December 2023 arXiv papers — page 8

Felipe Oliveira, Victoria Reis, Nelson Ebecken

Social media has become integral to human interaction, providing a platform for communication and expression. However, the rise of hate speech on these platforms poses significant risks to individuals and communities. Detecting and addressing hate speech is particularly challenging in languages like Portuguese due to its rich vocabulary, complex grammar, and

Mohit Gupta, Vipin Khade, Colin Riggert, Lior Shani

Josephson junctions are typically characterized by a single phase difference across two superconductors. This conventional two-terminal Josephson junction can be generalized to a multi-terminal device where the Josephson energy contains terms with contributions from multiple independent phase variables. Such multi-terminal Josephson junctions (MTJJs) are bei

Germán G. Blesio, Luis O. Manuel, Armando A. Aligia

A few years ago, a topological quantum phase transition (TQPT) has been found in Anderson and Kondo 2-channel spin-1 impurity models that include a hard-axis anisotropy term $DS_z^2$ with $D > 0$. The most remarkable manifestation of the TQPT is a jump in the spectral density of localized electrons, at the Fermi level, from very high to very low values as $D

Patrik Róbert Gerber, Tianze Jiang, Yury Polyanskiy, Rui Sun

We propose a new density estimation algorithm. Given $n$ i.i.d. observations from a distribution belonging to a class of densities on $\mathbb{R}^d$, our estimator outputs any density in the class whose "perceptron discrepancy" with the empirical distribution is at most $O(\sqrt{d / n})$. The perceptron discrepancy is defined as the largest difference in mas

Paul Worm, Matthias Reitner, Karsten Held, Alessandro Toschi

We present an analytically solvable model for correlated electrons, which is able to capture the major Fermi surface modifications occurring in both hole- and electron-doped cuprates as a function of doping. The proposed Hamiltonian qualitatively reproduces the results of numerically demanding many-body calculations, here obtained using the dynamical vertex

Saurabh Sharma, Aayushi Verma, Kshitiz Mallick, Lokesh K. Dewangan

We present a multi-wavelength analysis of the star cluster NGC 2316 and its surroundings. We estimated the physical parameters of the NGC 2316 cluster, including its shape (elongated), size (Rcluster = 0.4 pc), distance (1.3 +/- 0.3 kpc), and minimum reddening (AV = 1.55 mag). We discovered two massive stars (B2.0V-B1.5V, age ~12 Myr) embedded (AV = 4 mag) w

Johannes Kraus, Kundan Kumar, Maria Lymbery, Florin Adrian Radu

In this paper we consider a nonlinear poroelasticity model that describes the quasi-static mechanical behaviour of a fluid-saturated porous medium whose permeability depends on the divergence of the displacement. Such nonlinear models are typically used to study biological structures like tissues, organs, cartilage and bones, which are known for a nonlinear

Stefan Kluth, Wolfgang Ochs, Redamy Perez Ramos

The production of a heavy quark is accompanied by gluon bremsstrahlung with angular and momentum spectra predicted by perturbative Quantum Chromo Dynamics (QCD). The radiation off heavy quarks is predicted to be suppressed for large momentum particles, as a consequence of the angular ``dead cone effect''. In this paper, we studied this effect using data from

Yihao Chen, Simon A. Rogers, Suresh Narayanan, James L. Harden

An intrinsic feature of disordered and out-of-equilibrium materials, such as glasses, is the dependence of their properties on their history. An important example is rheological memory, in which disordered solids obtain properties based on their mechanical history. Here, we employ x-ray photon correlation spectroscopy (XPCS) with \textit{in situ} rheometry t

Stanislaw Mrowczynski

A strong enhancement of deuteron production in jets has been recently observed in proton-proton collisions at LHC. We show that the effect is due to two independent factors: a collimation of jet nucleons and a smallness of nucleon source which is significantly smaller than a deuteron.

