February 2024 arXiv papers — page 146

Rafael Silva de Alencar, William Alberto Cruz Castañeda, Marcellus Amadeus

This work presents the early development of a model of image captioning for the Brazilian Portuguese language. We used the GRIT (Grid - and Region-based Image captioning Transformer) model to accomplish this work. GRIT is a Transformer-only neural architecture that effectively utilizes two visual features to generate better captions. The GRIT method emerged

Arian L. von Blanckenburg, Philip K. Schwartz

Twistless-torsional Newton--Cartan (TTNC) geometry exists in two variants, type I and type II, which differ by their gauge transformations. In TTNC geometry there exists a specific locally Galilei-invariant function, called by different names in existing literature, that we dub the `locally Galilei-invariant potential'. We show that in both types of TTNC geo

Yonghun Lee, Xin Wei, Yijun Yu, Lopa Bhatt

Progress in the study of infinite-layer nickelates has always been highly linked to materials advances. In particular, the recent development of superconductivity via hole-doping was predicated on the controlled synthesis of Ni in a very high oxidation state, and subsequent topotactic reduction to a very low oxidation state, currently limited to epitaxial th

Marco De Renzi, Jules Martel, Bangxin Wang

Starting from an abelian group $G$ and a factorizable ribbon Hopf $G$-bialgebra $H$, we construct a TQFT $J_H$ for connected framed cobordisms between connected surfaces with connected boundary decorated with cohomology classes with coefficients in $G$. When restricted to the subcategory of cobordisms with trivial decorations, our functor recovers a special

Alix Decrop, Xavier Devroey, Mike Papadakis, Pierre-Yves Schobbens

REST APIs are prevalent among web service implementations, easing interoperability through the HTTP protocol. API testers and users exploit the widely adopted OpenAPI Specification (OAS), a machine-readable standard to document REST APIs. However, documenting APIs is a time-consuming and error-prone task, and existing documentation is not always complete, pu

Paul Viallard, Maxime Haddouche, Umut Şimşekli, Benjamin Guedj

This paper contains a recipe for deriving new PAC-Bayes generalisation bounds based on the $(f, \Gamma)$-divergence, and, in addition, presents PAC-Bayes generalisation bounds where we interpolate between a series of probability divergences (including but not limited to KL, Wasserstein, and total variation), making the best out of many worlds depending on th

Jordan Juravsky, Bradley Brown, Ryan Ehrlich, Daniel Y. Fu

Transformer-based large language models (LLMs) are now deployed to hundreds of millions of users. LLM inference is commonly performed on batches of sequences that share a prefix, such as few-shot examples or a chatbot system prompt. Decoding in this large-batch setting can be bottlenecked by the attention operation, which reads large key-value (KV) caches fr

Marcin Sendera, Minsu Kim, Sarthak Mittal, Pablo Lemos

We study the problem of training diffusion models to sample from a distribution with a given unnormalized density or energy function. We benchmark several diffusion-structured inference methods, including simulation-based variational approaches and off-policy methods (continuous generative flow networks). Our results shed light on the relative advantages of

Félix Foutel-Rodier

We introduce a notion of vague convergence for random marked metric measure spaces. Our main result shows that convergence of the moments of order $k \ge 1$ of a random marked metric measure space is sufficient to obtain its vague convergence in the Gromov-weak topology. This result improves on previous methods of moments that also require convergence of the

Jiyong Cheon, Joowang Son, Sungbin Lim, Yundon Jeong

Real-life bacteria often swim in complex fluids, but our understanding of the interactions between bacteria and complex surroundings is still evolving. In this work, rod-like \textit{Bacillus subtilis} swims in a quasi-2D environment with aqueous liquid-liquid interfaces, i.e., the isotropic-nematic coexistence phase of an aqueous chromonic liquid crystal. F

Jose Antonio Carrillo, Shuchen Guo

We prove the existence of weak solutions of a class of multi-species cross-diffusion systems as well as the propagation of chaos result by means of nonlocal approximation of the nonlinear diffusion terms, coupling methods and compactness arguments. We also prove the uniqueness under further structural assumption on the mobilities by combining the uniqueness

Janko Boehm, Magdaleen S. Marais, Gerhard Pfister

Our recent extension of Arnold's classification includes all singularities of corank up to two equivalent to a germ with a non-degenerate Newton boundary, thus broadening the classification's scope significantly by a class which is unbounded with respect to modality and Milnor number. This method is based on proving that all right-equivalence classes within

