October 2024 arXiv papers — page 20

Juan Diego Rodriguez, Aaron Mueller, Kanishka Misra

Property inheritance -- a phenomenon where novel properties are projected from higher level categories (e.g., birds) to lower level ones (e.g., sparrows) -- provides a unique window into how humans organize and deploy conceptual knowledge. It is debated whether this ability arises due to explicitly stored taxonomic knowledge vs. simple computations of simila

Vladimir Florinski, Dinshaw S. Balsara, Deepak Bhoriya, Gary P. Zank

We present a pioneering model of the interaction between the solar wind and the surrounding interstellar medium that includes the possibility of different pressures in directions parallel and perpendicular to the magnetic field. The outer heliosheath region is characterized by a low rate of turbulent scattering that would permit development of pressure aniso

Benjamin A. Dalton, Anton Klimek, Henrik Kiefer, Florian N. Brünig

Friction is a phenomenon that manifests across all spatial and temporal scales, from the molecular to the macroscopic scale. It describes the dissipation of energy from the motion of particles or abstract reaction coordinates and arises in the transition from a detailed molecular-level description to a simplified, coarse-grained model. It has long been under

Catherine Arnett, Eliot Jones, Ivan P. Yamshchikov, Pierre-Carl Langlais

Open-source large language models are becoming increasingly available and popular among researchers and practitioners. While significant progress has been made on open-weight models, open training data is a practice yet to be adopted by the leading open-weight models creators. At the same time, there researchers are working to make language models safer. We

Markus Kraft, Mariel Kempa, Jiaozi Wang, Sourav Nandy

Understanding the physics of the integrable spin-1/2 XXZ chain has witnessed substantial progress, due to the development and application of sophisticated analytical and numerical techniques. In particular, infinite-temperature magnetization transport has turned out to range from ballistic, over superdiffusive, to diffusive behavior in different parameter re

Yuxuan Yang, Hussein Sibai

End-to-end vision-based autonomous driving has achieved impressive success, but safety remains a major concern. The safe control problem has been addressed in low-dimensional settings using safety filters, e.g., those based on control barrier functions. Designing safety filters for vision-based controllers in the high-dimensional settings of autonomous drivi

Natasha Butt, Varun Chandrasekaran, Neel Joshi, Besmira Nushi

Evaluation insights are limited by the availability of high-quality benchmarks. As models evolve, there is a need to create benchmarks that can measure progress on new and complex generative capabilities. However, manually creating new benchmarks is slow and expensive, restricting comprehensive evaluations for any capability. We introduce BenchAgents, a mult

Lia Gander, Rolf Krause, Francisco Sahli Costabal, Simone Pezzuto

Precision cardiology based on cardiac digital twins requires accurate simulations of cardiac arrhythmias. However, detailed models, such as the monodomain model, are computationally costly and have limited applicability in practice. Thus, it desirable to have fast models that can still represent the main physiological features presented during cardiac arrhyt

Serdar Kalaycioglu, Anton de Ruiter, Ethan Fung, Harrison Zhang

This paper introduces a closed-form analytical solution for the inverse kinematics (IK) of a 6 Degrees of Freedom (DOF) serial robotic manipulator arm, configured with six revolute joints and utilized within the Lunar Exploration Rover System (LERS). As a critical asset for conducting precise operations in the demanding lunar environment, this robotic arm re

Sankhaneel Bisui, Haoxi Hu

This article investigates under which conditions the symbolic powers of the extension of an ideal is the same as the extension of the symbolic powers. Our result generalizes the known scenarios. As an application, we prove formulas for the resurgence of sum of two homogeneous ideals in finitely generated k-algebra domains, where k is algebraically closed. In

William T. Reach, Ngoc Le Tram, Curtis DeWitt, Pierre Lesaffre

Supernova shocks into dense molecular cores in IC 443 (clumps B, C, and G) and 3C 391 were observed using the Stratospheric Observatory for Infrared Astronomy and complemented by archival data from the Herschel Space Observatory. The pure rotational transitions 0-0 S(1) and S(5) of H2, and the ground-state 110-101 transition of H2O, are all broadened, arisin

Rômulo Damasclin Chaves dos Santos, Jorge Henrique de Oliveira Sales

This work presents a comprehensive framework for enhanced diffusion modeling in fluid-structure interactions by combining the Immersed Boundary Method (IBM) with stochastic trajectories and high-order spectral boundary conditions. Using semi-Lagrangian schemes, this approach captures complex diffusion dynamics at moving interfaces, integrating probabilistic

