December 2024 arXiv papers — page 84

Congning Ni, Qingxia Chen, Lijun Song, Patricia Commiskey

Informal caregivers (e.g.,family members or friends) of people living with Alzheimers Disease and Related Dementias (ADRD) face substantial challenges and often seek informational or emotional support through online communities. Understanding the factors that drive engagement within these platforms is crucial, as it can enhance their long-term value for care

J. Eduardo Vera-Valdés, Olivia Kvist

Climate change communication is crucial to raising awareness and motivating action. In the context of breaching the limits set out by the Paris Agreement, we argue that climate scientists should move away from point estimates and towards reporting probabilities. Reporting probabilities will provide policymakers with a range of possible outcomes and will allo

L. Feher

We study strongly isochronous Hamiltonians that generate periodic time evolution with the same basic period for a dense set of initial values. We explain that all such Hamiltonians are maximally superintegrable, and show that if the system is subjected to Hamiltonian reduction based on a compact symmetry group and certain conditions are met, then the reduced

Katharina Klioba, Christian Seifert

In this paper, we present an abstract framework to obtain convergence rates for the approximation of random evolution equations corresponding to a random family of forms determined by finite-dimensional noise. The full discretization error in space, time, and randomness is considered, where polynomial chaos expansion (PCE) is used for the semi-discretization

Peter Wu, Bohan Yu, Kevin Scheck, Alan W Black

The amount of articulatory data available for training deep learning models is much less compared to acoustic speech data. In order to improve articulatory-to-acoustic synthesis performance in these low-resource settings, we propose a multimodal pre-training framework. On single-speaker speech synthesis tasks from real-time magnetic resonance imaging and sur

Luís F. Gomes, Vincent J. Hellendoorn, Jonathan Aldrich, Rui Abreu

This paper explores the integration of Visual Code Assistants in Integrated Development Environments (IDEs). In Software Engineering, whiteboard sketching is often the initial step before coding, serving as a crucial collaboration tool for developers. Previous studies have investigated patterns in SE sketches and how they are used in practice, yet methods fo

Zainab Malik

Using the fact that, for a broad class of Morris-Thorne wormholes, the maximum of the effective potential is located at the throat, we derive accurate analytic WKB expressions for the quasinormal modes and grey-body factors of various traversable wormholes. In the eikonal limit, these analytic expressions acquire a compact form and satisfy the correspondence

Fedor Pakovich

We describe algebraic curves $ X : F(x, y) = 0 $ defined over $\overline{\mathbb{Q}}$ that satisfy the following property: there exist a number field $k$ and an infinite set $S \subset k$ such that, for every $y \in S$, the roots of the polynomial $F(x, y)$ belong to $k$.

Julius Busse

Motivated by a recent publication by Ishiwata and Nakata (2022), we prove that sufficiently regular stochastic delay differential equations (SDDEs) with a single discrete delay have blow up solutions if and only if their undelayed counterparts have them, using a comparison theorem by Ikeda and Watanabe (1977). This result has applications in mathematical bio

Ivan Alvarez-Rios, Francisco S. Guzman, Jens Niemeyer

In the context of Fuzzy Dark Matter (FDM) we study the core formation in the presence of an Ideal Gas (IG). Our analysis is based on the solution of the Schr\"odinger-Poisson-Euler system of equations that drives the evolution of FDM together with a compressible IG, both coupled through the gravitational potential they produce. Starting from random initial c

Jiazheng Li, Artem Bobrov, David West, Cesare Aloisi

In this demo, we present AERA Chat, an automated and explainable educational assessment system designed for interactive and visual evaluations of student responses. This system leverages large language models (LLMs) to generate automated marking and rationale explanations, addressing the challenge of limited explainability in automated educational assessment

Jonathan Shaki, Yonatan Aumann, Sarit Kraus

Issue salience is a major determinant in voters' decisions. Candidates and political parties campaign to shift salience to their advantage - a process termed priming. We study the dynamics, strategies and equilibria of campaign spending for voter priming in multi-issue multi-party settings. We consider both parliamentary elections, where parties aim to maxim

Aiden Gundersen, Neil J. Cornish

The analysis of pulsar timing array data has provided evidence for a gravitational wave background in the nanohertz band. This raises the question of what is the source of the signal, is it astrophysical or cosmological in origin? If the signal originates from a population of supermassive black hole binaries, as is generally assumed, we can expect to see evi

Onkar Thorat, Philippe Laban, Chien-Sheng Wu

Detecting factual inconsistencies in summarization is critical, yet existing benchmarks lack the necessary challenge and interpretability for robust evaluation. In this paper, we introduce SummExecEdit, a novel pipeline and benchmark leveraging executable edits to assess models on their ability to both detect factual errors and provide accurate explanations.

