May 2024 arXiv papers — page 92

Gang Li, Sebastien Deheuvels, Jerome Ballot

Tens of thousands of red giant stars in the Kepler data exhibit solar-like oscillations. Their oscillations enable us to study the internal physics from core to surface, such as differential rotation. However, envelope rotation rates have been measured for only a dozen RGB stars so far. The limited sample hinders the theoretical interpretation of angular mom

Marco Stronati, Denis Firsov, Antonio Locascio, Benjamin Livshits

Plonkish is a popular circuit format for developing zero-knowledge proof systems that powers a number of major projects in the blockchain space, responsible for holding billions of dollars and processing millions of transactions per day. These projects, including zero-knowledge rollups, rely on highly hand-optimized circuits whose correctness comes at the co

Zhigang Jia, Yuelian Xiang, Meixiang Zhao, Tingting Wu

The cross-channel deblurring problem in color image processing is difficult to solve due to the complex coupling and structural blurring of color pixels. Until now, there are few efficient algorithms that can reduce color artifacts in deblurring process. To solve this challenging problem, we present a novel cross-space total variation (CSTV) regularization m

Petteri Harjulehto, Ritva Hurri-Syrjänen

We introduce Riesz potentials for non-Lebesgue measurable functions by taking the integrals in the sense of Choquet with respect to Hausdorff content and prove boundedness results for these operators. Some earlier results are recovered or extended now using integrals taken in the sense of Choquet with respect to Hausdorff content. Some earlier results also f

Karlheinz Gröchenig, Irina Shafkulovska

Metaplectic Wigner distributions are joint time-frequency representations that are parametrized by a symplectic matrix and generalize the short-time Fourier transform and the Wigner distribution. We investigate the question which metaplectic Wigner distributions satisfy an uncertainty principle in the style of Benedicks and Amrein-Berthier. That is, if the m

L. N. Martínez-Ramírez, G. Calistro Rivera, Elisabeta Lusso, F. E. Bauer

We present new frontiers in the modelling of the spectral energy distributions (SED) of active galaxies by introducing the radio-to-X-ray fitting capabilities of the publicly available Bayesian code AGNfitter. The new code release, called AGNfitter-rx, models the broad-band photometry covering the radio, infrared (IR), optical, ultraviolet (UV) and X-ray ban

Jiawei Zhang, Jiahe Li, Xiaohan Yu, Lei Huang

3D Gaussian Splatting (3DGS) creates a radiance field consisting of 3D Gaussians to represent a scene. With sparse training views, 3DGS easily suffers from overfitting, negatively impacting rendering. This paper introduces a new co-regularization perspective for improving sparse-view 3DGS. When training two 3D Gaussian radiance fields, we observe that the tw

Richard Futrell, Michael Hahn

Human language has a distinct systematic structure, where utterances break into individually meaningful words which are combined to form phrases. We show that natural-language-like systematicity arises in codes that are constrained by a statistical measure of complexity called predictive information, also known as excess entropy. Predictive information is th

David Wiedemann

We consider the homogenisation of a diffusion equation in a porous medium. The microstructure is time-dependent and oscillating on a small time scale. This oscillation causes a novel advection in the homogenised equations. Allowing for a locally varying geometry, the oscillating microstructure demonstrates the ability to generate arbitrary and locally varyin

Zhenwei Shao, Zhou Yu, Jun Yu, Xuecheng Ouyang

By harnessing the capabilities of large language models (LLMs), recent large multimodal models (LMMs) have shown remarkable versatility in open-world multimodal understanding. Nevertheless, they are usually parameter-heavy and computation-intensive, thus hindering their applicability in resource-constrained scenarios. To this end, several lightweight LMMs ha

Aaron Calderon, James Farre

We address a conjecture of Mirzakhani about the statistical behavior of certain expanding families of ``twist tori'' in the moduli space of hyperbolic surfaces, showing that they equidistribute to a certain Lebesgue-class measure along almost all sequences. We also identify a number of other expanding families of twist tori whose limiting distributions are m

Antonio Ríos-Vila, Jorge Calvo-Zaragoza, David Rizo, Thierry Paquet

Optical Music Recognition (OMR) has made significant progress since its inception, with various approaches now capable of accurately transcribing music scores into digital formats. Despite these advancements, most so-called end-to-end OMR approaches still rely on multi-stage processing pipelines for transcribing full-page score images, which entails challeng

