December 2024 arXiv papers — page 22

Andreas Vollmer

Pre-geodesics of an affine connection are the curves that are geodesics after a reparametrization (the analogous concept in K\"ahler geometry is known as J-planar curves). Similarly, dual-geodesics on a Riemannian manifold are curves along which the 1-forms associated to the velocity are preserved after a reparametrization. Superintegrable systems are Hamilt

C. Sirimanna, Y. Tachibana, A. Majumder, A. Angerami

An investigation of high transverse momentum (high-$p_T$) photon triggered jets in proton-proton ($p$-$p$) and ion-ion ($A$-$A$) collisions at $\sqrt{s_{NN}} = 0.2$ and $5.02~\mathrm{TeV}$ is carried out, using the multistage description of in-medium jet evolution. Monte Carlo simulations of hard scattering and energy loss in heavy-ion collisions are perform

Shakil Ahmed, Saifur Rahman Sabuj, Ashfaq Khokhar

This paper introduces the Adaptive Context-Aware Multi-Path Transmission Control Protocol (ACMPTCP), an efficient approach designed to optimize the performance of Multi-Path Transmission Control Protocol (MPTCP) for data-intensive applications such as augmented and virtual reality (AR/VR) streaming. ACMPTCP addresses the limitations of conventional MPTCP by

Vatsana Tiwari, Devendra Singh Bhakuni, Auditya Sharma

We investigate the electric-field driven power-law random banded matrix(PLRBM) model where a variation in the power-law exponent $\alpha$ yields a delocalization-to-localization phase transition. We examine the periodically driven PLRBM model with the help of the Floquet operator. The level spacing ratio and the generalized participation ratio of the Floquet

Siqiang Su, Zhenghao Li, Long Feng, Ting Li

Imaging genetics is a growing field that employs structural or functional neuroimaging techniques to study individuals with genetic risk variants potentially linked to specific illnesses. This area presents considerable challenges to statisticians due to the heterogeneous information and different data forms it involves. In addition, both imaging and genetic

Alan Kostelecky, Ralf Lehnert, Marco Schreck, Babak Seradjeh

Regimes of Lorentz-violating effective field theories are studied in which departures from Lorentz symmetry are nonperturbative. Within a free toy theory exhibiting Lorentz breakdown involving an operator of mass dimension three, it is shown that conventional methods suffice to achieve field quantization and Fock-space construction. However, the absence of a

Damien Bouchabou, Sao Mai Nguyen

Within the evolving landscape of smart homes, the precise recognition of daily living activities using ambient sensor data stands paramount. This paper not only aims to bolster existing algorithms by evaluating two distinct pretrained embeddings suited for ambient sensor activations but also introduces a novel hierarchical architecture. We delve into an arch

Ericka Florio, E. Paul S. Shellard

We present a complete method for the initialisation and extraction of first-order inflationary tensor perturbations for fully relativistic simulations which incorporate gravitational back-reaction. We outline a correspondence between the Cosmological Perturbation Theory (CPT) framework and the numerical relativity BSSN variables in the appropriate limit. We

Jacopo Borga, Andrew Lin

Permutons, which are probability measures on the unit square $[0, 1]^2$ with uniform marginals, are the natural scaling limits for sequences of (random) permutations. We introduce a $d$-dimensional generalization of these measures for all $d \ge 2$, which we call $d$-dimensional permutons, and extend -- from the two-dimensional setting -- the theory to prove

Arvind Bhaskar, Yash Chaurasia, Arijit Das, Atirek Kumar

We introduce the leptoquark (LQ) toolkit, TooLQit, which includes leading-order FeynRules models for all types of LQs and a Python-based calculator, named CaLQ, to test if a set of parameter points are allowed by the LHC dilepton searches. The models include electroweak gauge interactions of the LQs and follow a set of intuitive notations. Currently, CaLQ ca

Bittu Chahal, Sneha Chaubey

We study two types of problems for polynomial Farey fractions. For a positive integer $Q$, and polynomial $P(x)\in\mathbb{Z}[X]$ with $P(0)=0$, we define polynomial Farey fractions as \[\mathcal{F}_{Q,P}:=\left\{\frac{a}{q}: 1\leq a\leq q\leq Q,\ \gcd (P(a),q)=1\right\}.\] The classical Farey fractions are obtained by considering $P(x)=x$. In this article, w

Yuchen Jiao, Gen Li

Multi-agent robust reinforcement learning, also known as multi-player robust Markov games (RMGs), is a crucial framework for modeling competitive interactions under environmental uncertainties, with wide applications in multi-agent systems. However, existing results on sample complexity in RMGs suffer from at least one of three obstacles: restrictive range o