Gagan Bhatia, MingZe Tang, Cristina Mahanta, Madiha Kazi

This paper introduces DateLogicQA, a benchmark with 190 questions covering diverse date formats, temporal contexts, and reasoning types. We propose the Semantic Integrity Metric to assess tokenization quality and analyse two biases: Representation-Level Bias, affecting embeddings, and Logical-Level Bias, influencing reasoning outputs. Our findings provide a

Christian Green, Mehmet Ergezer, Abdurrahman Zeybey

Adversarial attacks pose significant challenges in 3D object recognition, especially in scenarios involving multi-view analysis where objects can be observed from varying angles. This paper introduces View-Invariant Adversarial Perturbations (VIAP), a novel method for crafting robust adversarial examples that remain effective across multiple viewpoints. Unli

Samin Mahdizadeh Sani, Pouya Sadeghi, Thuy-Trang Vu, Yadollah Yaghoobzadeh

Large language models (LLMs) have made great progress in classification and text generation tasks. However, they are mainly trained on English data and often struggle with low-resource languages. In this study, we explore adding a new language, i.e., Persian, to Llama (a model with a limited understanding of Persian) using parameter-efficient fine-tuning. We

Raghul Saravanan, Sreenitha Kasarapu, Sai Manoj Pudukotai Dinakarrao

The increasing complexity of modern processor and IP designs presents significant challenges in identifying and mitigating hardware flaws early in the IC design cycle. Traditional hardware fuzzing techniques, inspired by software testing, have shown promise but face scalability issues, especially at the gate-level netlist where bugs introduced during synthes

Dimitri Gurevich, Pavel Saponov, Mikhail Zaitsev

Quantum differential operators on Reflection Equation Algebras, corresponding to Hecke symmetries R were introduced in previous publications. In the present paper we are mainly interested in quantum analogs of the Laplace and Casimir operators, which are invariant with respect to the action of the Quantum Groups U_q(sl(N)), provided R is the Drinfeld-Jimbo $

Sachin Shivakumar, Georgiy A. Bondar, Gabriel Khan, Abhishek Halder

For a given ground cost, approximating the Monge optimal transport map that pushes forward a given probability measure onto another has become a staple in several modern machine learning algorithms. The fourth-order Ma-Trudinger-Wang (MTW) tensor associated with this ground cost function provides a notion of curvature in optimal transport. The non-negativity

Yiping Wang, Xuehai He, Kuan Wang, Luyao Ma

The current state-of-the-art video generative models can produce commercial-grade videos with highly realistic details. However, they still struggle to coherently present multiple sequential events in the stories specified by the prompts, which is foreseeable an essential capability for future long video generation scenarios. For example, top T2V generative

Carlos Doebeli, Alessandro Astolfi, Dante Kalise, Alessio Moreschini

We propose a procedure for the numerical approximation of invariance equations arising in the moment matching technique associated with reduced-order modeling of high-dimensional dynamical systems. The Galerkin residual method is employed to find an approximate solution to the invariance equation using a Newton iteration on the coefficients of a monomial bas

Asghar A. Jadoon, Karl A. Kalina, Manuel K. Rausch, Reese Jones

Composite materials often exhibit mechanical anisotropy owing to the material properties or geometrical configurations of the microstructure. This makes their inverse design a two-fold problem. First, we must learn the type and orientation of anisotropy and then find the optimal design parameters to achieve the desired mechanical response. In our work, we so

David Klaška, Antonín Kučera, Vojtěch Kůr, Vít Musil

The long-run average payoff per transition (mean payoff) is the main tool for specifying the performance and dependability properties of discrete systems. The problem of constructing a controller (strategy) simultaneously optimizing several mean payoffs has been deeply studied for stochastic and game-theoretic models. One common issue of the constructed cont

Justin Berman, Henriette Elvang, Nicholas Geiser, Loki L. Lin

We re-examine positivity bounds on the $2\to2$ scattering of identical massless real scalars with a novel perspective on how these bounds can be used to constrain the spectrum of UV theories. We propose that the entire space of consistent weakly-coupled (and generically non-supersymmetric) UV amplitudes is determined as a convex hull of the massive scalar am