Chen Li, Qi Liang, Pradyumna Paranjape, RuGway Wu

We implement two types of matter-wave interferometers using trapped Bose-condensed Feshbach molecules, from weak to strong interactions. In each case, we focus on investigating interaction effects and their implications for the performance. In the Ramsey-type interferometer where interference between the two motional quantum states in an optical lattice is o

Thibaut Arnoulx de Pirey

We present an exact solution for one-dimensional overdamped dynamics near a hard wall, allowing us to connect steady-state distributions under confinement with the extreme value statistics of unconfined stochastic processes. This mapping holds regardless of the statistics of the noise driving the dynamics. We first apply this result within Brownian motion th

Dennis Hoftijzer, Gertjan Burghouts, Luuk Spreeuwers

Deep Reinforcement Learning (DRL) has shown great potential in enabling robots to find certain objects (e.g., `find a fridge') in environments like homes or schools. This task is known as Object-Goal Navigation (ObjectNav). DRL methods are predominantly trained and evaluated using environment simulators. Although DRL has shown impressive results, the simulat

Marco Barbieri, Pablo Spiga

We find a lower bound on the proportion of derangements in a finite transitive group that depends on the minimal nontrivial subdegree. As a consequence, we prove that, if $\Gamma$ is a $G$-vertex-transitive digraph of valency $d\ge 1$, then the proportion of derangements in $G$ is greater than $1/2d$.

Renzo Gómez, Juan Gutiérrez

Given a graph~$G$, the domination number, denoted by~$\gamma(G)$, is the minimum cardinality of a dominating set in~$G$. Dual to the notion of domination number is the packing number of a graph. A packing of~$G$ is a set of vertices whose pairwise distance is at least three. The packing number~$\rho(G)$ of~$G$ is the maximum cardinality of one such set. Furt

James Williams, Rajveer Nehra, Elina Sendonaris, Luis Ledezma

Photonics offers unique capabilities for quantum information processing (QIP) such as room-temperature operation, the scalability of nanophotonics, and access to ultrabroad bandwidths and consequently ultrafast operation. Ultrashort-pulse sources of quantum states in nanophotonics are an important building block for achieving scalable ultrafast QIP, however,

Giacomo Francisci, Anand N. Vidyashankar

Motivated by applications to the study of depth functions for tree-indexed random variables generated by point processes, we describe functional limit theorems for the intensity measure of point processes. Specifically, we establish uniform laws of large numbers and uniform central limit theorems over a class of bounded measurable functions for estimates of

Samuel Metais, Sisira Suresh, Paulo Diniz, Siddarth Shivkumar

We present a comprehensive strategy and its practical implementation using the commercial ScanImage software platform to perform hyperspectral point scanning microscopy when a fast time dependent signal varies at each pixel level. In the proposed acquisition scheme the scan along the X axis is slowed down while the data acquisition is maintained at high pace

Harrison LaBollita, Jesse Kapeghian, Michael R. Norman, Antia S. Botana

Motivated by the recent observation of superconductivity in the pressurized trilayer La$_4$Ni$_3$O$_{10}$ Ruddlesden-Popper (RP) nickelate, we explore its structural, electronic, and magnetic properties as a function of hydrostatic pressure from first-principles calculations. We find that in both the bilayer and trilayer nickelates, an orthorhombic(monoclini

Tanmay Neema, Susmit Jha, Tuhin Sahai

Reinforcement Learning (RL) techniques have been increasingly applied in optimizing control systems. However, their application in quantum systems is hampered by the challenge of performing closed-loop control due to the difficulty in measuring these systems. This often leads to reliance on assumed models, introducing model bias, a problem that is exacerbate

Marta Fernandez, David Guerra, Unai Gil, Inigo Trigo

This paper presents an evaluation of the WiFi exposure levels inside the university in the 2.4 GHz frequency band. The selected environment is the typical scenario where WiFi exposure concerns have increased in the last years, since a Wireless Local Area Network is deployed close to the users. Measurements of 1 h and 24 h of duration were performed to assess

Fabio Berra, Estefanía Dalmasso, Roberto Scotto

We will show that, contrary to the behavior of the higher order Riesz transforms studied so far on the atomic Hardy space $\mathcal{H}^1(\mathbb R^n, \gamma)$, associated with the Ornstein-Uhlenbeck operator with respect to the $n$-dimensional Gaussian measure $\gamma$, the new Gaussian Riesz transforms are bounded from $\mathcal{H}^1(\mathbb R^n, \gamma)$ t

