November 2024 arXiv papers — page 146

Alin Bostan, Thomas Yu, Sergey Yurkevich

The combination of recent results due to Yu and Chen [Proc. AMS 150(4), 2020, 1749-1765] and to Bostan and Yurkevich [Proc. AMS 150(5), 2022, 2131-2136] shows that the 3-D Euclidean shape of the square Clifford torus is uniquely determined by its isoperimetric ratio. This solves part of the still open uniqueness problem of the Canham model for biomembranes.

Christa Gall, Luca Izzo, Radoslaw Wojtak, Jens Hjorth

There is a persistent tension of about $5\sigma-6\sigma$ between the value of the Hubble constant, as derived from the local distance ladder vs. the cosmic microwave background, signaling either unaccounted for systematics in the measurements or `new physics', such as early dark energy. Determining the Hubble constant using Type Ia supernovae requires nontri

Long Truong To, Hung Tuan Le, Dat Van-Thanh Nguyen, Manh Trong Nguyen

Large Language Models (LLMs), with gradually improving reading comprehension and reasoning capabilities, are being applied to a range of complex language tasks, including the automatic generation of language data for various purposes. However, research on applying LLMs for automatic data generation in low-resource languages like Vietnamese is still underdeve

Rômulo Damasclin Chaves dos Santos, Jorge Henrique de Oliveira Sales

This paper enhances the classic Smagorinsky model by introducing an innovative, adaptive dissipation term that adjusts dynamically with distance from boundary regions. This modification addresses a known limitation of the standard model over dissipation near boundaries thereby improving accuracy in turbulent flow simulations in confined or wall-adjacent area

Mohammad Yeghaneh Abkenar, Weixing Wang, Hendrik Graupner, Manfred Stede

We explore the capability of four open-sourcelarge language models (LLMs) in argumentation mining (AM). We conduct experiments on three different corpora; persuasive essays(PE), argumentative microtexts (AMT) Part 1 and Part 2, based on two argumentation mining sub-tasks: (i) argumentative discourse units classifications (ADUC), and (ii) argumentative relati

Kahlil bin Abdul Hakim, Sathishkumar Veerappampalayam Easwaramoorthy

This study examines how fake news affects social media users across a range of age groups and how machine learning (ML) and artificial intelligence (AI) can help reduce the spread of false information. The paper evaluates various machine learning models for their efficacy in identifying and categorizing fake news and examines current trends in the spread of

Guanying Peng, Anthony Vuolo

In Kirchheim, M\"{u}ller and \v{S}ver\'{a}k [Studying nonlinear PDE by geometry in matrix space. Geometric analysis and nonlinear partial differential equations, 2003], the authors proposed the program to use the differential inclusion approach to study entropy solutions for systems of conservation laws. In particular, they raised questions concerning the lo

Zhuowen Yin, Chengru Li, Xingbo Dong

To address the challenges of high computational costs and long-distance dependencies in exist ing video understanding methods, such as CNNs and Transformers, this work introduces RWKV to the video domain in a novel way. We propose a LSTM CrossRWKV (LCR) framework, designed for spatiotemporal representation learning to tackle the video understanding task. Spe

Thomas J. Maldonado, Hakan E. Türeci, Alejandro W. Rodriguez

We derive a mesoscopic theory of the Josephson junction from non-relativistic scalar electrodynamics. Our theory reproduces the Josephson relations with the canonical current phase relation acquiring a weak second harmonic term, and it improves the standard lumped-element descriptions employed in circuit quantum electrodynamics by providing spatial resolutio

Eyal Neuman, Sturmius Tuschmann

We study finite-player dynamic stochastic games with heterogeneous interactions and non-Markovian linear-quadratic objective functionals. We derive the Nash equilibrium explicitly by converting the first-order conditions into a coupled system of stochastic Fredholm equations, which we solve in terms of operator resolvents. When the agents' interactions are m

Siti Nurdianah binti Mohamad Jalani, Sathishkumar Veerappampalayam Easwaramoorthy

Mobile banking apps have transformed the banking sector by offering customers with convenient, secure and easily accessible financial services. Even so, it is crucial for banks and the mobile banking apps developers to understand the factors that influence the utilisation of these apps among Malaysian consumer. This study will examine the influence of severa

Cristobal Laporte, Agustín Silva

Extended gravitational models have gained large attention in the last couple of decades. In this work, we examine the solution space of vacuum, static, and spherically symmetric spacetimes within $F(R)$ theories, introducing novel methods that reduce the vacuum equations to a single second-order equation. For the first time, we derive analytic expressions fo