Diego Rojas La Luz, Gheorghe Craciun, Polly Y. Yu

We study the global stability of generalized Lotka-Volterra systems with generalized polynomial right-hand side, without restrictions on the number of variables or the polynomial degree, including negative and non-integer degree. We introduce polyexponential dynamical systems, which are equivalent to the generalized Lotka-Volterra systems, and we use an anal

Jessie J. Smith, Wesley Hanwen Deng, William H. Smith, Maarten Sap

The Generative AI Ethics Playbook provides guidance for identifying and mitigating risks of machine learning systems across various domains, including natural language processing, computer vision, and generative AI. This playbook aims to assist practitioners in diagnosing potential harms that may arise during the design, development, and deployment of datase

Yueming Yan, Nathan J. Spear, Adam J. Cummings, Karina Khusainova

Heterostructures combining two or more metal and/or semiconductor nanoparticles exhibit enhanced upconversion arising from localized surface plasmon resonances (LSPRs). However, coupled plasmon-exciton systems are slowed by excitonic relaxation and metallic multi-plasmon systems are not broadly tunable. Here, we describe a heterostructure in which insulating

Shuyang Dong, Meiyi Ma, Josephine Lamp, Sebastian Elbaum

There is a growing trend toward AI systems interacting with humans to revolutionize a range of application domains such as healthcare and transportation. However, unsafe human-machine interaction can lead to catastrophic failures. We propose a novel approach that predicts future states by accounting for the uncertainty of human interaction, monitors whether

Xinliang Zhu, Michael Huang, Han Ding, Jinyu Yang

Image to image matching has been well studied in the computer vision community. Previous studies mainly focus on training a deep metric learning model matching visual patterns between the query image and gallery images. In this study, we show that pure image-to-image matching suffers from false positives caused by matching to local visual patterns. To allevi

Burak Gurlek, Daqing Wang

Single organic molecules embedded in solid-state matrices exhibit remarkable optical properties, making them competitive candidates for single-photon sources and quantum nonlinear optical elements. However, the lack of long-lived internal states imposes significant constraints on their application in the broader field of quantum technologies. In this article

Carole Bernard, Jinghui Chen, Steven Vanduffel

This paper shows that one needs to be careful when making statements on potential links between correlation and coskewness. Specifically, we first show that, on the one hand, it is possible to observe any possible values of coskewness among symmetric random variables but zero pairwise correlations of these variables. On the other hand, it is also possible to

Sudhaman Balguri, Mira B. Mahendru, Enrique O. Gonzalez Delgado, Kyle Fruhling

Recent reports of colossal negative magnetoresistance (CMR) in a few magnetic semimetals and semiconductors have attracted attention, because these materials are devoid of the conventional mechanisms of CMR such as mixed valence, double exchange interaction, and Jahn-Teller distortion. New mechanisms have thus been proposed, including topological band struct

Zhiyuan Wang

One of the most unconventional features of topological phases of matter is the emergence of quasiparticles with exotic statistics, such as non-Abelian anyons in two dimensional systems. Recently, a different type of exotic particle statistics that is consistently defined in any dimension, called $R$-parastatistics, is also shown to be possible in a special f

Jingtian Yan, Jiaoyang Li

Multi-Agent Motion Planning (MAMP) finds various applications in fields such as traffic management, airport operations, and warehouse automation. In many of these environments, differential drive robots are commonly used. These robots have a kinodynamic model that allows only in-place rotation and movement along their current orientation, subject to speed an

Mark de Berg, Arpan Sadhukhan, Frits Spieksma

We study the Dominating set problem and Independent Set Problem for dynamic graphs in the vertex-arrival model. We say that a dynamic algorithm for one of these problems is $k$-stable when it makes at most $k$ changes to its output independent set or dominating set upon the arrival of each vertex. We study trade-offs between the stability parameter $k$ of th

Mark de Berg, Arpan Sadhukhan

Let $P$ be a set of points in the plane and let $m$ be an integer. The goal of Max Cover by Unit Disks problem is to place $m$ unit disks whose union covers the maximum number of points from~$P$. We are interested in the dynamic version of Max Cover by Unit Disks problem, where the points in $P$ appear and disappear over time, and the algorithm must maintain

Yasmeen Aldossary, Nabil Hewahi, Abdulla Alasaadi

With industrial and technological development and the increasing demand for electric power, wind energy has gradually become the fastest-growing and most environmentally friendly new energy source. Nevertheless, wind power generation is always accompanied by uncertainty due to the wind speed's volatility. Wind speed forecasting (WSF) is essential for power g

