arXiv preprints from January 1, 2026 through October 1, 2026 — 07:06:09 EST
The BiTeX family of polar van der Waals (vdW) semiconductors offers a unique platform for exploring the interplay between polar crystalline structure and nonlinear optical phenomena. Here, we utilize second harmonic generation (SHG) polarimetry to demonstrate giant anisotropic optical nonlinearities in BiTeBr and BiTeI driven by...
Recovering the in-air colours of seafloor from satellite imagery is a challenging task due to the exponential attenuation of light with depth in the water column. In this study, we present DichroGAN, a conditional generative adversarial network (cGAN) designed for this purpose. DichroGAN employs a two-steps simultaneous training:...
This paper proposes a temporal two-grid compact difference (TTCD) scheme for solving the Benjamin-Bona-Mahony-Burgers (BBMB) equation with initial and periodic boundary conditions. The method consists of three main steps: first, solving a nonlinear system on a coarse time grid of size $τ_c$; then obtaining a coarse approximation on...
Cardiovascular diseases, particularly arrhythmias, remain a leading global cause of mortality, necessitating continuous monitoring via the Internet of Medical Things (IoMT). However, state-of-the-art deep learning approaches often impose prohibitive computational overheads, rendering them unsuitable for resource-constrained edge...
The Standard Model of particle physics, though remarkably successful, leaves open several major questions that continue to motivate searches for new phenomena. Multiboson interactions involving the Higgs boson are of special interest as probes of the electroweak Lagrangian where potential new physics may be hiding. In this work, we...
Structural superlubricity (SSL) promises nearly frictionless and wearless sliding, but has until now been considered a special and extreme interfacial phenomenon limited to micro- and nanoscale contacts. Here, we demonstrate robust macroscale SSL within a single sub-millimeter graphite contact. Previously reported near-zero friction...
Mosquitos are the main transmissive agents of arboviral diseases. Manual classification of their neuronal spike patterns is very labor-intensive and expensive. Most available deep learning solutions require fully labeled spike datasets and highly preprocessed neuronal signals. This reduces the feasibility of mass adoption in actual...
Maximum likelihood style estimators possesses a number of ideal characteristics, but require prior identification of the distribution of errors to ensure exact unbiasedness. Independent of the focus of the primary statistical analysis, the estimation of a covariance matrix \(S^{P \times P}\approx Σ^{P \times P}\) must possess a...
We study the formation and collision of one- and two-dimensional (1D and 2D) Gaussian-shaped and flat-top (FT) solitons in the framework of the nonlinear Schrödinger equation with the cubic-quintic nonlinearity and two intersecting potential troughs. We find that Gaussian-Gaussian and Gaussian-FT collisions between the solitons,...
This paper tackles the pressing challenge of preserving semantic meaning in communication systems constrained by limited bandwidth. We introduce a novel reinforcement learning framework that achieves per-dimension unequal error protection via adaptive repetition coding. Central to our approach is a composite semantic distortion metric...
Within a generally covariant Hamiltonian framework of loop quantum gravity (LQG), two black hole models parameterized by a quantum correction $ζ$ have recently been constructed. Using extreme mass-ratio inspirals (EMRIs) as high-precision probes, we investigate the imprints of this LQG deformation in the surrounding spacetime....
Topology forms a cornerstone in modern condensed matter and statistical physics, offering a new framework to classify the phases and phase transitions beyond the traditional Landau paradigm. However, it is widely believed that topological properties are destroyed when the bulk energy gap closes, making it highly nontrivial to consider...
A search for exotic Higgs boson decays H $\to$ $\mathcal{AA}$, with $\mathcal{A}$ $\to$ $γγ$ is presented, using events with a semi-merged topology. One of the hypothetical particles, $\mathcal{A}$, is assumed to decay promptly into a semi-merged diphoton system reconstructed as a single photon-like object, while the other...
We introduce a one-parameter family of intermediate topological pressures for nonautonomous dynamical systems which interpolate between the Pesin-Pitskel topological pressure and the lower and upper capacity pressures. The construction is based on the Carathéodory-Pesin structure in which all admissible strings in a covering satisfy $...
We address two persistent gaps in Emotion Recognition in Conversation: which modeling choices materially affect performance, and how recognition findings connect to interpretable discourse-level patterns. We study both through a systematic investigation on IEMOCAP with cross-dataset validation on MELD. For recognition, we run...
A multi-magnetron microwave source, a metamaterial transmitting antenna, and a large power rectenna array are presented to build a near-field 2.45 GHz microwave power transmission system. The square 1 m2 rectenna array consists of sixteen rectennas with 2048 Schottky diodes for large power microwave rectifying. It receives microwave...
In this paper we study the descriptive complexity of the topological orbit equvalence relation for some Borel classes of Cantor minimal systems. Specifically, we study the Borel class of all Cantor minimal systems with only finitely many ergodic measures, and show that the orbit equivalence for this class is Borel bireducible with the...
Synchronization control in networked dynamical systems requires regulating not only whether coherence is achieved, but also when and to what extent it emerges. We propose a physics-informed neural network (PINN) framework for continuous-time synchronization regulation, in which system trajectories and control inputs are jointly...
This paper aims to investigate a Harnack inequality for non-negative solutions of the normalized infinity Laplacian with nonlinear absorption and gradient terms. More specifically, we establish a Harnack inequality for non-negative viscosity solutions of the PDE $Δ_\infty^Nu=f(u)+g(u)|Du|^q$, where $0\le q\le 1$, and for a large class...
Chemical reaction networks are a widely accepted modeling framework for diverse science phenomena stemming from all disciplines of science, such as biochemistry, ecology, epidemiology, social and political science. In this paper we prove that every first order endotactic stochastic mass-action reaction system (SMART) is essential...
Objective: Develop and evaluate machine learning (ML) models for predicting incident liver cirrhosis (LC) one and two years prior to diagnosis using routinely collected electronic health record (EHR) data and benchmark their performance against the FIB-4 and APRI clinical scores. Methods: We conducted a retrospective cohort study...
Thermo-optic (TO) control is crucial for thin-film lithium niobate (TFLN) photonic integrated circuits (PICs), offering a simple and practical method for low-frequency and DC tuning while remaining compatible with high-frequency electro-optic (EO) modulation. In x-cut TFLN, the TO response is inherently anisotropic, depending on both...
We study first-return statistics for photons undergoing three-dimensional Henyey-Greenstein scattering in a semi-infinite medium. In previous work, we showed that one-dimensional first-passage probabilities can be expanded using Catalan and Motzkin generating functions. Extending this framework to three dimensions requires introducing...
Forecasting high-dimensional spatiotemporal systems remains computationally challenging for recurrent neural networks (RNNs) and long short-term memory (LSTM) models due to gradient-based training and memory bottlenecks. Reservoir Computing (RC) mitigates these challenges by replacing backpropagation with fixed recurrent layers and a...
This work explores the relationship between sensing accuracy and precoding coefficients for edge artificial intelligence (AI) inference in integrated sensing, communication and computation (ISCC) networks. We start by constructing a system model of an over-the-air-empowered ISCC network for edge AI inference, involving distributed...