Ying Li, Changling Li, Jiyao Chen, Christine Roinou

Mission-oriented drone networks have been widely used for structural inspection, disaster monitoring, border surveillance, etc. Due to the limited battery capacity of drones, mission execution strategy impacts network performance and mission completion. However, collaborative execution is a challenging problem for drones in such a dynamic environment as it a

Mohammad Shirzadi, Ahad N. Zehmakan

We study how the stubbornness of social network users influences opinion polarization and disagreement. Our work is in the context of the popular Friedkin-Johnson opinion formation model, where users update their opinion as a function of the opinion of their connections and their own innate opinion. Stubbornness then is formulated in terms of the stress a us

Guoxi Liu, Mattia Magnabosco, Yicheng Xia

In this paper, we prove existence of $L^p$-optimal transport maps with $p \in (1,\infty)$ in a class of branching metric spaces defined on $\mathbb{R}^N$. In particular, we introduce the notion of cylinder-like convex function and we prove an existence result for the Monge problem with cost functions of the type $c(x, y) = f(g(y - x))$, where $f: [0, \infty)

Taegyu Kang, Takashi Owada

A new estimator is proposed for estimating the tail exponent of a heavy-tailed distribution. This estimator, referred to as the layered Hill estimator, is a generalization of the traditional Hill estimator, building upon a layered structure formed by clusters of extreme values. We argue that the layered Hill estimator provides a robust alternative to the tra

Desh Ranjan, Mohammad Zubair

The Hessian-vector product computation appears in many scientific applications such as in optimization and finite element modeling. Often there is a need for computing Hessian-vector products at many data points concurrently. We propose an automatic differentiation (AD) based method, CHESSFAD (Chunked HESSian using Forward-mode AD), that is designed with eff

Chad Brown

I consider inference in a partially linear regression model under stationary $\beta$-mixing data after first stage deep neural network (DNN) estimation. Using the DNN results of Brown (2024), I show that the estimator for the finite dimensional parameter, constructed using DNN-estimated nuisance components, achieves $\sqrt{n}$-consistency and asymptotic norm

Benjamin Holzschuh, Nils Thuerey

Flow-based generative modeling is a powerful tool for solving inverse problems in physical sciences that can be used for sampling and likelihood evaluation with much lower inference times than traditional methods. We propose to refine flows with additional control signals based on a simulator. Control signals can include gradients and a problem-specific cost

Mohamed M. Elsayed, Bruno Uchoa, Valeri N. Kotov

Interactions have strong effects in systems with flat bands. We examine the role of Coulomb interactions in two dimensional chiral anisotropic quasiparticles that disperse linearly in one direction and have relatively flat bands near the neutrality point in the other direction, dispersing with an arbitrary positive even power law $2n\geq2$. As in the convent

Mirna Kramar, Lauritz Hahn, Aleksandra M Walczak, Thierry Mora

Cells use signalling pathways as windows into the environment to gather information, transduce it into their interior, and use it to drive behaviours. MAPK (ERK) is a highly conserved signalling pathway in eukaryotes, directing multiple fundamental cellular behaviours such as proliferation, migration, and differentiation, making it of few central hubs in the

Mark Neumann, James Gin, Benjamin Rhodes, Steven Bennett

We introduce Orb, a family of universal interatomic potentials for atomistic modelling of materials. Orb models are 3-6 times faster than existing universal potentials, stable under simulation for a range of out of distribution materials and, upon release, represented a 31% reduction in error over other methods on the Matbench Discovery benchmark. We explore

Volker Betz, Tobias Schmidt, Mark Sellke

Enhanced binding of a quantum particle coupled to a quantized field means that the Hamiltonian of the particle alone does not have a bound state, while the particle-field Hamiltonian does. For the Pauli--Fierz model, this is usually shown via the binding condition, which works less well in the case of a linear coupling to a scalar field. In particular, the c

Konrad Mueller, Amira Akkari, Lukas Gonon, Ben Wood

Hedging exotic options in presence of market frictions is an important risk management task. Deep hedging can solve such hedging problems by training neural network policies in realistic simulated markets. Training these neural networks may be delicate and suffer from slow convergence, particularly for options with long maturities and complex sensitivities t

Peter Cotton

Despite many attempts to make optimization-based portfolio construction in the spirit of Markowitz robust and approachable, it is far from universally adopted. Meanwhile, the collection of more heuristic divide-and-conquer approaches was revitalized by Lopez de Prado where Hierarchical Risk Parity (HRP) was introduced. This paper reveals the hidden connectio

