April 2026 arXiv papers — page 21

Ian Anderson, Agham Posadas, Alexander A. Demkov, Ruochen Lu

The growing number of wireless communication bands has driven demand for compact, low-loss, and frequency adjustable RF filtering. Tunable acoustic resonators are well suited to address these needs, offering a path toward reconfigurable front ends with reduced component count. In this work, we extend upon previous conference results to investigate epitaxial

Salvatore Tringali, Kerou Wen

If $H$ is a numerical semigroup (that is, a cofinite subset of the non-negative integers closed under addition), then the non-empty subsets of $H$ form a semigroup $\mathcal P(H)$ under the sumset operation induced by addition in $H$. Moreover, if $0 \in H$, then $\mathcal P(H)$ is a monoid with identity element $\{0\}$, and the family $\mathcal P_0(H)$ of a

Kean Chen, Qisheng Wang, Zhicheng Zhang

We consider the problem of quantum channel certification to unitary, where one is given access to an unknown $d$-dimensional channel $\mathcal{E}$, and wants to test whether $\mathcal{E}$ is equal to a target unitary channel or is $\varepsilon$-far from it in the diamond norm. We present optimal quantum algorithms for this problem, settling the query complex

J. E. Schöll, C. P. Dullemond, C. Dominik

Context: During the first stages of dust coagulation in protoplanetary disks, the dust aggregates are expected to have a high degree of porosity. Most models of dust growth, however, do not take this into account. The reason for this is the technical complexity of this problem. Furthermore, the coagulation/fragmentation kernel for colliding porous or fractal

Ram Kumar, K. E. Avers, V. Saini, D. S. Sokratov

We report a comprehensive investigation of the anisotropic magnetism and magnetic field-induced transitions in single crystals of the orthorhombic system TbAlGe, a member of the topological RAlGe (R = rare-earth) family with the highest ordering temeprature in the RAlX (X = Si, Ge) series. With a single rare earth site with triangular coordination in its Cmc

Roberto Bonamico, Josef Hanuš, Marco Delbo

Near-Earth asteroid (469219) Kamo'oalewa is an Earth quasi-satellite, temporarily trapped in a 1:1 orbital resonance with our planet. Despite its dynamical relevance and the hypothesis that it may be a lunar ejecta fragment, its physical properties are still poorly constrained. In particular, no reliable models of its shape and spin state have been publi

Turgut Yilmaz, Yi Sheng Ng, Muhammad Awais Fiaz, Anil Rajapitamahuni

Surface confined electronic states provide a fertile ground for discovering emergent phenomena that have no counterpart in the bulk, offering new routes to manipulate correlations, symmetry breaking, and dimensionality at the atomic scale. Here, we show that charge density wave (CDW) symmetry breaking can yield a surface states in 1T-TiSe2. Micro angle resol

Kayla Fallon, Reshma Peremadathil-Pradeep, Christopher E. A. Barker, Zoey Tumbleson

Magnetic skyrmions are topologically protected spin textures that can act as reconfigurable nanoscale information carriers. In synthetic antiferromagnets (SAFs), interlayer exchange coupling offers an additional control parameter beyond the interfacial Dzyaloshinskii-Moriya interaction (DMI) and magnetic anisotropy. Here, we engineer a SAF composed of two ch

C. Lim, F. Ballester, A. Kar, M. Alkorta

Kagome materials are known for hosting emergent quantum phenomena driven by the interaction between different lattice, charge and spin orders. Here, we present a detailed angle resolved photoemission (ARPES), density functional theory (DFT) and x-ray magnetic circular dichroism (XMCD) study of the electronic and magnetic structure of $R$Ti$_3$Bi$_4$ ($R$ = N

Claudio Del Sole, Antonio Lijoi, Igor Prünster

Competing risks occur in survival analysis when multiple causes of death are present. They play a prominent role in several domains extending beyond biostatistics to encompass epidemiology, actuarial sciences, and reliability theory. This paper adopts a multi-state modeling framework to competing risks. We introduce a class of flexible nonparametric priors,

Marcus V. S. Bonança, Sebastian Deffner, Gert-Ludwig Ingold

This article presents a brief account of Amir O. Caldeira's contributions to the theory of quantum Brownian motion. Motivated by its importance, we outline the description of Brownian motion in the quantum regime following Caldeira's first works. In this context, we particularly highlight the effect of dissipation on the tunneling rate out of a metas

Yannick Mvondo-She

We investigate the structure of logarithmic modes in critical topologically massive gravity (CTMG) at the chiral point $μ\ell=1$ from the perspective of analytic continuation and monodromy. Starting from the degeneration of massive and left-moving graviton modes, we construct the logarithmic mode as a derivative in parameter space and show that it acquires a