Tamara R. Lenhard, Andreas Weinmann, Kai Franke, Tobias Koch

Developing robust drone detection systems is often constrained by the limited availability of large-scale annotated training data and the high costs associated with real-world data collection. However, leveraging synthetic data generated via game engine-based simulations provides a promising and cost-effective solution to overcome this issue. Therefore, we p

Federico Gasparotto, Pouria Mazloumi, Xiaofeng Xu

We study mathematical aspects concerning two site tree-level cosmological correlators with massive internal and external states in a de Sitter universe. We employ integration by parts identities, (relative) twisted cohomology and the method of differential equations. We explicitly express the internally massive, externally conformally coupled correlator as a

Hunor Csala, Arvind Mohan, Daniel Livescu, Amirhossein Arzani

Computational cardiovascular flow modeling plays a crucial role in understanding blood flow dynamics. While 3D models provide acute details, they are computationally expensive, especially with fluid-structure interaction (FSI) simulations. 1D models offer a computationally efficient alternative, by simplifying the 3D Navier-Stokes equations through axisymmet

Rudi Gaelzer, Luiz Fernando Ziebell

We study the effects of the velocity distribution functions of the plasma particles on the equilibrium charge of dust grains, acquired through inelastic collisions of the particles with the grains. This paper is the second in a series of two papers on the subject. Here, we consider the charging process when the plasma particles are statistically described by

Massimiliano Marcellino, Andrea Renzetti, Tommaso Tornese

We propose a functional MIDAS model to leverage high-frequency information for forecasting and nowcasting distributions observed at a lower frequency. We approximate the low-frequency distribution using Functional Principal Component Analysis and consider a group lasso spike-and-slab prior to identify the relevant predictors in the finite-dimensional SUR-MID

Arianna Crippa, Karl Jansen, Enrico Rinaldi

Compact lattice Quantum Electrodynamics is a complex quantum field theory with dynamical gauge and matter fields and it has similarities with Quantum Chromodynamics, in particular asymptotic freedom and confinement. We consider a (2+1)-dimensional lattice discretization of Quantum Electrodynamics with the inclusion of dynamical fermionic matter. We define a

Gösta Stomberg, Maurice Raetsch, Alexander Engelmann, Timm Faulwasser

A key motivation in the development of Distributed Model Predictive Control (DMPC) is to accelerate centralized Model Predictive Control (MPC) for large-scale systems. DMPC has the prospect of scaling well by parallelizing computations among subsystems. However, communication delays may deteriorate the performance of decentralized optimization, if excessivel

Thomas G. Anderson, Mark Lyon, Tao Yin, Oscar P. Bruno

In view of recently demonstrated joint use of novel Fourier-transform techniques and effective high-accuracy frequency domain solvers related to the Method of Moments, it is argued that a set of transformative innovations could be developed for the effective, accurate and efficient simulation of problems of wave propagation and scattering of broadband, time-

Daniela Schkoda, Philipp Faller, Patrick Blöbaum, Dominik Janzing

We propose a new approach to falsify causal discovery algorithms without ground truth, which is based on testing the causal model on a variable pair excluded during learning the causal model. Specifically, given data on $X, Y, \boldsymbol{Z}=X, Y, Z_1,\dots,Z_k$, we apply the causal discovery algorithm separately to the 'leave-one-out' data sets $X,

Yifan Xie, Julian Berberich, Felix Brändle, Frank Allgöwer

This paper presents a data-driven min-max model predictive control (MPC) scheme for linear parameter-varying (LPV) systems. Contrary to existing data-driven LPV control approaches, we assume that the scheduling signal is unknown during offline data collection and online system operation. Assuming a quadratic matrix inequality (QMI) description for the schedu

Simon Cloutier, Robert H. Cameron, Laurent Gizon

The butterfly diagram of the solar cycle exhibits a poleward migration of the diffuse magnetic field resulting from the decay of trailing sunspots. It is one component of what is sometimes referred to as the "rush to the poles". We investigate under which conditions the rush to the poles can be reproduced in flux-transport Babcock-Leighton dynamo models. We

Wouter Termont, Ruben Dedecker, Wout Slabbinck, Beatriz Esteves

The User-Managed Access (UMA) extension to OAuth 2.0 is a promising candidate for increasing Digital Trust in personal data ecosystems like Solid. With minor modifications, it can achieve many requirements regarding usage control and transaction contextualization, even though additional specification is needed to address delegation of control and retraction

Krzysztof Pachucki, Vojtěch Patkóš, Vladimir A. Yerokhin

The complete second-order hyperfine-interaction correction is calculated for centroid energy levels of H, D, and $^3$He atoms. For $^3$He, the corrections of $-2.075$~kHz and $-0.305$~kHz beyond the leading hyperfine-mixing contribution are obtained for the $2^1S$ and $2^3S$ states, respectively. These results shift the nuclear charge radii difference derive