Shucheng Li, Mattia Magnabosco, Timo Schultz

We investigate metric conditions that allow to prove existence and uniqueness of a map solving the Monge problem between two marginals in a metric (measure) space, proving two main results. Firstly, we introduce a nonsmooth version of the Riemannian twist condition that we call local metric twist condition, showing, under this assumption on the cost function

Siddharath Narayan Shakya, Parimala Kancharla

In this work, we designed a completely blind video quality assessment algorithm using the deep video prior. This work mainly explores the utility of deep video prior in estimating the visual quality of the video. In our work, we have used a single distorted video and a reference video pair to learn the deep video prior. At inference time, the learned deep pr

Quentin Schmidt, Baptiste Jadot, Brian Martinez, Thomas Houriez

This paper demonstrates the first on-chip frequency multiplexed readout of two co-integrated single-electron transistors without the need for bulky resonators. We characterize single electron dynamics in both single electron transistors at 4.2K before validating their simultaneous readout within 2.2{\mu}s, achieving a 99.9% fidelity with a 1MHz frequency spa

Pedro Valdeira, Shiqiang Wang, Yuejie Chi

Vertical federated learning trains models from feature-partitioned datasets across multiple clients, who collaborate without sharing their local data. Standard approaches assume that all feature partitions are available during both training and inference. Yet, in practice, this assumption rarely holds, as for many samples only a subset of the clients observe

Indranil Ghosh, David J. W. Simpson

We treat $n$-dimensional piecewise-linear continuous maps with two pieces, each of which has exactly one unstable direction, and identify an explicit set of sufficient conditions for the existence of a chaotic attractor. The conditions correspond to an open set within the space of all such maps, allow all $n \ge 2$, and allow all possible values for the unst

Masoud Ahmadi, Andrew McBride, Paul Steinmann, Prashant Saxena

Modelling the large deformation of hyperelastic solids under plane stress conditions for arbitrary compressible and nearly incompressible material models is challenging. This is in contrast to the case of full incompressibility where the out-of-plane deformation can be entirely characterised by the in-plane components. A rigorous general procedure for the in

Mohamadreza Rostami, Chen Chen, Rahul Kande, Huimin Li

Hardware-level memory vulnerabilities severely threaten computing systems. However, hardware patching is inefficient or difficult postfabrication. We investigate the effectiveness of hardware fuzzing in detecting hardware memory vulnerabilities and highlight challenges and potential future research directions to enhance hardware fuzzing for memory safety.

Linchuan Tang

This paper evaluates the fairness of BBR congestion control using NS-3 simulator. While BBR improves performance over loss-based methods in single flows, unfairness issues emerge with competing BBR and BBR/Cubic flows. Unfairness correlates with factors like round-trip time and buffer size. The core reason is the lack of responding mechanisms for the flows t

Carl Allen

We characterise disentanglement in smooth generative pushforward models, such as in VAEs and GANs. For a generator/decoder $g:Z\to X$ and factorised prior $p(z)=\prod_i p_i(z_i)$, we define disentanglement as factorisation of the pushforward density $p_\mu= g_\#p$ into one-dimensional "seam" factors, where each latent dimension controls an independent genera

Matthew McKinney, Anthony Garland, Dale Cillessen, Jesse Adamczyk

Effective monitoring of manufacturing processes is crucial for maintaining product quality and operational efficiency. Modern manufacturing environments generate vast amounts of multimodal data, including visual imagery from various perspectives and resolutions, hyperspectral data, and machine health monitoring information such as actuator positions, acceler

MAGIC Collaboration, H. Abe, S. Abe, V. A. Acciari

OT 081 is a well-known, luminous blazar that is remarkably variable in many energy bands. We present the first broadband study of the source which includes very-high-energy (VHE, $E>$100\,GeV) $\gamma$-ray data taken by the MAGIC and H.E.S.S. imaging Cherenkov telescopes. The discovery of VHE $\gamma$-ray emission happened during a high state of $\gamma$-ray

Seth Hovland

This paper investigates the relationship between links in bridge position and plat presentations. We prove that Hilden double coset classes of plat presentations correspond exactly to bridge positions of a link up to bridge isotopy. This correspondence allows us to translate algebraic questions about plat presentations into geometric questions about bridge p

Mohamadreza Rostami, Shaza Zeitouni, Rahul Kande, Chen Chen

Microarchitectural attacks represent a challenging and persistent threat to modern processors, exploiting inherent design vulnerabilities in processors to leak sensitive information or compromise systems. Of particular concern is the susceptibility of Speculative Execution, a fundamental part of performance enhancement, to such attacks. We introduce Specure,