Ahmet Tekden, Dimitrios Kanoulas, Aude Billard, Yasemin Bekiroglu

Dynamical systems (DS) methods for Learning-from-Demonstration (LfD) provide stable, continuous policies from few demonstrations. First-order dynamical systems (DS) are effective for many point-to-point and periodic tasks, as long as a unique velocity is defined for each state. For tasks with intersections (e.g., drawing an "8"), extensions such as s

Xiaoyu Wang, Miriam Marqués, Sergio Gómez, Francesc Serratosa

We develop a machine-learning framework to predict the electron localization function (ELF) of pure, dense hydrogen directly from atomic geometry, bypassing explicit electronic-structure calculations. Trained on first-principles data spanning multiple pressure regimes in dense fluid hydrogen, the model achieves high accuracy ($R^2 > 0.99$) and faithfully rep

Mounir Abdkrimi, Olivier Rossetto, Olivier Bourrion, Christophe Hoarau

The CONCERTO millimeter-wave spectral-imaging instrument was deployed on the Atacama Pathfinder EXperiment (APEX), where it acquired science data between April 2021 and May 2023. The instrument features two focal-plane arrays, each composed of 2400 Microwave Kinetic Inductance Detectors (MKIDs). Each array is divided into six feedlines containing 400 MKIDs e

Ajay Dev, Martin Meyer, Simon P. Driver, Jonghwan Rhee

We investigate the relation between neutral atomic hydrogen (HI) and dark matter halo mass (HIHM) using observations from the Deep Investigation of Neutral Gas Origins (DINGO) pilot survey 100h data, combined with spectroscopic data from the Galaxy and Mass Assembly (GAMA) survey and photometric data from the Wide Area VISTA Extragalactic Survey (WAVES) phot

Christian Amor, Adrián Corrochano, Giovanni Soligo, Soledad Le Clainche

The addition of a small amount of long-chain polymers confers viscoelastic properties to Newtonian flows. The resulting non-Newtonian solution now exhibits different dynamics, such as enhanced mixing at low Reynolds, where elastic instabilities can trigger elastic turbulence even though inertial turbulence is absent. Here, we study this phenomenon in viscoel

Daniel F. Calero-Osorio, Paul W. Ayers

We propose a method to solve the Schrödinger equation for systems with static/strong electron correlation using Hamiltonian transformations. Building on our previous work on seniority-zero canonical transformation theory, which seeks a unitary transformation that maps the Hamiltonian into the seniority-zero space, this method presents an alternative way of e

Tomomi Tateishi, Akihito Kato, Alexander S. Ovchinnikov, Jun-ichiro Kishine

We present a microscopic theory of chirality-induced orbital selectivity (CIOS) in helical crystals, in which truly chiral phonons selectively transfer angular momentum to electronic orbital degrees of freedom. For a threefold helical crystal with line-group symmetry $L3_1$, we show that phonon-induced local rotations generate a rotational electron-phonon in

Bikram Pal

We study conductance fluctuations in random resistor networks with hyperuniform bond disorder, where the fluctuations of the number of bonds present in a test volume $V$ scale as $V^{-a}$ with $a > 1/2$. Since small changes in the concentration of bonds present in a local region give rise to a proportionate increase in the locally averaged conductance, one m

Jean-Marc Huré

We report the closed-form expression for Hill's surfaces in the circular restricted three-body problem. The solution $ϕ(r,θ)$, derived in the primary-centric spherical coordinate system, is deduced from a cubic equation delivering at most two roots on each side of a separatrix. The famous patterns (tadpole, horseshoe and peanut shapes, Roche lobes and Hi

Istvan Horvath, Zsolt Bagoly, Jon Hakkila, Lajos G. Balazs

In the past few decades, large universal structures have been found that challenge the homogeneity and isotropy expected in standard cosmological models. This study examines burst clustering in both galactic hemispheres using a recently developed methodology, using spheres in 3D space for testing regularities. Using our new method in both hemisphere we find

Md Aminur Hossain, Ayush V. Patel, Biplab Banerjee

Hybrid quantum-classical models offer a promising route for learning from complex data; however, their application to multi-band remote sensing imagery often relies on generic, data-agnostic quantum circuits that fail to account for channel-specific statistical variability. In this work, we propose a data-driven framework that maps band-level statistics such

Mikhail Itskov

In a previous paper \cite{Itskov-MoSM} we presented a hyperelastic isotropic material model whose stress-strain response is nonlinear even at infinitesimal deformations and cannot thus be linearized. As a result values of Poisson's ratio greater than one half were obtained. In this contribution, we further propose an isotropic strain energy function whic