Oleksiy Klurman, Igor E. Shparlinski, Joni Teräväinen

Let $N_a(x)$ denote the number of primes up to $x$ for which the integer $a$ is a primitive root. We show that $N_a(x)$ satisfies the asymptotic predicted by Artin's conjecture for almost all $1\le a\le \exp((\log \log x)^2)$. This improves on a result of Stephens (1969). A key ingredient in the proof is a new short character sum estimate over the integers,

Kai Mason, Florencia Maurino-Alperovich, Kirill Aristovich, David Holder

Magnetic Detection Electrical Impedance Tomography is a novel technique that could enable non-invasive imaging of fast neural activity in the brain. However, commercial magnetometers are not suited to its technical requirements. Computational modelling was used to determine the optimal number, size and orientation of magnetometers, to inform the future devel

Alexander Port

Motivic cohomology is powerful tool in algebraic geometry with associated realization maps giving important information about the relations between cohomological invariants of schemes and their classifying spaces. The problem of computing general cohomological invariants of these classifying spaces is ongoing. Most relevant to this paper is (1) Totaro's cons

Deijany Rodriguez Linares, Håkan Johansson

This paper introduces low-complexity frequency-dependent (memory) linearizers designed to suppress nonlinear distortion in analog-to-digital interfaces. Two different linearizers are considered, based on nonlinearity models which correspond to sampling before and after the nonlinearity operations, respectively. The proposed linearizers are inspired by convol

Paul Staat, Meik Dörpinghaus, Azadeh Sheikholeslami, Christof Paar

Today's information society relies on cryptography to achieve security goals such as confidentiality, integrity, authentication, and non-repudiation for digital communications. Here, public-key cryptosystems play a pivotal role to share encryption keys and create digital signatures. However, quantum computers threaten the security of traditional public-key c

Klaus Kroencke, Uwe Semmelmann

We show that every quaternion-K\"ahler manifold of negative scalar curvature is stable as an Einstein manifold and therefore scalar curvature rigid. In particular, this implies that every irreducible nonpositive Einstein manifold of special holonomy is stable. In contrast, we demonstrate that there exist quaternion-K\"ahler manifolds of positive scalar curva

A. K. Alkhayyata, N. M. Hewahi

In this paper, a novel classification algorithm that is based on Data Importance (DI) reformatting and Genetic Algorithms (GA) named GADIC is proposed to overcome the issues related to the nature of data which may hinder the performance of the Machine Learning (ML) classifiers. GADIC comprises three phases which are data reformatting phase which depends on D

Saeed Abbaslu, Mehran Dehpour, Yasaman Farzan, Sahar Safari

As well known, the cross sections of the resonance and Quasi-Elastic (QE) scattering off nucleons depend on quantities known as form factors that describe the nucleon structure. There are alternative approaches to determine the values of these non-perturbative quantities, some of them relying on the Neutral Current (NC) scattering of neutrinos off nucleons.

Carlos García-Martínez, Rebeca Cerezo, Manuel Bermúdez, Cristóbal Romero

Most MOOC platforms either use simple schemes for aggregating peer grades, e.g., taking the mean or the median, or apply methodologies that increase students' workload considerably, such as calibrated peer review. To reduce the error between the instructor and students' aggregated scores in the simple schemes, without requiring demanding grading calibration

Xiaofa Chen, Mattia Ornaghi

In this note we prove the existence, in the category of (strictly unital) A$_{\infty}$categories, of the pullback of a (strictly unital) A$_{\infty}$functor, satisfying a particular property (denoted by F1), along any A$_{\infty}$functor. As a consequence we provide a positive answer to Pascaleff's question whether (A$_{\infty}$Cat,$W^{\tiny\mbox{A}_{\infty}

Edward Huynh, Christian Parkinson

We consider the problem of optimal path planning on a manifold which is the image of a smooth function. Optimal path-planning is of crucial importance for motion planning, image processing, and statistical data analysis. In this work, we consider a particle lying on the graph of a smooth function that seeks to navigate from some initial point to another poin

Simina Brânzei, Nicholas J. Recker

We consider the quantum query complexity of local search as a function of graph geometry. Given a graph $G = (V,E)$ with $n$ vertices and black box access to a function $f : V \to \mathbb{R}$, the goal is find a vertex $v$ that is a local minimum, i.e. with $f(v) \leq f(u)$ for all $(u,v) \in E$, using as few oracle queries as possible. We show that the quan