Boyi Wei, Kaixuan Huang, Yangsibo Huang, Tinghao Xie

Large language models (LLMs) show inherent brittleness in their safety mechanisms, as evidenced by their susceptibility to jailbreaking and even non-malicious fine-tuning. This study explores this brittleness of safety alignment by leveraging pruning and low-rank modifications. We develop methods to identify critical regions that are vital for safety guardra

Ittai Fraenkel, Jorge Kurchan, Dov Levine

It is often stated that if one is presented with a snapshot of the positions of the molecules of a glass and one of a liquid, one is unable to tell the difference. Here we argue instead that given several such snapshots taken over a time-interval, even without specifying the times, there is a definite procedure to assess precisely the level of glassiness: it

Dinesh Kumar Panda, Colin Benjamin

Entanglement with single-particle states is advantageous in quantum technology because of their ability to encode and process information more securely than their multi-particle analogs. Threeway and nonlocal two-way entangled single-particle states are desirable in this context. Herein, we generate genuine three-way entanglement from an initially separable

Ziyang Wang, Jian-Qing Zheng, Yichi Zhang, Ge Cui

In recent advancements in medical image analysis, Convolutional Neural Networks (CNN) and Vision Transformers (ViT) have set significant benchmarks. While the former excels in capturing local features through its convolution operations, the latter achieves remarkable global context understanding by leveraging self-attention mechanisms. However, both architec

David Martin, Gianmarco Spera, Hugues Chaté, Charlie Duclut

The nature of the transition to collective motion in assemblies of aligning self-propelled particles remains a long-standing matter of debate. In this article, we focus on dry active matter and show that weak fluctuations suffice to generically turn second-order mean-field transitions into a `discontinuous' coexistence scenario. Our theory shows how fluctuat

Zhilan Wang, Jin Yan, Jie Zhang

Let $k$ be a positive integer. A $k$-cycle-factor of an oriented graph is a set of disjoint cycles of length $k$ that covers all vertices of the graph. In this paper, we prove that there exists a positive constant $c$ such that for $n$ sufficiently large, any oriented graph on $n$ vertices with both minimum out-degree and minimum in-degree at least $(1/2-c)n

Yuming Han

People often learn from other's actions when they make decisions while doing online shopping. This kind of observational learning may lead to information cascades, which means agents might ignore their own signals and follow the 'trend' created collectively by the actions of their predecessors. It is well-known that with rational agents, such a cascade model

Pratham Mehta, Harsha Karanth, Haoyang Yang, Timothy Slesnick

Surgical planning for congenital heart diseases requires a collaborative approach, traditionally involving the 3D-printing of physical heart models for inspection by surgeons and cardiologists. Recent advancements in mobile augmented reality (AR) technologies have offered a promising alternative, noted for their ease-of-use and portability. Despite this prog

Debarupa Saha, Kornikar Sen, Chirag Srivastava, Ujjwal Sen

We relate the the distinguishability of quantum states with their robustness of the entanglement, where the robustness of any resource quantifies how tolerant it is to noise. In particular, we identify upper and lower bounds on the probability of discriminating the states, appearing in an arbitrary multiparty ensemble, in terms of their robustness of entangl

Amin Heyrani Nobari, Giorgio Giannone, Lyle Regenwetter, Faez Ahmed

Topology optimization is a critical task in engineering design, where the goal is to optimally distribute material in a given space for maximum performance. We introduce Neural Implicit Topology Optimization (NITO), a novel approach to accelerate topology optimization problems using deep learning. NITO stands out as one of the first frameworks to offer a res

Alberto Dinelli, Jérémy O'Byrne, Julien Tailleur

In this article we derive and test the fluctuating hydrodynamic description of active particles interacting via taxis and quorum sensing, both for mono-disperse systems and for mixtures of co-existing species of active particles. We compute the average steady-state density profile in the presence of spatial motility regulation, as well as the structure facto

Ahmet Alacaoglu, Donghwan Kim, Stephen J. Wright

We focus on constrained, $L$-smooth, potentially stochastic and nonconvex-nonconcave min-max problems either satisfying $\rho$-cohypomonotonicity or admitting a solution to the $\rho$-weakly Minty Variational Inequality (MVI), where larger values of the parameter $\rho>0$ correspond to a greater degree of nonconvexity. These problem classes include examples

Munqath Al-atar, Attila Sali

A possible world of an incomplete database table is obtained by imputing values from the attributes (infinite) domain to the place of \texttt{NULL} s. A table satisfies a possible key or possible functional dependency constraint if there exists a possible world of the table that satisfies the given key or functional dependency constraint. A certain key or fu

Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell Gordon

With increased power and prevalence of AI systems, it is ever more critical that AI systems are designed to serve all, i.e., people with diverse values and perspectives. However, aligning models to serve pluralistic human values remains an open research question. In this piece, we propose a roadmap to pluralistic alignment, specifically using language models

Jakob Fuchs, Matthias Röger

In this paper we introduce a mesoscale continuum model for membranes made of two different types of amphiphilic lipids. The model extends work by Peletier and the second author [Arch. Ration. Mech. Anal. 193, 2009] for the one-phase case. We present a mathematical analysis of the asymptotic reduction to the macroscale when a key length parameter becomes arbi

Atal Tewari, Nitin Khanna

Craters are one of the most studied planetary features used for different scientific analyses, such as estimation of surface age and surface processes. Satellite images utilized for crater detection often have low resolution (LR) due to hardware constraints and transmission time. Super-resolution (SR) is a practical and cost-effective solution; however, most

Jing Wang, Zheng Li, Pengyu Lai, Rui Wang

Multiscale phenomena manifest across various scientific domains, presenting a ubiquitous challenge in accurately and effectively simulating multiscale dynamics in complex systems. In this paper, a novel decoupling solving paradigm is proposed through modelling large-scale dynamics independently and treating small-scale dynamics as a slaved system. A Spectral

Shathushan Sivashangaran, Apoorva Khairnar, Azim Eskandarian

Autonomous Mobile Robot (AMR) navigation in dynamic environments that may be GPS denied, without a-priori maps, is an unsolved problem with potential to improve humanity's capabilities. Conventional modular methods are computationally inefficient, and require explicit feature extraction and engineering that inhibit generalization and deployment at scale. We

Manuel Escabias, Ana M. Aguilera, Christian Acal

The functional logit regression model was proposed by Escabias et al. (2004) with the objective of modeling a scalar binary response variable from a functional predictor. The model estimation proposed in that case was performed in a subspace of L2(T) of squared integrable functions of finite dimension, generated by a finite set of basis functions. For that e

Wenyu Liang, Pablo R. Baldivieso, Ross Drummond, Donghwan Shin

Typical autonomous driving systems are a combination of machine learning algorithms (often involving neural networks) and classical feedback controllers. Whilst significant progress has been made in recent years on the neural network side of these systems, only limited progress has been made on the feedback controller side. Often, the feedback control gains

Thibaut Arnoulx de Pirey, Guy Bunin

Many-variable differential equations with random coefficients provide powerful models for the dynamics of many interacting species in ecology. These models are known to exhibit a dynamical phase transition from a phase where population sizes reach a fixed point, to a phase where they fluctuate indefinitely. Here we provide a theory for the critical behavior

R. Barille, A. Korbut, S. Zielinska, E. Ortyl

The dewetting of an azopolymer droplet, followed by the photostructuration of the evaporated droplet, is employed to create an amplitude mask. This straightforward process yields a large area featuring periodic micro- and nanostructures. The resulting pattern is utilized to generate a nondiffracting beam. Starting with a Gaussian beam illuminating the amplit

Declan S. Jagt, Matthew M. Peet

Any suitably well-posed PDE in two spatial dimensions can be represented as a Partial Integral Equation (PIE) -- with system dynamics parameterized using Partial Integral (PI) operators. Furthermore, $L_2$-gain analysis of PDEs with a PIE representation can be posed as a linear operator inequality, which can be solved using convex optimization. In this paper

Marek Klemes, Lan Hu, Greg Bowles, Mohammad Akbari

In this paper we document for the first time some of the effects of self-healing, a property of orbital-angular-momentum (OAM) or vortex beams, as observed on a millimeter-wave experimental communications link in an outdoors line-of-sight (LOS) scenario. The OAM beams have a helical phase and polarization structure and have conical amplitude shape in the far

József Balogh, Anita Liebenau, Letícia Mattos, Natasha Morrison

We address a problem which is a generalization of Tur\'an-type problems recently introduced by Imolay, Karl, Nagy and V\'ali. Let $F$ be a fixed graph and let $G$ be the union of $k$ edge-disjoint copies of $F$, namely $G = \mathbin{\dot{\cup}}_{i=1}^{k} F_i$, where each $F_i$ is isomorphic to a fixed graph $F$ and $E(F_i)\cap E(F_j)=\emptyset$ for all $i \n