Sergio Benvenuti, Riccardo Comi, Sara Pasquetti, Gabriel Pedde Ungureanu

We propose an Abelian mirror dual for the $\mathcal{N}=2$ SQCD$_3$ that we obtain as real mass deformation of known $\mathcal{N}=4$ mirror pairs. We match the superconformal index and the $\mathbf{S}^3_b$ partition function, discuss the agreement of the moduli spaces, and provide a map of the gauge invariant operators and the global symmetries as evidence of

Zhilong Zhang, Ruifeng Chen, Junyin Ye, Yihao Sun

World models play a crucial role in decision-making within embodied environments, enabling cost-free explorations that would otherwise be expensive in the real world. To facilitate effective decision-making, world models must be equipped with strong generalizability to support faithful imagination in out-of-distribution (OOD) regions and provide reliable unc

Ayobami Adewale, Chris Lee, Amnir Hadachi, Nicolly Lima da Silva

As we move towards a mixed-traffic scenario of Autonomous vehicles (AVs) and Human-driven vehicles (HDVs), understanding the car-following behaviour is important to improve traffic efficiency and road safety. Using a real-world trajectory dataset, this study uses descriptive and statistical analysis to investigate the car-following behaviours of three vehicl

Talha Mushtaq, Maziar S. Hemati

Recent investigations have established the physical relevance of spatially-localized instability mechanisms in fluid dynamics and their potential for technological innovations in flow control. In this letter, we show that the mathematical problem of identifying spatially-localized optimal perturbations that maximize perturbation-energy amplification can be c

Hendrik Schäfke, Tim-Lukas Habich, Christian Muhmann, Simon F. G. Ehlers

Soft robots pose difficulties in terms of control, requiring novel strategies to effectively manipulate their compliant structures. Model-based approaches face challenges due to the high dimensionality and nonlinearities such as hysteresis effects. In contrast, learning-based approaches provide nonlinear models of different soft robots based only on measured

Nickolas Solomey, Mark Christl, Brian Doty, Jonathan Folkerts

We have developed a neutrino detector with threshold energies from ~0.115 to 105 MeV in a clean detection mode almost completely void of accidental backgrounds. It was initially developed for the NASA $\nu$SOL project to put a solar neutrino detector very close to the Sun with 1,000 to 10,000 times higher solar neutrino flux than on Earth. Similar interactio

Zhihong Liu, Xin Xu, Peng Qiao, Dongsheng Li

Deep reinforcement learning has led to dramatic breakthroughs in the field of artificial intelligence for the past few years. As the amount of rollout experience data and the size of neural networks for deep reinforcement learning have grown continuously, handling the training process and reducing the time consumption using parallel and distributed computing

A. Hacar, R. Konietzka, D. Seifried, S. E. Clark

Identified as parsec-size, gas clumps at the junction of multiple filaments, hub-filament systems (HFS) play a crucial role during the formation of young clusters and high-mass stars. These HFS appear nevertheless to be detached from most galactic filaments when compared in the mass-length (M-L) phase-space. We aim to characterize the early evolution of HFS

Morgan J Grant, Yi Liu, Guang-Han Cao, Joseph A Wilcox

Experimental determination of the structure of the superconducting order parameter in the kagome lattice compound CsV$_3$Sb$_5$ is an essential step towards understanding the nature of the superconducting pairing in this material. Here we report measurements of the temperature dependence of the in-plane magnetic penetration depth, $\lambda(T)$, in crystals o

Riva Emanuele, Federico Bellinzoni, Francesco Braghin

We experimentally demonstrate the emergence of flat-band-induced compact-localized modes in acoustic Kagome lattices. Compact localized states populate singular dispersion bands characterized by band crossing, where a quadratic and a flat-band dispersion coalesce into a singularity. These conditions enable intriguing wave phenomena when the Hilbert Schmidt q

Cristiano Patrício, Luís F. Teixeira, João C. Neves

The main challenges hindering the adoption of deep learning-based systems in clinical settings are the scarcity of annotated data and the lack of interpretability and trust in these systems. Concept Bottleneck Models (CBMs) offer inherent interpretability by constraining the final disease prediction on a set of human-understandable concepts. However, this in

V. A. Allakhverdyan, A. D. Avrorin, A. V. Avrorin, V. M. Aynutdinov

Recent observations of the Galactic component of the high-energy neutrino flux, together with the detection of the diffuse Galactic gamma-ray emission up to sub-PeV energies, open new possibilities to study the acceleration and propagation of cosmic rays in the Milky Way. At the same time, both large non-astrophysical backgrounds at TeV energies and scarcity

