November 2024 arXiv papers — page 116

Benedetta Muscato, Praveen Bushipaka, Gizem Gezici, Lucia Passaro

Subjective NLP tasks usually rely on human annotations provided by multiple annotators, whose judgments may vary due to their diverse backgrounds and life experiences. Traditional methods often aggregate multiple annotations into a single ground truth, disregarding the diversity in perspectives that arises from annotator disagreement. In this preliminary stu

Federico Rossi, Eirik F. Kjønstad, Sara Angelico, Henrik Koch

Coupled cluster theory in the standard formulation is unable to correctly describe conical intersections among states of the same symmetry. This limitation has restricted the practical application of an otherwise highly accurate electronic structure model, particularly in nonadiabatic dynamics. Recently, the intersection problem among the excited states was

Moaad Khamlich, Federico Pichi, Michele Girfoglio, Annalisa Quaini

We present a novel reduced-order Model (ROM) that leverages optimal transport (OT) theory and displacement interpolation to enhance the representation of nonlinear dynamics in complex systems. While traditional ROM techniques face challenges in this scenario, especially when data (i.e., observational snapshots) is limited, our method addresses these issues b

Irfan Habib

Any maximal root subsystem of a finite crystallographic reduced root system is either a closed root subsystem or its dual is a closed root subsystem in the dual root system. In this article, we classify the maximal root subsystems of an affine reflection system (reduced and non-reduced) and prove that this result holds in much more generality for reduced aff

V. Gutlyanskii, V. Ryazanov, A. Salimov, R. Salimov

Here we give a survey of consequences from the theory of the Beltrami equations in the complex plane $\mathbb C$ to generalized Cauchy-Riemann equations $\nabla v = B \nabla u$ in the real plane $\mathbb R^2$ and clarify the relationships of the latter to the $A-$harmonic equation ${\rm div} A\,{\rm grad}\, u = 0$ with matrix valued coefficients $A$ that is

Miguel Ratis Laude

In recent years, the study of holomorphic correspondences as dynamical systems that can display behaviors of both rational maps and Kleinian groups has gained a good amount of attention. This phenomenon is related to the Sullivan dictionary, a list of parallels between the theories of these two systems. We build upon a surgical construction of such matings,

Tao Jing, Cheng Li

We have developed a new regression technique, the maximum likelihood (ML)-based method and its variant, the KS-test based method, designed to obtain unbiased regression results from typical astronomical data. A normalizing flow model is employed to automatically estimate the unobservable intrinsic distribution of the independent variable as well as the unobs

Marco Schlichting

We prove basic statements about the Hermitian K-theory of exact form categories with weak equivalences. Notably, we extend a quadratic functor with values in abelian groups from an exact category to its category of bounded chain complexes in a way that does not change Grothendieck-Witt spaces. This is used in joint work with Marlowe for the comparison of the

Clément Dumas, Chris Wendler, Veniamin Veselovsky, Giovanni Monea

A central question in multilingual language modeling is whether large language models (LLMs) develop a universal concept representation, disentangled from specific languages. In this paper, we address this question by analyzing latent representations (latents) during a word-translation task in transformer-based LLMs. We strategically extract latents from a s

Jahanzaib Malik, Fabrizio Pastore

Software-defined systems revolutionized the management of hardware devices but introduced quality assurance challenges that remain to be tackled. For example, software defined networks (SDNs) became a key technology for the prompt reconfigurations of network services in many sectors including telecommunications, data centers, financial services, cloud provid

Nastassia Grimm, Martin Pijnenburg, Giulia Cusin, Camille Bonvin

Pulsar timing array experiments have recently found evidence for a stochastic gravitational wave (GW) background, which induces correlations among pulsar timing residuals described by the Hellings and Downs (HD) curve. Standard calculations of the HD correlation and its variance assume an isotropic background. However, for a background of astrophysical origi

Xiang Yu, Shuqiang Zhu

We apply the singular sequence method to investigate the finiteness problem for stationary configurations of the planar five-vortex problem. The initial step of the singular sequence method involves identifying all two-colored diagrams. These diagrams represent potential scenarios where finiteness may fail. We determined all such diagrams for the planar five

Guido Violano, Savino Dibitonto, Luciano Afferrante

Engineering technologies frequently draw inspiration from nature, as exemplified in bio-inspired adhesive surfaces. These surfaces present textures adorned by pillars, mimicking the topography found on the pads of certain animals renowned for their exceptional adhesive capabilities. The adhesive response is strongly influenced by the morphology of these pill