Nabarun Deka, Minjian Zhang, Rohit Chadha, Mahesh Viswanathan

Security properties of real-time systems often involve reasoning about hyper-properties, as opposed to properties of single executions or trees of executions. These hyper-properties need to additionally be expressive enough to reason about real-time constraints. Examples of such properties include information flow, side channel attacks and service-level agre

L. Marinho, F. Herpin, H. Wiesemeyer, A. López Ariste

Both magnetic fields and photospheric/atmospheric dynamics can be involved in triggering the important mass loss observed in evolved cool stars. Previous works have revealed that these objects exhibit a magnetic field extending beyond their surface. The origin of this magnetic field is still under debate with mechanisms involving a turbulent dynamo, convecti

Jian Huang, Dangyuan Lei, Girish S. Agarwal, Zhedong Zhang

We propose an optomechanical scheme for reaching quantum entanglement in vibration polaritons. The system involves $N$ molecules, whose vibrations can be fairly entangled with plasmonic cavities. We find that the vibration-photon entanglement can exist at room temperature and is robust against thermal noise. We further demonstrate the quantum entanglement be

Gyan Wickremasinghe, Siofra Frost, Karen Rafferty, Vishal Sharma

Industry 4.0 and beyond will rely heavily on sustainable Business Decision Modelling (BDM) that can be accelerated by blockchain and Digital Twin (DT) solutions. BDM is built on models and frameworks refined by key identification factors, data analysis, and mathematical or computational aspects applicable to complex business scenarios. Gaining actionable int

Rameez Raja Kureshi, Bhupesh Kumar Mishra, Dhavalkumar Thakker, Suvodeep Mazumdar

The detrimental effects of air pollutants on human health have prompted increasing concerns regarding indoor air quality (IAQ). The emergence of digital health interventions and citizen science initiatives has provided new avenues for raising awareness, improving IAQ, and promoting behavioural changes. The Technology Acceptance Model (TAM) offers a theoretic

Hao Chen, Biaojie Zeng, Xin Lin, Liang He

Math world problems correction(MWPC) is a novel task dedicated to rectifying reasoning errors in the process of solving mathematical problems. In this paper, leveraging the advancements in large language models (LLMs), we address two key objectives:(1) Distinguishing between mathematical reasoning and error correction; (2) Exploring strategies to enhance the

Sida Wang, Rowan Walker-Gibbons, Bethany Watkins, Binghui Lin

Self-assembly of matter in solution generally relies on attractive interactions that overcome entropy and drive the formation of higher-order molecular and particulate structures. Such interactions play key roles in a variety of contexts, e.g., crystallisation, biomolecular folding and condensation, pathological protein aggregation, pharmaceuticals and fine

Sebastian Zug, Georg Jäger, Norman Seyffer, Martin Plank

This study identifies a gap in data-driven approaches to robot-centric pedestrian interactions and proposes a corresponding pipeline. The pipeline utilizes unsupervised learning techniques to identify patterns in interaction data of urban environments, specifically focusing on conflict scenarios. Analyzed features include the robot's and pedestrian's speed a

Jemal Yimer Damte, Jiri Houska

We employ density functional theory (DFT) to investigate the adsorption and dehydrogenation of methane on the BNG-Ir13 cluster at both low and high oxygen coverage. The DFT calculations show that the low-oxygen-coverage BNG-Ir13 cluster (BNG-Ir13O cluster) forms methanol and formaldehyde with a lower activation energy barrier compared to the high-oxygen-cove

Ramin Ghorbani, Marcel J. T. Reinders, David M. J. Tax

Evaluating anomaly detection algorithms in time series data is critical as inaccuracies can lead to flawed decision-making in various domains where real-time analytics and data-driven strategies are essential. Traditional performance metrics assume iid data and fail to capture the complex temporal dynamics and specific characteristics of time series anomalie

Tomoya Naito, Masaaki Kimura, Masaki Sasano

We confirm by using the Skyrme Hartree-Fock-Bogoliubov calculation that $ {}^{164} \mathrm{Pb} $ is a possible heaviest $ N = Z $ doubly magic nucleus whose lifetime is long enough to be measured on accelerator experiments. We estimate the proton-emission and alpha-decay half-lives of $ {}^{164} \mathrm{Pb} $. The estimated proton-emission half-life ranges f