Jithu Paul, Karel N. van Dalen, Andrei B. Faragau, Rens J. van Leijden

In this paper, we study the stability of a simple model of a Hyperloop vehicle resulting from the interaction between electromagnetic and aeroelastic forces for both constant and periodically varying coefficients (i.e., parametric excitation). For the constant coefficients, through linear stability analysis, we analytically identify three distinct regions fo

Jian-Guo Liu, Robert L. Pego

We study all the ways that a given convex body in $d$ dimensions can break into countably many pieces that move away from each other rigidly at constant velocity, with no rotation or shearing. The initial velocity field is locally constant, but may be continuous and/or fail to be integrable. For any choice of mass-velocity pairs for the pieces, such a motion

Yevgen Melikhov, Maria L. Ekiel-Jezewska

The settling of highly elastic non-Brownian closed fibres (called loops) under gravity in a viscous fluid is investigated numerically. The loops are represented using a bead-spring model with harmonic bending potential and finitely extensible nonlinear elastic (FENE) stretching potential. Numerical solutions to the Stokes equations are obtained with the use

Arindam Bhattacharjee, Shruti Menon, Muktajyoti Saha

Recently a one-dimensional Schwarzian type theory was proposed as an effective dual theory of pure gravity in (2+1) dimensional asymptotically flat spacetimes \cite{Bhattacharjee:2023sfd}. This codimension-two `celestial' dual captures the Bekenstein-Hawking entropy of bulk flat cosmologies in semiclassical limit. In this paper, we extend this analysis beyon

Christoforos Neofytidis

For each $m\geq0$ and any prime $p\equiv3\ \mathrm{(mod \ 4)}$, we construct strongly chiral rational homology $(4m+3)$-spheres, which have real hyperbolic fundamental groups and only non-zero integral intermediate homology groups isomorphic to $\mathbb{Z}_{2p}$ in degrees $1,2m+1$ and $4m+1$. This gives group theoretic analogues in high dimensions of the ex

Mahrukh Awan, Asmar Nadeem, Armin Mustafa

We present Attend-Fusion, a novel and efficient approach for audio-visual fusion in video classification tasks. Our method addresses the challenge of exploiting both audio and visual modalities while maintaining a compact model architecture. Through extensive experiments on the YouTube-8M dataset, we demonstrate that our Attend-Fusion achieves competitive pe

Federico Manzoni

The surface charges associated with $p$-form gauge fields in the Bondi patch of $D$-dimensional Minkowski spacetime are computed. We show that, under the Hodge duality between the field strengths of the dual formulations, electric-like charges for $p$-forms are mapped to magnetic-like charges for the dual $q$-forms, with $q=D-p-2$. We observe that the comple

Simon A. Willis, David J. Flannigan

Broader adoption of 4D ultrafast electron microscopy (UEM) for the study of chemical, materials, and quantum systems is being driven by development of new instruments as well as continuous improvement and characterization of existing technologies. Perhaps owing to the still-high barrier to entry, the full range of capabilities of laser-driven 4D UEM instrume

Jiaren Peng, Hongda Sun, Wenzhong Yang, Fuyuan Wei

Document-level Event Argument Extraction (EAE) faces two challenges due to increased input length: 1) difficulty in distinguishing semantic boundaries between events, and 2) interference from redundant information. To address these issues, we propose two methods. The first method introduces the Co and Structure Event Argument Extraction model (CsEAE) based o

Alain Hecq, Ivan Ricardo, Ines Wilms

This paper proposes a Matrix Error Correction Model to identify cointegration relations in matrix-valued time series. We hereby allow separate cointegrating relations along the rows and columns of the matrix-valued time series and use information criteria to select the cointegration ranks. Through Monte Carlo simulations and a macroeconomic application, we d

Xingchen Shen, Zhonghao Xia, Jun Zhou, Yuling Huang

Crystals exhibiting glass-like and low lattice thermal conductivity ($\kappa_{\rm L}$) are not only scientifically intriguing but also practically valuable in various applications, including thermal barrier coatings, thermoelectric energy conversion, and thermal management. However, such unusual $\kappa_{\rm L}$ are typically observed only in compounds conta

Marta Kwiatkowska, Gethin Norman, David Parker, Gabriel Santos

Game theory provides an effective way to model strategic interactions among rational agents. In the context of formal verification, these ideas can be used to produce guarantees on the correctness of multi-agent systems, with a diverse range of applications from computer security to autonomous driving. Psychological games (PGs) were developed as a way to mod

