November 2024 arXiv papers — page 6

Aidan P. Reddy, D. N. Sheng, Ahmed Abouelkomsan, Emil J. Bergholtz

We show that electron crystals compete closely with non-Abelian fractional Chern insulators in the half-filled second moir\'e band of twisted bilayer MoTe$_2$. Depending on the twist angle and microscopic model, these crystals can have non-zero or zero Chern numbers $C$. The $C=0$ crystal occurs because contributions to the total Chern number from the full f

Abhijit Sen, Bikram Keshari Parida, Kurt Jacobs, Denys I. Bondar

The response of many-body quantum systems to an optical pulse can be extremely challenging to model. Here we explore the use of neural networks, both traditional and generative, to learn and thus simulate the response of such a system from data. The quantum system can be viewed as performing a complex mapping from an input time-series (the optical pulse) to

Zixuan Chen, Guangcong Wang, Jiahao Zhu, Jianhuang Lai

3D Gaussian Splatting (3DGS) has recently created impressive 3D assets for various applications. However, considering security, capacity, invisibility, and training efficiency, the copyright of 3DGS assets is not well protected as existing watermarking methods are unsuited for its rendering pipeline. In this paper, we propose GuardSplat, an innovative and ef

Araceli Guzmán-Tristán, Antonio Rieser, Eduardo Velázquez-Richards

We propose three completely data-driven methods for estimating the real cohomology groups $H^k (X ; \mathbb{R})$ of a compact metric-measure space $(X, d_X, \mu_X)$ embedded in a metric-measure space $(Y,d_Y,\mu_Y)$, given a finite set of points $S$ sampled from a uniform distrbution $\mu_X$ on $X$, possibly corrupted with noise from $Y$. We present the resu

Hiroto Yanagisawa, Masami Ouchi, Kimihiko Nakajima, Yuichi Harikane

We investigate UV continuum slopes $\beta$ of 863 galaxies at $z=4-14$ using archival JWST/NIRSpec PRISM spectra obtained from major JWST GTO, ERS, and GO programs, including JADES, CEERS, and UNCOVER. Among these galaxies, we identify a remarkable galaxy at $z=9.25$, dubbed EBG-1, with a significantly blue UV slope $\beta=-2.99\pm0.15$, unlike the rest of t

Martino Michelotti, Rodrigo Gonzalez Quaglia, Ema Dimastrogiovanni, Matteo Fasiello

We study an extension of the natural inflation model comprising a non-Abelian gauge sector coupled to the axion-inflaton kinetic term. We show how such non-minimal coupling serves as a source of friction for the rolling inflaton granting sixty or more $e$-folds of accelerated expansion for sub-Planckian values of the axion decay constant. The analysis of per

Bruce C. Berndt, Likun Xie

We derive a general formula for the product of two Dirichlet series that satisfy Hecke's functional equation. Several examples are provided to demonstrate the applicability of the formula. In addition, we discuss prior work on similar products and clarify certain issues arising in the existing literature.

Paula Belzig, Li Gao, Graeme Smith, Peixue Wu

The quantum data processing inequality asserts that two quantum states become harder to distinguish when a noisy channel is applied. On the other hand, a reverse quantum data processing inequality characterizes whether distinguishability is preserved after the application of a noisy channel. In this work, we explore these concepts through contraction and exp

Jaiung Jun, Kalina Mincheva, Jeffrey Tolliver

We explore several facets of tropical subrepresentations of a linear representation of a group over the tropical semifield $\mathbb{T}$. A key role in the study of tropical subrepresentations is played by two types of modules over a semiring: weakly free and quasi-free modules. We also investigate subgroups of $\text{GL}_n(K)$ for $K=\mathbb{T}$, $ \mathbb{R

Chang Won Lee, Selina Leveugle, Svetlana Stolpner, Chris Langley

Anomaly segmentation is an essential capability for safety-critical robotics applications that must be aware of unexpected events. Normalizing flows (NFs), a class of generative models, are a promising approach for this task due to their ability to model the inlier data distribution efficiently. However, their performance falters in dynamic scenes, where com

Jakob Hedicke, Egor Shelukhin

We relate non-orderability in contact topology to shortening in the contact Hofer norm. Combined with considerations of open books, this provides many new examples of non-orderable contact manifolds, including contact boundaries of subcritical Weinstein domains, and in particular the long-standing case of the standard $S^1 \times S^2.$ We also produce new ex

Vedant Khandelwal, Amit Sheth, Forest Agostinelli

Various real-world challenges require planning algorithms that can adapt to a broad range of domains. Traditionally, the creation of planning domains has relied heavily on human implementation, which limits the scale and diversity of available domains. While recent advancements have leveraged generative AI technologies such as large language models (LLMs) fo