Mats Volmer, Tom Struck, Arnau Sala, Bingjie Chen

In Si/SiGe heterostructures, the low-lying excited valley state seriously limit operability and scalability of electron spin qubits. For characterizing and understanding the local variations in valley splitting, fast probing methods with high spatial and energy resolution are lacking. Leveraging the spatial control granted by conveyor-mode spin-coherent elec

Stefan Weigert

Thomas S. Kuhn interprets the development of the (natural) sciences as a specific dynamical process. Periods of piecemeal growth of knowledge based on widely accepted paradigms are interrupted by bursts of revolutionary changes which lead to new paradigms incommensurate with the earlier ones. This process is briefly illustrated by recalling the changes to cl

Faizan Bhat, Pronobesh Maity

We compute the Mellin amplitude of the planar four-point correlator of weight-two half-BPS operators in $\mathcal{N}=4$ SYM at one and two-loop orders in the small 't Hooft coupling expansion. The two-loop Mellin amplitude has an infinite number of poles, as expected from a stringy bulk dual. We then perform a Mellin conformal block expansion of the amplitud

Alicia Bassière, Roxana Dumitrescu, Peter Tankov

We develop a model for the long-term dynamics of electricity market, based on mean-field games of optimal stopping. Our paper extends the recent contribution [A\"id, Ren\'e, Roxana Dumitrescu, and Peter Tankov, ``The entry and exit game in the electricity markets: A mean-field game approach." Journal of Dynamics \& Games 8.4 (2021): 331] in several ways, mak

Nikolai Peshcherenko, Claudia Felser, Yang Zhang

Nonlinear Hall effect arises in materials without inversion symmetry, and the intrinsic contribution is typically from Berry curvature dipole of non-universal Fermi pockets. Here we propose that nonlinear Hall effect can reach quantization in chiral Weyl semimetals without mirror symmetries. The energy shift between a pair of Weyl nodes leads to chirally asy

Marco Falda, Angela Grassi

The HTTPS protocol has enforced a higher level of robustness to several attacks; however, it is not easy to set up the required certificates on intranets, nor is it effective in the case the server confidentiality is not reliable, as in the case of cloud services, or it could be compromised. A simple method is proposed to encrypt the data on the client side,

Juan Porras, Davide Pecci, Gian Maria Bocchini, Sonja Gaviano

Distributed Acoustic Sensing (DAS) is becoming increasingly popular in microseismic monitoring operations. This data acquisition technology converts fiber-optic cables into dense arrays of seismic sensors that can sample the seismic wavefield produced by active or passive sources with a high spatial density, over distances ranging from a few hundred meters t

A. Duaibes, Yu. Karpeshina

The goal is a construction of stationary solutions close to a non-trivial combination of two plane waves at high energies for a periodic non-linear Schroedinger equation in dimension two. The corresponding isoenergetic surfaces are described for every sufficiently large energy.

Ioanna Ntinou, Enrique Sanchez, Georgios Tzimiropoulos

Action Localization is a challenging problem that combines detection and recognition tasks, which are often addressed separately. State-of-the-art methods rely on off-the-shelf bounding box detections pre-computed at high resolution, and propose transformer models that focus on the classification task alone. Such two-stage solutions are prohibitive for real-

Roman Poberezhnyuk, Oleh Savchuk, Volodymyr Vovchenko, Volodymyr Kuznietsov

Subensemble Acceptance Method (SAM) [1,2] is an essential link between measured event-by-event fluctuations and their grand canonical theoretical predictions such as lattice QCD. The method allows quantifying the global conservation law effects in fluctuations. In its basic formulation, SAM requires a sufficiently large system such as created in central nucl

Miloš Nikolić, Victoria Antonetti, Feng Liu, Gentian Muhaxheri

The body plan of the fruit fly is determined by the expression of just a handful of genes. We show that the spatial patterns of expression for several of these genes scale precisely with the size of the embryo. Concretely, discrete positional markers such as the peaks in striped patterns have absolute positions along the anterior-posterior axis that are prop

Ali Mehrban, Pegah Ahadian

Malware detection in IoT environments necessitates robust methodologies. This study introduces a CNN-LSTM hybrid model for IoT malware identification and evaluates its performance against established methods. Leveraging K-fold cross-validation, the proposed approach achieved 95.5% accuracy, surpassing existing methods. The CNN algorithm enabled superior lear

Jonathan Van der Cruysse, Christophe Dubach

Accelerating programs is typically done by recognizing code idioms matching high-performance libraries or hardware interfaces. However, recognizing such idioms automatically is challenging. The idiom recognition machinery is difficult to write and requires expert knowledge. In addition, slight variations in the input program might hide the idiom and defeat t

Lorenz Milla, Chao-Ping Chen

In this paper, we consider rational hypergeometric series of the form \[\frac{p}{\pi}= \sum_{k=0}^\infty u_k\quad\text{with}\quad u_k=\frac{\left(\frac{1}{2}\right)_k \left(q\right)_k \left(1-q\right)_k}{(k!)^3}(r+s\,k)\,t^k,\] where $(a)_k$ denotes the Pochhammer symbol and $p,q,r,s,t$ are algebraic coefficients. Using only the first $n+1$ terms of this ser