Kirsten Eisentraeger, Gabrielle Scullard

We give a deterministic polynomial time algorithm to compute the endomorphism ring of a supersingular elliptic curve in characteristic p, provided that we are given two noncommuting endomorphisms and the factorization of the discriminant of the ring $\mathcal{O}_0$ they generate. At each prime $q$ for which $\mathcal{O}_0$ is not maximal, we compute the endo

Yunkai Tang, Donghui Liu, Shouhong Shan, Dongke Li

Rare-earth (Re)Ba2Cu3O7-x (ReBCO) no-insulation (NI) coil is widely concerned due to its excellent electromagnetic and thermal properties. However, the presence of the turn-to-turn shunts in NI coils leads to that complexity of numerical simulation is increased. In this paper, a modified J model is proposed and the corresponding explicit-implicit hybrid algo

Munqath Al-atar, Attila Sali

In case of incomplete database tables, a possible world is obtained by replacing any missing value by a value from the corresponding attribute's domain that can be infinite. A possible key or possible functional dependency constraint is satisfied by an incomplete table if we can obtain a possible world that satisfies the given key or functional dependency. O

Weixin Liang, Nazneen Rajani, Xinyu Yang, Ezinwanne Ozoani

The rapid proliferation of AI models has underscored the importance of thorough documentation, as it enables users to understand, trust, and effectively utilize these models in various applications. Although developers are encouraged to produce model cards, it's not clear how much information or what information these cards contain. In this study, we conduct

Benjamin Michele, Ivan Pena, Pablo Angueira

The DVB standard does not mandate the use of authentication and integrity protection for transport streams. This allows malicious third parties to replace legitimate broadcasts by overpowering terrestrial transmissions. The rogue signal can then deliver a malicious broadcast stream to exploit security vulnerabilities on Smart TVs (STVs) in range. We implemen

AKM Shahariar Azad Rabby, Hasmot Ali, Md. Majedul Islam, Sheikh Abujar

This research paper presents a unique Bengali OCR system with some capabilities. The system excels in reconstructing document layouts while preserving structure, alignment, and images. It incorporates advanced image and signature detection for accurate extraction. Specialized models for word segmentation cater to diverse document types, including computer-co

Ananya Bandopadhyay, Keisi Kacanja, Rahul Somasundaram, Alexander H. Nitz

The next generation of ground-based interferometric gravitational wave detectors will observe mergers of black holes and neutron stars throughout cosmic time. A large number of the binary neutron star merger events will be observed with extreme high fidelity, and will provide stringent constraints on the equation of state of nuclear matter. In this paper, we

Sam Adriaensen, Maarten De Boeck

In this paper, we study association schemes on the anisotropic points of classical polar spaces. Our main result concerns non-degenerate elliptic and hyperbolic quadrics in PG$(n,q)$ with $q$ odd. We define relations on the anisotropic points of such a quadric that depend on the type of line spanned by the points and whether or not they are of the same "quad

Jiaxiang Tang, Zhaoxi Chen, Xiaokang Chen, Tengfei Wang

3D content creation has achieved significant progress in terms of both quality and speed. Although current feed-forward models can produce 3D objects in seconds, their resolution is constrained by the intensive computation required during training. In this paper, we introduce Large Multi-View Gaussian Model (LGM), a novel framework designed to generate high-

Junhong Nie, Wei Zi, Xiaoming Sun

Resource consumption is an important issue in quantum information processing, particularly during the present NISQ era. In this paper, we investigate resource optimization of implementing multiple controlled operations, which are fundamental building blocks in the field of quantum computing and quantum simulation. We design new quantum circuits for the $n$-T

Kun Zhang, Shaoan Xie, Ignavier Ng, Yujia Zheng

In many problems, the measured variables (e.g., image pixels) are just mathematical functions of the latent causal variables (e.g., the underlying concepts or objects). For the purpose of making predictions in changing environments or making proper changes to the system, it is helpful to recover the latent causal variables $Z_i$ and their causal relations re

Dominik Krasula

For Dynkin and Euclidean quivers, it is shown that Gabriel-Roiter measures of thin representations equal the induced chain length functions on the corresponding system of subquivers. This allows a combinatorial procedure to find a GR filtration of thin representations, showing that GR measures of thin representations are field-independent. It is proved that

Nazarii Tupitsa, Samuel Horváth, Martin Takáč, Eduard Gorbunov

In Federated Learning (FL), the distributed nature and heterogeneity of client data present both opportunities and challenges. While collaboration among clients can significantly enhance the learning process, not all collaborations are beneficial; some may even be detrimental. In this study, we introduce a novel algorithm that assigns adaptive aggregation we