Emanuele Frittaion

We analyze Coquand's game-theoretic interpretation of Peano Arithmetic through the lens of elementary descent recursion. In Coquand's game semantics, winning strategies correspond to infinitary cut-free proofs and cut elimination corresponds to debates between these winning strategies. The proof of cut elimination, i.e., the proof that such debates eventuall

Jaiung Jun, Kalina Mincheva, Jeffrey Tolliver

We study and classify representations of a torsion group $G$ over an idempotent semifield with special attention on the case over the Boolean semifield $\mathbb{B}$. In subsequent work we extend this theory to studying representations of matroids of low rank.

Rakshit Kr. Singh, Aaron Rock Menezes, Rida Irfan, Bharath Ramsundar

Ordinary Differential Equations (ODEs) are widely used in physics, chemistry, and biology to model dynamic systems, including reaction kinetics, population dynamics, and biological processes. In this work, we integrate GPU-accelerated ODE solvers into the open-source DeepChem framework, making these tools easily accessible. These solvers support multiple num

Umang Bhaskar, Gunjan Kumar, Yeshwant Pandit, Rakshitha

In the fair division of items among interested agents, envy-freeness is possibly the most favoured and widely studied formalisation of fairness. For indivisible items, envy-free allocations may not exist in trivial cases, and hence research and practice focus on relaxations, particularly envy-freeness up to one item (EF1). A significant reason for the popula

Daniel Sanchez Rosales, Roderick D. Cochran, Samantha D. Isaac, Paul G. Kwiat

Quantum key distribution (QKD) allows two users to exchange a provably secure key for cryptographic applications. In prepare-and-measure QKD protocols, the states must be indistinguishable to prevent information leakage to an eavesdropper performing a side-channel attack. Here, we measure the indistinguishability of quantum states in a prepare-and-measure th

Jesús Pineda, Sergi Masó-Orriols, Montse Masoliver, Joan Bertran

Single-molecule localization microscopy generates point clouds corresponding to fluorophore localizations. Spatial cluster identification and analysis of these point clouds are crucial for extracting insights about molecular organization. However, this task becomes challenging in the presence of localization noise, high point density, or complex biological s

G. Kalaivani, R. Rajkumar

In this paper, we introduce a matrix for a mixed graph, called the integrated adjacency matrix. This matrix uniquely determines a mixed graph, as long as the indices of the matrix are specified. Additionally, we associate an (undirected) graph with each mixed graph, enabling the spectral analysis of the integrated adjacency matrix to connect the structural p

Chi Wing Chu, Hok Kan Ling, Chaoyu Yuan

We consider the nonparametric maximum likelihood estimation for the underlying event time based on mixed-case interval-censored data, under a log-concavity assumption on its distribution function. This generalized framework relaxes the assumptions of a log-concave density function or a concave distribution function considered in the literature. A log-concave

Carl Feghali

We give a pen and paper and (comparatively) much simpler proof to verify of the Four Colour Theorem.

Ethan N. Epperly, Gil Goldshlager, Robert J. Webber

The randomized Kaczmarz (RK) method is a well-known approach for solving linear least-squares problems with a large number of rows. RK accesses and processes just one row at a time, leading to exponentially fast convergence for consistent linear systems. However, RK fails to converge to the least-squares solution for inconsistent systems. This work presents

Luis Ibanez-Lissen, Lorena Gonzalez-Manzano, Jose Maria de Fuentes, Nicolas Anciaux

Large Language Models (LLMs) are increasingly used in a variety of applications, but concerns around membership inference have grown in parallel. Previous efforts focus on black-to-grey-box models, thus neglecting the potential benefit from internal LLM information. To address this, we propose the use of Linear Probes (LPs) as a method to detect Membership I

Abdulrahman Al-Fakih, A. Koeshidayatullah, Tapan Mukerji, SanLinn I. Kaka

Although generative adversarial networks (GANs) have shown significant success in modeling data distributions for image datasets, their application to structured or tabular data, such as well logs, remains relatively underexplored. This study extends the ensemble GANs (EGANs) framework to capture the distribution of well log data and detect anomalies that fa

Weixin Mao, Weiheng Zhong, Zhou Jiang, Dong Fang

Existing robot policies predominantly adopt the task-centric approach, requiring end-to-end task data collection. This results in limited generalization to new tasks and difficulties in pinpointing errors within long-horizon, multi-stage tasks. To address this, we propose RoboMatrix, a skill-centric hierarchical framework designed for scalable robot task pla