Yang Dai, Oubo Ma, Longfei Zhang, Xingxing Liang

Transformer-based trajectory optimization methods have demonstrated exceptional performance in offline Reinforcement Learning (offline RL). Yet, it poses challenges due to substantial parameter size and limited scalability, which is particularly critical in sequential decision-making scenarios where resources are constrained such as in robots and drones with

Sigmund Kohler

We investigate the properties of Floquet states in the vicinity of a conical intersection of quasienergies and work out the consequences of the underlying spatio-temporal symmetries for a driven two-level system coupled to an ohmic heat bath. We find that on manifolds with constant quasienergy splitting, the mean energies of the Floquet states are continuous

Ryan C. Fortenberry, Brett A. McGuire

The formation of silicon monosulfide (SiS) in space appears to be a difficult process, but the present work is showing that a previously excluded pathway may contribute to its astronomical abundance. Reaction of the radicals SH + SiH produces SiS with a submerged transition state and generates a stabilizing H$_2$ molecule as a product to dissipate the kineti

Théo Duboscq, Natalie B. Hogg, Pierre Fleury, Julien Larena

The analysis of strong lensing images usually involves an external convergence and shear, which are meant to model the effect of perturbations along the line of sight, on top of the main lens. Such a description of line-of-sight perturbations supposes that the corresponding gravitational fields can be treated in the tidal regime. Going one step further intro

Bojan Nikolic, Christopher L. Carilli, Nithyanandan Thyagarajan, Laura Torino

Double-aperture Young interferometry is widely used in accelerators to provide a one-dimensional beam measurement. We improve this technique by combining and further developing techniques of non-redundant, two-dimensional, aperture masking and self-calibration from astronomy. Using visible synchrotron radiation, tests at the ALBA synchrotron show that this m

Bing Xue, Mark Zwolinski

Reliability has been a major concern in embedded systems. Higher transistor density and lower voltage supply increase the vulnerability of embedded systems to soft errors. A Single Event Upset (SEU), which is also called a soft error, can reverse a bit in a sequential element, resulting in a system failure. Simulation-based fault injection has been widely us

Zsigmond György Fleiner, Márk Hunor Juhász, Blanka Kövér, Péter Pál Pach

Let $F_{k,d}(n)$ be the maximal size of a set ${A}\subseteq [n]$ such that the equation \[a_1a_2\dots a_k=x^d, \; a_1<a_2<\ldots<a_k\] has no solution with $a_1,a_2,\ldots,a_k\in {A}$ and integer $x$. Erd\H{o}s, S\'ark\"ozy and T. S\'os studied $F_{k,2}$, and gave bounds when $k=2,3,4,6$ and also in the general case. We study the problem for $d=3$, and provi

Vincent Davis, Emanuele Rossi, Vikash Singh

The Bitcoin Lightning Network is a Layer 2 payment protocol that addresses Bitcoin's scalability by facilitating quick and cost effective transactions through payment channels. This research explores the feasibility of using machine learning models to interpolate channel balances within the network, which can be used for optimizing the network's pathfinding

Taiga Kato, Hanming Ma, Kazuyoshi Yoshimi, Takahiro Misawa

External pressure and associated changes in lattice structures are key to realizing exotic quantum phases such as high-$T_{\rm c}$ superconductivity. While applying external pressure is a standard method to induce novel lattice structures, its impact on organic molecular crystals has been less explored. Here we report a unique structural phase transition in

Chirag Wadhwa, Mina Doosti

In this work, we study the learnability of quantum circuits in the near term. We demonstrate the natural robustness of quantum statistical queries for learning quantum processes, motivating their use as a theoretical tool for near-term learning problems. We adapt a learning algorithm for constant-depth quantum circuits to the quantum statistical query settin

Jumbly Grindrod, J. D. Porter, Nat Hansen

Large Language Models are built on the so-called distributional semantic approach to linguistic meaning that has the distributional hypothesis at its core. The distributional hypothesis involves a holistic conception of word meaning: the meaning of a word depends upon its relations to other words in the model. A standard objection to holism is the charge of