Willian Carvalho, A. C. Lehum, J. R. Nascimento, A. Yu. Petrov

We formulate a renormalizable complex extension of the bumblebee theory in which the bumblebee field is promoted to a complex one and coupled to an Abelian gauge sector. Besides the minimal gauge covariant interaction, the model includes a longitudinal kinetic term controlled by a dimensionless parameter $g_l$ and a non-minimal magnetic-type coupling $g_m$ b

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $(10\,087 \pm 44) \times 10^6$ $J/ψ$ events collected with the BESIII detector, we perform the first amplitude analysis of the process $J/ψ\toγηπ^0$. The decay is dominated by the intermediate processes $J/ψ\toπ^0 b_1(1235)^0 \toγηπ^0$, $J/ψ\toπ^{0}ρ(1450)^0 \toγηπ^0$ and $J/ψ\toηh_1(1170) \toγηπ^0$. Contributions from $J/ψ\toγa_0(980)^0\toγηπ^0$, $J/ψ

Eric R. Bittner

We formulate a geometric framework for quasistatic thermodynamics in open quantum systems by parameterizing the dynamics on a control manifold. In the quasistatic limit, the system follows a manifold of stationary states, and the work performed over a cycle is given by the flux of a curvature two-form, $W \sim \int Ω$, defined by the parametric response of t

Andrey Babichev, Mikhail Bobrov, Alexey Vasilev, Sergey Blokhin

High-quality planar cavities with low-absorption mirrors based on $Al_{0.2}Ga_{0.8}As/Al_{0.9}Ga_{0.1}As$ layers demonstrate continuous wave lasing at a wavelength of 956 nm. At 300 K, the threshold power density and quality-factor at the threshold are (4.2$\pm$0.3) $kW/cm^2$ and (6800$\pm$220). Increasing the pump level above two thresholds lead to an enlar

Antonio Franchi, Chiara Gabellieri

We present a robotics-oriented, coordinate-free formulation of inverse flight dynamics for fixed-wing aircraft on SO(3). Translational force balance is written in the world frame and rotational dynamics in the body frame; aerodynamic directions (drag, lift, side) are defined geometrically, avoiding local attitude coordinates. Enforcing coordinated flight (no

Toshiki Kondo, Mamoru Okamoto

We consider the Cauchy problem for quadratic derivative fractional nonlinear Schrödinger equations on $\mathbb{R}$ or $\mathbb{T}$. We determine the sharp exponents of the fractional derivatives for which the Cauchy problem is well-posed in the Sobolev space. Thanks to the global well-posedness result established by Nakanishi and Wang (2025), we can expand t

Anna N. Morozovska, Eugene A. Eliseev, Sergei V. Kalinin, Long-Qing Chen

Heterogeneous nucleation from defects dominates the electric field required for polarization switching of ferroelectrics. Here, we consider the switching of a nominally non-switchable polar thin film of AlN due to the proximity effect arising from embedded ferroelectric nanoclusters of Al1-xScxN. Using a Landau-Ginzburg-Devonshire thermodynamic approach and

Gi-Chol Cho, Chikako Idegawa, Chiaki Nose

We study a two Higgs doublet model extended by a complex singlet scalar, in which the imaginary part of the singlet serves as a dark matter (DM) candidate. In this model, degenerate masses of the three neutral Higgs bosons are crucial for achieving consistency with current constraints from DM direct-detection experiments and Higgs searches. This is called th

Gourab Roy, Ekta Kushwaha, Mohit Kumar, Sayan Ghosh

Double perovskites containing 4d--4f interactions provide a platform to study complex magnetic phenomena in correlated systems. Here, we investigate the magnetic ground state and quasiparticle excitations of the fascinating double perovskite system, Ba$_2$DyRuO$_6$, through Time of flight (TOF) neutron diffraction (TOF), inelastic neutron scattering (INS), a

Roey Shafran, Ron Ziv, Mordechai Segev

Photonic quantum technologies utilize various degrees of freedom (DOFs) of light, such as polarization, frequency, and spatial modes, to encode quantum information. In the effort of further improving channel capacity of quantum communication, and for increasing the complexity of available quantum operations, high-dimensional and hyperentangled states are now

Shengkun Cui, Rahul Krishna, Saurabh Jha, Ravishankar K. Iyer

Unresolved production cloud incidents cost an average of over $2M per hour. This paper introduces PRAXIS, an orchestrator that manages and deploys an agentic workflow for diagnosing code- and configuration-caused cloud incidents. PRAXIS employs an LLM-driven structured traversal over two types of graph: (1) a service dependency graph (SDG) that captures micr