Saughmon Boujkian

This study examines the cross-linguistic effectiveness of transfer learning for low-resource machine translation by fine-tuning models initially trained on typologically similar high-resource languages, using limited data from the target low-resource language. We hypothesize that linguistic similarity enables efficient adaptation, reducing the need for exten

Csaba Tóth, Masaki Adachi, Michael A. Osborne, Harald Oberhauser

The signature kernel is a kernel between time series of arbitrary length and comes with strong theoretical guarantees from stochastic analysis. It has found applications in machine learning such as covariance functions for Gaussian processes. A strength of the underlying signature features is that they provide a structured global description of a time series

Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf, Payel Das

Our paper argues that the majority of theory of mind benchmarks are broken because of their inability to directly test how large language models (LLMs) adapt to new partners. This problem stems from the fact that theory of mind benchmarks for LLMs are overwhelmingly inspired by the methods used to test theory of mind in humans and fall victim to a fallacy of

Daniil A. Berdyshev, Artem M. Grachev, Sergei L. Shishkin, Bogdan L. Kozyrskiy

Meta-learning, i.e., "learning to learn", is a promising approach to enable efficient BCI classifier training with limited amounts of data. It can effectively use collections of in some way similar classification tasks, with rapid adaptation to new tasks where only minimal data are available. However, applying meta-learning to existing classifiers and BCI ta

Yuyuan Zhou, Lorenzo Audibert, Shixu Meng, Bo Zhang

In this work, we introduce a novel low-rank structure tailored for solving the inverse scattering problem. The particular low-rank structure is given by the generalized prolate spheroidal wave functions, computed stably and accurately via a Sturm-Liouville problem. We first process the far-field data to obtain a post-processed data set within a disk domain.

Qiushi Sun, Kanzhi Cheng, Zichen Ding, Chuanyang Jin

Graphical User Interface (GUI) agents powered by Vision-Language Models (VLMs) have demonstrated human-like computer control capability. Despite their utility in advancing digital automation, a critical bottleneck persists: collecting high-quality trajectory data for training. Common practices for collecting such data rely on human supervision or synthetic d

Benjamin Berczi, Magdalena Eriksson, Thanasis Giannakopoulos, Paul M. Saffin

We report on work using a newly developed code, SpheriCo.jl, that computes the gravitational collapse of a spherical scalar field, where the scalar can be either a classical field, or a quantum field operator. By utilising summation-by-parts methods for the numerical derivatives we are able to simulate the collapse longer than was possible previously due to

V. Sathish Kumar, Jacinta Torres

We prove a bijection between the branching models of Kwon and Sundaram, conjectured previously by Lenart-Lecouvey. To do so, we use a symmetry of Littlewood-Richardson coefficients in terms of the hive model. Along the way, we obtain a new branching model in terms of flagged hives.

Chao Chen, Yu-Shen Liu, Zhizhong Han

Signed Distance Functions (SDFs) are vital implicit representations to represent high fidelity 3D surfaces. Current methods mainly leverage a neural network to learn an SDF from various supervisions including signed distances, 3D point clouds, or multi-view images. However, due to various reasons including the bias of neural network on low frequency content,

Max T. M. Ng, Adrian Hernandez, Pablo L. Durango-Cohen, Hani S. Mahmassani

To support planning of alternative fuel technology (e.g., battery-electric locomotives) deployment for decarbonizing non-electrified freight rail, we develop a convex optimization formulation with a closed-form solution to determine the optimal number of energy storage tender cars in a train. The formulation shares a similar structure to an Economic Order Qu

Vivek S Borkar

Two time scale stochastic approximation is analyzed when the iterates on either or both time scales do not necessarily converge.

Pradeep Sain

The growing demand for dynamic, user-centric data analysis and visualization is evident across domains like healthcare, finance, and research. Traditional visualization tools often fail to meet individual user needs due to their static and predefined nature. To address this gap, Text2Insight is introduced as an innovative solution that delivers customized da

Jaye Sudweeks, Christoph Hauert

Phages use bacterial host resources to replicate, intrinsically linking phage and host survival. To understand phage dynamics, it is essential to understand phage-host ecology. A key step in this ecology is infection of bacterial hosts. Previous work has explored single and multiple, sequential infections. Here we focus on the theory of simultaneous infectio

Massimo Tessarotto, Claudio Cremaschini, Claudio Asci, Alessandro Soranzo

One of the most challenging and fascinating issues in mathematical and theoretical physics concerns identifying the common logic, if any, which underlies the physical world. More precisely, this involves the search of the possibly-unique axiomatic logical proposition calculus to apply simultaneously both to classical and quantum realms of physics and to be c

