arXiv preprints from January 1, 2026 through September 27, 2026 — 01:23:53 EST
We investigate the critical behavior of a family of $\mathbb{Z}_2$-symmetric scalar field theories on the Bethe lattice (the tree limit of regular hyperbolic tessellations) using both the non-perturbative Functional Renormalization Group and lattice perturbation theory. The family is indexed by the parameter $ζ\in (0,1]$, which...
We consider the nature of the wave function using the example of a harmonic oscillator. We show that the eigenfunctions $ψ_n{=}z^n$ of the quantum Hamiltonian in the complex Bargmann-Fock-Segal representation with $z\in\mathbb C$ are the coordinates of a classical oscillator with energy $E_n=\hbarωn$, $n=0,1,2,...\,$. They are defined...
Generative AI models, such as score-based diffusion models, have recently advanced the field of computational materials science by enabling the generation of new materials with desired properties. In addition, these models could also be leveraged to reconstruct crystal structures for which partial information is available. One...
Vision language foundation models such as CLIP exhibit impressive zero-shot generalization yet remain vulnerable to spurious correlations across visual and textual modalities. Existing debiasing approaches often address a single modality either visual or textual leading to partial robustness and unstable adaptation under distribution...
Electrochemical creatinine sensors offer great promise towards rapid, reagent-free and point-of-care (POC) kidney-function monitoring. However, challenges related to analyte binding, data reproducibility, sensitivity, fouling and device degradation deter its widespread implementation. Here, we show how a carbon electrode modified with...
In this study, we investigate feature-based 2.5D controlled source marine electromagnetic (mCSEM) data inversion using generative priors. Two-and-half dimensional modeling using finite difference method (FDM) is adopted to compute the response of horizontal electric dipole (HED) excitation. Rather than using a neural network to...
Mixture-of-Experts (MoE) architectures scale large language models efficiently by employing a parametric ``router'' to dispatch tokens to a sparse subset of experts. Typically, this router is trained once and then frozen, rendering routing decisions brittle under distribution shifts. We address this limitation by introducing kNN-MoE,...
Smoking remains the leading cause of preventable mortality worldwide. Adolescents are particularly vulnerable to the development of tobacco addiction due to ongoing brain maturation and susceptibility to social influences, such as exposure to environmental tobacco smoke (ETS). Craving -the strong desire to use drugs -already emerges...
This paper establishes a rigorous spectral framework for the Weighted Weyl Fractional Calculus, designed to model non-local systems exhibiting aging and subjective time scales. By constructing a conjugation map involving a time-dependent weight $ω(t)$ and a scale function $ψ(t)$, we define a new class of fractional operators that...
Deep learning-based methods have revolutionized the field of imaging inverse problems, yielding state-of-the-art performance across various imaging domains. The best performing networks incorporate the imaging operator within the network architecture, typically in the form of deep unrolling. However, in large-scale problems, such as...
Where does what happens happen in a quantum system? The standard textbook formulation of quantum mechanics provides a strange, imprecise and yet successful-in-practice answer to this question. In the struggle to unify our understanding of gravity with quantum theory, though, the textbook answer no longer suffices, and an alternative...
Marine oil spills are urgent environmental hazards that demand rapid and reliable detection to minimise ecological and economic damage. While Synthetic Aperture Radar (SAR) imagery has become a key tool for large-scale oil spill monitoring, most existing detection methods rely on deep learning-based segmentation applied to single SAR...
Accurate identification of protein binding sites is crucial for understanding biomolecular interaction mechanisms and for the rational design of drug targets. Traditional predictive methods often struggle to balance prediction accuracy with computational efficiency when capturing complex spatial conformations. To address this...
Frequency-tunable superconducting transmon qubits are a cornerstone of scalable quantum processors, yet their performance is often degraded by sensitivity to low-frequency flux noise. Here we present a doubly-connected gradiometric transmon (the ``8-mon") that incorporates a nano-airbridge to link its two loops. This design preserves...
Using data samples with a total integrated luminosity of $22.1~\rm fb^{-1}$ at center-of-mass energies between 4.008 and 4.951~GeV collected with the BESIII detector, the cross sections of $e^{+}e^{-}\rightarrow π^{0}π^{0}ψ(3686)$ process are measured. The obtained cross sections are found to be approximately one-half of those of...
RWKV is a modern RNN architecture that approaches the performance of Transformers, with the advantage of processing long contexts at a linear memory cost. However, its sequential computation pattern struggles to efficiently leverage GPU parallelism, which leads to low compute resource utilization. Furthermore, frequent off-chip weight...
We study the quadratic penalty method (QPM) for smooth nonconvex optimization problems with equality constraints. Assuming the constraint violation satisfies the PL condition near the feasible set, we derive sharper worst-case complexity bounds for obtaining approximate first-order KKT points. When the objective and constraints are...
Binaries of supermassive black holes (MBHBs) represent the primary sources of the gravitational wave background (GWB) detectable by Pulsar Timing Arrays (PTAs). The eccentricity with which binaries form in galactic mergers is the key parameter determining their evolutionary timescale from pairing to coalescence. However, accurately...
Understanding the spatio-temporal evolution of radiolytic species created by high-energy electrons in water underpins key applications from radiotherapy and nuclear safety to environmental processing and electron microscopy. Here, using the Manchester Inhomogeneous Radiation Chemistry by Linear Expansions (MIRaCLE) toolkit, we...
The recently-proposed resummation procedure for anti-collinear logarithms in the JIMWLK kernel~\cite{Kovner:2023vsy} is studied in the linear (BFKL) regime in the fixed-coupling approximation. Simple closed form expressions for the resummed momentum space kernel and characteristic function $χ(n,γ)$ are found. We find that the...
The Indian Summer Monsoon (ISM) is a critical climate phenomenon, fundamentally impacting the agriculture, economy, and water security of over a billion people. Traditional long-range forecasting, whether statistical or dynamical, has predominantly focused on predicting a single, spatially-averaged seasonal value, lacking the spatial...
The present paper sketches a framework for solving the wave and Fokker-Planck equations in the ion cyclotron resonance frequency domain fully selfconsistently. It illustrates this can be done by first constructing "building blocks" that are commonly needed by the wave and Fokker-Planck equations, allowing e.g. to account for wave...
The recent asteroseismic observations constitute a great challenge for rotating stellar evolution models, which predict too fast internal rotation rates when only hydrodynamic processes are included. This suggests the absence of one or several unidentified angular momentum transport processes in these models. Transport by large-scale...
Segmenting speech transcripts into thematic sections benefits both downstream processing and users who depend on written text for accessibility. We introduce a novel approach to hierarchical topic segmentation in transcripts, generating multi-level tables of contents that capture both topic and subtopic boundaries. We compare...
The statistical "monomer-based" segment length $b$ and the Kuhn length $l_k$ are central to polymer physics, yet the minimal size required for a truly statistical segment - Gaussian, uncorrelated, and valid as an entropic spring - is not rigorously established. Using atomistic simulations of entangled polyethylene, we re-evaluate...