Sho Miyaji

Many studies exploit variation in the timing of policy adoption across units as an instrument for treatment. This paper formalizes the underlying identification strategy as an instrumented difference-in-differences (DID-IV). In this design, a Wald-DID estimand, which scales the DID estimand of the outcome by the DID estimand of the treatment, captures the lo

B. Magacho, L. Moriconi, J. B. R. Loureiro

We simulated a turbulent pipe flow within the Lattice Boltzmann Method using a multiple-relaxation-time collision operator with Maxwell-Boltzmann equilibrium distribution expanded, for the sake of a more accurate description, up to the sixth order in Hermite polynomials. The moderately turbulent flow ($Re_{\tau} \approx 181.3$) is able to reproduce up to the

Chen Huang, Yang Deng, Wenqiang Lei, Jiancheng Lv

To obtain high-quality annotations under limited budget, semi-automatic annotation methods are commonly used, where a portion of the data is annotated by experts and a model is then trained to complete the annotations for the remaining data. However, these methods mainly focus on selecting informative data for expert annotations to improve the model predicti

Zu-Jian Ying

Light-matter interactions provide an ideal testground for interplay of critical phenomena, topological transitions, quantum metrology and non-Hermitian physics. We consider two fundamental non-Hermitian Jaynes-Cummings models which possess real energy spectra in parity-time (PT) symmetry and anti-PT symmetry. We show that the quantum Fisher information is cr

Xingda Wei, Zhuobin Huang, Tianle Sun, Yingyi Hao

PHOENIXOS (PHOS) is the first OS service that can concurrently checkpoint and restore (C/R) GPU processes--a fundamental capability for critical tasks such as fault tolerance, process migration, and fast startup. While concurrent C/R is well-established on CPUs, it poses unique challenges on GPUs due to their lack of essential features for efficiently tracin

Emanuele Zuccoli, Edward James Brambley, Dwight Barkley

We consider the propagation of linear gravity waves on the free surface of steady, axisymmetric flows with purely azimuthal velocity. We propose a two-dimensional set of governing equations for surface waves valid in the deep-water limit. These equations come from a closure condition at the free surface that reduces the three-dimensional Euler equations in t

Vladimir Lotoreichik

We consider the magnetic Laplacian with the homogeneous magnetic field in two and three dimensions. We prove that the $(k+1)$-th magnetic Neumann eigenvalue of a bounded convex planar domain is not larger than its $k$-th magnetic Dirichlet eigenvalue. In three dimensions, we restrict our attention to convex domains, which are invariant under rotation by an a

Cristian Bodnar, Wessel P. Bruinsma, Ana Lucic, Megan Stanley

Reliable forecasts of the Earth system are crucial for human progress and safety from natural disasters. Artificial intelligence offers substantial potential to improve prediction accuracy and computational efficiency in this field, however this remains underexplored in many domains. Here we introduce Aurora, a large-scale foundation model for the Earth syst

Emad Efatinasab, Alessandro Brighente, Mirco Rampazzo, Nahal Azadi

The smart grid represents a pivotal innovation in modernizing the electricity sector, offering an intelligent, digitalized energy network capable of optimizing energy delivery from source to consumer. It hence represents the backbone of the energy sector of a nation. Due to its central role, the availability of the smart grid is paramount and is hence necess

G. Valle, M. Dell'Omodarme, P. G. Prada Moroni, S. Degl'Innocenti

We investigated the theoretical possibility of accurately determining the helium-to-metal enrichment ratio $\Delta Y/\Delta Z$ from precise observations of double lined eclipsing binary systems. Using Monte Carlo simulations, we drew synthetic binary systems with masses between 0.85 and 1.00 $M_{\odot}$ from a grid of stellar models with $\Delta Y/\Delta Z =

Ahmad Al-Badawi

The purpose of this study is to investigate the quasinormal modes (QNMs), greybody factors (GFs) and shadows in a plasma of a black hole (BH) surrounded by an exotic fluid of quintessence type in a scalar-vector-tensor modified gravity. The effects of a quintessence scalar field and the modified gravity (MOG) field on the QNM, GF, and shadow are examined. Us