Ahmed A. Zahia, M. Y. Abd-Rabbou, Ahmed M. Megahed

This study investigates the dynamics of quantum batteries (QBs), focusing on the pivotal role of quantum entanglement in mediating inter-cellular energy transfer within a two-cell configuration (two-qubit), wherein one cell is directly coupled to the charging source. Employing the Lindblad master equation to model the system's evolution, the influence of coh

Divyang G. Bhimani, Diksha Dhingra, Vijay Kumar Sohani

We establish global well-posedness for the mass subcritical nonlinear fractional Schr\"odinger equation $$iu_t - (-\Delta)^\frac{\beta}{2} u+F(u)=0$$ having radial initial data in modulation spaces $M^{p,\frac{p}{p-1}}(\mathbb R^n)$ for $n \geq 2, p>2$ and $p$ sufficiently close to $2.$ The nonlinearity $F(u)$ is either of power-type $F(u)=\pm (|u|^{\alpha}u

Bhavesh Gyanchandani, Aditya Oza, Abhinav Roy

The growing need for accurate and efficient 3D identification of tumors, particularly in liver segmentation, has spurred considerable research into deep learning models. While many existing architectures offer strong performance, they often face challenges such as overfitting and excessive computational costs. An adjustable and flexible architecture that str

Jiawei Lin, Shizhao Sun, Danqing Huang, Ting Liu

In this work, we investigate automatic design composition from multimodal graphic elements. Although recent studies have developed various generative models for graphic design, they usually face the following limitations: they only focus on certain subtasks and are far from achieving the design composition task; they do not consider the hierarchical informat

Matthew Pryce, Karla Diaz-Ordaz, Ruth H. Keogh, Stijn Vansteelandt

When estimating heterogeneous treatment effects, missing outcome data can complicate treatment effect estimation, causing certain subgroups of the population to be poorly represented. In this work, we discuss this commonly overlooked problem and consider the impact that missing at random (MAR) outcome data has on causal machine learning estimators for the co

Markus Exner, Rohan Srikumar, Richard Blättner, Matthew T. Eiles

We perform three-photon photoassociation to obtain high resolution spectra of $^{87}$Rb trilobite dimers for the principal quantum numbers $n = 22,24,25,26$, and $27$. The large binding energy of the molecules in combination with a relative spectroscopic resolution of $10^{-4}$ provides a rigorous benchmark for existing theoretical models. A recently develop

Gianluca Degli Esposti, Greger Torgrimsson

We use a worldline-instanton formalism to study the momentum spectrum of Schwinger pair production in spacetime fields with multiple stationary points. We show that the interference structure changes fundamentally when going from purely time-dependent to space-time-dependent fields. For example, it was known that two time-dependent pulses give interference i

Richard A. W. Bradford

Because of the importance of unitarity in quantum physics, work on the representations of the de Sitter group has focussed on the unitary case, which necessarily means infinite dimensional matrices for this non-compact group. Here we address the finite dimensional representations resulting from the requirement that the Lie algebra generators are either Hermi

Sijia Chen, Baochun Li

Large language models (LLMs) have been routinely used to solve various tasks using step-by-step reasoning. However, the structure of intermediate reasoning steps, or thoughts, is rigid and unidirectional, such as chains, trees, or acyclic-directed graphs. Consequently, the resulting inflexible and forward-only reasoning may not address challenging tasks and

Sharareh Alipour, Kajal Baghestani, Mahdis Mirzaei, Soroush Sahraei

We study the Freeze-Tag Problem (FTP), introduced by Arkin et al. (SODA'02), where the goal is to wake up a group of $n$ robots, starting from a single active robot. Our focus is on the geometric version of the problem, where robots are positioned in $\mathbb{R}^d$, and once activated, a robot can move at a constant speed to wake up others. The objective is

Xiong Zeng, Laurent Bako, Necmiye Ozay

In this paper, we study the noise sensitivity of the semidefinite program (SDP) proposed for direct data-driven infinite-horizon linear quadratic regulator (LQR) problem for discrete-time linear time-invariant systems. While this SDP is shown to find the true LQR controller in the noise-free setting, we show that it leads to a trivial solution with zero gain

B. Chauhan, R. Tripathi

We perform the Becchi-Rouet-Stora-Tyutin (BRST) quantization of a $(0 + 1)$-dimensional cosmological Friedmann-Robertson-Walker (FRW) model. This quantization leverages the classical infinitesimal and continuous re-parameterization symmetry transformations of the system. To derive the nilpotent re-parameterization invariant BRST-anti-BRST symmetry transforma