Dingdong Wang, Mingyu Cui, Dongchao Yang, Xueyuan Chen

With the rise of Speech Large Language Models (Speech LLMs), there has been growing interest in discrete speech tokens for their ability to integrate with text-based tokens seamlessly. Compared to most studies that focus on continuous speech features, although discrete-token based LLMs have shown promising results on certain tasks, the performance gap betwee

Zhen Huang, Yuanran Zhu, Gunhee Park, Lin Lin

We present perturbative error bounds for the non-Markovian dynamics of observables in open quantum systems interacting with Gaussian environments, governed by a general Liouville dynamics. This extends the work of [Mascherpa et al., Phys. Rev. Lett. 118, 100401, 2017], which demonstrated qualitatively tighter bounds over the standard Gr\"onwall-type inequali

Eduardo Ploerer, Hitoshi Baba, Jerome Baudot, Auguste Besson

Within the context of the ALICE ITS3 collaboration, a set of MAPS small-scale test structures were developed using the 65 nm TPSCo CMOS imaging process with the upgrade of the ALICE inner tracking system as its primary focus. One such sensor, the Circuit Exploratoire 65 nm (CE-65), and its evolution the CE-65v2, were developed to explore charge collection pr

Heiko H. Schütt

Which neural networks are similar is a fundamental question for both machine learning and neuroscience. Here, it is proposed to base comparisons on the predictive distributions of linear readouts from intermediate representations. In Bayesian statistics, the prior predictive distribution is a full description of the inductive bias and generalization of a mod

Sven Ebel, Yonas Lebsir, Torgom Yezekyan, N. Asger Mortensen

Cathodoluminescence (CL) microscopy has emerged as a powerful tool for investigating the optical properties of materials at the nanoscale, offering unique insights into the behavior of photonic and plasmonic materials under electron excitation. We introduce an atlas of bulk CL spectra and intensity for a broad range of materials used in photonics and plasmon

Martin Beneke, Tobias Binder, Lorenzo de Ros, Mathias Garny

We investigate the formation of bound states of non-relativistic dark matter particles subject to long-range interactions through radiative capture. The initial scattering and final bound states are described by Coulomb potentials with different strengths, as relevant for non-abelian gauge interactions or theories featuring charged scalars. For bound states

Nicolò Beato, Pranay Patil, Marin Bukov

In optimal quantum control, control landscape phase transitions (CLPTs) indicate sharp changes occurring in the set of optimal protocols, as a physical model parameter is varied. Here, we demonstrate the existence of a new class of CLPTs, associated with changes in the topological properties of the optimal level set in a two-qubit state-preparation problem.

Dennis Rochau, Robin Chan, Hanno Gottschalk

We prove several universal approximation results at minimal or near-minimal width for approximation of $L^p(\mathbb{R}^{d_x}, \mathbb{R}^{d_y})$ and $C^0(\mathbb{R}^{d_x}, \mathbb{R}^{d_y})$ on compact sets. Our approach uses a unified coding scheme that yields explicit constructions relying only on standard analytic tools. We show that feedforward neural ne

Wenhao Zhang, Matias Quintana, Clayton Miller

The indoor environment significantly impacts human health and well-being; enhancing health and reducing energy consumption in these settings is a central research focus. With the advancement of Information and Communication Technology (ICT), recommendation systems and reinforcement learning (RL) have emerged as promising approaches to induce behavioral chang

Martyna Poziomska, Marian Dovgialo, Przemysław Olbratowski, Paweł Niedbalski

This study investigates the impact of quantity and diversity of data on the performance of various machine-learning models for detecting general EEG pathology. We utilized an EEG dataset of 2,993 recordings from Temple University Hospital and a dataset of 55,787 recordings from Elmiko Biosignals sp. z o.o. The latter contains data from 39 hospitals and a div

Somanshu Singla, Zhen Wang, Tianyang Liu, Abdullah Ashfaq

Aligning Large Language Models (LLMs) traditionally relies on costly training and human preference annotations. Self-alignment seeks to reduce these expenses by enabling models to align themselves. To further lower costs and achieve alignment without any expensive tuning or annotations, we introduce a new tuning-free approach for self-alignment, Dynamic Rewa

On-Yu Dung, Stephan Boden, Albertus W. Vreman, Niels G. Deen

X-ray radioscopy was used to measure the 2D projected dynamic void fraction in a zero/narrow gap alkaline water electrolyzer at a spatial resolution of 15 $\mu$m, for narrow gap sizes up to 300 $\mu$m and current densities up to 0.54 A/cm$^2$. As expected, the void fraction in the bulk was found to increase along the cell height and with increasing current d