Felipe Castro, Glauber Quadros, Thaísa Tamusiunas

We introduce the notion of partial representation of a weak Hopf algebra. We present the universal algebra $H_{par}^w$, which factorizes these partial representations by algebra morphisms. Also, it is shown that $\Hp$ is isomorphic to a partial smash product, that it has the structure of a Hopf algebroid and also that it can be endowed with a quantum inverse

Mohammadhossein Nahavandian, Eda Aydogan, Jesper Byggmästar, Matheus A. Tunes

High entropy alloys (HEAs) have captured much attention in recent years due to their conceivably improved radiation resistance compared to pure metals and traditional alloys. However, among HEAs, there are millions of design possibilities considering all potential compositions. In this study, we develop criteria to design HEAs with improved radiation resilie

Michal Neset, Jiří Fadrný, Martin Bielak, Jaromír Fiurášek

Noiseless quantum amplifiers are probabilistic quantum devices that enhance amplitude of coherent states without adding any noise, which has far reaching applications in quantum optics and quantum information processing. Here, we report on experimental implementation of an advanced noiseless quantum amplifier for coherent states of light that is based on con

Keltin Grimes, Marco Christiani, David Shriver, Marissa Connor

Model editing methods modify specific behaviors of Large Language Models by altering a small, targeted set of network weights and require very little data and compute. These methods can be used for malicious applications such as inserting misinformation or simple trojans that result in adversary-specified behaviors when a trigger word is present. While previ

Umang Bhaskar, A. R. Sricharan, Rohit Vaish

We study the problem of fair cake-cutting where each agent receives a connected piece of the cake. A division of the cake is deemed fair if it is equitable, which means that all agents derive the same value from their assigned piece. Prior work has established the existence of a connected equitable division for agents with nonnegative valuations using variou

Taylor Paul, William Regli

In this position paper we argue for standardizing how we share and process data in scientific workflows at the network-level to maximize step re-use and workflow portability across platforms and networks in pursuit of a foundational workflow stack. We look to evolve workflows from steps connected point-to-point in a directed acyclic graph (DAG) to steps conn

Edoardo Negri, Federico Giusti, Walter Fuscaldo, Paolo Burghignoli

Open stop-band (OSB) mitigation techniques are commonly used to improve the far-field radiating properties of leakywave antennas based on periodic structures. Recently, leaky waves have been proposed to focus energy in the near field through Bessel beams. However, the focusing character of Bessel beams is notably limited to a maximum distance known as the no

Aldo Pareja, Nikhil Shivakumar Nayak, Hao Wang, Krishnateja Killamsetty

The rise of large language models (LLMs) has created a significant disparity: industrial research labs with their computational resources, expert teams, and advanced infrastructures, can effectively fine-tune LLMs, while individual developers and small organizations face barriers due to limited resources. In this paper, we aim to bridge this gap by presentin

Laxmi, Tamer Oraby, Michael G Tyshenko, Ina Danquah

The WHO 2021 malaria report revealed that its Global Technical Strategy (GTS) 2020 milestones for morbidity and mortality, based on the 2015 baseline, have not been achieved globally -- the world is off-track by 42% and, can be extended up to 91% in 2030. Most of the Sub-Saharan African (SSA) countries failed to achieve GTS 2020 -- only 4 out of 40 highest b

Miles Q. Li, Benjamin C. M. Fung, Shih-Chia Huang

Pretraining large language models is a complex endeavor influenced by multiple factors, including model architecture, data quality, training continuity, and hardware constraints. In this paper, we share insights gained from the experience of training DMaS-LLaMa-Lite, a fully open source, 1.7-billion-parameter, LLaMa-based model, on approximately 20 billion t

Faizuddin Ahmed, Ahmad Al-Badawi, İzzet Sakallı

In this paper, we investigate the geodesic motion of test particles in the spacetime surrounding a static, spherically symmetric black hole, which is described by an AdS-Schwarzschild-like metric and incorporates a quantum correction. This black hole also features phantom global monopoles, which modify the structure of the black hole space-time. We begin by

Qitong Wang, Tang Li, Kien X. Nguyen, Xi Peng

Vision-Language Models (VLMs), such as CLIP, have already seen widespread applications. Researchers actively engage in further fine-tuning VLMs in safety-critical domains. In these domains, prediction rationality is crucial: the prediction should be correct and based on valid evidence. Yet, for VLMs, the impact of fine-tuning on prediction rationality is sel