Ishita Bansal, Peder Olsen, Roberto Estevão

Italian ryegrass is a grass weed commonly found in winter wheat fields that are competitive with winter wheat for moisture and nutrients. Ryegrass can cause substantial reductions in yield and grain quality if not properly controlled with the use of herbicides. To control the cost and environmental impact we detect weeds in drone and satellite imagery. Satel

Perla Mayo, Carolin M. Pirkl, Alin Achim, Bjoern H. Menze

Magnetic Resonance Fingerprinting (MRF) is a time-efficient approach to quantitative MRI, enabling the mapping of multiple tissue properties from a single, accelerated scan. However, achieving accurate reconstructions remains challenging, particularly in highly accelerated and undersampled acquisitions, which are crucial for reducing scan times. While deep l

Matthew Kenney

Artificial intelligence agents are increasingly capable of performing complex tasks across various domains. As these agents advance, there is a growing need to accurately measure and benchmark their capabilities, particularly in accelerating AI research and development. Current benchmarks focus on general machine learning tasks, but lack comprehensive evalua

Jaekyeom Kim, Dong-Ki Kim, Lajanugen Logeswaran, Sungryull Sohn

In this paper, we introduce Auto-Intent, a method to adapt a pre-trained large language model (LLM) as an agent for a target domain without direct fine-tuning, where we empirically focus on web navigation tasks. Our approach first discovers the underlying intents from target domain demonstrations unsupervisedly, in a highly compact form (up to three words).

Ruichen Zhang, Yuguang Yao, Zhen Tan, Zhiming Li

Image generation is a prevailing technique for clinical data augmentation for advancing diagnostic accuracy and reducing healthcare disparities. Diffusion Model (DM) has become a leading method in generating synthetic medical images, but it suffers from a critical twofold bias: (1) The quality of images generated for Caucasian individuals is significantly hi

Leïla Bessila, Adrien Deckx Van Ruys, Valentin Buriasco, Stéphane Mathis

We evaluate the impact of the rotation on the stochastic excitation of acoustic (p) modes in solar-like pulsators. First, we derive the forced wave equation taking rotation into account and we compute the source terms, which inject energy into the oscillations. We make use of the Rotating Mixing Length Theory (R-MLT) to assess how the convective root mean sq

Jonathan Parlett

We study a family of maps from $S_n \to S_n$ we call fixed point homing shuffles. These maps generalize a few known problems such as Conway's Topswops, and a card shuffling process studied by Gweneth McKinley. We show that the iterates of these homing shuffles always converge, and characterize the set $U_n$ of permutations that no homing shuffle sorts. We al

Gabriel Biscarrat, Leïla Bessila, Stéphane Mathis

We model the stochastic excitation of acoustic modes in solar-like pulsators taking into account the action of differential rotation. We derive the theoretical formalism for the stochastic excitation with differential rotation and make use of rotating convection Mixing-Length Theory to assess how the convective velocity is modified by rotation. Finally, we u

Rahul Pandharipande, Dhruv Ranganathan, Johannes Schmitt, Pim Spelier

We define the logarithmic tautological rings of the moduli spaces of Deligne-Mumford stable curves (together with a set of additive generators lifting the decorated strata classes of the standard tautological rings). While these algebras are infinite dimensional, a connection to polyhedral combinatorics via a new theory of homological piecewise polynomials a

Panagiotis Koutsogiannakis, Theodosios Papathanasiou, Francesco Dal Corso

With recent advances in variable-length structures for use in soft actuation, energy harvesting, energy dissipation and metamaterials, the mathematical modelling and numerical simulation of physical systems with time-varying domains is becoming increasingly important. The planar nonlinear dynamics of one-dimensional elastic structures with variable domain is

Csaba Kiss, Thomas G. Müller, Anikó Farkas-Takács, Attila Moór

We report on the discovery of a very prominent mid-infrared (18-25 {\mu}m) excess associated with the trans-Neptunian dwarf planet (136472) Makemake. The excess, detected by the MIRI instrument of the James Webb Space Telescope, along with previous measurements from the Spitzer and Herschel space telescopes, indicates the occurrence of temperatures of about

G. I. Kokhirova, M. Zhang, X. -G. Li, A. I. Zhonmuhammadi

The $\delta$-Cancrid meteoroid stream forms four active meteor showers which are observable on the Earth annually during January-February and August-September. The stream's definite parent comet has not been established. We performed a search for near-Earth asteroids (NEAs) associated with this stream. We have followed the backward evolution of the orbital e