Aikaterini Gkogkou, Barbara Prinari, Thomas Trogdon

We present a method to solve numerically the Cauchy problem for the defocusing nonlinear Schr\"{o}dinger (NLS) equation with a box-type initial condition (IC) having a nontrivial background of amplitude $q_o>0$ as $x\to \pm \infty$ by implementing numerically the corresponding Inverse Scattering Transform (IST). The Riemann--Hilbert problem associated to the

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

Using a data sample of $(10087 \pm 44) \times {10^{6}}$ $J/{\psi}$ events collected with the BESIII detector, we search for the decays $\eta/\eta'\to e^+e^-\mu^+\mu^-$ and $\eta' \to \mu^+\mu^-\mu^+\mu^-$ via the radiative decays $J/{\psi}\to\gamma\eta$/$\gamma\eta'$. No excess of events over expected background is observed for any of the decays of interest.

Shivani Gupta, Archana Soam, Janik Karoly, Chang Won Lee

L328 core has three sub-cores S1, S2, and S3, among which the sub-core S2 contains L328-IRS, a Very Low Luminosity Object (VeLLO), which shows a CO bipolar outflow. Earlier investigations of L328 mapped cloud/envelope (parsec-scale) magnetic fields (B-fields). In this work, we used JCMT/POL-2 submillimeter (sub-mm) polarisation measurements at 850 $\mu$m to

Devang Bhagat, Ranga Teja Pidathala, Badri Narayanan

Controlled introduction of oxygen vacancies offers an effective route to induce metal-to-insulator transition in strongly correlated rare-earth nickelates ($R$NiO$_3$) at room temperature. However, the role played by the rare-earth cations on the structure, thermodynamic stability, and electronic properties of oxygen-deficient nickelates remains unclear. Her

Malcolm Perry, Maria J. Rodriguez

We perform a detailed study of the gravitational tidal Love numbers of extremal zero-temperature Kerr black holes. These coefficients are finite and exhibit the dissipative nature of these maximally spinning black holes. Upon considering the dynamical behavior of the tidal deformations of the extremal Kerr black holes, we provide explicit expressions of the

Jan de Boer, Giuseppe Di Giulio, Esko Keski-Vakkuri, Erik Tonni

In quantum resource theory, one is often interested in identifying which states serve as the best resources for particular quantum tasks. If a relative comparison between quantum states can be made, this gives rise to a partial order, where states are ordered according to their suitability to act as a resource. In the literature, various different partial or

Lory Aintablian, Christian Blohmann

The infinitesimal counterpart of a Lie groupoid is its Lie algebroid. As a vector bundle, it is given by the source vertical tangent bundle restricted to the identity bisection. Its sections can be identified with the invariant vector fields on the groupoid, which are closed under the Lie bracket. We generalize this differentiation procedure to groupoid obje

Arezoo Borji, Hossam Haick, Birgit Pohn, Antonia Graf

In vitro fertilization (IVF) is a widely utilized assisted reproductive technology, yet predicting its success remains challenging due to the multifaceted interplay of clinical, demographic, and procedural factors. This study develops a robust artificial intelligence (AI) pipeline aimed at predicting live birth outcomes in IVF treatments. The pipeline uses a

Stijn Cambie, Wouter Cames van Batenburg, Daniel W. Cranston

A recolouring sequence, between $k$-colourings $\alpha$ and $\beta$ of a graph $G$, transforms $\alpha$ into $\beta$ by recolouring one vertex at a time, such that after each recolouring step we again have a proper $k$-colouring of $G$. The diameter of the $k$-recolouring graph, $\textrm{diam}~\mathcal{C}_k(G)$, is the maximum over all pairs $\alpha$ and $\b

M. Zhu, Leandro M. Chinellato, V. Romerio, N. Murai

We combine ultra-high-resolution inelastic neutron scattering and quantum Monte Carlo simulations to study thermodynamics and spin excitations in the spin-supersolid phase of the triangular lattice XXZ antiferromagnet K$_2$Co(SeO$_3$)$_2$ under zero and non-zero magnetic field. BKT transitions signaling the onset of Ising and supersolid order are clearly ide

Rongping Shen

The profound impact of online reviews on consumer decision-making has made it crucial for businesses to manage negative reviews. Recent advancements in artificial intelligence (AI) technology have offered businesses novel and effective ways to manage and analyze substantial consumer feedback. In response to the growing demand for explainablility and transpar