Feng Liang, Bichen Wu, Jialiang Wang, Licheng Yu

Diffusion models have transformed the image-to-image (I2I) synthesis and are now permeating into videos. However, the advancement of video-to-video (V2V) synthesis has been hampered by the challenge of maintaining temporal consistency across video frames. This paper proposes a consistent V2V synthesis framework by jointly leveraging spatial conditions and te

Lionel London, Michelle Foucoin

We present a polynomial basis that exactly tridiagonalizes Teukolsky's radial equation for quasi-normal modes. These polynomials naturally emerge from the radial problem, and they are canonical in that they possess key features of classical polynomials. Our canonical polynomials may be constructed using various methods, the simplest of which is the Gram-Schm

Kay Liu, Hengrui Zhang, Ziqing Hu, Fangxin Wang

A fundamental challenge confronting supervised graph outlier detection algorithms is the prevalent problem of class imbalance, where the scarcity of outlier instances compared to normal instances often results in suboptimal performance. Recently, generative models, especially diffusion models, have demonstrated their efficacy in synthesizing high-fidelity im

Salman Haidri

The advent of compact, handheld devices has given us a pool of tracked movement data that could be used to infer trends and patterns that can be made to use. With this flooding of various trajectory data of animals, humans, vehicles, etc., the idea of ANALYTiC originated, using active learning to infer semantic annotations from the trajectories by learning f

Lionel London

A scalar product for quasinormal mode solutions to Teukolsky's homogeneous radial equation is presented. Evaluation of this scalar product can be performed either by direct integration, or by evaluation of a confluent hypergeometric functions. The related scalar product will be useful for better understanding analytic solutions to Teukolsky's radial equation

Yunlong Lyu, Yuxuan Xie, Peng Chen, Hao Chen

Crafting high-quality fuzz drivers not only is time-consuming but also requires a deep understanding of the library. However, the state-of-the-art automatic fuzz driver generation techniques fall short of expectations. While fuzz drivers derived from consumer code can reach deep states, they have limited coverage. Conversely, interpretative fuzzing can explo

Annalivia Polselli

With the violation of the assumption of homoskedasticity, least squares estimators of the variance become inefficient and statistical inference conducted with invalid standard errors leads to misleading rejection rates. Despite a vast cross-sectional literature on the downward bias of robust standard errors, the problem is not extensively covered in the pane

Taeksoo Kwon, Connor Kim

This paper examines the efficacy of utilizing large language models (LLMs) to detect public threats posted online. Amid rising concerns over the spread of threatening rhetoric and advance notices of violence, automated content analysis techniques may aid in early identification and moderation. Custom data collection tools were developed to amass post titles

Xuwei Fan, Zhipeng Cheng, Ning Chen, Lianfen Huang

Task scheduling as an effective strategy can improve application performance on computing resource-limited devices over distributed networks. However, existing evaluation mechanisms fail to depict the complexity of diverse applications, which involve dependencies among tasks, computing resource requirements, and multi-dimensional quality of service (QoS) con

Julien Piet, Maha Alrashed, Chawin Sitawarin, Sizhe Chen

Large Language Models (LLMs) are attracting significant research attention due to their instruction-following abilities, allowing users and developers to leverage LLMs for a variety of tasks. However, LLMs are vulnerable to prompt-injection attacks: a class of attacks that hijack the model's instruction-following abilities, changing responses to prompts to u

David S. Schlegel, Stefan Kehrein

We examine the emergence of periodicity in a non-interacting steady-state quantum system without external drive inspired by quantum time crystals' spontaneous time-translation symmetry breaking. Specifically, we consider a lattice ring of non-interacting electrons undergoing weak local position measurements. Our analysis uncovers time-periodic structures in

Florian Kogelbauer, Shinsuke Koyama, Daniel E. Callan, Shigeru Shinomoto

Skateboarders perform a reciprocating motion on a curved ramp, called pumping, by moving their bodies up and down perpendicular to the ramp's surface. We propose a simple mechanical model for this pumping motion and solve the equation of motion explicitly in angular coordinates. This allows us to derive an optimal control strategy to maximize amplitude by dy

Surasree Sadhukhan, Sudipta Kanungo

The coupling between electron orbital momentum and spin momentum, known as spin-orbit coupling (SOC), is a fundamental origin of a multitude of fascinating physical phenomena, especially it holds paramount significance in the realm of topological materials. In our work, we have predicted the topological phase in Hg-based chalcopyrite compounds using the firs