Matthew D. Booth, Pankaj Singh, Adela Vraciu

We provide a description of initial ideals for almost complete intersections generated by powers of general linear forms and prove that WLP in a fixed degree $d$ holds when the number of variables $n$ is sufficiently large compared to $d$. In particular, we show that if $n\geq 3d-2$ then WLP holds for the ideal generated by squares at the degree $d$ spot and

Siddharth Kumar Singh, A. Gupta, P. T. Madathil, C. Wang

Termination of the fractional quantum Hall states (FQHSs) and the emergence of Wigner crystal phases at very small Landau level filling factors ($\nu$) have been of continued interest for decades. Recently, in ultra-high-quality, dilute GaAs 2D electron systems (2DESs), strong evidence was reported for FQHSs at $\nu=1/7, 2/13$ and 2/11 which fall in the $\nu

Noam Zilberstein, Dexter Kozen, Alexandra Silva, Joseph Tassarotti

Programs increasingly rely on randomization in applications such as cryptography and machine learning. Analyzing randomized programs has been a fruitful research direction, but there is a gap when programs also exploit nondeterminism (for concurrency, efficiency, or algorithmic design). In this paper, we introduce Demonic Outcome Logic for reasoning about pr

Jason Spyromilio

There is no such thing as quenching of forbidden lines.

W. S. Nascimento, A. M. Maniero, F. V. Prudente, C. R. de Carvalho

A quasi-unidimensional one-electron double quantum dot is studied within the framework of Shannon informational entropy. Its confinement potential, which is described by an asymmetric harmonic-gaussian function, consists of two wells separated by a potential barrier, and the asymmetry of the potential in respect to the center of the barrier is parameterized

Gregory M. Green, Xiangyu Zhang, Ruoyi Zhang

The dust extinction curve is typically parameterized by a single variable, R(V), in optical and near-infrared wavelengths. R(V) controls the slope of the extinction-vs.-wavelength curve, and is thought to reflect the grain-size distribution and composition of dust. Low-resolution, flux-calibrated BP/RP spectra from Gaia have allowed the determination of the

Daniel Lenz, Christoph Richard, Nicolae Strungaru

In 2012, Meyer introduced the notions of generalized almost periodic measure and almost periodic pattern and proved that regular model sets in Euclidean space are almost periodic patterns. Here, we prove the converse in a slightly more general setting. Specifically, we show that a Meyer set in any $\sigma$-compact locally compact abelian group is a regular m

Hwaseob Lee, Lorry Chang, Ali Kecebas, Dun Mao

Exceptional points (EPs) have been extensively explored in mechanical, acoustic, plasmonic, and photonic systems. However, little is known about the role of EPs in tailoring the dynamic tunability of optical devices. A specific type of EPs known as chiral EPs has recently attracted much attention for controlling the flow of light and for building sensors wit

Sida Chen, Danilo Alvares, Marco Palma, Jessica K. Barrett

Joint models (JMs) for longitudinal and time-to-event data are an important class of biostatistical models in health and medical research. When the study population consists of heterogeneous subgroups, the standard JM may be inadequate and lead to misleading results. Joint latent class models (JLCMs) and their variants have been proposed to incorporate laten

S. Kaliszewski, John Quigg, Dana P. Williams

We use the Ladder Technique to establish bijections between the ideals of related Fell bundles.

Ozan Alp Topal, Özlem Tuğfe Demir, Emil Björnson, Cicek Cavdar

Integrated sensing and communications (ISAC) allows networks to perform sensing alongside data transmission. While most ISAC studies focus on single-target, multi-user scenarios, multi-target sensing is scarcely researched. This letter examines the monostatic sensing performance of a multi-target massive MIMO system, aiming to minimize the sum of Cram\'er-Ra

Hongyi Pan, Gorkem Durak, Zheyuan Zhang, Yavuz Taktak

Federated learning (FL) enables collaborative model training across institutions without sharing sensitive data, making it an attractive solution for medical imaging tasks. However, traditional FL methods, such as Federated Averaging (FedAvg), face difficulties in generalizing across domains due to variations in imaging protocols and patient demographics acr

Mark M. Malamud, H. Neidhardt, Vladimir V. Peller

In recent joint papers the authors of this note solved a famous problem remained open for many years and proved that for arbitrary contractions with trace class difference there exists an integrable spectral shift function, for which an analogue of the Lifshits--Krein trace formula holds. Similar results were also obtained for pairs of dissipative operators.