Yang-Yang Li, Juven Wang, Yi-Zhuang You

Charge conjugation (C), mirror reflection (R), and time reversal (T) symmetries, along with internal symmetries, are essential for massless Majorana and Dirac fermions. These symmetries are sufficient to rule out potential fermion bilinear mass terms, thereby establishing a gapless free fermion fixed point phase, pivotal for symmetric mass generation (SMG) t

Sebastián Buss, Diego Castaño, José Patricio Díaz Varela

A nucleus $\gamma$ on a (bounded commutative integral) residuated lattice $\mathbf{A}$ is a closure operator that satisfies the inequality $\gamma(a) \cdot \gamma(b) \leq \gamma(a \cdot b)$ for all $a,b \in A$. In this article, among several results, a description of an arbitrary nucleus on a residuated lattice is given. Special attention is given to terms t

Antoine Deza, Kai Huang, Carlos Aníbal Suárez

This paper presents an extension of a recently introduced multistage stochastic integer model designed for optimizing the deployment of charging stations under uncertainty. A key contribution of this work is incorporating additional constraints accounting for congestion management at charging stations. The solution approach combines a greedy heuristic with a

Jana Zakall, Birgit Pohn, Antonia Graf, Daniel Kovatchki

Artificial intelligence (AI) has emerged as a powerful tool to enhance decision-making and optimize treatment protocols in in vitro fertilization (IVF). In particular, AI shows significant promise in supporting decision-making during the ovarian stimulation phase of the IVF process. This review evaluates studies focused on the applications of AI combined wit

Razu Ahmed, Md. Sohel Rana, Md. Sajidul Islam, S. H. Naqib

Transition-metal borides (TMBs) have long attracted attention of the researchers because of their unique mechanical and electrical properties including superconductivity. We have explored the structural, mechanical, electronic, optical, and some thermophysical properties of XB$_2$ (X = Cr, Mo and W) binary metallic diborides in detail employing density funct

Harish P. Jain, Richard D. J. G. Ho, Luiza Angheluta

T1 transitions, which are localised cell rearrangements, play an important role in the fluidization of epithelial monolayers. Using a multi-phase field model and an active elastic solid model, we show that although each cell undergoes T1 transitions in time as uncorrelated, random events, the spatial distribution of these events is highly correlated and is d

Jingchun Lian, Lingyu Liu, Yaxiong Wang, Yujiao Wu

Existing facial forgery detection methods typically focus on binary classification or pixel-level localization, providing little semantic insight into the nature of the manipulation. To address this, we introduce Forgery Attribution Report Generation, a new multimodal task that jointly localizes forged regions ("Where") and generates natural language explana

Jiang Liu, Bolin Li, Haoyuan Li, Tianwei Lin

Efficient multimodal large language models (EMLLMs), in contrast to multimodal large language models (MLLMs), reduce model size and computational costs and are often deployed on resource-constrained devices. However, due to data privacy concerns, existing open-source EMLLMs rarely have access to private domain-specific data during the pre-training process, m

Ondřej Zelenka, Ondřej Kopáček, Georgios Lukes-Gerakopoulos

The width of a resonance in a nearly integrable system, i.e. in a non-integrable system where chaotic motion is still not prominent, can tell us how a perturbation parameter is driving the system away from integrability. Although the tool that we are presenting here can be used is quite generic and can be used in a variety of systems, our particular interest

Mahendra Kumar Gohil, Anirudha Bhattacharjee, Rwik Rana, Kishan Lal

Over the past decade, several image-processing methods and algorithms have been proposed for identifying plant diseases based on visual data. DNN (Deep Neural Networks) have recently become popular for this task. Both traditional image processing and DNN-based methods encounter significant performance issues in real-time detection owing to computational limi

Philip Schlösser, Mikhail Isachenkov

We use Matsuki's decomposition for symmetric pairs $(G, H)$ of (not necessarily compact) reductive Lie groups to construct the radial parts for invariant differential operators acting on matrix-spherical functions. As an application, we employ this machinery to formulate an alternative, mathematically rigorous approach to obtaining radial parts of Casimir op

Sanjay Pant, Himanshu Parihar

We study mixed state entanglement measures in a higher dimensional $T\bar{T}$ deformed field theory at finite temperature. The holographic dual is described by AdS$_{d+1}$ black brane geometry with a finite cutoff. We compute the entanglement wedge cross section (EWCS), proposed to be dual to entanglement of purification (EoP) and holographic entanglement ne

Krzysztof Bartoszek, Ying Luo

Visualizing data through Czekanowski's diagram has as its aim the illustration of the relationships between objects. Often, obvious clusters of observations are directly visible. However, it is not straightforward to precisely delineate these clusters. This paper presents the development of the package RMaCzek, which now includes features for cluster identif