Bhupendra C. S. Chauhan, Pawan Kumar Joshi, B. C. Chanyal

In the present discussion, we have studied the Z2-grading of quaternion algebra (H). We have made an attempt to extend the quaternion Lie algebra to the graded Lie algebra by using the matrix representations of quaternion units. The generalized Jacobi identities of Z2-graded algebra then result in symmetric graded partners (N1;N2;N3). The graded partner alge

Paul Ramond, Soichiro Isoyama

This work constitutes the second part of a series of studies that aim to utilise tools from Hamiltonian mechanics to investigate the motion of an extended body in general relativity. The first part of this work [Refs. [1, 2]] constructed a ten-dimensional, covariant Hamiltonian framework encompassing all the linear-in-spin corrections to the geodesic motion

Leonardo C. T. Bezerra, Alexander E. I. Brownlee, Luana Ferraz Alvarenga, Renan Cipriano Moioli

Artificial intelligence (AI) has driven many information and communication technology (ICT) breakthroughs. Nonetheless, the scope of ICT systems has expanded far beyond AI since the Turing test proposal. Critically, recent AI regulation proposals adopt AI definitions affecting ICT techniques, approaches, and systems that are not AI. In some cases, even works

Tianlong Yu

In this note we prove that every bounded pseudoconvex domain in $\mathbb{C}^n$ with H$\ddot{o}$lder boundary has positive log-hyperconvexity index.

Hector Hutin, Antoine Essig, Réouven Assouly, Pierre Rouchon

The number of excitations in a large quantum system (harmonic oscillator or qudit) can be measured in a quantum nondemolition manner using a dispersively coupled qubit. It typically requires a series of qubit pulses that encode various binary questions about the photon number. Recently, a method based on the fluorescence measurement of a qubit driven by a tr

Rafael Prieto-Curiel, Pavel Luengas-Sierra, Christian Borja-Vega

Many cities are expanding in areas with scarce rainfall and limited water retention capacity, and are also becoming elongated and sprawled, making it harder to deliver services. This study quantifies the impact of urban form on access to water. We craft comparable urban forms for over 100 cities in Asia, Africa, and Latin America. For each city, we analyse t

Hersh Vakharia, Xiaoxiao Du

Multi-modal sensor data fusion takes advantage of complementary or reinforcing information from each sensor and can boost overall performance in applications such as scene classification and target detection. This paper presents a new method for fusing multi-modal and multi-resolution remote sensor data without requiring pixel-level training labels, which ca

Lijun Li, Bowen Dong, Ruohui Wang, Xuhao Hu

In the rapidly evolving landscape of Large Language Models (LLMs), ensuring robust safety measures is paramount. To meet this crucial need, we propose \emph{SALAD-Bench}, a safety benchmark specifically designed for evaluating LLMs, attack, and defense methods. Distinguished by its breadth, SALAD-Bench transcends conventional benchmarks through its large sca

Lucas Rovige, Filipe D. Cruz, Robert S. Dorst, Jessica J. Pilgram

Mini-magnetospheres are small ion-scale structures that are well-suited to studying kinetic-scale physics of collisionless space plasmas. Such ion-scale magnetospheres can be found on local regions of the Moon, associated with the lunar crustal magnetic field. In this paper, we report on the laboratory experimental study of magnetic reconnection in laser-dri

Joshua Smailes, Edd Salkield, Sebastian Köhler, Simon Birnbach

In the wake of increasing numbers of attacks on radio communication systems, a range of techniques are being deployed to increase the security of these systems. One such technique is radio fingerprinting, in which the transmitter can be identified and authenticated by observing small hardware differences expressed in the signal. Fingerprinting has been explo

Andreas Eberle, Francis Lörler

We propose a new concept of lifts of reversible diffusion processes and show that various well-known non-reversible Markov processes arising in applications are lifts in this sense of simple reversible diffusions. Furthermore, we introduce a concept of non-asymptotic relaxation times and show that these can at most be reduced by a square root through lifting

Alexander Gladkov

In this paper we consider initial boundary value problem for a parabolic equation with nonlinear memory and absorption under nonlinear nonlocal boundary condition. We prove global existence and blow-up of solutions.