Boris Bilich, Adam Dor-On, Efren Ruiz

We continue the study of shift equivalence relations from the perspective of C*-bimodule theory. We study emerging shift equivalence relations following work of the second-named author with Carlsen and Eilers, both in terms of adjacency matrices and in terms of their C*-correspondences, and orient them when possible. In particular, we show that if two regula

Yuqing Huang, Bastian Wittmann, Olga Demler, Bjoern Menze

Early identification of stroke is crucial for intervention, requiring reliable models. We proposed an efficient retinal image representation together with clinical information to capture a comprehensive overview of cardiovascular health, leveraging large multimodal datasets for new medical insights. Our approach is one of the first contrastive frameworks tha

Arthur Candalot, James Hurrell, Malik Manel Hashim, Brigid Hickey

Wheeled rovers have been the primary choice for lunar exploration due to their speed and efficiency. However, deeper areas, such as lunar caves and craters, require the mobility of legged robots. To do so, appropriate end effectors must be designed to enable climbing and walking on the granular surface of the Moon. This paper investigates the behavior of an

Pablo Gómez, Roland D. Vavrek, Guillermo Buenadicha, John Hoar

State-of-the-art space science missions increasingly rely on automation due to spacecraft complexity and the costs of human oversight. The high volume of data, including scientific and telemetry data, makes manual inspection challenging. Machine learning offers significant potential to meet these demands. The Euclid space telescope, in its survey phase since

Liviu Ornea, Misha Verbitsky

Let $M$ be a compact complex $n$-manifold. A Gauduchon metric is a Hermitian metric whose fundamental 2-form $\omega$ satisfies the equation $dd^c(\omega^{n-1})=0$. Paul Gauduchon has proven that any Hermitian metric is conformally equivalent to a Gauduchon metric, which is unique (up to a constant multiplier) in its conformal class. Then $d^c(\omega^{n-1})$

David F. Rentería-Estrada

Understanding the cancellation of ultraviolet and infrared singularities in perturbative quantum field theory is of central importance for the development and automation of various theoretical tools that make accurate predictions for observables at high-energy colliders. The loop-tree duality aims to find an efficient solution by treating loop and tree-level

JA Meaney, Beatrice Alex, William Lamb

Folktales are a rich resource of knowledge about the society and culture of a civilisation. Digital folklore research aims to use automated techniques to better understand these folktales, and it relies on abstract representations of the textual data. Although a number of large language models (LLMs) claim to be able to represent low-resource langauges such

Ricard Montalà, Benet Eiximeno, Arnau Miró, Oriol Lehmkuhl

A wall-resolved large-eddy simulation (LES) of the fluid flow around a 30P30N airfoil is conducted at a Reynolds number of Rec=750,000 and an angle of attack (AoA) of 9 degrees. The simulation results are validated against experimental data from previous studies and further analyzed, focusing on the suction side of the wing main element. The boundary layer d

Esteban González, Carlos Maldonado, N. Stefanía Mite, Rodrigo Salinas

In this paper, we revisit the extension of the classical non-standard cosmological model in which dissipative processes are considered through a bulk viscous term in the new field $\phi$, which interacts with the radiation component during the early universe. Specifically, we consider an interaction term of the form $\Gamma_{\phi} \rho_{\phi}$, where $\Gamma

Saedeh Tahery, Fatemeh Hamid Akhlaghi, Termeh Amirsoleimani

The HeartBert model is introduced with three primary objectives: reducing the need for labeled data, minimizing computational resources, and simultaneously improving performance in machine learning systems that analyze Electrocardiogram (ECG) signals. Inspired by Bidirectional Encoder Representations from Transformers (BERT) in natural language processing an

Martin Charron, Zachary Roelen, Deekshant Wadhwa, Vincent Tabard-Cossa

Resistive pulse sensing is used to characterize and count single particles in solution moving through channels under an electric bias, with nanoscale pores providing enough spatial resolution for single-molecule identification and sequencing. This technique relies on measuring the ionic current drop produced by the passage of a molecule and, through conducta

René Walendy, Markus Weber, Steffen Becker, Christof Paar

The increasing importance of supply chain security for digital devices -- from consumer electronics to critical infrastructure -- has created a high demand for skilled cybersecurity experts. These experts use Hardware Reverse Engineering (HRE) as a crucial technique to ensure trust in digital semiconductors. Recently, the US and EU have provided substantial

Mohammad Hossein Masoudi, Ali Naji

We employ deep reinforcement learning methods to investigate shortest-time navigation strategies for smart active Brownian particles (microagents), which self-propel through a rotating potential barrier in a static, viscous, fluid background. The microagent's motion begins at a specified origin and terminates at a designated destination. The potential barrie