Jakob Mannstadt, Arash Rahimi-Iman

A machine-learning non-contact method to determine the temperature of a laser gain medium via its laser emission with a trained few-layer neural net model is presented. The training of the feed-forward Neural Network (NN) enables the prediction of the device's properties solely from spectral data, here recorded by visible-/nearinfrared-light compact micro-sp

Yufeng Yang, Minghao Ning, Shucheng Huang, Ehsan Hashemi

This paper introduces a framework for an indoor autonomous mobility system that can perform patient transfers and materials handling. Unlike traditional systems that rely on onboard perception sensors, the proposed approach leverages a global perception and localization (PL) through Infrastructure Sensor Nodes (ISNs) and cloud computing technology. Using the

Johannes Girsch

We define the twisted doubling zeta integrals of Cai-Friedberg-Ginzburg-Kaplan in the setting of algebraic families. We then prove a rationality result and a functional equation for these zeta integrals. This allows us to define an unnormalized $\gamma$-factor associated to certain families of representation of a classical group times a general linear group.

Douglas C. Crowder, Darrien M. McKenzie, Matthew L. Trappett, Frances S. Chance

Hindsight experience replay (HER) accelerates off-policy reinforcement learning algorithms for environments that emit sparse rewards by modifying the goal of the episode post-hoc to be some state achieved during the episode. Because post-hoc modification of the observed goal violates the assumptions of on-policy algorithms, HER is not typically applied to on

Aleksei B. Aleksandrov, Vladimir V. Peller

In this paper we compare various classes of Schur multipliers: classical matrix Schur multipliers, discrete Schur multipliers, Schur multipliers with respect to measures and Schur multipliers with respect to spectral measures. The main result says that in the case of Schur multipliers with respect to measures and spectral measures such Schur multipliers coin

Matthias Urban, Carsten Binnig

In this paper, we present ELEET, a novel execution engine that allows one to seamlessly query and process text as a first-class citizen along with tables. To enable such a seamless integration of text and tables, ELEET leverages learned multi-modal operators (MMOps) such as joins and unions that seamlessly combine structured with unstructured textual data. W

Saeed Ahmed, Patrick Bachmann, Stephan Trenn

In this study, we investigate the ISS of impulsive switched systems that have modes with both stable and unstable flows. We assume that the switching signal satisfies mode-dependent average dwell and leave time conditions. To establish ISS conditions, we propose two types of time-varying ISS-Lyapunov functions: one that is non-decreasing and another one that

Chang Liu, Jieshi Chen, Lee H. Harrison, Artur Dubrawski

When selecting data to build machine learning models in practical applications, factors such as availability, acquisition cost, and discriminatory power are crucial considerations. Different data modalities often capture unique aspects of the underlying phenomenon, making their utilities complementary. On the other hand, some sources of data host structural

Hugo E. Caceres, Ben Moews

Financial regulators such as central banks collect vast amounts of data, but access to the resulting fine-grained banking microdata is severely restricted by banking secrecy laws. Recent developments have resulted in mechanisms that generate faithful synthetic data, but current evaluation frameworks lack a focus on the specific challenges of banking institut

Jon Chaika, Sebastian Hensel

A lamination $\lambda$ is $\epsilon$-thick (with respect to a basepoint $X$), if the Teichm\"uller ray from $X$ in the direction of $\lambda$ stays in the $\epsilon$-thick part. We show that, for surfaces of high enough genus, any two $\epsilon$-thick laminations can be joined by a path of $\delta$-thick laminations. As a consequence, we show that the Morse

Rishabh Adiga, Besmira Nushi, Varun Chandrasekaran

We explore the internal mechanisms of how bias emerges in large language models (LLMs) when provided with ambiguous comparative prompts: inputs that compare or enforce choosing between two or more entities without providing clear context for preference. Most approaches for bias mitigation focus on either post-hoc analysis or data augmentation. However, these

Sudip Mukherjee, Abhik basu

We explore the stationary densities in totally asymmetric exclusion processes (TASEP) with open boundary conditions and spatially inhomogeneous hopping rates. We calculate the steady state density profiles that characterise the associated phases. We show that in the contrast to the low and high density phases, the stationary density profile in the maximal cu

Cesar A. Ipanaque Zapata

The genus of a fibration was introduced by Schwarz in 1962. Given a continuous map $g:A\to B$, the usual sectional number $\text{sec}_u(g)$ is the least integer~$m$ such that $B$ can be covered by $m$ open subsets, each of which admits a local section of~$g$. Likewise, the sectional category $\text{secat}(g)$ is the least integer~$m$ such that $B$ can be cov