Marc Lieser, Ulrich Schwanecke

As the presence of flying robots continues to grow in both commercial and private sectors, it necessitates an understanding of appropriate methods for nonverbal interaction with humans. While visual cues, such as gestures incorporated into trajectories, are more apparent and thoroughly researched, acoustic cues have remained unexplored, despite their potenti

Xin Cai, Jingyu Yang, Zhibao Li, Hongqiao Wang

Stochastic Differential Equations (SDEs) serve as a powerful modeling tool in various scientific domains, including systems science, engineering, and ecological science. While the specific form of SDEs is typically known for a given problem, certain model parameters remain unknown. Efficiently inferring these unknown parameters based on observations of the s

Hideaki Takahashi

This paper introduces AIJack, an open-source library designed to assess security and privacy risks associated with the training and deployment of machine learning models. Amid the growing interest in big data and AI, advancements in machine learning research and business are accelerating. However, recent studies reveal potential threats, such as the theft of

Sarah H. Cen, Andrew Ilyas, Aleksander Madry

Many human-facing algorithms -- including those that power recommender systems or hiring decision tools -- are trained on data provided by their users. The developers of these algorithms commonly adopt the assumption that the data generating process is exogenous: that is, how a user reacts to a given prompt (e.g., a recommendation or hiring suggestion) depen

Antonio Giuseppe Grimaldi

In this paper, we consider minimizers of integral functionals of the type \begin{equation*} \mathcal{F}(u):= \int_\Omega \dfrac{1}{p} \bigl( |Du(x)|_{\gamma(x)}-1\bigr)_+^p \ \mathrm{d}x, \end{equation*} for $p >1$, where $u : \Omega \subset \mathbb{R}^n \to \mathbb{R}^N$, with $N \ge 1$, is a possibly vector-valued function. Here, $| \cdot |_\gamma$ is the

Joris van der Hoeven, Grégoire Lecerf

Consider a sparse multivariate polynomial f with integer coefficients. Assume that f is represented as a "modular black box polynomial", e.g. via an algorithm to evaluate f at arbitrary integer points, modulo arbitrary positive integers. The problem of sparse interpolation is to recover f in its usual sparse representation, as a sum of coefficients times mon

Hao Zhang, Shuaijie Zhang

As an important component of the detector localization branch, bounding box regression loss plays a significant role in object detection tasks. The existing bounding box regression methods usually consider the geometric relationship between the GT box and the predicted box, and calculate the loss by using the relative position and shape of the bounding boxes

Gérard Clément, Khireddine Nouicer

It is well-known that the theory of Cotton gravity proposed by Harada is trivially solved by all isotropic and homogeneous cosmologies. We show that this under-determination is more general. More precisely, the degree of arbitrariness in the solutions increases with the degree of symmetry. We give two simple examples. The first is that of static spherically

Yuqing Wang, Yun Zhao

The burgeoning interest in Multimodal Large Language Models (MLLMs), such as OpenAI's GPT-4V(ision), has significantly impacted both academic and industrial realms. These models enhance Large Language Models (LLMs) with advanced visual understanding capabilities, facilitating their application in a variety of multimodal tasks. Recently, Google introduced Gem

Pijus Kasparaitis

Text Normalization is an integral part of any text-to-speech synthesis system. In a natural language text, there are elements such as numbers, dates, abbreviations, etc. that belong to other semiotic classes. They are called non-standard words (NSW) and need to be expanded into ordinary words. For this purpose, it is necessary to identify the semiotic class

Jordy Anchundia Troncoso, Ángel Torres Quijije, Byron Oviedo, Cristian Zambrano-Vega

This research explores the effectiveness of various Machine Learning (ML) models used to predicting solar radiation at the Central Campus of the State Technical University of Quevedo (UTEQ). The data was obtained from a pyranometer, strategically located in a high area of the campus. This instrument continuously recorded solar irradiance data since 2020, off

S. X. Nakamura, X. -H. Li, H. -P. Peng, Z. -T. Sun

Recent high-precision $e^+e^-\to c\bar{c}$ data from the BESIII and Belle are highly useful to understand vector charmonium ($\psi$) pole structures and puzzling lineshapes due to the exotic hadron candidates $Y$. We thus perform a global coupled-channel analysis of most of the available data (10 two-body, 9 three-body, and 1 four-body final states) in $\sqr

Pablo Martin-Ramiro, Unai Sainz de la Maza, Sukhbinder Singh, Roman Orus

Defect detection is one of the most important yet challenging tasks in the quality control stage in the manufacturing sector. In this work, we introduce a Tensor Convolutional Neural Network (T-CNN) and examine its performance on a real defect detection application in one of the components of the ultrasonic sensors produced at Robert Bosch's manufacturing pl