Hubert Szolc, Karol Desnos, Tomasz Kryjak

Deep reinforcement learning (DRL) is currently the most popular AI-based approach to autonomous vehicle control. An agent, trained for this purpose in simulation, can interact with the real environment with a human-level performance. Despite very good results in terms of selected metrics, this approach has some significant drawbacks: high computational requi

Sandro L. Camenzind, Lukas Lang, Benjamin Willenberg, Justinas Pupeikis

Dual-comb ranging has emerged as an effective technology for long-distance metrology, providing absolute distance measurements with high speed, precision, and accuracy. Here, we demonstrate a dual-comb ranging method that utilizes a free-space transceiver unit, enabling dead-zone-free measurements and simultaneous ranging with interchanged comb roles to allo

Michael Balzer, Adhen Benlahlou

For many public research organizations, funding creation of science and maximizing scientific output is of central interest. Typically, when evaluating scientific production for funding, citations are utilized as a proxy, although these are severely influenced by factors beyond scientific impact. This study aims to mitigate the consequences of the Matthew ef

Youssef Hussein, Mohamad Assaad, Thierry Clessienne

This paper explores distributed Reconfigurable Intelligent Surfaces (RISs) by introducing a cooperative dimension that enhances adaptability and performance. It focuses on strategically deploying multiple RISs to improve connectivity with the Base Station (BS) and among RISs, thereby aiding users in areas with weak BS coverage and enhancing spatial multiplex

Daniel Spitz, Kirill Boguslavski, Thimo Preis

The far-from-equilibrium dynamics of spatial Polyakov loop correlations, which provide gauge-invariant observables akin to effective particle numbers for gluon plasmas, are investigated within real-time $\mathrm{SU}(N_c)$ lattice gauge theory at weak couplings and large gluon occupations. The momentum zero mode of these correlations reveals the dynamic forma

S. Tricot, H. Ikeda, H. -C. Tchouekem, J. -C. Le Breton

Photoelectron diffraction (PED) is a powerful spectroscopic technique that combines elemental resolution with a high sensitivity to the local atomic arrangement at crystal surfaces, thus providing unique fingerprints of selected atomic sites in matter. Stimulated by the rapid innovation in the development of various analysis methods for probing the atomic an

Hormuzd A. Katki, Li C. Cheung

Background: Screening trials require large sample sizes and long time-horizons to demonstrate mortality reductions. We recently proposed increasing statistical power by testing stored control-arm specimens, called the Intended Effect (IE) design. To evaluate feasibility of the IE design, the US National Cancer Institute (NCI) is collecting blood specimens in

Neli Laštovičková Streshkova, Petr Koutenský, Martin Kozák

In this work we propose a method for probing the chirality of nanoscale electromagnetic near fields utilizing the properties of a coherent superposition of free-electron vortex states in electron microscopes. Electron beams optically modulated into vortices carry orbital angular momentum, thanks to which they are sensitive to the spatial phase distribution a

Yubao Liu, Wenjie Zhong, Yanbei Chen, Yiqiu Ma

The evolution of quantum states influenced by semiclassical gravity is distinct from that in quantum gravity theory due to the presence of a state-dependent gravitational potential. This state-dependent potential introduces nonlinearity into the state evolution, of which the theory is named Schroedinger-Newton (SN) theory. The formalism for understanding the

Meysam Alizadeh, Yasaman Asgari, Zeynab Samei, Sara Yari

Academics increasingly acknowledge the predictive power of social media for a wide variety of events and, more specifically, for financial markets. Anecdotal and empirical findings show that cryptocurrencies are among the financial assets that have been affected by news and influencers' activities on Twitter. However, the extent to which Twitter crypto influ

Lan Zhang, Lipeng Wan, Weimin Deng, Liang Hou

Skyrmions are topological defects belonging to nontrivial homotopy classes in particle theory. Their remarkably stable topology has recently been observed in electromagnetic waves. For the evanescent fields near a surface, this has been realized so far only for elementary optical skyrmions, with a fixed skyrmion number. Here we report, both in theory and exp

Ruben Schmeitz, Joris Remmers, Olga Mula, Olaf van der Sluis

This study introduces a surrogate modeling framework merging proper orthogonal decomposition, long short-term memory networks, and multi-task learning, to accurately predict elastoplastic deformations in real-time. Superior to single-task neural networks, this approach achieves a mean absolute error below 0.40\% across various state variables, with the multi