Adrian Reich, Dmitriy S. Shapiro, Alexander Shnirman

We investigate quantum phase transitions in a topological Josephson junction with an embedded ferromagnetic layer, revealing a rich landscape of critical phenomena. The low-energy excitations comprise Majorana fermions propagating along the junction, coupled to the magnons in the ferromagnet. Based on mean-field and renormalization group arguments, we predic

Vishal Dubey

Super Resolution (SR) plays a critical role in computer vision, particularly in medical imaging, where hardware and acquisition time constraints often result in low spatial and temporal resolution. While diffusion models have been applied for both spatial and temporal SR, few studies have explored their use for joint spatial and temporal SR, particularly in

Lucas S. Marinho, Michelle O. Araújo, Daniel Felinto

Quantum correlations in four-wave-mixing from ensembles of cold two-level atoms may prevail without filtering over background light with well-known classical interpretations, such as Rayleigh scattering, as recently experimentally demonstrated in Phys. Rev. Lett. {\bf 128}, 083601 (2022). Here we provide an extended investigation of this effect, in which we

Steven Dale Cutkosky

Let $\mathcal I=\{I_n\}$ be a divisorial filtration on a two dimensional normal excellent local ring $(R,m_R)$. Let $R[\mathcal I]=\oplus_{n\ge 0}I_n$ be the Rees algebra of $\mathcal I$ and $\tau:\mbox{Proj}R[\mathcal I])\rightarrow \mbox{Spec}(R)$ be the natural morphism. The reduced fiber cone of $\mathcal I$ is the $R$-algebra $R[\mathcal I]/\sqrt{m_RR[\

Dezhan Tu, Danylo Vashchilenko, Yuzhe Lu, Panpan Xu

Vision-Language Models (VLMs) have demonstrated impressive performance across a versatile set of tasks. A key challenge in accelerating VLMs is storing and accessing the large Key-Value (KV) cache that encodes long visual contexts, such as images or videos. While existing KV cache compression methods are effective for Large Language Models (LLMs), directly m

Matteo Ciardi, Fabio Cinti, Giuseppe Pellicane, Santi Prestipino

Unveiling the principles behind self-organization in quantum systems is of paramount importance, both intrinsically and practically, in view of foreseeable technological applications. Recently, increasing attention is being paid to atomic systems in curved geometries, which are a promising platform for the discovery of new emergent phenomena. A notable examp

Harry Caufield, Carlo Kroll, Shawn T O'Neil, Justin T Reese

Effective data-driven biomedical discovery requires data curation: a time-consuming process of finding, organizing, distilling, integrating, interpreting, annotating, and validating diverse information into a structured form suitable for databases and knowledge bases. Accurate and efficient curation of these digital assets is critical to ensuring that they a

Igor Panov, Anton Ignatovskiy, Andrey Yudin

The pattern of nucleosynthesis during the explosion of a low-mass neutron star formed in a close binary system in the stripping scenario is considered. In the scenario considered the shock arising during the explosion is shown to strongly heat the expanding neutron star matter. The heavy nuclei produced at the preceding stage of nucleosynthesis are partially

Javier Henríquez-Amador, Carlos F. Álvarez

In this note, we consider a class of composition operators on Lebesgue spaces with variable exponents over metric measure spaces. Taking advantage of the compatibility between the metric-measurable structure and the regularity properties of the variable exponent, we provide necessary and sufficient conditions for this class of operators to be bounded and com

R. A. Shaw, S. Fotopoulou, M. Birkinshaw, N. Maddox

Source detection is a vital part of any astronomical survey analysis pipeline. In addition, a versatile source finder that can recover and handle sources of all morphological types is becoming more important as surveys get bigger and achieve a higher resolution than ever before. Here we present Detector of astRonomical soUrces in optIcal and raDio images (DR

Efstratios Koukoutsis, Panagiotis Papagiannis, Kyriakos Hizanidis, Abhay K. Ram

Motivated by the contemporary advances in quantum implementation of non-unitary operations, we propose a new dilation method based on the biorthogonal representation of the non-unitary operator, mapping it to an isomorphic unitary matrix in the orthonormal computational basis. The proposed method excels in implementing non-unitary operators whose eigenvalues

Anis Biswas, Ajay Kumar, Prashant Singh, Tyler Del Rose

We explore the impact of introducing IIIA-group element Ga in place of IIB-group element Zn in binary intermetallic GdZn on its magnetic and magnetocaloric properties, as well as explicate the modified electronic band structure of the compound. The magnetic transition temperature of the compound decreases with the increase of Ga concentration in GdZn1-xGax (

Yan Guo, Junhwa Jung

The exterior domain problem is essential in fluid and kinetic equations. In this paper, we establish the validity of the diffusive expansion for the Boltzmann equations to the Navier-Stokes-Fourier system up to the critical time in an exterior domain with non-zero passing flow. We apply the $L^3-L^6$ framework to the unbounded domain in this paper.