Yuhang Liu, Fengpeng An, Guang Luo, Wei Wang

Discrimination of fast neutrons, thermal neutrons, and $γ$ rays in mixed radiation fields is important for radiation monitoring, reactor-related measurements, and background suppression in nuclear experiments. In this work, we investigate a compact plastic-scintillator sensor composed of EJ276 or EJ200 optically coupled to an EJ426 thermal neutron screen and

Shubhankar Paul, Atsutoshi Ikeda, Hisakazu Matsuki, Giordano Mattoni

The magnetic nature of the altermagnet candidate RuO$_2$ remains under debate. It has been recently shown from quantum oscillations and angle-resolved photoemission spectroscopy (ARPES) that the high-quality RuO$_2$ bulk single crystal is a paramagnetic metal. Here we report the specific heat and magnetic susceptibility in ultra-clean RuO$_2$ single crystals

Evan C. Mayer, Ian N. Lowe, Daniel P. Marrone, James J. Bock

The spatial sensitivity pattern of millimeter-wavelength receivers is an important diagnostic of performance and is affected by the alignment of coupling optics. Characterization can be challenging in the field, particularly in the decentered and tightly packed optical configurations that are employed for many astronomical millimeter-wave cameras. In this pa

Paulin Aubert, Etienne Chevalier, Vathana Ly Vath

This paper develops a model for option market making in which the hedging activity of the market maker generates price impact on the underlying asset. The option order flow is modeled by Cox processes, with intensities depending on the state of the underlying and on the market maker's quoted prices. The resulting dynamics combine stochastic option demand

Tommaso Rondini, Gregorio Berselli, Mirko Degli Esposti, Armando Bazzani

Power-law distributions are widely recognized in complex systems physics as indicative of underlying complexity in interaction networks and critical macroscopic behavior. Previous studies, notably those of Newman and others, have emphasized the importance of network structure and dynamics in understanding the emergence of such statistical patterns and predic

D. Castelão, I. Tereno

The standard Lambda cold dark matter ($Λ$CDM) paradigm of the physical Universe suffers from well-known conceptual problems and is challenged by observational data. Alternative models exist in the literature, both phenomenological and physically motivated, but many of them suffer from similar or new problems. We propose a method to mechanically generate alte

Cornelius J. Bauer, Frank Schneider, Ida D. Göbel, Hans Oppitz

Introduction: Real-time dosimetry of surface doses in electron beams has not been widely established yet. Plastic scintillation detectors (PSD) promise high spatial resolution and real-time dosimetry with minimum perturbation of the radiation field. This study characterizes a novel PSD in an electron beam to determine its suitability for in vivo dosimetry. M

Josep Plana-Riu, F. Xavier Trias, Àdel Alsalti-Baldellou, Xavier Álvarez-Farré

Computational Fluid Dynamics (CFD) simulations are often constrained by the memory-bound nature of sparse matrix-vector operations, which eventually limits performance on modern high-performance computing (HPC) systems. This work introduces a novel approach to increase arithmetic intensity in CFD by leveraging repeated matrix block structures. The method tra

Aryabrat Mahapatra, Adarsh Pandey, Pritam Banerjee, Tapobrata Sarkar

We perform a suite of numerical simulations of tidal disruption events, using smoothed particle hydrodynamics, for a close binary system consisting of two low-mass white dwarfs, and an intermediate mass non-spinning black hole. The binary components are considered to be detached and on the same plane with the black hole. Our results quantify how the outcomes

Sean Cox, Jonathan Feigert, Mark Kamsma, Marcos Mazari-Armida

We characterise when the pure monomorphisms in a presheaf category $\mathbf{Set}^\mathcal{C}$ are cofibrantly generated in terms of the category $\mathcal{C}$. In particular, when $\mathcal{C}$ is a monoid $S$ this characterises cofibrant generation of pure monomorphisms between sets with an $S$-action in terms of $S$: this happens if and only if for all $a,

Mohsen Soltanifar

This survey synthesizes the principal descriptive set-theoretic perspectives on deterministic Cantor sets on the real line and charts directions for future study. After recounting their historical genesis and compiling an up-to-date taxonomy, we review the Borel hierarchy and four hierarchically ordered representations-general, nested, iterated-function-syst

Tim Zolkin, Sergei Nagaitsev, Ivan Morozov, Sergei Kladov

We present a perturbative method for constructing approximate invariants of motion directly from the equations of discrete-time symplectic systems. This framework offers a natural nonlinear extension of the classic Courant-Snyder (CS) theory for systems with one degree of freedom -- a foundational cornerstone in accelerator physics now spanning seven decades