Ryoto Ando, Kei Kimura, Taiki Todo, Makoto Yokoo

Diffusion mechanism design, which investigate how to incentivise agents to invite as many colleagues to a multi-agent decision making as possible, is a new research paradigm at the intersection between microeconomics and computer science. In this paper we extend traditional facility location games into the model of diffusion mechanism design. Our objective i

Noel Jeffrey Pinton, Alexandre Bousse, Zhihan Wang, Catherine Cheze-Le-Rest

We propose in this work a framework for synergistic positron emission tomography (PET)/computed tomography (CT) reconstruction using a joint generative model as a penalty. We use a synergistic penalty function that promotes PET/CT pairs that are likely to occur together. The synergistic penalty function is based on a generative model, namely $\beta$-variatio

Christopher Hughes, Solomon Lugmayer, Andrew Pearce-Crump

Conrey and Ghosh studied the second moment of the Riemann zeta function, evaluated at its local extrema along the critical line, finding the leading order behaviour to be $\frac{e^2 - 5}{2 \pi} T (\log T)^2$. This problem is closely related to a mixed moment of the Riemann zeta function and its derivative. We present a new approach which will uncover the low

Sangam Lee, Ryang Heo, SeongKu Kang, Susik Yoon

Generative retrieval directly decode a document identifier (i.e., docid) in response to a query, making it impossible to provide users with explanations as an answer for ``why is this document retrieved?''. To address this limitation, we propose Hierarchical Category Path-Enhanced Generative Retrieval (HyPE), which enhances explainability by first generating

Qinghai Huo, Pan Lian, Jiajia Si, Zhenghua Xu

Very recently, the concept of generalized partial-slice monogenic (or regular) functions has been introduced to unify the theory of monogenic functions and of slice monogenic functions over Clifford algebras. Inspired by the work of A. Perotti, in this paper we provide two analogous versions of the Almansi decomposition in this new setting. Additionally, two

Ali Ajorian, Erick Lavoie, Christian Tschudin

Obfuscation of computer programs has historically been approached either as a practical but \textit{ad hoc} craft to make reverse engineering subjectively difficult, or as a sound theoretical investigation unfortunately detached from the numerous existing constraints of engineering practical systems. In this paper, we propose \textit{instruction decorrelatio

Zhixun Lin, Wei He, Xinyi Liu, Mingchen Ye

Virtual reality (VR) environments have greatly expanded opportunities for immersive exploration, yet physically navigating these digital spaces remains a significant challenge. In this paper, we present the conceptual framework of NAVIS (Navigating Virtual Spaces with Immersive Scooters), a novel system that utilizes a scooter-based interface to enhance both

Andrew Pearce-Crump

Conrey, Ghosh and Gonek studied the first moment of the derivative of the Riemann zeta function evaluated at the non-trivial zeros of the zeta function, resolving a problem known as Shanks' conjecture. Conrey and Ghosh studied the second moment of the Riemann zeta function evaluated at its local extrema along the critical line to leading order. In this paper

Francesco Del Prato, Marc Fleurbaey

What happens when employers value worker welfare in frictional labor markets? We show this "responsibility" creates an endogenous wedge in the marginal labor cost -- akin to a hiring subsidy -- altering wage and vacancy incentives rather than only changing the surplus split. The wedge is strongest when outside options are weak and separations rare, implying

Siarhei Finski

We demonstrate that the weight operator associated with a submultiplicative filtration on the section ring of a polarized complex projective manifold is a Toeplitz operator. We further analyze the asymptotics of the associated weighted Bergman kernel, presenting the local refinement of earlier results on the convergence of jumping measures for submultiplicat

Yun-Jui Tsai, Ting Han Wei, Chi-Huang Lin, Chung-Chin Shih

Game solving is the process of finding the theoretical outcome for a game, assuming that all player choices are optimal. This paper focuses on a technique that can reduce the heuristic search space significantly for 7x7 Killall-Go. In Go and Killall-Go, live patterns are stones that are protected from opponent capture. Mutual life, also referred to as seki,

Hejer Ammar, Nikita Kiselov, Guillaume Lapouge, Romaric Audigier

In real-world applications where confidence is key, like autonomous driving, the accurate detection and appropriate handling of classes differing from those used during training are crucial. Despite the proposal of various unknown object detection approaches, we have observed widespread inconsistencies among them regarding the datasets, metrics, and scenario

Lucas de Amorin, Martin Mereb

We provided explicit formulas for the number of stringy points over finite fields of parabolic type A character varieties with generic semisimple monodromy. This leads to formulas for their stringy E-polynomials. In particular, they satisfy the Betti Topological Mirror Symmetry Conjecture of T. Hausel and M. Thaddeus, as well as a refinement regarding isotyp