Henan Xu, Yeying Zhu, Donna L. Coffman

Hospital readmissions following coronary artery bypass grafting (CABG) not only impose a substantial cost burden on healthcare systems but also serve as a potential indicator of the quality of medical care. Previous studies of gender effects on complications after CABG surgery have consistently revealed that women tend to suffer worse outcomes. To better und

Taha Hasan, Touqeer Ahmad

Mixture experiments often involve process variables, such as different chemical reactors in a laboratory or varying mixing speeds in a production line. Organizing the runs in orthogonal blocks allows the mixture model to be fitted independently of the process effects, ensuring clearer insights into the role of each mixture component. Current literature on mi

Mohammad Samin Nur Chowdhury, Diyu Yang, Shimin Tang, Singanallur V. Venkatakrishnan

Hyperspectral neutron computed tomography is a tomographic imaging technique in which thousands of wavelength-specific neutron radiographs are measured for each tomographic view. In conventional hyperspectral reconstruction, data from each neutron wavelength bin are reconstructed separately, which is extremely time-consuming. These reconstructions often suff

Siqi Ouyang, Oleksii Hrinchuk, Zhehuai Chen, Vitaly Lavrukhin

Simultaneous machine translation (SMT) takes streaming input utterances and incrementally produces target text. Existing SMT methods mainly use the partial utterance that has already arrived at the input and the generated hypothesis. Motivated by human interpreters' technique to forecast future words before hearing them, we propose $\textbf{T}$ranslation by

Yanbin Yang, Feiyu Zhao, Ruxi Liang, Quan Guo

The emerging era of big data in radio astronomy demands more efficient and higher-quality processing of observational data. While deep learning methods have been applied to tasks such as automatic radio frequency interference (RFI) detection, these methods often face limitations, including dependence on training data and poor generalization, which are also c

Hyunggon Park, Kaitlyn M. Mullin, Vijay Kumar, Olivia A. Wander

Metal additive manufacturing (AM) processes, such as laser powder bed fusion (L-PBF), can yield high-value parts with unique geometries and features, substantially reducing costs and enhancing performance. However, the material properties from L-PBF processes are highly sensitive to the laser processing conditions and the resulting dynamic temperature fields

Eric R Bittner, Bhavay Tyagi

We consider the quantum dynamics of a pair of coupled quantum oscillators coupled to a common correlated dissipative environment. The resulting equations of motion for both the operator moments and covariances can be integrated analytically using the Lyapunov equations. We find that for fully correlated and fully anti-correlated environments, the oscillators

Davide Barbarossa

G\"odel's Dialectica has been introduced and developed in the tradition of the so-called functional interpretations. Only recently has it been related with the a priori unrelated notion of differentiation, by taking a program-theoretic approach. We revisit the deep connection between these two notions in order to understand its structural reasons, as well as

David Lüdke, Enric Rabasseda Raventós, Marcel Kollovieh, Stephan Günnemann

Point processes model the distribution of random point sets in mathematical spaces, such as spatial and temporal domains, with applications in fields like seismology, neuroscience, and economics. Existing statistical and machine learning models for point processes are predominantly constrained by their reliance on the characteristic intensity function, intro

Saleem Ahmed, Srirangaraj Setlur, Venu Govindaraju

Multimodal reasoning models often produce fluent answers supported by seemingly coherent rationales. Existing benchmarks evaluate only final-answer correctness. They do not support atomic visual entailment verification of intermediate steps, especially visual compositional logic. This limitation is especially acute in scientific chart understanding, where an

Elena Kardanova, Alina Ivanova, Ksenia Tarasova, Taras Pashchenko

The era of large language models (LLM) raises questions not only about how to train models, but also about how to evaluate them. Despite numerous existing benchmarks, insufficient attention is often given to creating assessments that test LLMs in a valid and reliable manner. To address this challenge, we accommodate the Evidence-centered design (ECD) methodo