Federico Grasselli, Giovanni Chesi, Nathan Walk, Hermann Kampermann

Quantum Key Distribution (QKD) is a promising technology for secure communication. Nevertheless, QKD is still treated with caution in certain contexts due to potential gaps between theoretical models and actual QKD implementations. A common assumption in security proofs is that the detection probability at the receiver, for a given input state, is independen

Lavinia Heisenberg, Alessandro Longo, Giovanni Tambalo, Miguel Zumalacarregui

We consider evolving, spatially flat isotropic and homogeneous (FLRW) cosmologies in ghost-free (dRGT) massive gravity. In this theory, no dynamical flat FLRW background exists if the reference metric is chosen to be Minkowski and the Stueckelberg fields are homogeneous. Relaxing the assumptions on the Stueckelberg profiles gives access to dynamical backgrou

Evans Javary, Edward Thorpe-Woods, Irene Cortinovis, Marcus Mähring

Positronium and muonium, as purely leptonic atoms without internal structure, provide ideal systems for high-precision tests of quantum electrodynamics (QED) and measurements of fundamental constants. However, the high velocities of these lightweight atoms complicate precision spectroscopy, particularly in the 1S-2S transition, due to transit time broadening

Daniel Kaddaj, Stef Baas, Edwin Y. N. Tang, David S. Robertson

Bayesian adaptive designs enable flexible clinical trials by adapting features based on accumulating data. Among these, Bayesian Response-Adaptive Randomization (BRAR) skews patient allocation towards more promising treatments based on interim data. Implementing BRAR requires the relatively quick evaluation of posterior probabilities. However, the limitation

Bowen Peng, Lizhang Chen, Baiyu Su, Jeffrey Quesnelle

Scaling neural network training increasingly depends on synchronous data-parallelism, yet full-precision gradient all-reduce imposes a severe communication bottleneck. We propose Decoupled Momentum Optimization (DeMo), a drop-in replacement for any momentum-based optimizers that significantly reduces the communication bandwidth while maintaining convergence.

Leonardo Almeida, Pedro Rodrigues, Diogo Magalhães, Armando J. Pinho

This paper introduces AIDetx, a novel method for detecting machine-generated text using data compression techniques. Traditional approaches, such as deep learning classifiers, often suffer from high computational costs and limited interpretability. To address these limitations, we propose a compression-based classification framework that leverages finite-con

Gojko Vujanovic

In relativistic heavy-ion collisions, electromagnetic (EM) radiation has been used as a sensitive probe of Quark Gluon Plasma (QGP) properties, owing to the smaller EM coupling relative to QCD coupling. To better understand the constraining power of EM emissions on transport properties of the QGP, a deeper understanding of both the theory and phenomenology o

Soroush Karimi, Marcos Oliveira, Diogo Pacheco

Understanding the relationship between network features and misinformation propagation is crucial for mitigating the spread of false information. Here, we investigate how network density and segregation affect the dissemination of misinformation using a susceptible-infectious-recovered framework. We find that a higher density consistently increases the propo

Justin Chih-Yao Chen, Zifeng Wang, Hamid Palangi, Rujun Han

Reverse thinking plays a crucial role in human reasoning. Humans can reason not only from a problem to a solution but also in reverse, i.e., start from the solution and reason towards the problem. This often enhances overall reasoning performance as it enables consistency checks between their forward and backward thinking. To enable Large Language Models (LL

Matí as Menni

To each simplicial set $X$ we naturally assign an \'etendue ${\'E X}$ whose internal logic captures information about the geometry of $X$. In particular, we show that, for 'non-singular' objects $X$ and $Y$, the \'etendues ${\'E X}$ and ${\'E Y}$ are equivalent if, and only if, $X$ and $Y$ have the same dimension. Many of the results apply to presheaf topose

Ajay Krishna Vajjala, Dipak Meher, Ziwei Zhu, David S. Rosenblum

Cross-domain recommendation (CDR) has emerged as a promising solution to the cold-start problem, faced by single-domain recommender systems. However, existing CDR models rely on complex neural architectures, large datasets, and significant computational resources, making them less effective in data-scarce scenarios or when simplicity is crucial. In this work

Martin Gorbahn, Sebastian Jäger, Sandra Kvedaraitė

The Kaon bag parameter $ {\hat{B}}_K $ plays a critical role in constraining the parameters of the CKM matrix and in probing physics beyond the Standard Model. In this work, we improve the precision of $ \hat{B}_K $ to next-to-next-to-leading order (NNLO) and provide world averages for both $3$- and $4$-flavour theories. In the course of this, as our main te