Paolo Acquistapace, Francesco Bartaloni

An abstract nonautonomous parabolic linear-quadratic regulator problem with very general final cost operator P_T is considered, subject to the same assumptions under which a classical solution of the associated differential Riccati equation was shown to exist, in two papers appeared in 1999 and 2000, by Terreni and the first named author. We prove an optimal

Mihailo Stojnic

We study deep ReLU feed forward neural networks (NN) and their injectivity abilities. The main focus is on \emph{precisely} determining the so-called injectivity capacity. For any given hidden layers architecture, it is defined as the minimal ratio between number of network's outputs and inputs which ensures unique recoverability of the input from a realizab

Guangsheng Xu, Guoyi Zhang, Lejia Ye, Shuwei Gan

Transformer-based methods have recently achieved significant success in 3D human pose estimation, owing to their strong ability to model long-range dependencies. However, relying solely on the global attention mechanism is insufficient for capturing the fine-grained local details, which are crucial for accurate pose estimation. To address this, we propose SS

A. Hammad, Raymundo Ramos

In this paper, we introduce a scanner package enhanced by deep learning (DL) techniques. The proposed package addresses two significant challenges associated with previously developed DL-based methods: slow convergence in high-dimensional scans and the limited generalization of the DL network when mapping random points to the target space. To tackle the firs

Sai Satyam Samal, Smitha Vishveshwara, Yuval Gefen, Jukka I. Väyrynen

Collision of quantum particles remains an effective way of probing their mutual statistics. Colliders based on quantum point contacts in quantum Hall edge states have been successfully used to probe the statistics of the underlying quantum particles. Notwithstanding the extensive theoretical work focusing on point-like colliders, when it comes to experiment,

Arjan van der Schaft

Control theory often takes the mathematical model of the to-be-control-led system for granted. In contrast, port-Hamiltonian systems theory bridges the gap between modelling and control for physical systems. It provides a unified framework for the modelling of complex multiphysics systems. At the same time it offers powerful tools for analysis and control by

Dmitry S. Ageev, Vasilii V. Pushkarev, Anastasia N. Zueva

The spectral form factor is believed to exhibit a special type of behavior called ``dip-ramp-plateau'' in chaotic quantum systems that originates from random matrix theory. This suggests that the shape of the spectral form factor could serve as an indicator of chaos in various quantum systems. It has been shown recently that the dip-ramp-plateau structure ap

Daniel A. M. Villela

Predicting whether to expect a high incidence of infectious diseases is critical for health surveillance. In the epidemiology of dengue, environmental conditions can significantly impact the transmission of the virus. Utilizing epidemiological indicators alongside environmental variables can enhance predictions of dengue incidence risk. This study analyzed a

Cecilia R. Cimadamore, Laura A. Rueda, Néstor Thome, Melina V. Verdecchia

The aim of this paper is to study lattice properties of the sharp partial order for complex matrices having index at most 1. We investigate the down-set of a fixed matrix $B$ under this partial order via isomorphisms with two different partially ordered sets of projectors. These are, respectively, the set of projectors that commute with a certain (nonsingula

Xinze Li, Yixin Cao, Yubo Ma, Aixin Sun

Extending context windows (i.e., Long Context, LC) and using retrievers to selectively access relevant information (i.e., Retrieval-Augmented Generation, RAG) are the two main strategies to enable LLMs to incorporate extremely long external contexts. This paper revisits recent studies on this topic, highlighting their key insights and discrepancies. We then

Joscha Diehl, Rosa Preiß, Jeremy Reizenstein

Given a feature set for the shape of a closed loop, it is natural to ask which features in that set do not change when the starting point of the path is moved. For example, in two dimensions, the area enclosed by the path does not depend on the starting point. In the present article, we characterize such loop invariants among all those features known as inte

Xinglong Zhang, Wei Pan, Cong Li, Xin Xu

Distributed model predictive control (DMPC) is promising in achieving optimal cooperative control in multirobot systems (MRS). However, real-time DMPC implementation relies on numerical optimization tools to periodically calculate local control sequences online. This process is computationally demanding and lacks scalability for large-scale, nonlinear MRS. T

Marco Autili, Martina De Sanctis, Paola Inverardi, Patrizio Pelliccione

As testified by new regulations like the European AI Act, worries about the human and societal impact of (autonomous) software technologies are becoming of public concern. Human, societal, and environmental values, alongside traditional software quality, are increasingly recognized as essential for sustainability and long-term well-being. Traditionally, syst

