spectrum consistent with synchrotron emission. ASKAP J0055-2558 is spatially coincident with a low-mass, star-forming galaxy at redshift $z = 0.116$ ($d_{\rm L}$= 543 Mpc), placing its peak radio luminosity at $\nu L_\nu \sim 10^{39}\,\rm erg\,s^{-1}$. Analysis of its radio light curve, inferred blastwave velocity, energetics, host galaxy properties and the absence of counterparts at other wavelengths suggest that ASKAP J0055-2558 is most consistent with either the late-time phase of an orphan long gamma-ray burst afterglow or a tidal disruption event involving an intermediate-mass black hole spatially offset from the galaxy nucleus. The radio discovery of either of these phenomena is extremely rare, with only a few or no confirmed examples to date.

astro-ph.HE↗
arXiv2026

Topological photonics in one-dimensional settings

Over the past decade, topological photonics has emerged as a vibrant field, attracting significant attention and witnessing remarkable advancements. This growth can be attributed to its fundamental appeal and the unique opportunities it offers for unconventional control of light, promising innovations in next-generation photonic devices. At the heart of topological photonics lies the one-dimensional (1D) SSH model. Originally conceived to elucidate the physics of a molecular chain of polyacetylene, this model has found widespread applications in exploring a wide range of topological phenomena in photonics and beyond. In this chapter, we aim to provide an overview of topological photonics in one-dimensional (1D) settings. After briefly introducing paradigmatic 1D models, including the SSH, Rice-Mele, and AAH models, we review recent advances in experimental studies and applications of topological photonics based on 1D platforms. Our discussion highlights demonstrated examples, such as the nonlinear tuning of topological states in both Hermitian and non-Hermitian photonic SSH lattices, as well as nonlinear harmonic generation and topological lasing in SSH-type photonic microstructures. We further discuss characteristic topological phenomena in other representative 1D settings, including Floquet systems, topological pumping, quasicrystals, and synthetic non-Hermitian systems. Finally, we examine selected examples of two-dimensional (2D) photonic topological crystalline insulators that are closely linked to the SSH model. Towards the end, we summarize the chapter and provide a list of key contributions, together with an outlook on possible future directions in 1D topological photonics. While this review focuses specifically on 1D topological photonics, it is not intended to be comprehensive or exhaustive.

physics.optics↗
arXiv2026

Scaling Text-to-Image Diffusion Transformers with Representation Autoencoders

Representation Autoencoders (RAEs) have shown distinct advantages in diffusion modeling on ImageNet by training in high-dimensional semantic latent spaces. In this work, we investigate whether this framework can scale to large-scale, freeform text-to-image (T2I) generation. We first scale RAE decoders on the frozen representation encoder (SigLIP-2) beyond ImageNet by training on web, synthetic, and text-rendering data, finding that while scale improves general fidelity, targeted data composition is essential for specific domains like text. We then rigorously stress-test the RAE design choices originally proposed for ImageNet. Our analysis reveals that scaling simplifies the framework: while dimension-dependent noise scheduling remains critical, architectural complexities such as wide diffusion heads and noise-augmented decoding offer negligible benefits at scale Building on this simplified framework, we conduct a controlled comparison of RAE against the state-of-the-art FLUX VAE across diffusion transformer scales from 0.5B to 9.8B parameters. RAEs consistently outperform VAEs during pretraining across all model scales. Further, during finetuning on high-quality datasets, VAE-based models catastrophically overfit after 64 epochs, while RAE models remain stable through 256 epochs and achieve consistently better performance. Across all experiments, RAE-based diffusion models demonstrate faster convergence and better generation quality, establishing RAEs as a simpler and stronger foundation than VAEs for large-scale T2I generation. Additionally, because both visual understanding and generation can operate in a shared representation space, the multimodal model can directly reason over generated latents, opening new possibilities for unified models.

cs.CV↗
arXiv2026

V-FAT: Benchmarking Visual Fidelity Against Text-bias

Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated impressive performance on standard visual reasoning benchmarks. However, there is growing concern that these models rely excessively on linguistic shortcuts rather than genuine visual grounding, a phenomenon we term Text Bias. In this paper, we investigate the fundamental tension between visual perception and linguistic priors. We decouple the sources of this bias into two dimensions: Internal Corpus Bias, stemming from statistical correlations in pretraining, and External Instruction Bias, arising from the alignment-induced tendency toward sycophancy. To quantify this effect, we introduce V-FAT (Visual Fidelity Against Text-bias), a diagnostic benchmark comprising 4,026 VQA instances across six semantic domains. V-FAT employs a Three-Level Evaluation Framework that systematically increases the conflict between visual evidence and textual information: (L1) internal bias from atypical images, (L2) external bias from misleading instructions, and (L3) synergistic bias where both coincide. We introduce the Visual Robustness Score (VRS), a metric designed to penalize "lucky" linguistic guesses and reward true visual fidelity. Our evaluation of 12 frontier MLLMs reveals that while models excel in existing benchmarks, they experience significant visual collapse under high linguistic dominance.

cs.CL↗