arXiv preprints from January 1, 2026 through September 29, 2026 — 20:45:19 EST
We develop a model of particle energization and emission from strongly turbulent black-hole coronae. Our local model is based on a set of 2D radiative particle-in-cell simulations with an electron-ion plasma composition, injection and diffusive escape of photons and charged particles, and self-consistent Compton scattering. We show...
In this study, we introduce a sophisticated generative conditional strategy designed to impute missing values within datasets, an area of considerable importance in statistical analysis. Specifically, we initially elucidate the theoretical underpinnings of the Generative Conditional Missing Imputation Networks (GCMI), demonstrating...
Autonomous LLM agents generate multi-step action plans that can fail due to contextual misalignment or structural incoherence. Existing anomaly detection methods are ill-suited for this challenge: mean-pooling embeddings dilutes anomalous steps, while contrastive-only approaches ignore sequential structure. Standard unsupervised...
Assembly theory (AT) introduces causation as a material property and establishes a metrology for objects produced by evolution and selection. The physical scale of causation is quantified by the assembly index, defined as the minimum number of recursive steps necessary to make an object. Observing countable copies of high assembly...
NTRU is one of the important lattice-based post-quantum cryptography methods, offering resistance against quantum computing attacks. However, a drawback of NTRU lies in its relatively low efficiency in generating key pairs. Therefore, this study proposes an NTRU-based key expansion method that enables efficient public key expansion....
Do reasoning models have "Aha!" moments? Prior work suggests that models like DeepSeek-R1-Zero undergo sudden mid-trace realizations that lead to accurate outputs, implying an intrinsic capacity for self-correction. Yet, it remains unclear whether such intrinsic shifts in reasoning strategy actually improve performance. Here, we study...
Long-form video question answering remains challenging for modern vision-language models, which struggle to reason over hour-scale footage without exceeding practical token and compute budgets. Existing systems typically downsample frames or feed dense visual embeddings to large-context language models, trading off temporal coverage...
Continuous electroencephalography (EEG) is routinely used in neurocritical care to monitor seizures and other harmful brain activity, including rhythmic and periodic patterns that are clinically significant. Although deep learning methods have achieved high accuracy in seizure detection, most existing approaches remain...
Ultra-low-dose CT (ULDCT) imaging can greatly reduce patient radiation exposure, but the resulting scans suffer from severe structured and random noise that degrades image quality. To address this challenge, we propose a novel Plug-and-Play model-based iterative reconstruction framework (PnP-MBIR) that integrates a deep convolutional...
Spiking Neural Networks (SNNs) are dynamical systems that operate on spatiotemporal data, yet their learnable parameters are often limited to synaptic weights, contributing little to temporal pattern recognition. Learnable parameters that delay spike times can improve classification performance in temporal tasks, but existing methods...
Let $F$ be a non-Archimedean local field. For any irreducible smooth representation $π$ of $\mathrm{GL}_n(F)$ and a multisegment $\mathfrak m$, we have an operation $D_{\mathfrak m}(π)$ to construct a simple quotient $τ$ of a Bernstein-Zelevinsky derivative of $π$. This article continues the previous one to study the following poset...
We investigate the gamma-ray spectrum in the MeV range arising from electron-positron pair annihilation in fireballs associated with magnetar giant flares (MGFs), motivated by the recent observation of a MeV gamma-ray line feature in a bright gamma-ray burst, GRB~221009A. We develop an analytic model of line emission, demonstrating...
We investigate the strong-field limit of a charged particle in an electromagnetic field as a toy model for general covariant systems, establishing a novel connection between constrained Hamiltonian dynamics and noncommutative geometry. Starting from the action $S=\int dτ\, \dot{x}^i A_i(x)$, which represents the holonomy of the...
Talking head generation creates lifelike avatars from static portraits for virtual communication and content creation. However, current models do not yet convey the feeling of truly interactive communication, often generating one-way responses that lack emotional engagement. We identify two key challenges toward truly interactive...
We aim to evaluate how well the variation of small-scale magnetic fields on the stellar surface can be monitored with time-series observations. Further, we aim to establish to what extent the measured total unsigned magnetic field traces other activity indicators. We measured the total unsigned magnetic field on four young, stars...
We construct in detail the irreducible representations of the BMS group with super rotations in three and four dimensions that have the same rest frame momenta as the massive and massless Poincare point particles. We compare these representations to those of the Poincare group and also to the analogous representations of global BMS....
The adoption of Centralized Radio Access Network (C-RAN) architectures requires fronthaul systems capable of carrying large volumes of radio data while meeting stringent delay and jitter requirements. Ethernet Passive Optical Networks (EPONs) have emerged as a promising fronthaul solution due to their cost efficiency and compatibility...
In this article, we study the mixed fourth moments of Hecke--Maass cusp forms and Eisenstein series with type $(2, 2)$. Under the assumptions of the Generalized Riemann Hypothesis (GRH) and the Generalized Ramanujan Conjecture (GRC), we establish asymptotic formulas for these moments. Our results give an interesting...
Despite the rapid success of Large Vision-Language Models (LVLMs), a persistent challenge is their tendency to generate hallucinated content, undermining reliability in real-world use. Existing training-free methods address hallucinations but face two limitations: (i) they rely on narrow assumptions about hallucination sources, and...
Reliable building height estimation is essential for various urban applications. Spaceborne SAR tomography (TomoSAR) provides weather-independent, side-looking observations that capture facade-level structure, offering a promising alternative to conventional optical methods. However, TomoSAR point clouds often suffer from noise,...
We study the nonleptonic decays of $Ω_{b}\rightarrowΩ_{c} P (V)$ with eight pseudoscalar and vector mesons using the naive factorization approach. We analyze all relevant topologies (the tree-level, color-suppressed, and penguin) of these decays and calculate the decay amplitude for each separately. We determine the decay rates,...
Background: Understanding electronic interactions in protein active sites is fundamental to drug discovery and enzyme engineering, but remains computationally challenging due to exponential scaling of quantum mechanical calculations. Results: We present a quantum-classical hybrid framework for simulating protein fragment electronic...
This paper introduces Interpretability-Guided Bi-objective Optimization (IGBO), a framework that trains interpretable models by incorporating structured domain knowledge via a bi-objective formulation. IGBO encodes feature importance hierarchies as a Directed Acyclic Graph (DAG) via Central Limit Theorem-based construction and uses...
We prove $\ell^p(\mathbb{Z}^n)-$estimates for long $r$-variational seminorm of two families of averages: discrete Birch-Magyar averages, for $r>max\{p,p'\}$ with $p>\frac{2c_{\mathfrak{R}}-2}{2c_{\mathfrak{R}}-3}$ and discrete Hardy-Littlewood type averages over certain algebraic varieties, for $r>max\{p,p'\}$ with $p>1$. Further, we...
We study a reputational cheap-talk environment in which a judge, who is privately and imperfectly informed about a state, must choose between two speakers of unknown reliability. Exactly one speaker is an expert who perfectly observes the state, while the other is a quack with no information. Both speakers seek to be selected, while...