Wouter Deleersnyder, David Dudal, Thomas Hermans

Knowing the distribution between fresh and saline groundwater is imperative for sustainable and integrated management of water resources in coastal areas. The airborne electromagnetic (AEM) method is increasingly used for hydrogeological mapping over large areas via bulk electrical resistivity. However, accurately and reliably mapping the fresh/saltwater int

Tânia Rocha, Ana Ribeiro, Joana Oliveira, Ricardo Nunes

The use of 3D modelling in medical education is a revolutionary tool during the learning process. In fact, this type of technology enables a more interactive teaching approach, making information retention more effective and enhancing students' understanding. 3D modelling allows for the creation of precise representations of the human body, as well as intera

Amin Hashemi, Elizabeth Louis Pereira, Hongwei Li, Jose L. Lado

Understanding the interplay of non-Hermiticity and topology is crucial given the intrinsic openness of most natural and engineered systems and it has important ramifications in topological lasers and sensors. Intense efforts have been devoted to unveiling how non-Hermiticity may impact the most significant features of topological systems, but only recently i

Chao Huang, Huichen Xiao, Chen Chen, Chunyan Chen

As the application of large language models in various fields continues to expand, materials science also ushers in opportunities for AI-driven innovation. The traditional way of relying on manual search for materials science-related information is now using artificial intelligence technology as an auxiliary tool to improve the efficiency of materials scienc

Jose-Luis Matez-Bandera, Pepe Ojeda, Javier Monroy, Javier Gonzalez-Jimenez

Robots in human-centered environments require accurate scene understanding to perform high-level tasks effectively. This understanding can be achieved through instance-aware semantic mapping, which involves reconstructing elements at the level of individual instances. Neural networks, the de facto solution for scene understanding, still face limitations such

Tom Favereau, Mathieu Hoyrup

In this article, we apply the techniques developed in our previous article ``Local generation of tilings'', in which we introduced two definitions capturing the intuitive idea that some subshifts admit a procedure that can generate any tiling and working in a local way. We classify all the Wang tilesets with two colors in which each tile has an even number o

Rui Liu, Jiayou Liang, Haolong Chen, Yujia Hu

This article applies natural language processing (NLP) to extract and quantify textual information to predict stock performance. Using an extensive dataset of Chinese analyst reports and employing a customized BERT deep learning model for Chinese text, this study categorizes the sentiment of the reports as positive, neutral, or negative. The findings undersc

Seiichiro Kusuoka, Yuichi Shiozawa

We consider solutions of stochastic differential equations which diverge to infinity as the time parameter goes to infinity. If the coefficients converge as the spacial variable goes to infinity, then the solutions will get close to some Gaussian processes with positive drifts as the time parameter goes to infinity. In this paper, we prove Berry-Esseen type

Christian Kipp

We study necessary conditions for local maximizers of the isotropic constant that are related to notions of decomposability. Our main result asserts that the polar body of a local maximizer of the isotropic constant can only have few Minkowski summands; more precisely, its dimension of decomposability is at most $\frac12(n^2+3n)$. Using a similar proof strat

Florian Honz, Paul Müllner, Michael Hentschel, Stefan Nevlacsil

We show simplified DPS-QKD using a SiN micro-ring resonator operated at 852 nm. A raw-key rate of up to 25.3 kb/s is reached at a QBER suitable for secure-key extraction. Short-reach QKD operation is maintained for zero-touch link layouts with C-band telecom fiber.

Junhuai Xu, Zhi Qin, Renjie Zou, Dawei Si

By combining femtoscopic interferometry with an optical deblurring algorithm, we present a novel method to image the source in heavy-ion collisions (HICs) while simultaneously determining the interaction strength between particle pairs. The spatial distribution of the emission source has been reconstructed for protons ($p$) and antiprotons ($\bar{p}$) from t

Josep Grau-Bove, Richard Higham, Scott Orr, Pakhee Kumar

This short note presents preliminary findings on the impact of the October 2024 floods on cultural heritage sites in Valencia, Spain. Using publicly available data, we assess the extent of potential damage by overlaying flood maps with heritage site coordinates. We identify that 3.3% of heritage sites in the region have been potentially impacted, with church

Isacco Nonino

In this paper we find the first infinite family of hyperbolic 3-manifolds which admit tight contact structures but do not have any tight projectively Anosov flow. These manifolds are obtained as rational surgeries on the figure eight knot.