Xu Zheng, Farhad Shirani, Tianchun Wang, Shouwei Gao

Graphical models capture relations between entities in a wide range of applications including social networks, biology, and natural language processing, among others. Graph neural networks (GNN) are neural models that operate over graphs, enabling the model to leverage the complex relationships and dependencies in graph-structured data. A graph explanation i

Evgeny Abakumov, Arafat Abbar

This paper explores the notions of $\mathcal{F}$-transitivity and topological $\mathcal{F}$-recurrence for backward shift operators on weighted $\ell^p$-spaces and $c_0$-spaces on directed trees, where $\mathcal{F}$ represents a Furstenberg family of subsets of $\mathbb{N}_0$. In particular, we establish the equivalence between recurrence and hypercyclicity

Ainoor Teimoorzadeh, Frederico Fernandes Afonso Silva, Luis F. C. Figueredo, Sami Haddadin

This paper investigates the tracking problem of a smooth coordinate-invariant trajectory using dual quaternion algebra. The proposed architecture consists of a cascade structure in which the outer-loop MPC performs real-time smoothing of the manipulator's end-effector twist while an inner-loop kinematic controller ensures tracking of the instantaneous desire

Biswajit Mondal, P. S. Athiray, Amy R. Winebarger, Sabrina L. Savage

Nanoflares are thought to be one of the prime candidates that can heat the solar corona to its multi-million kelvin temperature. Individual nanoflares are difficult to detect with the present generation instruments, however their presence can be inferred by comparing simulated nanoflare-heated plasma emissions with the observed emission. Using HYDRAD coronal

Ziwei Niu, Shuyi Ouyang, Shiao Xie, Yen-wei Chen

Medical Image Analysis (MedIA) has emerged as a crucial tool in computer-aided diagnosis systems, particularly with the advancement of deep learning (DL) in recent years. However, well-trained deep models often experience significant performance degradation when deployed in different medical sites, modalities, and sequences, known as a domain shift issue. In

Miriam Cuscito, Alfio Ferrara, Martin Ruskov

In this paper, we explore the idea of analysing the historical bias of contextual language models based on BERT by measuring their adequacy with respect to Early Modern (EME) and Modern (ME) English. In our preliminary experiments, we perform fill-in-the-blank tests with 60 masked sentences (20 EME-specific, 20 ME-specific and 20 generic) and three different

Hanna Mazzawi, Pranjal Awasthi, Xavi Gonzalvo, Srikumar Ramalingam

Recent breakthroughs and successful deployment of large language and vision models in a constrained environment predominantly follow a two phase approach. First, large models are trained to achieve peak performance, followed by a model shrinking method to meet hardware constraints; Methods like distillation, compression or quantization help leverage the high

Ikhyun Cho, Changyeon Park, Julia Hockenmaier

Machine unlearning (MUL) is an arising field in machine learning that seeks to erase the learned information of specific training data points from a trained model. Despite the recent active research in MUL within computer vision, the majority of work has focused on ResNet-based models. Given that Vision Transformers (ViT) have become the predominant model ar

Sue L. Rhâmidda, Mauricio Girardi-Schappo, Osame Kinouchi

Transient or partial synchronization can be used to do computations, although a fully synchronized network is frequently related to epileptic seizures. Here, we propose a homeostatic mechanism that is capable of maintaining a neuronal network at the edge of a synchronization transition, thereby avoiding the harmful consequences of a fully synchronized networ

Natalia Chepiga

We study dimerization transitions in a frustrated spin-3 chain with next-nearest neighbor and three-site interactions. We show that two independent coupling constants of the model are sufficient to fine-tune the system to the critical point in the Wess-Zumino-Witten SU(2)$_6$ universality class. This critical point appears as the end point of an extended SU(

Aristide Houndetoungan, Abdoul Haki Maoude

We present a simulation-based inference approach for two-stage estimators, focusing on extremum estimators in the second stage. We accommodate a broad range of first-stage estimators, including extremum estimators, high-dimensional estimators, and other types of estimators such as Bayesian estimators. The key contribution of our approach lies in its ability

Hyesop Shin

This study evaluates the health effects of long-term exposure to PM10 in Seoul. Building on the preliminary model Shin and Bithell (2019), an in-silico agent-based model (ABM) is used to simulate the travel patterns of individuals according to their origins and destinations. During the simulation, each person, with their inherent socio-economic attributes an

Inmaculada Gutiérrez, Juan Antonio Guevara, Daniel Gómez, Javier Castro

In this paper, we address one of the most important topics in the field of Social Networks Analysis: the community detection problem with additional information. That additional information is modeled by a fuzzy measure that represents the risk of polarization. Particularly, we are interested in dealing with the problem of taking into account the polarizatio