Philipp Wolters, Johannes Gilg, Torben Teepe, Fabian Herzog

In this work, we present SpaRC, a novel Sparse fusion transformer for 3D perception that integrates multi-view image semantics with Radar and Camera point features. The fusion of radar and camera modalities has emerged as an efficient perception paradigm for autonomous driving systems. While conventional approaches utilize dense Bird's Eye View (BEV)-based a

Jinfeng Dou, Thorsten Götte, Henning Hillebrandt, Christian Scheideler

We consider the distributed and parallel construction of low-diameter decompositions with strong diameter for (weighted) graphs and (weighted) graphs that can be separated through $k \in \tilde{O}(1)$ shortest paths. This class of graphs includes planar graphs, graphs of bounded treewidth, and graphs that exclude a fixed minor $K_r$. We present algorithms in

Urvashi Joshi, Aniruddha Kumar Sharma, Rajan Arora

This research paper talks about using complex mathematical tools to study and figure out the behavior of biological populations in porous media. Porous media offer a unique environment where various factors, including fluid flow and nutrient diffusion, significantly influence population dynamics. The theory of Lie symmetries is used to find inherent symmetri

Mohammed Q. Shormani

There is a strong correlation between linguistics and artificial intelligence (AI), best manifested by deep learning language models. This study provides a thorough scientometric analysis of this correlation, synthesizing the intellectual production over 51 years, from 1974 to 2024. Web of Science Core Collection (WoSCC) database was the data source. The dat

Felix Brandt, Chris Dong, Dominik Peters

A voting rule is a Condorcet extension if it returns a candidate that beats every other candidate in pairwise majority comparisons whenever one exists. Condorcet extensions have faced criticism due to their susceptibility to variable-electorate paradoxes, especially the reinforcement paradox (Young and Levenglick, 1978) and the no-show paradox (Moulin, 1988)

Hugo Aimar, Ivana Gómez, Ignacio Gómez Vargas, Francisco Javier Martín-Reyes

In this work, we introduce the geometric concept of one-sided weakly porous sets in the real line and show that a set $E\subset\mathbb{R}$ satisfies $d(\cdot,E)^{-\alpha}\in A_1^+(\mathbb{R})\cap L^1_\textrm{loc}(\mathbb{R})$ for some $\alpha>0$ if and only if $E$ is right-sided weakly porous. Furthermore, we find that the property of being both left-sided a

Mohammed Q. Shormani, Yehia A. Al-Sohbani

This study provides a comprehensive analysis of artificial intelligence (AI) contribution to research in the translation industry (ACTI), synthesizing it over forty-five years from 1980-2024. 13220 articles were retrieved from three sources, namely WoS, Scopus, and Lens; 9836 were unique records, which were used for the analysis. We provided two types of ana

Vishakha Ramani, Ivan Seskar, Roy D. Yates

This work explores systems where source updates require multiple sequential processing steps. We model and analyze the Age of Information (AoI) performance of various system designs under both parallel and series server setups. In parallel setups, each processor executes all computation steps with multiple processors working in parallel, while in series setu

Tejaswini Medi, Julia Grabinski, Margret Keuper

While being very successful in solving many downstream tasks, the application of deep neural networks is limited in real-life scenarios because of their susceptibility to domain shifts such as common corruptions, and adversarial attacks. The existence of adversarial examples and data corruption significantly reduces the performance of deep classification mod

Shavkat Alimov, Ravshan Ashurov

Determining the unknown order of the fractional derivative in differential equations simulating various processes is an important task of modern applied mathematics. In the last decade, this problem has been actively studied by specialists. A number of interesting results with a certain applied significance were obtained. This paper provides a short overview

Vasilis Livanos, Ruta Mehta

The I.I.D. Prophet Inequality is a fundamental problem where, given $n$ independent random variables $X_1,\dots,X_n$ drawn from a known distribution $\mathcal{D}$, one has to decide at every step $i$ whether to stop and accept $X_i$ or discard it forever and continue. The goal is to maximize or minimize the selected value and compete against the all-knowing

Ulrich Eckern, Karol I. Wysokiński

In condensed matter systems with the Coulomb interaction playing an important role one expects, besides the on-site (local) Hubbard-type interaction, that also other (non-local) terms depending on the site occupancy, known as correlated or assisted hopping, exist. Even though such terms in quantum dots tunnel coupled to external electrodes may have quite an

Domenico G. Meduri, Rainer Arlt, Alfio Bonanno, Giovanni Licciardello

The stability of toroidal magnetic fields in radiative stellar interiors is a key open problem in astrophysics. We investigate the Tayler instability of purely toroidal fields $B_\phi$ in a nonrotating, thermally stably stratified stellar region using global linear perturbation analysis and 3D direct numerical simulations in spherical geometry. Both approach