Guoshan Liu, Hailong Yin, Bin Zhu, Jingjing Chen

Given the potential applications of generating recipes from food images, this area has garnered significant attention from researchers in recent years. Existing works for recipe generation primarily utilize a two-stage training method, first generating ingredients and then obtaining instructions from both the image and ingredients. Large Multi-modal Models (

Łukasz Janowski, Dimitrios Skarlatos, Panagiotis Agrafiotis, Paweł Tysiąc

The very shallow marine basin of Puck Lagoon in the southern Baltic Sea, on the Northern coast of Poland, hosts valuable benthic habitats and cultural heritage sites. These include, among others, protected Zostera marina meadows, one of the Baltic's major medieval harbours, a ship graveyard, and likely other submerged features that are yet to be discovered.

Hanamichi Kawamura

There are three kinds of multiple polylogarithms; complex, finite and symmetric. The dualities for the complex and finite cases are known. In this paper, we present proofs of them via iterated integrals and its symmetric counterpart by a similar method.

José Luis Hernández, Cristina Manuel, Laura Tolos

In this contribution, we extend the discussion about the calculation of the bulk viscosity of quark matter in the normal phase due to electroweak processes and its effect on the damping of baryon density oscillations that might occur in the coalescence of two compact stars. Employing the EoSs from the MIT bag model and perturbative quantum chromodynamics (pQ

Marco Baldovin, Giacomo Gradenigo, Angelo Vulpiani, Nino Zanghì

Although not as wide, and popular, as that of quantum mechanics, the investigation of fundamental aspects of statistical mechanics constitutes an important research field in the building of modern physics. Besides the interest for itself, both for physicists and philosophers, and the obvious pedagogical motivations, there is a further, compelling reason for

Shaden Shaar, Wayne Chen, Maitreyi Chatterjee, Barry Wang

Most existing work on event extraction has focused on sentence-level texts and presumes the identification of a trigger-span -- a word or phrase in the input that evokes the occurrence of an event of interest. Event arguments are then extracted with respect to the trigger. Indeed, triggers are treated as integral to, and trigger detection as an essential com

Benhui Yang, Chen Qu, J. M. Bowman, Dongzheng Yang

The rovibrational level populations, and subsequent emission in various astrophysical environments, is driven by inelastic collision processes. The available rovibrational rate coefficients for water have been calculated using a number of approximations. We present a numerically exact calculation for the rovibrational quenching for all water vibrational mode

Matthew V Macfarlane, Clement Bonnet

General intelligence requires systems that acquire new skills efficiently and generalize beyond their training distributions. Although program synthesis approaches have strong generalization power, they face scaling issues due to the large combinatorial spaces that quickly render them impractical, requiring human-generated DSLs or pre-trained priors to narro

Justin P. Cooke, George I. Park, Douglas J. Jerolmack, Paulo E. Arratia

When turbulent boundary layer flows encounter abrupt roughness changes, an Internal Boundary Layer (IBL) forms. Equilibrium theory breaks down in the nonequilibrium IBL, which may extend O(10) km for natural atmospheric flows. Here, we find that the IBL possesses a characteristic time-scale associated with the IBL height, ${\delta}_i$. We show that ${\delta}

D. Villarruel, W. E. Banda-Barragán, B. Casavecchia

Stellar-driven galactic winds are multiphase outflows of energy and matter connecting the interstellar and circumgalactic media (CGM) with the intergalactic medium. Galactic winds contain a hot and diffuse phase detected in X-rays, and a cold and dense phase detected via emission and absorption lines from the ions populating the outflow. The ion production w

Shan Cong, Zhiling Sang, Hongwei Liu, Haoran Luo

The distinct characteristics of multiomics data, including complex interactions within and across biological layers and disease heterogeneity (e.g., heterogeneity in etiology and clinical symptoms), drive us to develop novel designs to address unique challenges in multiomics prediction. In this paper, we propose the multi-view knowledge transfer learning (MV

Charalambos G. Makridakis, Aaron Pim, Tristan Pryer

We introduce a deep learning-based framework for weakly enforcing boundary conditions in the numerical approximation of partial differential equations. Building on existing physics-informed neural network and deep Ritz methods, we propose the Deep Uzawa algorithm, which incorporates Lagrange multipliers to handle boundary conditions effectively. This modific

Dionysis Christopoulos, Sotiris Spanos, Valsamis Ntouskos, Konstantinos Karantzalos

We present TRACE (Transformer-based Risk Assessment for Clinical Evaluation), a novel method for clinical risk assessment based on clinical data, leveraging the self-attention mechanism for enhanced feature interaction and result interpretation. Our approach is able to handle different data modalities, including continuous, categorical and multiple-choice (c