Matias Bundgaard-Nielsen, Dirk Englund, Mikkel Heuck, Stefan Krastanov

In this paper, we introduce a numerical framework designed to solve problems within the emerging field of Waveguide Quantum Electrodynamics (WQED). The framework is based on collision quantum optics, where a localized quantum system interacts sequentially with individual time-bin modes. This approach provides a physically intuitive model that allows research

Alain Boldini, Pietro De Lellis, Salvatore Imperatore, Rishita Das

Whether in search of better trade opportunities or escaping wars, humans have always been on the move. For almost a century, mathematical models of human mobility have been instrumental in the quantification of commuting patterns and migratory fluxes. Equity is a common premise of most of these mathematical models, such that living conditions and job opportu

John Steinmetz, Maike Ostmann, Alex Neville, Brendan Pankovich

Fault-tolerant photonic quantum computing requires the generation of large entangled resource states. The required size of these states makes it challenging to simulate the effects of errors such as loss and partial distinguishability. For an interferometer with $N$ partially distinguishable input photons and $M$ spatial modes, the Fock basis can have up to

Lin Zhang, Igor Tyulnev, Lenard Vamos, Julita Poborska

Titanium diselenide (TiSe$_{2}$) is a transition-metal dichalcogenide material that undergoes a charge-density-wave (CDW) transition at $T_{c}\approx 200\,\mathrm{K}$. In a recent experiment [I. Tyulnev {\it et al.}, Commun. Mater. 6, 152 (2025)], the high harmonic generation (HHG) spectra of this material has been studied, which exhibits asymmetric behavior

Elvis Nunez, Luca Zancato, Benjamin Bowman, Aditya Golatkar

The "state" of State Space Models (SSMs) represents their memory, which fades exponentially over an unbounded span. By contrast, Attention-based models have "eidetic" (i.e., verbatim, or photographic) memory over a finite span (context size). Hybrid architectures combine State Space layers with Attention, but still cannot recall the distant past and can acce

Pierre Nataf

We show that the SU(N) Fermi-Hubbard model (FHM) on two sites, where N is the number of flavors of each fermion, corresponds to an exactly solvable two-level many-boson model that Richardson [J. Math. Phys. 9, 1327 (1968)] analytically solved long ago. We express the Bethe ansatz solutions as a function of the physical parameters of the SU(N) FHM, and recast

Arnaud Eteve

Let $\mathbf{G}$ be a connected reductive group over a finite field $\mathbb{F}_q$ of characteristic $p > 0$. In this paper, we study a category which we call Deligne--Lusztig category $\mathcal{O}$ and whose definition is similar to category $\mathcal{O}$. We use this to construct a collection of representations of $\mathbf{G}(\mathbb{F}_q)$ which we call t

Daniela Martinez Correa, Felipe Yukihide Yasumura

We compute the graded polynomial identities for the variety of graded algebras generated by the Lie algebra of upper triangular matrices of order 3 over an arbitrary field and endowed with an elementary grading. We investigate the Specht property for the same family of varieties.

He Cheng, Depeng Xu, Shuhan Yuan

Image anomaly detection (IAD) is essential in applications such as industrial inspection, medical imaging, and security. Despite the progress achieved with deep learning models like Deep Semi-Supervised Anomaly Detection (DeepSAD), these models remain susceptible to backdoor attacks, presenting significant security challenges. In this paper, we introduce Bad

Arnaud Eteve

The goal of this paper is to give a new construction of the free monodromic categories defined by Yun. We then use this formalism to give simpler constructions of the free monodromic Hecke categories and then compute the trace of Frobenius and of the identity on them. As a first application of the formalism, we produce new proofs of key theorems in Deligne--

H. Nematollahi, K. Azizi

We calculate the valence generalized parton distribution functions (GPDs) of pion at zero skewness applying a theoretical approach in which the valence GPDs are related to valence quark distribution functions, directly. To this end, we use the results of modified chiral quark model ($\chi QM$) for the valence quark distributions of pion obtained in our previ

Tiankai Xie, Jiaqing Chen, Yaoqing Yang, Caleb Geniesse

Modern machine learning often relies on optimizing a neural network's parameters using a loss function to learn complex features. Beyond training, examining the loss function with respect to a network's parameters (i.e., as a loss landscape) can reveal insights into the architecture and learning process. While the local structure of the loss landscape surrou

Pierre Nataf

We have developed an efficient method for performing density matrix renormalization group (DMRG) simulations of the SU(N) Fermi-Hubbard chain with open boundary conditions, fully leveraging the SU(N) symmetry of the problem. This method extends a previously developed approach for the SU(N) Heisenberg model and relies on the systematic use of the semi-standar