Justin Provazza, Klaas Gunst, Huanchen Zhai, Garnet K. -L. Chan

We describe a matrix product state (MPS) extension for the Fermionic Quantum Emulator (FQE) software library. We discuss the theory behind symmetry adapted matrix product states for approximating many-body wavefunctions of spin-1/2 fermions, and we present an open-source, MPS-enabled implementation of the FQE interface (MPS-FQE). The software uses the open-s

Peter Spacek, Charles Wang

In this report we use our methods in arXiv:2204.03548 and its upcoming generalization to complete the construction of canonical mirror models for all cominuscule homogeneous spaces, by considering the maximal orthogonal Grassmannians $\mathrm{OG}(n + 1, 2n + 2)$.

Zetong Yang, Li Chen, Yanan Sun, Hongyang Li

In contrast to extensive studies on general vision, pre-training for scalable visual autonomous driving remains seldom explored. Visual autonomous driving applications require features encompassing semantics, 3D geometry, and temporal information simultaneously for joint perception, prediction, and planning, posing dramatic challenges for pre-training. To re

Maja Rudolph, Stefan Kurz, Barbara Rakitsch

Design patterns provide a systematic way to convey solutions to recurring modeling challenges. This paper introduces design patterns for hybrid modeling, an approach that combines modeling based on first principles with data-driven modeling techniques. While both approaches have complementary advantages there are often multiple ways to combine them into a hy

M. C. Gordillo

The structure of self-bound one-dimensional droplets containing a mixture of Ytterbium fermionic isotopes ($^{173}$Yb, $^{171}$Yb) is calculated by means of a diffusion Monte Carlo technique. We considered only balanced setups in which all the atoms of one isotope are spin-polarized, while the atoms of the other can have up to three different spin values, th

Federica Nasr, Federico Binda, Charles-Henri Lambert, Giacomo Sala

Light transition metals have recently emerged as a sustainable material class for efficient spin-charge interconversion. We report measurements of current-induced spin-orbit torques generated by Ni$_{1-x}$Cu$_{x}$ alloys in perpendicularly magnetized ferrimagnetic Gd/Fe multilayers. We show that the spin-orbit torque efficiency of Ni$_{1-x}$Cu$_{x}$ increase

Carlo Marinelli

We establish well-posedness in the mild sense for a class of stochastic semilinear evolution equations on $L^p$ spaces on bounded domains of $\mathbb{R}^n$ with a nonlinear drift term given by the superposition operator generated by a monotone function on the real line with power-like growth. The noise is of additive type with respect to a cylindrical Wiener

Joyce Xin-Yan Lim, Quang-Cuong Pham

The rise in additive manufacturing comes with unique opportunities and challenges. Rapid changes to part design and massive part customization distinctive to 3D-Print (3DP) can be easily achieved. Customized parts that are unique, yet exhibit similar features such as dental moulds, shoe insoles, or engine vanes could be industrially manufactured with 3DP. Ho

Ferdinand Schlatt, Maik Fröbe, Matthias Hagen

Cross-encoders are effective passage and document re-rankers but less efficient than other neural or classic retrieval models. A few previous studies have applied windowed self-attention to make cross-encoders more efficient. However, these studies did not investigate the potential and limits of different attention patterns or window sizes. We close this gap

Jiaxi Wang, Wenhui Hu, Xueyang Liu, Beihu Wu

Visual grounding aims to align visual information of specific regions of images with corresponding natural language expressions. Current visual grounding methods leverage pre-trained visual and language backbones independently to obtain visual features and linguistic features. Although these two types of features are then fused through elaborately designed n

Rudolf Baier, Christian Peterson

The recent analysis of quantum cosmology by S. Gielen [1] is extended by discussing the case of dust (in the flat case). The dependence of the Wheeler-DeWitt equation on the operator ordering of the Hamiltonian in the case of a position dependent mass is explored, together with the {\Lambda} dependence. As a main result, it is shown that matter enforces a qu

Xuebin Zhao, Andrew Curtis

Geoscientists use observed data to estimate properties of the Earth's interior. This often requires non-linear inverse problems to be solved and uncertainties to be estimated. Bayesian inference solves inverse problems under a probabilistic framework, in which uncertainty is represented by a so-called posterior probability distribution. Recently, variational