Mathieu Besançon, Jannis Kurtz

We tackle robust optimization problems under objective uncertainty in the oracle model, i.e., when the deterministic problem is solved by an oracle. The oracle-based setup is favorable in many situations, e.g., when a compact formulation of the feasible region is unknown or does not exist. We propose an iterative method based on a Frank-Wolfe type algorithm

Mariya Antyufeyeva, Victor Pacheco-Peña

The introduction of time as an additional degree of freedom to control wave-matter interactions have opened new avenues to fully control wave propagation in four dimensions (x,y,z,t). Time interfaces (rapid changes of the constitutive relations of the medium where a wave propagates) have recently become popular as they are the temporal analogue of spatial in

Liqiang Zhang, Ye Tian, Dongyan Wei

With the development of smart cities, the demand for continuous pedestrian navigation in large-scale urban environments has significantly increased. While global navigation satellite systems (GNSS) provide low-cost and reliable positioning services, they are often hindered in complex urban canyon environments. Thus, exploring opportunistic signals for positi

Anirudh Bangalore Shankar, Avhishek Chatterjee, Bhaswar Chakrabarti, Anjan Chakravorty

Recently, it has been experimentally demonstrated that individual memory units coupled in certain topology can provide the intended performance. However, experimental or simulation based evaluation of different coupled memory topologies and materials are costly and time consuming. In this paper, inspired by Glauber dynamics models in non-equilibrium statisti

Jong-Phil Lee

We investigate new physics effects on $B\to D^{(*)}\tau\nu$ decays in a general and model-independent way. The $\chi^2$ fits for fractions of the branching ratios $R(D^{(*)})$ and other polarization parameters are implemented. We parameterize the relevant Wilson coefficients with a new physics scale and its power together with combined fermionic couplings. C

Julian D Parker, Anton Smirnov, Jordi Pons, CJ Carr

The tokenization of speech with neural audio codec models is a vital part of modern AI pipelines for the generation or understanding of speech, alone or in a multimodal context. Traditionally such tokenization models have concentrated on low parameter-count architectures using only components with strong inductive biases. In this work we show that by scaling

Awais Khan, Ijaz Ul Haq, Khalid Mahmood Malik

Voice authentication on IoT-enabled smart devices has gained prominence in recent years due to increasing concerns over user privacy and security. The current authentication systems are vulnerable to different voice-spoofing attacks (e.g., replay, voice cloning, and audio deepfakes) that mimic legitimate voices to deceive authentication systems and enable fr

Claudio Agnorelli, Meg Spriggs, Kate Godfrey, Gabriela Sawicka

Neuroplasticity, the ability of the nervous system to adapt throughout an organism's lifespan, offers potential as both a biomarker and treatment target for neuropsychiatric conditions. Psychedelics, a burgeoning category of drugs, are increasingly prominent in psychiatric research, prompting inquiries into their mechanisms of action. Distinguishing themselv

Chris Lambie-Hanson, Šárka Stejskalová

Building upon work of L\"{u}cke and Schlicht, we study (higher) Kurepa trees through the lens of higher descriptive set theory, focusing in particular on various perfect set properties and representations of sets of branches through trees as continuous images of function spaces. Answering a question of L\"{u}cke and Schlicht, we prove that it is consistent w

Ruben Flores-Mendieta, Guillermo Sanchez-Almanza

The baryon axial vector current is computed in a combined formalism in $1/N_c$ and chiral corrections. Flavor $SU(3)$ symmetry breaking is accounted for in two ways: Implicitly through the integrals occurring in the one-loop graphs and explicitly through perturbative symmetry breaking. Loop integrals can be expanded in a power series in the ratio of the decu

Eoghan Farrell, Chris Parker

We introduce the normalising graph of a group and study the connectivity of the normalising and permuting graphs of a group when the group is finite and soluble. In particular, we classify finite soluble groups with disconnected normalising graph. The main results shows that if a finite soluble group has connected normalising graph then this graph has diamet

Anna M. Suliga, George M. Fuller

The indirect detection of dark matter (DM) through its annihilation products is one of the primary strategies for DM detection. One of the least constrained classes of models is neutrinophilic DM, because the annihilation products, weakly interacting neutrinos, are challenging to observe. Here, we consider a scenario where MeV-mass DM exclusively annihilates