Somadutta Bhatta, Aman Dimri, Jiangyong Jia

Radial flow, a key collective phenomenon in heavy-ion collisions, manifests itself through event-by-event fluctuations of transverse-momentum ($p_{\mathrm{T}}$) spectra. The $p_{\mathrm{T}}$-differential radial flow observable, $v_0(p_{\mathrm{T}})$, was introduced to quantify local spectral-shape fluctuations, but it is unavoidably influenced by global mult

Enhua Xu, William Dawson, Himadri Pathak, Takahito Nakajima

Selected configuration interaction (SCI) methods are effective for treating strongly correlated electronic systems, yet their scalability has long been limited by implementations that replicate the configuration interaction (CI) vector across processes, leading to severe memory bottlenecks. Here, we present a fully distributed diagonalization framework tailo

Marjan Rahimi Nezhad, Fatemeh Taghavi-Shahri, Kurosh Javidan

This paper investigates the influence of heavy-quark momentum on their interaction rate and the resulting drag coefficient in a quark-gluon plasma. To go beyond simplified treatments, we introduce a phenomenological extension of the drag coefficient by expressing the energy loss coefficients as polynomial expansions of momentum, thereby providing a flexible

Ziwen Wang, Li Lin Yang

We present an interesting study of Feynman integral reduction that does not employ integration-by-parts identities. Our approach proceeds by studying the equivalence relations of integral contours in the Feynman parameterization. We find that the integration contour can take a more general form than that given by the Cheng-Wu theorem. We apply this idea to o

Athanasios Sourmelidis

We improve upon an Omega result due to Soundararajan with respect to general trigonometric polynomials having positive Fourier coefficients. Instead of Dirichlet's approximation theorem we employ the resonance method and this leads to better extreme results in lattice point problems such as Dirichlet's divisor problem and Gauss' circle problem. M

Chris Williams

Let $F$ be a number field, and $π$ a regular algebraic cuspidal automorphic representation of $\mathrm{GL}_N(\mathbb{A}_F)$ of symplectic type. When $π$ is spherical at all primes $\mathfrak{p}|p$, we construct a $p$-adic $L$-function attached to any regular non-critical spin $p$-refinement $\tildeπ$ of $π$ to $Q$-parahoric level, where $Q$ is the $(n,n)$-pa

Jason Wu, Shir-Kang Scott Jin, Yuyang Yuan, Maggie Wigness

Multimodal deep neural networks deployed in realistic environments must contend with runtime variations: changes in modality quality, overall input complexity, and available platform resources. Current networks struggle with such fluctuations -- adaptive networks cannot adhere to a strict compute budget, controller-based networks neglect to consider input co

Wonjun Seo

This paper investigates the asymptotics of eigenstructure of sample covariance matrix under the spiked covariance matrix model in ultra-high-dimensional settings, where the dimensionality can grow much faster than the sample size with $ p \asymp n^{\alpha} $, $ \alpha > 1 $. We establish the first-order convergence limits of eigenvalue locations and eigenvec

Paul Apisa, Juliet Aygun

We obtain a complete classification of components of strata of holomorphic and meromorphic k-differentials. We show that, when genus is at least two and outside of explicit exceptions when k < 4, there is one primitive nonhyperelliptic component unless k is odd and all singularities have even order, in which case there are two distinguished by their Arf inva

Talha Azfar, Ruimin Ke, Sean He, Cara Wang

Transportation systems such as urban logistics, vehicle routing, and infrastructure planning require solving large-scale combinatorial optimization problems under complex constraints. Problems such as the vehicle routing problem (VRP), traveling salesman problem (TSP), and facility location problem (FLP) involve large discrete search spaces and the need to g

Xingjue Jiang, Seok-Hee Hong, Amyra Meidiana, Xianyuan Zeng

Edge bundling reduces the visual complexity of drawings of large and complex graphs by clustering "compatible" edges. However, it often introduces distortion by bundling "unrelated" edges, resulting in misleading, ambiguous drawings. Moreover, existing edge bundling methods often have high computational complexity. We present new edge bundling methods and fa

Melanie Wille, Dimity Miller, Tobias Fischer, Scarlett Raine

Domain shift, where deviations between training and deployment data distributions degrade model performance, is a key challenge in underwater environments. Existing benchmarks testing performance for underwater domain shift simulate variability through synthetic style transfer. This fails to capture intrinsic scene factors such as visibility, illumination, s

Wenshuo Zhao, Qi Zhu, Xingshan Zeng, Fei Mi

An effective way to scale up test-time compute of large language models is to sample multiple responses and then select the best one, as in Grok Heavy and Gemini Deep Think. Existing selection methods often rely on external reward models, which requires training a strong reward model and introduces additional computation overhead. As an alternative, previous