Lucas Maciel Raad

We will solve a problem by Aliaga and Perneck\'a about Lipschitz free spaces (denoted by $\mathcal F(M)$): $$\text{Does every Borel measure $\mu$ on a complete metric space $M$ such that $\int d(m,0) d |\mu|(m)< \infty$ induce a weak$^*$ continuous functional $\mathcal L\mu \in \mathcal F(M)$ by the mapping $\mathcal L\mu(f)=\int f d \mu$ ? }$$ In particular

Tyler B. Smith, Manoj Kaplinghat

The LIGO-Virgo-KAGRA (LVK) collaboration has detected over 150 confirmed gravitational wave events through O4a. Binary black hole (BBH) systems represent the overwhelming majority of these observations. We construct a model for the population of the BBHs based on the distribution of metallicities in galaxies and state-of-the-art stellar evolution models impl

Jan-Hendrik Ewers, David Anderson, Douglas Thomson

Predicting the location where a lost person could be found is crucial for search and rescue operations with limited resources. To improve the precision and efficiency of these predictions, simulated agents can be created to emulate the behavior of the lost person. Within this study, we introduce an innovative agent-based model designed to replicate diverse p

Adrien Deloro, Frank O. Wagner

We show that the action of two infinite commuting invariant rings of endomorphisms of a finite-dimensional virtually connected irreducible bi-module linearizes into a vector space over a definable field. The same holds if the action is merely by strongly commuting endogenies, modulo some finite katakernel.

Jonathan Hickman, Ajša Jančar

We present a simple geometric approach to studying the $L^p$ boundedness properties of Stein's spherical maximal operator, which does not rely on the Fourier transform. Using this, we recover a weak form of Stein's spherical maximal theorem.

Tianyu Li, Badrish Chandramouli, Philip A. Bernstein, Samuel Madden

Fault-tolerance is critically important in highly-distributed modern cloud applications. Solutions such as Temporal, Azure Durable Functions, and Beldi hide fault-tolerance complexity from developers by persisting execution state and resuming seamlessly from persisted state after failure. This pattern, often called durable execution, usually forces frequent

Rachel Woods-Robinson, Amila Abeynayaka, Mik Carbajales-Dale, Hao Chen

Public and private interest in life cycle assessment (LCA) has grown as environmental disclosure norms tighten, driving demand for decision-relevant assessment early in technological development cycles. Early-stage LCA has the potential to guide design choices, steer innovation, and mitigate lock-in of adverse environmental impacts. However, many aspects of

Masha Vlasenko

These are notes of my lecture courses given in the summer of 2024 in the School on Number Theory and Physics at ICTP in Trieste and in the 27th Brazilian Algebra Meeting at IME-USP in S\~ao Paulo. We give an elementary account of $p$-adic methods in de Rham cohomology of algebraic hypersurfaces with explicit examples and applications in number theory and com

Till Aust, Eduard Buss, Felix Mohr, Heiko Hamann

In our project WatchPlant, we propose to use a decentralized network of living plants as air-quality sensors by measuring their electrophysiology to infer the environmental state, also called phytosensing. We conducted in-lab experiments exposing ivy (Hedera helix) plants to ozone, an important pollutant to monitor, and measured their electrophysiological re

Veer Vohra, Devyani Vij, Jehil Mehta, Arman Ozcan

This paper investigates cash productivity as a signal for future stock performance, building on the cash-return framework of Faulkender and Wang (2006). Using financial and market data from WRDS, we calculate cash returns as a proxy for operational efficiency and evaluate a long-only strategy applied to Nasdaq-listed non-financial firms. Results show limited

Thomas Jan Mikhail

We introduce and study a purely syntactic notion of lax cones and $(\infty,\infty)$-limits on finite computads in \texttt{CaTT}, a type theory for $(\infty,\infty)$-categories due to Finster and Mimram. Conveniently, finite computads are precisely the contexts in \texttt{CaTT}. We define a cone over a context to be a context, which is obtained by induction o

Felipe Brevis, Lukas Körber, B. Mimica-Figari, Rodolfo A. Gallardo

The nonreciprocity created by dipolar coupling, electric currents, and Dzyaloshinskii-Moriya interactions is discussed in cases where the magnon propagation direction has a component parallel to the toroidal moment. A criterion for calculating the toroidal moments is established, addressing the issue of correct origin selection by considering compensated and