Miguel Ângelo Rebelo, João Vinagre, Ivo Pereira, Álvaro Figueira

News recommender systems are hindered by the brief lifespan of articles, as they undergo rapid relevance decay. Recent studies have demonstrated the potential of content-based neural techniques in tackling this problem. However, these models often involve complex neural architectures and often lack consideration for negative examples. In this study, we posit

Mattia Giovanni Campana, Franca Delmastro

Personalized Federated Learning aims at addressing the challenges of non-IID data in collaborative model training. However, existing methods struggle to balance personalization and generalization, often oversimplifying client similarities or relying too heavily on global models. In this paper, we propose FedSub, a novel approach that introduces class-aware m

Hao Sun, Hsin-Yu Lin, Jieqi Tu, Revathi Ananthakrishnan

Traditional phase I dose finding cancer clinical trial designs aim to determine the maximum tolerated dose (MTD) of the investigational cytotoxic agent based on a single toxicity outcome, assuming a monotone dose-response relationship. However, this assumption might not always hold for newly emerging therapies such as immuno-oncology therapies and molecularl

Tom Favereau, Mathieu Hoyrup

In this article, we investigate the possibility of generating all the configurations of a subshift in a local way. We propose two definitions of local generation, explore their properties and develop techniques to determine whether a subshift satisfies these definitions. We illustrate the results with several examples.

Nandana Mihindukulasooriya, Sanju Tiwari, Daniil Dobriy, Finn Årup Nielsen

Several initiatives have been undertaken to conceptually model the domain of scholarly data using ontologies and to create respective Knowledge Graphs. Yet, the full potential seems unleashed, as automated means for automatic population of said ontologies are lacking, and respective initiatives from the Semantic Web community are not necessarily connected: w

Alina Marian, Andrei Neguţ

We define a categorical action of the shifted quantum loop group of $\mathfrak{sl}_2$ on the derived categories of Quot schemes of finite length quotient sheaves on a smooth projective curve. As an application, we obtain a semi-orthogonal decomposition of the derived categories of Quot schemes, of representation theoretic origin. We use this decomposition to

Katherine Holmes, Joseph Hall, Eva-Maria Graefe

Billiard models of single particles moving freely in two-dimensional regions enclosed by hard walls, have long provided ideal toy models for the investigation of dynamical systems and chaos. Recently, billiards with (semi-)permeable walls and internal holes have been used to study open systems. Here we introduce a billiard model containing an internal region

Theocharis Tavantzis, Robert Feldt

As Artificial Intelligence (AI) becomes integral to software development, understanding the social and cooperative dynamics that affect AI-driven organizational change is important. Yet, despite AI's rapid progress and influence, the human and cooperative facets of these shifts in software organizations remain relatively less explored. This study uses Behavi

Baoyu Xu, Keyi Ding, Hong Su, Ju Chen

Axions and axion-like particles can be probed through gravitational waves indirectly, often referred to as "audible axions". The usual concept of audible axion relies on the coupling between the axions and the gauge fields. Here we consider an axion-like mechanism with coupling to the Nieh-Yan term. This interaction leads to the direct and efficient producti

Romain Branchereau

We define a theta lift between the homology in degree $N-1$ of a locally symmetric space associated to $\mathrm{SL}_N(\mathbb{R})$ and the space of modular forms of weight $N$, similar to the Kudla-Millson lift in the orthogonal setting. We show that the Fourier coefficients of this lift are Poincar\'e duals of modular symbols associated to maximal parabolic

Eldhose Benny, Sreenath K. Manikandan

We investigate the emission characteristics of a measurement-driven quantum emitter in a continuously monitored optical environment. The quantum emitter is stimulated by observing the Pauli spin along its transition dipole that maximally noncommutes with the Hamiltonian of the emitter. It also exchanges energy resonantly with the optical environment, observa

Paulin Ferro, Pierre-Etienne Meiller, Paul Landel, Carla Landrodie

This work focuses on the development of a new incompressible solver, incompressibleFoam, within OpenFOAM and integrating several numerical methods within the same framework. Two momentum interpolation (NCMI/CMI) methods are implemented, two forms of the pressure Poisson equation (corrected/standard). Regarding time discretization, steady-state, Backward Diff