Ankur Kamboj, Biswadip Dey, Vaibhav Srivastava

We develop a physics-informed learning framework for energy-shaping control of port-Hamiltonian (pH) systems from trajectory data. The proposed approach co-learns a pH system model and an optimal energy-balancing passivity-based controller (EB-PBC) through alternating optimization with policy-aware data collection. At each iteration, the system model is refi

Zhang XueGuang

The scenario of variations in accreting process around central black hole has been widely accepted as the preferred physical origin of changing-look active galactic nuclei (CLAGN), rather than obscuration effects by moving dust clouds. In this manuscript, after analyzing long-term photometric variability in Type-1.8 AGN SDSS J1346+1736 with apparent broad H$

Ting-Wei Li, Sirui Chen, Jiaru Zou, Yingbing Huang

Adapting large language models (LLMs) to a targeted task efficiently and effectively remains a fundamental challenge. Such adaptation often requires iteratively improving the model toward a targeted task, yet collecting high-quality human-labeled data to support this process is costly and difficult to scale. As a result, synthetic data generation has emerged

Abhirami Pillai

Treatment allocation under budget constraints is a central challenge in digital advertising. The standard approach trains an offline uplift model on historical data, then solves a constrained optimization to allocate budget. This fails in cold-start settings where little historical data exists. We propose Budget-Constrained Causal Bandits (BCCB), an online f

Sunny Phan, Andrei Kogan, Jesse Thompson, Trent Johnson

To test the hypothesis that the chiral anomaly is responsible for negative magnetoresitance (MR) in \atn{}, we have studied magnetotransport in strained, epitaxial films of pure \aSn{} and the alloy \aSnGe{} that are in the Dirac semimetal and 3D topological insulator state, respectively. We have observed for both states a negative MR with current either par

Baturay Saglam, Dionysis Kalogerias

Recent work has shown that a model's input word embeddings can serve as effective control variables for steering its behavior toward outputs that satisfy desired properties. However, this has only been demonstrated for pretrained text-completion models on the relatively simple objective of reducing surface-level profanity in short continuations. A natural an

Jerome Lewandowski

The current thermo-industrial civilization is critically dependent on fossil fuel energy sources. An intuitive model capturing the interplay between economic activity, physical power consumption, depletion and energy quality is presented.

Yangchen He, Jessica Kienbaum, Wuzhang Fang, Hongrui Ma

Strain engineering is a powerful tool for tuning the electronic, magnetic, and topological properties of two-dimensional (2D) materials and thin films - particularly at high values of strain (>3%) where many electronic, magnetic, and structural transitions have been predicted. However, most approaches to tuning strain in 2D materials are limited below 1.5%,

Chen Wang, Guoqiang Wu

Let $(M^4, g, f)$ be a four-dimensional complete noncompact gradient shrinking Ricci soliton with the equation $Ric+\nabla^2f= \frac{1}{2}g$. If its scalar curvature is $1$, Cheng-Zhou \cite{Cheng-Zhou} proved that it is a finite quotient of $\mathbb{R}^2\times \mathbb{S}^2$. In this note we present an alternative proof by analyzing the asymptotic geometry a

Jinkai Yang, Kumudu N. Ranasinghe, Lei Kang, Jennifer R. Decker

Random lasing exploits multiple scattering to provide optical feedback without conventional resonant cavities, enabling simplified architectures that are readily integrated into compact photonic platforms such as wearable sensors and lab-on-chip devices. However, the same disorder that enables cavity-free lasing also makes it challenging to control and tune

Michael Arntzenius, Max Willsey

We unify functional and logic programming by treating predicatesas functions equipped with their support: the set of inputs whose output is nonzero. Datalog, for instance, is a language of finitely supported boolean functions. Finite support allows representing functions as input-output tables. Generalizing from boolean functions to other pointed sets neatly

Mohamed Tarek, Pedro Afonso

Nonlinear Mixed Effects models (NLME) models are widely used in pharmacometrics and related fields to analyze hierarchical and longitudinal data. However, as the number of parameters and random effects increases, traditional methods for maximizing the marginal likelihood become computationally expensive. This paper explores the Variational Expectation Maximi

Qiaosen Wang, Shuwen Chai, Chao Gao

Robust uncertainty quantification is increasingly important in modern data analysis and is often formalized under Huber's model, which allows an $\varepsilon$-fraction of arbitrary corruptions. In many experimental sciences, however, the measurement protocol is well controlled, and contamination is more plausibly introduced upstream. Motivated by this noise-

Ethan Shelburne, Stephanie van Willigenburg

A graph is Schur-positive if its chromatic symmetric function expands non-negatively in the Schur basis. We determine a full Schur-positivity classification for complete multipartite graphs by showing that a complete multipartite graph $K_\lambda$ is Schur-positive if and only if either $\lambda_i\in \{1,2\}$ for all $i$ or $\lambda=(3,2^\beta)$ for some $\b