Majid Manteghi

In this paper, we present a rigorous framework for analyzing arbitrary passive matching networks using a generalized Thevenin-Helmholtz equivalent circuit. Unlike prior formulations, which often impose restrictive assumptions such as diagonal matching impedance matrices, our approach accommodates fully passive and interconnected multiport matching networks i

Gretchen R. Stahlman, Inna Kouper

This review paper explores the evolution of discussions about "long-tail" scientific data in the scholarly literature. The "long-tail" concept, originally used to explain trends in digital consumer goods, was first applied to scientific data in 2007 to refer to a vast array of smaller, heterogeneous data collections that cumulatively represent a substantial

Irina A. Kogan

Invariants withstand transformations and, therefore, represent the essence of objects or phenomena. In mathematics, transformations often constitute a group action. Since the 19th century, studying the structure of various types of invariants and designing methods and algorithms to compute them remains an active area of ongoing research with an abundance of

Qianyi Zhang, Jinzheng Guang, Zhenzhong Cao, Jingtai Liu

Navigating narrow roads with oncoming vehicles is a significant challenge that has garnered considerable public interest. These scenarios often involve sections that cannot accommodate two moving vehicles simultaneously due to the presence of stationary vehicles or limited road width. Autonomous vehicles must therefore profoundly comprehend their surrounding

Nikolaos Triantafyllou, Giorgos Korkidis, Vasiliki Pavlidou, Paolo Bonfini

Galaxy clusters are important cosmological probes that have helped to establish the $\mathrm{\Lambda}$CDM paradigm as the standard model of cosmology. However, recent tensions between different types of high-accuracy data highlight the need for novel probes of the cosmological parameters. Such a probe is the turnaround density: the mass density on the scale

Pavan Kumar Anasosalu Vasu, Fartash Faghri, Chun-Liang Li, Cem Koc

Scaling the input image resolution is essential for enhancing the performance of Vision Language Models (VLMs), particularly in text-rich image understanding tasks. However, popular visual encoders such as ViTs become inefficient at high resolutions due to the large number of tokens and high encoding latency caused by stacked self-attention layers. At differ

Emile Pangburn, Catherine Pépin, Anurag Banerjee

We investigate the emergence of topological features in the charge excitations of Mott insulators in the Chern-Hubbard model. In the strong correlation regime, treating electrons as the sum of holons and doublons excitations, we compute the topological phase diagram of Mott insulators at half-filling using composite operator formalism. The Green function zer

Praveen Bharadwaj, Ranjeet Kumar, Hemant Kumar Prajapati, Rahul Srivastava

The current generation of Dark Matter Direct Detection Experiments has ruled out a large region of parameter space for dark matter, particularly in the ($10 - 1000$) GeV mass range. However, due to very low event rates, searching for dark matter in the heavy mass range, $\mathcal{O}$(TeV), is a daunting task requiring even larger volume detectors and long ex

Bastien Duboeuf, Michele Galli, Emanuel Malek, Henning Samtleben

Maximal supergravities in ten and eleven dimensions admit consistent truncations on particular spheres to maximal supergravities in lower dimensions. Concurrently, the truncation to singlets under any subgroup of the sphere isometry group leads to consistent truncations with less or no supersymmetry. We review the relation between these truncations in the fr

Eichi Takaya, Shinnosuke Yamamoto

Annotation of medical images, such as MRI and CT scans, is crucial for evaluating treatment efficacy and planning radiotherapy. However, the extensive workload of medical professionals limits their ability to annotate large image datasets, posing a bottleneck for AI applications in medical imaging. To address this, we propose In-context Cascade Segmentation

Daniel Andrés Díaz-Pachón, H. Renata Gallegos, Ola Hössjer, J. Sunil Rao

In this paper, we study learning and knowledge acquisition (LKA) of an agent about a proposition that is either true or false. We use a Bayesian approach, where the agent receives data to update his beliefs about the proposition according to a posterior distribution. The LKA is formulated in terms of active information, with data representing external or exo

Alexandra Gurinovich

Development of high-power pulsed radiation sources in any frequency range requires both generation of high power to drive the source and increasing the efficiency of supplied power to radiated electromagnetic field conversion. The former implies generation of high power (that is equal to high-voltage and high-current) pulses. The latter means use of an elect

Saher Mohamed, Kirollos Farah, Abdelrahman Lotfy, Kareem Rizk

Knowledge graphs are an efficient method for representing and connecting information across various concepts, useful in reasoning, question answering, and knowledge base completion tasks. They organize data by linking points, enabling researchers to combine diverse information sources into a single database. This interdisciplinary approach helps uncover new