Joaquin Almeira, Tomas S. Grigera, Daniel A. Martin, Dante R. Chialvo

We present a mean field solution of the dynamics of a Greenberg-Hastings neural network with both excitatory and inhibitory units. We analyse the dynamical phase transitions that appear in the stationary state as the model parameters are varied. Analytical solutions are compared with numerical simulations of the microscopic model defined on a fully connected

Giuliano Boava, Gilles G. de Castro, Daniel Gonçalves, Daniel W. van Wyk

We associate a C*-algebra $\widetilde{\mathcal{O}}_{\textsf{X}}$ with a subshift over an arbitrary, possibly infinite, alphabet. We show that $\widetilde{\mathcal{O}}_{\textsf{X}}$ is a full invariant for topological conjugacy of the subshifts of Ott, Tomforde, and Willis. When the alphabet is countable, we show that $\widetilde{\mathcal{O}}_{\textsf{X}}$ is

Kevin Patel, Vamsi Kalagaturu, Vivek Mannava, Ravisankar Selvaraju

This paper presents the b-it-bots RoboCup@Work team and its current hardware and functional architecture for the KUKA youBot robot. We describe the underlying software framework and the developed capabilities required for operating in industrial environments including features such as reliable and precise navigation, flexible manipulation, robust object reco

Ran Chen, Xueqi Yao, Jing Zhao, Shuhan Xu

This study aims to explore the complex relationship between perceptual and cognitive interactions in multimodal data analysis,with a specific emphasis on spatial experience design in overseas Chinese gardens. It is found that evaluation content and images on social media can reflect individuals' concerns and sentiment responses, providing a rich data base fo

Yang Feng, Liao Pan, Wu Di, Liu Bo

In the realm of video analysis, the field of multiple object tracking (MOT) assumes paramount importance, with the motion state of objects-whether static or dynamic relative to the ground-holding practical significance across diverse scenarios. However, the extant literature exhibits a notable dearth in the exploration of this aspect. Deep learning methodolo

Víctor Bucarey, Sophia Calderón, Gonzalo Muñoz, Frederic Semet

Dealing with uncertainty in optimization parameters is an important and longstanding challenge. Typically, uncertain parameters are predicted accurately, and then a deterministic optimization problem is solved. However, the decisions produced by this so-called predict-then-optimize procedure can be highly sensitive to uncertain parameters. In this work, we c

Huajie Gong, Shulan Li, Dan Zhang, Guoyang Fu

In this paper, we investigate the quasinormal mode (QNM) spectra for scalar perturbation over a quantum-corrected black hole (BH). The fundamental modes of this quantum-corrected BH exhibit two key properties. Firstly, there is a non-monotonic behavior concerning the quantum-corrected parameter for zero multipole number. Secondly, the quantum gravity effects

Igor V. Nikolaev

Using the ideas of Deninger, we prove that the Artin $L$-functions coincide with such of the noncommutative tori. This result can be viewed as the Langlands reciprocity for noncommutative tori.

Wei Huang

The Hadley circulation (or Hadley cell) is traditionally described as a large-scale atmospheric circulation phenomenon driven by differential heating of the Earth surface: warm, moist air rises near the equator, diverges poleward in the upper troposphere, and subsides in the subtropics. In this article, the mechanism of the Hadley circulation is revisited an

Yutong He, Sambit K. Giri, Ramkishor Sharma, Salome Mtchedlidze

We apply the inverse Gertsenshtein effect, i.e., the graviton-photon conversion in the presence of a magnetic field, to constrain high-frequency gravitational waves (HFGWs). Using existing astrophysical measurements, we compute upper limits on the GW energy densities $\Omega_{\rm GW}$ at 16 different frequency bands. Given the observed magnetisation of galax

Elisa Davoli, Ulisse Stefanelli

Let $u$ be the unique nonnegative viscosity solution of the Hamilton-Jacobi equation $H(x,\nabla u)=0$ in the external domain ${\mathbb R}^{ n} \setminus K$ with $u=0$ on $K$. Under general conditions on $H$, we prove that all sublevels of $u$ are John domains. Moreover, if $K$ itself is a John domain, we provide a uniform lower bound on the John constant of

Naizhong Zhang. Yaoqiang Pan, Yangwen Jin, Peiqi Jin, Kewei Hu

This work presents an innovative solution for robotic odometry, path planning and exploration in wild unknown environments, focusing on digital modelling. The approach uses a minimum cost formulation with pseudo-randomly generated objectives, integrating multi-path planning and evaluation, with emphasis on full coverage of unknown maps based on feasible boun

Pedro Boavida de Brito, Michael S. Weiss

We investigate the relationship between the configuration category of a manifold and the configuration category of a covering space of that manifold.