Zichao Wei

Structural generalization in semantic parsing requires systems to apply learned compositional rules to novel structural combinations. Existing approaches either rely on hand-written algebraic rules (AM-Parser) or fail to generalize structurally (Transformer-based models). We present an alternative requiring no hand-written compositional rules, based on a neu

F. Mavoa, M. B. Barry, R. Ndioukane, M. G. Ganiou

In this work, we investigated several inflationary scenarios within the framework of modified $f(Q,\phi)$ gravity with a nonminimal coupling between the scalar field and the nonmetricity scalar. We focused on the impact of the coupling parameter $\xi$ on the inflationary observables, namely the scalar spectral index $n_s$ and the tensor-to-scalar ratio $r$.

Arthur F. Ramos, David B. Hulak, Ruy J. G. B. de Queiroz

Let $K$ be a field with $2 \in K^\times$, and let $H_W$ denote the standard hyperbolic form on $W \oplus W^*$. We study the exterior spinor model $S = \bigwedge V(W)$ together with the spin-to-orthogonal map for this split form, keeping the chosen hyperbolic presentation explicit. The main results determine the field-sensitive part of the split Levi image. I

Dana Zilberberg

We consider the inverse scattering problem for inhomogeneous media of compact support governed by the fractional s-Helmholtz equation, with $0<s<1$, in dimensions $d=1,2,3$. In particular, we study the determination of the support of the inhomogeneity from the far-field pattern of the scattered field generated by plane waves for all incident directions at a

Shiva Ahir, Alex Doboli

Heuristic design upholds modern electronic design automation (EDA) tools, yet crafting effective placement, routing, and scheduling strategies entails substantial expertise. We study how large language models (LLMs) can systematically synthesize reusable optimization heuristics beyond one-shot code generation. We propose RAG-Enhanced Kernel-Based Heuristic S

Twinkll Sisodia

The deployment of large language models (LLMs) in production environments has created an urgent need for observability systems that span the full stack -- from model internals to GPU kernels. Yet existing monitoring approaches address isolated layers of this stack, and no comprehensive analysis has examined how these techniques relate, overlap, or complement

Valentin Tissot-Daguette

We introduce the Local Occupied Volatility (LOV) model that sits between Dupire's local volatility and fully path-dependent dynamics. By design, the LOV model ensures automatic calibration to European vanilla options, while offering the flexibility to capture stylized facts of volatility or fit additional instruments. This is achieved by tuning the occupatio

Prasanna Raut, Chaoyue Zhao, Alexandre Moreira

Power grid infrastructure is an increasingly significant source of wildfire ignitions and poses severe risks to communities in fire-prone regions. Public Safety Power Shutoffs (PSPS) have emerged as a critical operational tool for utilities to mitigate this risk by proactively de-energizing portions of the grid under high-threat conditions. These shutoffs, h

Hemn. G. H, Nzar. R. Abdullah, Vidar Gudmundsson

DFT and AIMD are used to investigate the structural, stability, electronic, thermal, and optical properties of the quasi-2D C2N2O structure. The structure exhibits thermal and energy stability, signifying robustness under ambient conditions, however less dynamical stability is observed. The electronic structure investigation reveals that C2N2O displays semic

Chen Liang, Xirui Jiang, Naihao Deng, Eytan Adar

AI agents operating on user interfaces must understand how interfaces communicate state and feedback to act reliably. As a core communicative modality, animations are increasingly used in modern interfaces, serving critical functional purposes beyond mere aesthetics. Thus, understanding UI animation is essential for comprehensive interface interpretation. Ho

Silvia Noble Anbunesan, Mohamed Abul Hassan, Jinyi Qi, Lisanne Kraft

Accurate intraoperative assessment of glioma infiltration is essential for maximizing tumor resection while preserving functional brain tissue. Fluorescence lifetime imaging (FLIm) offers real-time, label-free biochemical contrast, but its clinical utility is challenged by biological heterogeneity, class imbalance, and variability in histopathological labeli

Rafael Bentes de Sales, Krissia Zawadzki

One of the main difficulties in preparing many-body ground states is achieving the target state through simple counterdiabatic controls. For critical systems crossing a transition to a topological phase, this task becomes even more challenging due to the closing of the gaps in multiple symmetry sectors. This is the case of the Kitaev chain, whose transition

Lionel Siess

This review explores the physical mechanisms driving the evolution of low- and intermediate-mass binary star systems, with particular emphasis on emerging mechanisms that challenge classical paradigms. We begin by describing the principal formation channels and orbital properties of binary systems. A critical reassessment of the Roche lobe formalism is prese