Sönke Tenckhoff, Mario Koddenbrock, Erik Rodner

Automated object detection has become increasingly valuable across diverse applications, yet efficient, high-quality annotation remains a persistent challenge. In this paper, we present the development and evaluation of a platform designed to interactively improve object detection models. The platform allows uploading and annotating images as well as fine-tu

Stefan Heinz, Adeyemi Fagbade

The simulation of high Reynolds number (Re) separated turbulent flows faces significant problems for decades: large eddy simulation (LES) is computationally too expensive, and Reynolds-averaged Navier-Stokes (RANS) methods and hybrid RANS-LES methods often provide unreliable results. This has serious consequences, we are currently unable to reliably predict

Dániel Gerbner, András Imolay, Gyula O. H. Katona, Dániel T. Nagy

We study the number of queries needed to identify a monotone Boolean function $f:\{0,1\}^n \rightarrow \{0,1\}$. A query consists of a 0-1-sequence, and the answer is the value of $f$ on that sequence. It is well-known that the number of queries needed is $\binom{n}{\lfloor n/2\rfloor}+\binom{n}{\lfloor n/2\rfloor+1}$ in general. Here we study a variant wher

Dimosthenis Antypas, Indira Sen, Carla Perez-Almendros, Jose Camacho-Collados

The detection of sensitive content in large datasets is crucial for ensuring that shared and analysed data is free from harmful material. However, current moderation tools, such as external APIs, suffer from limitations in customisation, accuracy across diverse sensitive categories, and privacy concerns. Additionally, existing datasets and open-source models

Suhail Gulzar, N. A. Rather, M. S Wani

If $P(z)=\sum_{j=0}^{n}a_jz^j$ is a polynomial of degree $n$ having no zero in $|z|<1,$ then it was recently proved that for every $p\in[0,+\infty]$ and $s=0,1,\ldots,n-1,$ \begin{align*} \left\|a_nz+\frac{a_s}{\binom{n}{s}}\right\|_{p}\leq \frac{\left\|z+\delta_{0s}\right\|_p}{\left\|1+z\right\|_p}\left\|P\right\|_{p}, \end{align*} where $\delta_{0s}$ is th

Amit Chinwan, Catherine B. Hurley

We provide a pipeline for calculating, managing and visualising correlations and other pairwise association scores for numerical and categorical data. We present a uniform interface for calculating a plethora of pairwise scores and propose a tidy data structure for organising the results. We also provide new visualisations which simultaneously show multiple

Yunus Sevinchan, Petro Sarkanych, Abi Tenenbaum, Yurij Holovatch

The ability of groups to make accurate collective decisions depends on a complex interplay of various factors, such as prior information, biases, social influence, and the structure of the interaction network. Here, we investigate a spin model that accounts for heterogeneous preferences and enables control over the non-linearity of social interactions. Build

William Alderson, Rémy Dubertrand, Akira Shudo

A model for a lattice of coupled cat maps has been recently introduced. This new and specific choice of the coupling makes the description especially easy and nontrivial quantities as Lyapunov exponents determined exactly. We studied the ergodic property of the dynamics along such a chain for a local perturbation. While the perturbation spreads across a fron

Louisa A Mason, Michael A Garrett, Kelvin Wandia, Andrew P V Siemion

The Atacama Millimeter/Submillimeter Array (ALMA) remains unparalleled in sensitivity at radio frequencies above 35 GHz. In this paper, we explore ALMA's potential for narrowband technosignature detection, considering factors such as the interferometer's undistorted field of view, signal dilution due to significant drift rates at high frequencies and the pos

Rajib Rana, Niall Higgins, Kazi N. Haque, John Reilly

Background: Formulation, associated with suicide risk assessment, is an individualised process that seeks to understand the idiosyncratic nature and development of an individual's problems. Auditing clinical documentation on an electronic health record (EHR) is challenging as it requires resource-intensive manual efforts to identify keywords in relevant sect

S. I. Tertychniy

Separate consideration of properties of roots of Third Painlev\'e transcendents (P_III-functions) is necessary due to irregularity the differential equation defining them reveals on the subset of the phase space where its solution would vanish. Application of the Hamiltonian formalism enables one to replace the mentioned second order differential equation (T

Jineon Baek

We resolve the moving sofa problem by showing that Gerver's construction with 18 curve sections attains the maximum area $2.2195\cdots$.