Paola Cattabriga

In this article we discuss the proof in the short unpublished paper appeared in the 3rd volume of Godel's Collected Works entitled "On undecidable sentences" (*1931?), which provides an introduction to Godel's 1931 ideas regarding the incompleteness of arithmetic. We analyze the meaning of the negation of the provability predicate, and how it is meant not to

M. Lopez-Corredoira, X. -C. Tang, H. Tian, H. -F. Wang

AIMS. We derive the morphology of the stellar component in the outer halo volume, and search for possible overdensities due to substructures therein. METHODS. We made use of some of the data releases of the spectroscopic survey LAMOST DR8-DR9 in tandem with distance determinations for two subsamples, that is, of K-giants and M-giants, respectively, making up

Jannis Weil, Zhenghua Bao, Osama Abboud, Tobias Meuser

Graph-based environments pose unique challenges to multi-agent reinforcement learning. In decentralized approaches, agents operate within a given graph and make decisions based on partial or outdated observations. The size of the observed neighborhood limits the generalizability to different graphs and affects the reactivity of agents, the quality of the sel

Chenguang Su, Qian Liu, Linqquan Kong, Shi Chen

In this study, we comprehensively characterized and optimized a cryogenic pure CsI (pCsI) detector. We utilized a {$\SI{2}{cm}\times\SI{2}{cm}\times\SI{2}{cm}$} cube crystal coupled with a HAMAMATSU R11065 photomultiplier tube, achieving a remarkable light yield of \SI{35.2}{PE/\keV_{ee}} and an unprecedented energy resolution of \SI{6.9}{\%} at {\SI{59.54}{

Rahul Yedida, Snehanshu Saha

We propose a novel white-box approach to hyper-parameter optimization. Motivated by recent work establishing a relationship between flat minima and generalization, we first establish a relationship between the strong convexity of the loss and its flatness. Based on this, we seek to find hyper-parameter configurations that improve flatness by minimizing the s

Yulin Yu, Daniel M. Romero

Scientific datasets play a crucial role in contemporary data-driven research, as they allow for the progress of science by facilitating the discovery of new patterns and phenomena. This mounting demand for empirical research raises important questions on how strategic data utilization in research projects can stimulate scientific advancement. In this study,

Georg Hartl, Conrad Gstöttner, Bernd Kolar, Markus Schöberl

In this paper, we examine the exact linearization of configuration flat Lagrangian control systems in generalized state representation with p degrees of freedom and p-1 control inputs by quasi-static feedback of its generalized state. We formally introduce generalized Lagrangian control systems, which are obtained when configuration variables are considered

Anson Kost, Lucas Johns, Huaiyu Duan

Collective neutrino oscillations are typically studied using the lowest-order quantum kinetic equation, also known as the mean-field approximation. However, some recent quantum many-body simulations suggest that quantum entanglement among neutrinos may be important and may result in flavor equilibration of the neutrino gas. In this work, we develop new quant

Enrica Floris, Sokratis Zikas

We study the equivariant geometry of special quadric fibrations, called Umemura quadric fibrations, as well as the maximality of their automorphism groups inside $Cr_n(\mathbb{C})$. We produce infinite families of pairwise non-conjugate maximal connected algebraic subgroups of $Cr_n(\mathbb{C})$.

Hamza Mahdi, Eptehal Nashnoush, Rami Saab, Arjun Balachandar

This study assesses deep learning models for audio classification in a clinical setting with the constraint of small datasets reflecting real-world prospective data collection. We analyze CNNs, including DenseNet and ConvNeXt, alongside transformer models like ViT, SWIN, and AST, and compare them against pre-trained audio models such as YAMNet and VGGish. Ou

Martin Bishop

In this paper we compute the integral Chow ring of the moduli space of stable elliptic curves with three marked points by combining several patching techniques, including higher Chow groups with $\ell$-adic coefficients.

M. Nowak, S. Lacour, R. Abuter, A. Amorim

Dual-field interferometric observations with VLTI/GRAVITY sometimes require the use of a "binary calibrator", a binary star whose individual components remain unresolved by the interferometer, with a separation between 400 and 2000 mas for observations with the Units Telescopes (UTs), or 1200 to 3000 mas for the Auxiliary Telescopes (ATs). The separation vec

Refik Mansuroglu, Arsalan Adil, Michael J. Hartmann, Zoë Holmes

The Schmidt decomposition is the go-to tool for measuring bipartite entanglement of pure quantum states. Similarly, it is possible to study the entangling features of a quantum operation using its operator-Schmidt, or tensor product decomposition. While quantum technological implementations of the former are thoroughly studied, entangling properties on the o