Gabriel de Miranda Nascimento, Marc L. Descoteaux, Laura Zichi, Chuin Wei Tan

First-principles atomistic simulations are essential for understanding complex material phenomena but are fundamentally limited by their computational cost. While Machine Learning Interatomic Potentials (MLIPs) have drastically improved cost for a given accuracy, their inference cost remains a bottleneck for massive systems or long timescales. To address thi

Emre Furkan Akyol, Mehmet Dedeler, Eray Tüzün

Bug tracking systems play a crucial role in software maintenance, yet developers frequently struggle with low-quality user-submitted reports that omit essential details such as Steps to Reproduce (S2R), Observed Behavior (OB), and Expected Behavior (EB). We propose ImproBR, an LLM-based pipeline that automatically detects and improves bug reports by addressi

Eugenio Bianchi, Pietro Donà, Erick Muiño

We consider a many-body Hilbert space with a fixed global charge and show that the typical entanglement entropy of a subsystem, at the leading and subleading order in the thermodynamic limit, can be expressed in terms of a single quantity which represents the local thermal entropy at fixed charge density. We find a general formula which applies both to abeli

Mohammed Q. Alkhatib, Ali Jamali

Over the past decade, hyperspectral image (HSI) classification has drawn considerable interest due to HSIs' ability to effectively distinguish terrestrial objects by capturing detailed, continuous spectral information. The strong performance of recent deep learning techniques in tasks like image classification and semantic segmentation has led to their growi

Weijie Sun, Tai Phan, Jia Huang, Yi-Hsin Liu

Magnetic reconnection is a fundamental physical process that can drive rapid conversion of magnetic energy into plasma bulk flows, thermal heating, and particle acceleration in space and astrophysical plasmas. Classical reconnection theory predicts that the Alfvenic reconnection exhausts are bounded by pairs of slow-mode shocks. However, identifying and char

Steven Nguyen, Nicholas Orndorff, Jorge Cortés, Boris Kramer

This paper presents a method for incorporating control analysis into design optimization for highly-maneuverable aircraft. By studying reachable sets for aircraft dynamics, we ensure that the optimizer will take the aircraft's controlled capabilities into account. We compute reachable sets of linear dynamics for computational efficiency, and account for airc

Baptiste Clemence, Thomas Hallopeau, Vanderlei Pascoal De Matos, Laurent Demagistri

Informal settlements face disproportionate exposure to climate-related health hazards. However, existing methodologies lack systematic approaches to link diverse settlement characteristics with environmental health outcomes. We develop a data-driven framework to assess heat vulnerability in Rio de Janeiro's favelas by combining spatially-constrained clusteri

Kargi Chauhan, Sadiba Nusrat Nur

With the rapid growth of large language models for code generation, distinguishing between human-written and AI-generated code has become increasingly critical for academic integrity, hiring evaluations, and software security. We present our system for SemEval-2026 Task 13: Multilingual Machine-Generated Code Detection, participating in Subtask A (binary det

Bahar Oveisgharan, Gene Cheung, Andrew Eckford

We aim to learn a sparse and connected graph from sparse data, where the number of observations K can be substantially smaller than the signal dimension N for signals x in R^N, and the underlying distribution is unknown. In this severely ill-posed setting, we incorporate Fiedler number (the second eigenvalue of the graph Laplacian matrix that quantifies conn

Florian Pop

In this note we give generalizations and prove 'minimalistic' refinements of the t-birational Section Conjecture (t-BSC), cf. [Be], by doing both: First, by extending the class of base fields over which the t-BSC holds, and second, by proving refinements of the t-BSC which involve much less, that is minimalistic, Galois theoretical information.

Mohammed Suhail B Nadaf

Every RLHF-trained language model is shaped by a reward model, yet the mechanistic interpretability toolkit -- logit lens, direct logit attribution, activation patching, sparse autoencoders -- was built for generative LLMs whose primitives all project onto a vocabulary unembedding. Reward models replace that with a scalar regression head, breaking each tool.

Sylvy Anscombe, Blaise Boissonneau

Building on work of Kuhlmann and Lisinski, we study the theory of the Hahn series field $\mathbb{F}_{q}(\!(\mathbb{Q})\!)$, over a finite field $\mathbb{F}_{q}$, equipped with the $t$-adic valuation, in a language of valued fields. We prove that every formula is equivalent to a formula $\exists y\colon f(x_{1},\ldots,x_{n},y)=0$, for a polynomial $f\in\mathb

Yuli Slavutsky, David M. Blei

We consider learning from labeled data collected across multiple environments, where the data distribution may vary across these environments. This problem is commonly approached from a causal perspective, seeking invariant representations that retain causal factors while discarding spurious ones. However, this framework assumes that the environment has no d