Tiago F. Tavares, Fabio Ayres, Paris Smaragdis

Representational similarity in neural networks is inherently scale-dependent, yet widely used metrics such as Centered Kernel Alignment (CKA) and Procrustes analysis provide only global scalar estimates. These scalars often fail to distinguish micro-scale geometric jitter (local noise) from macro-scale semantic reorganization, compressing multi-scale structu

Lorenzo Iorio

Recently, the temporal evolution of the angles characterizing the spatial configuration of the jet in the supermassive black hole M87$^\ast$ was measured exhibiting a precessional pattern around the hole's spin axis. It would be due to the dragging induced by the fact that the hole's external spacetime is described by the Kerr metric. Here, it is shown that

Julien Duron, Louis Esperet, Jean-Florent Raymond

Consider a graph $G$ with a path $P$ of order $n$. What conditions force $G$ to also have a long induced path? As complete bipartite graphs have long paths but no long induced paths, a natural restriction is to forbid some fixed complete bipartite graph $K_{t,t}$ as a subgraph. In this case we show that $G$ has an induced path of order $(\log \log n)^{1/5-o(

Howard Goldowsky, Vasanth Sarathy

We propose an approach to analogical inference that marries the neuro-symbolic computational power of complex-sampled hyperdimensional computing (HDC) with Conceptual Spaces Theory (CST), a promising theory of semantic meaning. CST sketches, at an abstract level, approaches to analogical inference that go beyond the standard predicate-based structure mapping

Barnik Mandal, Adrian-Marie Philippe, Nathalie Valle, Emmanuel Defay

Since the discovery of ferroelectricity in HfO$_2$ thin films, significant research has focused on Zr-doped HfO$_2$ and solid solution (Hf,Zr)O$_2$ thin films. Functional properties can be further tuned via multilayering, however, this approach has not yet been fully explored in HfO$_2$-ZrO$_2$ films. This work demonstrates ferroelectricity in a 50 nm thick,

Tomás R. Rodríguez

The structure of the nucleus $^{84}$Mo has been studied using the projected generator coordinate method (PGCM) with the Gogny D1S interaction. The calculations incorporate a mixing of particle-number and angular-momentum projected intrinsic wave functions, defined over triaxial quadrupole degrees of freedom. This approach yields an excellent agreement with t

D. A. Cooke, F. Pannell, G. Zevi Della Porta, J. Farmer

The vertical plane transverse emittance of accelerated electron bunches at the AWAKE experiment at CERN has been determined, using three different methods of data analysis. This is a proof-of-principle measurement using the existing AWAKE electron spectrometer to validate the measurement technique. Large values of the geometric emittance, compared to that of

Haoyang Di, Xiaodong Zhu, Yulin Shao

Unmanned aerial vehicles (UAVs) have become key enablers in relay-assisted wireless communications thanks to their flexibility and line-of-sight channel advantage. However, most existing trajectory optimization frameworks assume ideal Gaussian inputs, overlooking the fact that practical wireless systems rely on structured, finite-alphabet constellations. Thi

Clarence Kineider, Roméo Troubat

We count and give a parametrization of connected components in the space of flags transverse to a given transverse pair in every flag varieties of $\mathrm{SO}_0(p,q)$. We compute the effect the involution of the unipotent radical has on those components and, using methods of Dey--Greenberg--Riestenberg, we show that for certain parabolic subgroups $P_{\Thet

Hannes M. H. Wolf, Christian A. Hans

In future power systems, the detailed structure and dynamics may not always be fully known. This is due to an increasing number of distributed energy resources, such as photovoltaic generators, battery storage systems, heat pumps and electric vehicles, as well as a shift towards active distribution grids. Obtaining physically-based models for simulation and

Cuiying Pei, Mingxin Zhang, Di Peng, Yang Shen

The recent discovery of superconductivity in pressurized Ruddlesden-Popper (RP) nickelates has provided new perspectives on the mechanism of high-temperature superconductivity. Up to now, most experiments concentrated on the lanthanum-related RP phase, so the discovery of new superconducting RP nickelates is highly desirable to reveal their generality. Here

A. Jana, C. Ricci, M. J. Temple, H. -K. Chang

Changing-look active galactic nuclei (CLAGNs) show the appearance and disappearance of broad emission lines in their UV/optical spectra on timescales of months to decades. Here, we investigate how CL transitions depend on several AGN parameters such as accretion rate, obscuration properties and black hole mass. We study a sample of 20 nearby optically-identi

Shawn X. Cui, César Galindo, Diego Romero

We study the Twisted Kitaev Quantum Double model within the framework of Local Topological Order (LTO). We extend its definition to arbitrary 2D lattices, enabling an explicit characterization of the ground state space through the invariant spaces of monomial representations. We reformulate the LTO conditions to include general lattices and prove that the tw