Jorn van Voorthuizen

Multipole moments in general relativity serve as a powerful tool for characterising the gravitational field. In this paper, we review the construction of the Geroch--Hansen multipole moments for stationary asymptotically flat vacuum spacetimes. A particular focus is placed on the well-definedness of these moments, which hinges on the uniqueness of the one-po

Alessandro D'Adda, Noboru Kawamoto, Jun Saito, Kazuhiro Nagata

We propose a lattice formulation of four dimensional super Yang-Mills model with a twisted N=4 supersymmetry in a manifestly gauge covariant manner. The formulation we employ here is a four dimensional extension of the manifestly gauge covariant method which was developed in our proposals of Dirac-Kahler twisted N=D=2 and N=4 D=3 super Yang-Mills on a lattic

Shulei Cao, Amit Kumar Mandal, Michal Zajaček, Bożena Czerny

We test the standardizability of a homogeneous sample of 41 lower-redshift ($0.00415\leq z \leq 0.474$) active galactic nuclei (AGNs) reverberation-mapped (RM) using the broad H$\alpha$ and H$\beta$ emission lines. We find that these sources can be standardized using four radius$-$luminosity ($R-L$) relations incorporating H$\alpha$ and H$\beta$ time delays

Soumya K. Saha, P. K. Mohanty

We study the $q$-state Potts model on a square lattice with directed nearest-neighbor spin-spin interactions that are inherently non-reciprocal. Both equilibrium and non-equilibrium dynamics are investigated. Analytically, we demonstrate that non-reciprocal interactions do not alter the critical exponents of the model under equilibrium dynamics. In contrast,

Siyu Wang, Cailian Chen, Xinyi Le, Qimin Xu

Computer-aided design (CAD) significantly enhances the efficiency, accuracy, and innovation of design processes by enabling precise 2D and 3D modeling, extensive analysis, and optimization. Existing methods for creating CAD models rely on latent vectors or point clouds, which are difficult to obtain, and storage costs are substantial. Recent advances in Mult

Youwei He, Jeong-Dong Lee, Seungmin Lee

The frameworks that explore scientific and technological evolution suggest that discoveries and inventions are intrinsic processes, while the wealth of knowledge accumulated over time enables researchers to make further advancements, echoing Newton's sentiment of "standing on the shoulders of giants." Despite the exponential growth in new scientific and tech

Valentina Pederzoli, Mattia Corti, Davide Riccobelli, Paola F. Antonietti

The aim of this paper is to introduce, analyse and test in practice a new mathematical model describing the interplay between biological tissue atrophy driven by pathogen diffusion, with applications to neurodegenerative disorders. This study introduces a novel mathematical and computational model comprising a Fisher-Kolmogorov equation for species diffusion

Takashi Toma

Minimal dark matter is an attractive candidate for dark matter because it is stabilized without the need to impose additional symmetries. It is known that the $SU(2)_L$ quintuplet fermion can serve as a minimal dark matter candidate, with its mass predicted to be around $14~\mathrm{TeV}$, based on the thermal production mechanism. In this work, we embed the

Ruchi Guo

One remarkable feature of virtual element methods (VEMs) is their great flexibility and robustness when used on almost arbitrary polytopal meshes. This very feature makes it widely used in both fitted and unfitted mesh methods. Despite extensive numerical studies, a rigorous analysis of robust optimal convergence has remained open for highly anisotropic 3D p

Ratip Emin Berker, Emanuel Tewolde, Ioannis Anagnostides, Tuomas Sandholm

Imperfect-recall games, in which players may forget previously acquired information, have found many practical applications, ranging from game abstractions to team games and testing AI agents. In this paper, we quantify the utility gain by endowing a player with perfect recall, which we call the value of recall (VoR). While VoR can be unbounded in general, w

Jérôme Buzzi, Chiyi Luo, Dawei Yang

Let $f$ be a $C^r$ surface diffeomorphism with large entropy (more precisely, $h_{\rm top}(f)>\lambda_{\min}(f)/{r}$). Then the number of ergodic measures of maximal entropy is upper semicontinuous at $f$. This generalizes the $C^\infty$ case studied in \cite{BCS22}, answering Question 1.9 there. Moreover, the number of such measures is locally constant if a

Zhian Jia

We propose a (1+1)D lattice model, inspired by a weak Hopf algebra generalization of the cluster state model, which realizes Haagerup fusion category symmetry and features a tensor product Hilbert space. The construction begins with a reconstruction of the Haagerup weak Hopf algebra $H_3$ from the Haagerup fusion category, ensuring that the representation ca