Luca Ferrarini, Samuel Fiorini, Stefan Kober, Yelena Yuditsky

In the total matching problem, one is given a graph $G$ with weights on the vertices and edges. The goal is to find a maximum weight set of vertices and edges that is the non-incident union of a stable set and a matching. We consider the natural formulation of the problem as an integer program (IP), with variables corresponding to vertices and edges. Let $M

Alan Givré, Silvina Ponce Dawson

Cells continuously interact with their environment mediating their responses through signaling cascades. Very often, external stimuli induce pulsatile behaviors in intermediaries of the cascade of increasing frequency with the stimulus strength. This is characteristic of intracellular Ca$^{2+}$ signals involving Ca$^{2+}$ release through Inositol Trisphospha

Xiaoyu Ou, Shuping Dang, Zhihan Ren, Angela Doufexi

This paper investigates the resource management problem in multi-carrier rate-splitting multiple access (MC-RSMA) systems with imperfect channel state information (CSI) and successive interference cancellation (SIC) for ultra-reliable and low-latency communications (URLLC) applications. To explore the trade-off between the decoding error probability and achi

Daniel S. Seara, Jonathan Colen, Michel Fruchart, Yael Avni

Living systems display complex behaviors driven by physical forces as well as decision-making. Hydrodynamic theories hold promise for simplified universal descriptions of socially-generated collective behaviors. However, the construction of such theories is often divorced from the data they should describe. Here, we develop and apply a data-driven pipeline t

Vidya Sagar Sharma

The structure of Markov equivalence classes (MECs) of causal DAGs has been studied extensively. A natural question in this regard is to algorithmically find the number of MECs with a given skeleton. Until recently, the known results for this problem were in the setting of very special graphs (such as paths, cycles, and star graphs). More recently, a fixed-pa

Shay Solomon, Amitai Uzrad

The minimum set cover (MSC) problem admits two classic algorithms: a greedy $\ln n$-approximation and a primal-dual $f$-approximation, where $n$ is the universe size and $f$ is the maximum frequency of an element. Both algorithms are simple and efficient, and remarkably -- one cannot improve these approximations under hardness results by more than a factor o

Xingqiao Li, Jindong Gu, Zhiyong Wang, Yancheng Yuan

Predicting in-hospital mortality for intensive care unit (ICU) patients is key to final clinical outcomes. AI has shown advantaged accuracy but suffers from the lack of explainability. To address this issue, this paper proposes an eXplainable Multimodal Mortality Predictor (X-MMP) approaching an efficient, explainable AI solution for predicting in-hospital m

José Luis Montiel Olea, Chen Qiu, Jörg Stoye

We apply classical statistical decision theory to a large class of treatment choice problems with partial identification. We show that, in a general class of problems with Gaussian likelihood, all decision rules are admissible; it is maximin-welfare optimal to ignore all data; and, for severe enough partial identification, there are infinitely many minimax-r

Asmaa Mazoun, Sebastian Bocquet, Mathias Garny, Joseph J. Mohr

We forecast the sensitivity of ongoing and future galaxy cluster abundance measurements to detect deviations from the cold dark matter (CDM) paradigm. Concretely, we consider a class of dark sector models that feature an interaction between dark matter and a dark radiation species (IDM-DR). This setup can be naturally realized by a non-Abelian gauge symmetry

Ji-Hui Pei, Jin-Fu Chen, H. T. Quan

The principle of covariance, a cornerstone of modern physics, asserts the equivalence of all inertial frames of reference. Fluctuation theorems, as extensions of the second law of thermodynamics, establish universal connections between irreversibility and fluctuation in terms of stochastic thermodynamic quantities. However, these relations typically assume t

Long-Kun Du, Chenyu Hu, Shuang Liu, Chenjin Deng

Computational imaging~(CI) has been attracting a lot of interest in recent years for its superiority over traditional imaging in various applications. In CI systems, information is generally acquired in an encoded form and subsequently decoded via processing algorithms, which is quite in line with the information transmission mode of modern communication, an

Xian Shi

To quantify the entanglement of bipartite systems in terms of some entanglement measure is a challenging problem in general, and it is much worse when the information about the system is less. In this manuscript, based on two classes of entanglement criteria, we present a method to obtain the lower bounds of the entanglement measures, concurrence, entangleme