Fabio van Dissel, George Zahariade

The backreaction of quantum degrees of freedom on classical backgrounds is a poorly understood topic in theoretical physics. Most often it is treated within the semiclassical approximation with the help of various ad hoc prescriptions accounting for the effect of quantum excitations on the dynamics of the background. We focus on two popular ones: (i) the mea

Chi Su, Xiaoxuan Ma, Jiajun Su, Yizhou Wang

We propose a one-stage framework for real-time multi-person 3D human mesh estimation from a single RGB image. While current one-stage methods, which follow a DETR-style pipeline, achieve state-of-the-art (SOTA) performance with high-resolution inputs, we observe that this particularly benefits the estimation of individuals in smaller scales of the image (e.g

Debasish Mohanty, V Shreyas, Akshaya Palai, Bharath Ramsundar

Polymers play a crucial role in the development of engineering materials, with applications ranging from mechanical to biomedical fields. However, the limited polymerization processes constrain the variety of organic building blocks that can be experimentally tested. We propose an open-source computational generative pipeline that integrates neural-network-b

Eion Mulrenin, Cosmin Pohoata, Dmitrii Zakharov

In 2014, Moshkovitz and Shapira determined the tower height for hypergraph Ramsey numbers of tight monotone paths. We address the color-avoiding version of this problem in which one no longer necessarily seeks a monochromatic subgraph, but rather one which avoids some colors. This problem was previously studied in uniformity two by Loh and by Gowers and Long

Fangze Fu, Wei Ai, Fan Yang, Yuntao Shou

Multimodal Emotion Recognition in Conversations (MERC) aims to classify utterance emotions using textual, auditory, and visual modal features. Most existing MERC methods assume each utterance has complete modalities, overlooking the common issue of incomplete modalities in real-world scenarios. Recently, graph neural networks (GNNs) have achieved notable res

S. Gulzar, Ravinder Kumar, Mudassir A Bhat

In this review paper, we explore operator aspects in extremal properties of Bernstein-type polynomial inequalities. We shall also see that a linear operator which send polynomials to polynomials and have zero-preserving property naturally preserve Bernstein's inequality.

Jeroen J. de Boer, Bruno Ehrler

Hardware neural networks could perform certain computational tasks orders of magnitude more energy-efficiently than conventional computers. Artificial neurons are a key component of these networks and are currently implemented with electronic circuits based on capacitors and transistors. However, artificial neurons based on memristive devices are a promising

Yuxuan Li, Yunhui Guo

Architecture plays an important role in deciding the performance of deep neural networks. However, the search for the optimal architecture is often hindered by the vast search space, making it a time-intensive process. Recently, a novel approach known as training-free neural architecture search (NAS) has emerged, aiming to discover the ideal architecture wit

Romain Rescanieres, Romain Pierrat, Arthur Goetschy

We present a statistical study of the transmission and dwell-time matrices in disordered media composed of resonators, focusing on how frequency detuning influences their eigenvalue distributions. Our analysis reveals that the distribution of transmission eigenvalues undergoes a transition from a monomodal to a bimodal profile, and back to monomodal, as the

Nina Javerzat, Eric Bertin, Misaki Ozawa

Configurational entropy, or complexity, plays a critical role in characterizing disordered systems such as glasses, yet its measurement often requires significant computational resources. Recently, R\'enyi entropy, a one-parameter generalization of Shannon entropy, has gained attention across various fields of physics due to its simpler functional form, maki

Mackenzie Amann, Liam Gallagher, Rachael Norton, Efren Ruiz

Higher rank graphs, also known as $k$-graphs, are a $k$-dimensional generalization of directed graphs and a rich source of examples of $C^*$-algebras. In the present paper, we contribute to the geometric classification program for $k$-graph $C^*$-algebras by introducing a new move on $k$-graphs, called LiMaR-split, which is a generalization of outsplit for d

Claudia Maria Chanu, Giovanni Rastelli

We review the results of several of our papers about the procedure of extension of Hamiltonians, allowing the construction of families of superintegrable systems with non-trivial polynomial first integrals (or symmetry operators) of arbitrarily high degree. In particular, we focus on the geometric structures involved by the procedure: warped manifolds and Ri

Ángel F. García-Fernández, Simo Särkkä

This paper proposes multi-target filtering algorithms in which target dynamics are given in continuous time and measurements are obtained at discrete time instants. In particular, targets appear according to a Poisson point process (PPP) in time with a given Gaussian spatial distribution, targets move according to a general time-invariant linear stochastic d

Juan-Juan Luo, Liang Zhang, Li-Yun Zhang, Yong-Feng Huang

Gamma-ray bursts (GRBs) are usually classified into long/short categories according to their durations, but controversy still exists in this aspect. Here we re-examine the long/short classification of GRBs and further compare the cosmological distribution and evolution of each potential subclass. A large number of $Swift/BAT$ GRBs are analyzed in this study.