Florentia Afentaki, Paula Carolina Lozano Duarte, Georgios Zervakis, Mehdi B. Tahoori

Printed electronics technology offers a cost-effectiveand fully-customizable solution to computational needs beyondthe capabilities of traditional silicon technologies, offering ad-vantages such as on-demand manufacturing and conformal, low-cost hardware. However, the low-resolution fabrication of printedelectronics, which results in large feature sizes, pos

Soumyaratna Debnath, Ashish Tiwari, Shanmuganathan Raman

Art has long been a medium for individuals to engage with the world. Scribble art, a form of abstract visual expression, features spontaneous, gestural strokes made with pens or brushes. These dynamic and expressive compositions, created quickly and impulsively, reveal intricate patterns and hidden meanings upon closer inspection. While scribble art is often

Zhang Liu, Hongyang Du, Lianfen Huang, Zhibin Gao

With the rapid advancement of artificial intelligence (AI), generative AI (GenAI) has emerged as a transformative tool, enabling customized and personalized AI-generated content (AIGC) services. However, GenAI models with billions of parameters require substantial memory capacity and computational power for deployment and execution, presenting significant ch

László Kozma, Johannes Voderholzer

Byte-Pair Encoding (BPE) is a widely used method for subword tokenization, with origins in grammar-based text compression. It is employed in a variety of language processing tasks such as machine translation or large language model (LLM) pretraining, to create a token dictionary of a prescribed size. Most evaluations of BPE to date are empirical, and the rea

João Barbosa, Jack C. Brennan, Alessandro Casaburi, M. D. Hutchings

One of the most important and topical challenges of quantum circuits is their scalability. Rapid Single Flux Quantum (RSFQ) technology is at the forefront of replacing current standard CMOS-based control architectures for a number of applications, including quantum computing and quantum sensor arrays. By condensing the control and readout to SFQ-based on-chi

Murad Badshah, Muhammad Waqas, Ahmed M. Khubrani, Muhammad Ajaz

This work focuses on the study of identified hadrons and strange hadrons, recorded by CMS, and light nuclei and their anti-nuclei, recorded by ALICE, at 0.9 TeV, 2.76 TeV, 7 TeV and 13 TeV centre of mass energies in pp collision at mid rapidities. The transverse momentum distributions of these particles are analyzed using the Tsallis model, which fits the ex

Xianhua Peng, Steven Kou, Lekang Zhang

We propose a machine learning algorithm for solving finite-horizon stochastic control problems based on a deep neural network representation of the optimal policy functions. The algorithm has three features: (1) It can solve high-dimensional (e.g., over 100 dimensions) and finite-horizon time-inhomogeneous stochastic control problems. (2) It has a monotonici

Shu-Liang Ren, Simin Pang, Shan Guan, Yu-Jia Sun

Broken symmetry plays a pivotal role in determining the macroscopic electrical, optical, magnetic, and topological properties of materials. Circular dichroism (CD) has been widely employed to probe broken symmetry in various systems, from small molecules to bulk crystals, but designing CD responses on demand remains a challenge, especially for antiferromagne

Kai Jiang, Jiaxing Huang

Autoregressive models have demonstrated great performance in natural language processing (NLP) with impressive scalability, adaptability and generalizability. Inspired by their notable success in NLP field, autoregressive models have been intensively investigated recently for computer vision, which perform next-token predictions by representing visual data a

Youqi Liao, Xieyuanli Chen, Shuhao Kang, Jianping Li

OpenStreetMap (OSM), a rich and versatile source of volunteered geographic information (VGI), facilitates human self-localization and scene understanding by integrating nearby visual observations with vectorized map data. However, the disparity in modalities and perspectives poses a major challenge for effectively matching camera imagery with compact map rep

Janghoon Ock, Joseph Montoya, Daniel Schweigert, Linda Hung

Materials science datasets are inherently heterogeneous and are available in different modalities such as characterization spectra, atomic structures, microscopic images, and text-based synthesis conditions. The advancements in multi-modal learning, particularly in vision and language models, have opened new avenues for integrating data in different forms. I

Hanz Cuevas-Velasquez, Priyanka Patel, Haiwen Feng, Michael Black

Training methods to perform robust 3D human pose and shape (HPS) estimation requires diverse training images with accurate ground truth. While BEDLAM demonstrates the potential of traditional procedural graphics to generate such data, the training images are clearly synthetic. In contrast, generative image models produce highly realistic images but without g