Dominique S. Hoskin, R. Loek Van Heyningen, Ngoc Cuong Nguyen, Jordi Vila-Pérez

In recent years, high-order discontinuous Galerkin (DG) methods have emerged as an attractive approach for numerical simulations of compressible flows. This paper presents an overview of the recent development of DG methods for compressible flows with particular focus on hypersononic flows. First, we survey state-of-the-art DG methods for computational fluid

Abdelilah Karara, Khadija Mabrouk

In this peaper we stady certain Bessel sequences $\left\{f_k\right\}_{k=1}^{\infty}$ in Hilbert C*- modules $\mathcal{H}$ for which operator $S$ defined by \ref{eq2} is of the form $\mathcal{T}+\xi I$, for some real number $\xi$ and a adjointable linear operator $\mathcal{T}$. Additionally, we investigate frames known as compact-tight frames, which have fram

Derong Xu, Wei Chen, Wenjun Peng, Chao Zhang

Information extraction (IE) aims to extract structural knowledge from plain natural language texts. Recently, generative Large Language Models (LLMs) have demonstrated remarkable capabilities in text understanding and generation. As a result, numerous works have been proposed to integrate LLMs for IE tasks based on a generative paradigm. To conduct a compreh

Sylvy Anscombe, Arno Fehm

We set up general machinery to study interpretations of fragments of theories. We then apply this to existential fragments of theories of fields, and especially of henselian valued fields. As an application we prove many-one reductions between various existential theories of fields. In particular we exhibit several theories of fields many-one equivalent to t

Hichem Sahbi

In this paper, we devise a novel lightweight Graph Convolutional Network (GCN) design dubbed as Multi-Rate Magnitude Pruning (MRMP) that jointly trains network topology and weights. Our method is variational and proceeds by aligning the weight distribution of the learned networks with an a priori distribution. In the one hand, this allows implementing any fi

Annapurna Banik

The earliest examples of visibility domains, given by Bharali--Zimmer, are pseudoconvex. In fact, all known examples of visibility domains are pseudoconvex. We show that there exist non-pseudoconvex visibility domains. We supplement this proof by a general method to construct a wide range of non-pseudoconvex, hence non-Kobayashi-complete, visibility domains.

Henrik Junkerkalefeld

We present recent tests of lepton universality as crucial probes of the Standard Model in semileptonic $B$-meson decays at Belle II. All presented analyses use a data sample collected at the $\Upsilon(4S)$ resonance by the Belle II experiment corresponding to an integrated luminosity of $189\,\mathrm{fb}^{-1}$. We report three analyses that probe light-lepto

Florentia Afentaki, Gurol Saglam, Argyris Kokkinis, Kostas Siozios

Printed Electronics (PE) feature distinct and remarkable characteristics that make them a prominent technology for achieving true ubiquitous computing. This is particularly relevant in application domains that require conformal and ultra-low cost solutions, which have experienced limited penetration of computing until now. Unlike silicon-based technologies,

Linlian Jiang, Pan Chen, Ye Wang, Tieru Wu

Inferring missing regions from severely occluded point clouds is highly challenging. Especially for 3D shapes with rich geometry and structure details, inherent ambiguities of the unknown parts are existing. Existing approaches either learn a one-to-one mapping in a supervised manner or train a generative model to synthesize the missing points for the comple

Tarek M. Elgindi, Ryan W. Murray, Ayman R. Said

We introduce a local-in-time existence and uniqueness class for solutions to the 2d Euler equation with unbounded vorticity. Furthermore, we show that solutions belonging to this class can develop stronger singularities in finite time, meaning that they experience finite time blow up and exit the wellposedness class. Such solutions may be continued as weak s

Manuel Hohmann

We study transformations of the dynamical fields - a metric, a flat affine connection and a scalar field - in scalar-teleparallel gravity theories. The theories we study belong either to the general teleparallel setting, where no further condition besides vanishing curvature is imposed on the affine connection, or the symmetric or metric teleparallel gravity

Kousuke Nakano, Michele Casula, Giacomo Tenti

Ab initio quantum Monte Carlo (QMC) is a state-of-the-art numerical approach for evaluating accurate expectation values of many-body wavefunctions. However, one of the major drawbacks that still hinders widespread QMC applications is the lack of an affordable scheme to compute unbiased atomic forces. In this study, we propose a very efficient method to obtai

Linda M. Carpenter, Taylor Murphy

In this work we build out complete mediator sectors for models of frustrated dark matter (fDM), a new paradigm in which fermionic dark matter couples to the Standard Model (SM) through a scalar-fermionic mediator pair. The fDM paradigm allows great freedom in the charge assignments of the mediators: it accommodates any representation of the SM gauge group pr