Zhenqiao Cheng, Chongjun Ouyang, Xingqi Zhang

A novel movable antenna (MA)-aided secure transmission framework is proposed to enhance the secrecy transmission rate without relying on the eavesdropper's channel state information. Within this framework, a joint beamforming and jamming scheme is proposed, where the power of the confidential signal is minimized by optimizing the positions of the MAs, and th

Sung-Soo Kim, Xiaobin Li, Futoshi Yagi, Rui-Dong Zhu

We revisit the instanton partition function for 5d $\mathcal{N}=1$ SO($N$) gauge theories compactified on S$^1$, computed from the topological vertex formalism with the O-vertex based on a 5-brane web diagram with an O5-plane. We introduce an identity that enables us to rewrite the unrefined partition function into a new expression in terms of the Nekrasov f

Jiaqi Wang, Ziyi Yin, Quanzeng You, Lingjuan Lyu

Geographic health disparities pose a pressing global challenge, particularly in underserved regions of low- and middle-income nations. Addressing this issue requires a collaborative approach to enhance healthcare quality, leveraging support from medically more developed areas. Federated learning emerges as a promising tool for this purpose. However, the scar

Alfredo Guevara, Yangrui Hu

A holographic CFT description of asymptotically flat spacetimes inherits vacuum degeneracies and IR divergences from its gravitational dual. We devise a Quantum Error Correcting (QEC) framework to encode both effects as correctable fluctuations on the CFT dual. The framework is physically motivated by embedding a chain of qudits in the so-called Klein spacet

Feilong Tang, Zhongxing Xu, Ming Hu, Wenxue Li

In medical image analysis, multi-organ semi-supervised segmentation faces challenges such as insufficient labels and low contrast in soft tissues. To address these issues, existing studies typically employ semi-supervised segmentation techniques using pseudo-labeling and consistency regularization. However, these methods mainly rely on individual data sample

Jan Kiwi, Hongming Nie

We study extensions of the measure of maximal entropy to suitable compactifications of the parameter space and the moduli space of rational maps acting on the Riemann sphere. For parameter space, we consider a space which resolves the discontinuity of the iterate map. We show that the measure of maximal entropy extends continuously to this resolution space.

Zhongxing Xu, Feilong Tang, Zhe Chen, Yingxue Su

The application of Contrastive Language-Image Pre-training (CLIP) in Weakly Supervised Semantic Segmentation (WSSS) research powerful cross-modal semantic understanding capabilities. Existing methods attempt to optimize input text prompts for improved alignment of images and text, by finely adjusting text prototypes to facilitate semantic matching. Neverthel

John Augustine, Soumyottam Chatterjee, Valerie King, Manish Kumar

We extend the study of retrieval problems in distributed networks, focusing on improving the efficiency and resilience of protocols in the \emph{Data Retrieval (DR) Model}. The DR Model consists of a complete network (i.e., a clique) with $k$ peers, up to $\beta k$ of which may be Byzantine (for $\beta \in [0, 1)$), and a trusted \emph{External Data Source}

X. Feng, D. Zhang, S. Hu, X. Li

Vision-Language Tracking (VLT) aims to localize a target in video sequences using a visual template and language description. While textual cues enhance tracking potential, current datasets typically contain much more image data than text, limiting the ability of VLT methods to align the two modalities effectively. To address this imbalance, we propose a nov

Junkang Huang, Satoshi Nawata, Yutai Zhang, Shutong Zhuang

We study the representation theory of the spherical double affine Hecke algebra (DAHA) of $C^\vee C_1$, using brane quantization. By showing a one-to-one correspondence between Lagrangian $A$-branes with compact support and finite-dimensional representations of the spherical DAHA, we provide evidence of derived equivalence between the $A$-brane category of $

Diego A. Silva, Ahmed Elsheikh, Kamilya Smagulova, Mohammed E. Fouda

Event-based cameras are sensors that simulate the human eye, offering advantages such as high-speed robustness and low power consumption. Established Deep Learning techniques have shown effectiveness in processing event data. Chimera is a Block-Based Neural Architecture Search (NAS) framework specifically designed for Event-Based Object Detection, aiming to

Tao Wu, Yong Zhang, Xiaodong Cun, Zhongang Qi

Zero-shot customized video generation has gained significant attention due to its substantial application potential. Existing methods rely on additional models to extract and inject reference subject features, assuming that the Video Diffusion Model (VDM) alone is insufficient for zero-shot customized video generation. However, these methods often struggle t

Adam J. Harper

We prove two estimates for the Barban--Davenport--Halberstam type variance of a general complex sequence in arithmetic progressions. The proofs are elementary, and our estimates are capable of yielding an asymptotic for the variance when the sequence is sufficiently nice, and is either somewhat sparse or is sufficiently like the integers in its divisibility