Haitao Lin, Xu Wang, Weiwei Zhang

Accurate and complete aerodynamic data sets are the basis for comprehensive and accurate evaluation of the overall performance of aircraft. However, the sampling cost of full-state aerodynamic data is extremely high, and there are often differences between wind tunnel conditions and actual flight conditions. Conventional scaling parameter extraction methods

Akshay Mathur, Ella Atkins

Advanced Air Mobility aircraft require energy efficient flight plans to be economically viable. This paper defines minimum energy direct trajectories between waypoints for Lift+Cruise electric Vertical Take-Off and Landing (eVTOL) aircraft. Energy consumption is optimized over accelerated and cruise flight profiles with consideration of mode transitions. Bec

Zilong Ding, Ying-nan Mao, Kechen Wang

We assume the coupling of Axion-like particle (ALP) to diphoton $g_{a\gamma\gamma} \sim 0$ and accomplish detailed analyses for the $\gamma Z$ decay mode of such heavy photophobic ALPs at the high luminosity-Large Hadron Collider (HL-LHC). ALPs are produced with two jets via both the $s$-channel vector boson exchange and vector boson fusion processes, with t

Yukino Kawai, Tatsuya Hisada, Kozue Shiomi, Momoko Hayamizu

Birds exhibit a variety of flight styles, primarily classified as flapping, which is characterized by rapid up-and-down wing movements, and soaring, which involves gliding with wings outstretched. Each species usually performs specific flight styles, and this has been argued in terms of morphological and physiological adaptation. However, it remains a challe

Uri Malamud, Hagai Perets

The multiple impact hypothesis proposes that the Moon formed through a series of smaller collisions, rather than a single giant impact. This study advances our understanding of this hypothesis, as well as moon collisions in other contexts, by exploring the implications of these smaller impacts, employing a novel methodological approach that combines self-con

Maya Fishbach

By observing binary black hole (BBH) mergers out to the edge of the Universe, next-generation (XG) ground-based gravitational-wave (GW) detectors like Cosmic Explorer and Einstein Telescope will map the BBH merger rate across all of cosmic history. This merger rate traces the formation rate of their progenitor stars convolved with a delay time distribution.

Song-Ren Fu, Yongyi Yu, Philipp Zimmermann

In this article, we study the Calder\'on problem for nonlocal generalizations of the semilinear Moore--Gibson--Thompson (MGT) equation and the Jordan--Moore--Gibson--Thompson (JMGT) equation of Westervelt-type. These partial differential equations are third order wave equations that appear in nonlinear acoustics, describe the propagation of high-intensity so

Jiaxu Zhang, Xianfang Zeng, Xin Chen, Wei Zuo

We propose MikuDance, a diffusion-based pipeline incorporating mixed motion dynamics to animate stylized character art. MikuDance consists of two key techniques: Mixed Motion Modeling and Mixed-Control Diffusion, to address the challenges of high-dynamic motion and reference-guidance misalignment in character art animation. Specifically, a Scene Motion Track

Murad Badshah, Muhammad Ajaz, Muhammad Waqas, Hannan Younis

This article focuses on the study of strange hadrons at 0.2 TeV centre of mass energy, recorded by STAR at RHIC, and at 0.9 TeV, 5.02 TeV and 7 TeV, recorded by CMS at LHC, in pp collision in the rapidity range from 0 to 2. The transverse momentum distributions of these strange particles have been processed using two statistical models, the Tsallis and the m

Simon Ouellette

ARC-AGI is an open-world problem domain in which the ability to generalize out-of-distribution is a crucial quality. Under the program induction paradigm, we present a series of experiments that reveal the efficiency and generalization characteristics of various neurally-guided program induction approaches. The three paradigms we consider are Learning the gr

Y. Li, W. Zeng, R. Shen

Monolayer 1{\it T}$^{\prime}$-\ce{MoS2} exhibits spin- and valley-dependent massive tilted Dirac cones with two velocity correction terms in low-energy effective Hamiltonian. We theoretically investigate the longitudinal diffusive magnetoconductivity of monolayer 1{\it T}$^{\prime}$-\ce{MoS2} by using the linear response theory. It is shown that, when the Fe

Alban Puech, François Mirallès, Jonas Weiss, Vincent Mai

Quasi-static time series (QSTS) simulations have great potential for evaluating the grid's ability to accommodate the large-scale integration of distributed energy resources. However, as grids expand and operate closer to their limits, iterative power flow solvers, central to QSTS simulations, become computationally prohibitive and face increasing convergenc