Ying Zhu, Giorgio Krstulovic, Sergey Nazarenko

When a turbulent Bose-Einstein condensate is driven out-of-equilibrium at a scale much smaller than the system size, nonlinear wave interactions transfer particles towards large scales in an inverse cascade process. In this work, we study numerically wave turbulence in a three-dimensional Bose-Einstein condensate in forced and dissipated inverse cascade sett

N. A. Rather, Aijaz Bhat, Suhail Guzlar

Let $P(z)$ be a polynomial of degree $n,$ then it is known that for $\alpha\in\mathbb{C}$ with $|\alpha|\leq \frac{n}{2},$ \begin{align*} \underset{|z|=1}{\max}|\left|zP^{\prime}(z)-\alpha P(z)\right|\leq \left|n-\alpha\right|\underset{|z|=1}{\max}|P(z)|. \end{align*} This inequality includes Bernstein's inequality, concerning the estimate for $|P^\prime(z)|

Morris Ang, Pu Yu

The seminal work of Sheffield showed that when random surfaces called Liouville quantum gravity (LQG) are conformally welded, the resulting interface is Schramm-Loewner evolution (SLE). This has been proved for a variety of configurations, and has applications to the scaling limits of random planar maps and the solvability of SLE and Liouville conformal fiel

Guo Ning Sue, Yogita Choudhary, Richard Desatnik, Carmel Majidi

Ensuring safety via safety filters in real-world robotics presents significant challenges, particularly when the system dynamics is complex or unavailable. To handle this issue, learning-based safety filters recently gained popularity, which can be classified as model-based and model-free methods. Existing model-based approaches requires various assumptions

Nicolas Burq, Mickaël Latocca

We prove Strichartz estimates for a class of Baouendi--Grushin operators acting either on the Euclidean space or a product of the type $\mathbb{R}^{d_1} \times M$, where $(M,g)$ is a smooth compact manifold with no boundary. We then give an application of these Strichartz estimates to the Cauchy theory for the associated Schr\"odinger equations.

Yanda Geng, Junheng Tao, Mingshu Zhao, Shouvik Mukherjee

Instabilities, where small fluctuations seed the formation of large-scale structures, govern dynamics in a variety of fluid systems. The Rayleigh-Taylor instability (RTI), present from tabletop to astronomical scales, is an iconic example characterized by mushroom-shaped incursions appearing when immiscible fluids are forced together. Despite its ubiquity, R

Alain Riou, Antonin Gagneré, Gaëtan Hadjeres, Stefan Lattner

In this paper, we tackle the task of musical stem retrieval. Given a musical mix, it consists in retrieving a stem that would fit with it, i.e., that would sound pleasant if played together. To do so, we introduce a new method based on Joint-Embedding Predictive Architectures, where an encoder and a predictor are jointly trained to produce latent representat

Stefan Heinz

The discovery of the law of the wall, the log-law including the von Karman constant, is seen to be one of the biggest accomplishments of fluid mechanics. However, after more than ninety years there is still a controversial debate about the validity and universality of the law of the wall. Clarity about this question matters: in absence of alternatives, a rel

Robin D. Pesl, Jerin G. Mathew, Massimo Mecella, Marco Aiello

Integrating multiple (sub-)systems is essential to create advanced Information Systems (ISs). Difficulties mainly arise when integrating dynamic environments across the IS lifecycle. A traditional approach is a registry that provides the API documentation of the systems' endpoints. Large Language Models (LLMs) have shown to be capable of automatically creati

Youcef Ferdi

The advances in computer vision made possible by deep learning technology are increasingly being used in precision agriculture to automate the detection and classification of plant diseases. Symptoms of plant diseases are often seen on their leaves. The leaf images in existing datasets have been collected either under controlled conditions or in the field. T

Weichan Liu, Xin Zhang

An equitable coloring of a graph is a proper coloring where the sizes of any two distinct color classes differ by at most one. The celebrated Chen-Lih-Wu Conjecture (CLWC for short) states that every connected graph $G$ that is neither an odd cycle, a $K_r$, nor a $K_{2m+1,2m+1}$ has an equitable $\Delta(G)$-coloring. A graph $G$ is in $\mathcal{G}_{m_1,m_2}

Zin Mar Myint, Ashish Saxena

The concept of a monitoring edge-geodetic set (MEG-set) in a graph $G$, denoted $MEG(G)$, refers to a subset of vertices $MEG(G)\subseteq V(G)$ such that every edge $e$ in $G$ is monitored by some pair of vertices $ u, v \in MEG(G)$, where $e$ lies on all shortest paths between $u$ and $v$. The minimum number of vertices required to form such a set is called