Zacharie Van Herstraeten, Nicolas J. Cerf

Wigner-positive quantum states have the peculiarity to admit a Wigner function that is a genuine probability distribution over phase space. The Shannon differential entropy of the Wigner function of such states -- called Wigner entropy for brevity -- emerges as a fundamental information-theoretic measure in phase space and is subject to a conjectured lower b

Laure Ciernik, Lorenz Linhardt, Marco Morik, Jonas Dippel

The Platonic Representation Hypothesis claims that recent foundation models are converging to a shared representation space as a function of their downstream task performance, irrespective of the objectives and data modalities used to train these models (Huh et al., 2024). Representational similarity is generally measured for individual datasets and is not n

Krystal Guo, Vincent Schmeits

In this paper, we analyze state transfer in quantum walks by using combinatorial methods. We generalize perfect state transfer in two-reflection discrete-time quantum walks to a notion that we call 'peak state transfer'; we define peak state transfer as the highest state transfer that can be achieved between an initial and a target state under unitary evolut

Guilherme Zambon, Gerardo Adesso

Quantum thermodynamics studies how quantum systems and operations may be exploited as sources of work to perform useful thermodynamic tasks. In real-world conditions, the evolution of open quantum systems typically displays memory effects, resulting in a non-Markovian dynamics. The associated information backflow has been observed to provide advantage in cer

T. Banks

We comment on the fact that certain mathematical models that have been proposed in the quantum gravity literature, may not be subject to experimental checks, even if they turn out to be mathematically well defined. This means that they would be indistinguishable from other models, with a smaller number of quantum states. These considerations follow from very

Shubham Sharma, Animesh Renanse

A space $X$ is said to be $C$-trivial if the total Chern class $c(\alpha)$ equals $1$ for every complex vector bundle $\alpha$ over $X$. In this note we give a complete homological classification of $C$-trivial closed smooth manifolds of dimension $< 7$. In dimension $7$ we give a complete classification of orientable $C$-trivial manifolds and in the non-ori

Zongcheng Zuo, Yuanxiang Li, Tongtong Zhang

Due to different seasons, illumination, and atmospheric conditions, the photometric of the acquired image varies greatly, which leads to obvious stitching seams at the edges of the mosaic image. Traditional methods can be divided into two categories, one is absolute radiation correction and the other is relative radiation normalization. We propose a NeRF-bas

Eva Gunn, Nikhil Sengupta, Ben Swallow

Gaussian process are a widely-used statistical tool for conducting non-parametric inference in applied sciences, with many computational packages available to fit to data and predict future observations. We study the use of the Greta software for Bayesian inference to apply Gaussian process regression to spatio-temporal data of infectious disease outbreaks a

Ilias Bournias, Lukas Cavigelli, Georgios Zacharopoulos

Large Language Model (LLM) inference on large-scale systems is expected to dominate future cloud infrastructures. Efficient LLM inference in cloud environments with numerous AI accelerators is challenging, necessitating extensive optimizations for optimal performance. Current systems batch prefill and decoding to boost throughput but encounter latency issues

Jianqiang Ding, Shankar A. Deka

In this work, we present a novel Koopman spectrum-based reachability verification method for nonlinear systems. Contrary to conventional methods that focus on characterizing all potential states of a dynamical system over a presupposed time span, our approach seeks to verify the reachability by assessing the non-emptiness of estimated time-to-reach intervals

Yuval Filmus, Roy Schwartz, Alexander V. Smal

We consider two classic problems: maximum coverage and monotone submodular maximization subject to a cardinality constraint. [Nemhauser--Wolsey--Fisher '78] proved that the greedy algorithm provides an approximation of $1-1/e$ for both problems, and it is known that this guarantee is tight ([Nemhauser--Wolsey '78; Feige '98]). Thus, one would naturally assum

Rafael Berral-Soler, Rafael Muñoz-Salinas, Rafael Medina-Carnicer, Manuel J. Marín-Jiménez

Fiducial markers are a computer vision tool used for object pose estimation and detection. These markers are highly useful in fields such as industry, medicine and logistics. However, optimal lighting conditions are not always available,and other factors such as blur or sensor noise can affect image quality. Classical computer vision techniques that precisel

Yu Wu, Liangliang Guo, Renfei Wang, Jiawei Guo

A perpendicular magnetic field penetrating a thin type-II superconductor slab produces vortices, with one vortex per flux quantum, h/2e. The vortices interact repulsively and form an ordered array (Abrikosov lattice) in clean systems, while strong disorder changes the lattice into a vortex glass. Here we investigate type-II superconducting films (PdBi2 and N