Pavlos S. Bouzinis, Panagiotis Radoglou-Grammatikis, Ioannis Makris, Thomas Lagkas

Federated learning (FL) is a decentralized learning technique that enables participating devices to collaboratively build a shared Machine Leaning (ML) or Deep Learning (DL) model without revealing their raw data to a third party. Due to its privacy-preserving nature, FL has sparked widespread attention for building Intrusion Detection Systems (IDS) within t

Mohamad Assaad, Touraj Soleymani

In this paper, we develop a theoretical framework for goal-oriented communication assisted by reconfigurable meta-surfaces in the context of networked control systems. The relation to goal-oriented communication stems from the fact that optimization of the phase shifts of the meta-surfaces is guided by the performance of networked control systems tasks. To t

Xiaotian Wang, Jingbo Bai, Jianhua Wang, Zhenxiang Cheng

There has been a significant focus on real topological systems that enjoy space-time inversion symmetry (PT ) and lack spin-orbit coupling. While the theoretical classification of the real topology has been established, more progress has yet to be made in the materials realization of such real topological systems in three dimensions (3D). To address this cru

Milena Skvortsova

We investigate quasinormal ringing in both time and frequency domains for scalar and neutrino perturbations around black hole solutions that simultaneously describe regular and extreme configurations within a non-linear electrodynamics framework. Two types of solutions are considered: those with de Sitter and Minkowski cores. The quasinormal frequencies obta

Robert Worden

Neural theories of consciousness face three difficulties: (1) The selection problem: how are those neurons which cause consciousness selected, from all the other neurons which do not? (2) the precision problem: how do neurons hold a detailed internal model of 3D space, as the origin of our spatial conscious experience? and (3) the decoding problem: how are t

Calvin Yeung, Kenjiro Ide, Keisuke Fujii

Image understanding is a foundational task in computer vision, with recent applications emerging in soccer posture analysis. However, existing publicly available datasets lack comprehensive information, notably in the form of posture sequences and 2D pose annotations. Moreover, current analysis models often rely on interpretable linear models (e.g., PCA and

Tianhao Wu, Jing Yang, Zhilin Guo, Jingyi Wan

By equipping the most recent 3D Gaussian Splatting representation with head 3D morphable models (3DMM), existing methods manage to create head avatars with high fidelity. However, most existing methods only reconstruct a head without the body, substantially limiting their application scenarios. We found that naively applying Gaussians to model the clothed ch

Jingyin Huang

We introduce a method of finding large non-positively curved subcomplexes in certain spherical Deligne complexes, which is effective for studying fillings of certain 6-cycles in spherical Deligne complexes. As applications, we show the $K(\pi,1)$-conjecture holds for all 3-dimensional hyperbolic type Artin groups, except one single example; and the conjectur

Autumn E. Kent, Christopher J. Leininger

We show that there is a type-preserving homomorphism from the fundamental group of the figure-eight knot complement to the mapping class group of the thrice-punctured torus. As a corollary, we obtain infinitely many commensurability classes of purely pseudo-Anosov surface subgroups of mapping class groups of closed surfaces. This gives the first examples of

Baptiste Klein, Suzanne Aigrain, Michael Cretignier, Khaled Al Moulla

Stellar magnetic activity induces both distortions and Doppler-shifts in the absorption line profiles of Sun-like stars. Those effects produce apparent radial velocity (RV) signals which greatly hamper the search for potentially habitable, Earth-like planets. In this work, we investigate these distortions in the Sun using cross-correlation functions (CCFs),

Yuhan Li, Tianyao Huang, Yimin Liu, Xiqin Wang

We study the problem of representing a discrete tensor that comes from finite uniform samplings of a multi-dimensional and multiband analog signal. Particularly, we consider two typical cases in which the shape of the subbands is cubic or parallelepipedic. For the cubic case, by examining the spectrum of its corresponding time- and band-limited operators, we

Tong Zhang, Peixin Qin, Yang Deng, Chen Huang

Large language models (LLMs) are increasingly used to meet user information needs, but their effectiveness in dealing with user queries that contain various types of ambiguity remains unknown, ultimately risking user trust and satisfaction. To this end, we introduce CLAMBER, a benchmark for evaluating LLMs using a well-organized taxonomy. Building upon the t

G. Calé, G. Chachamis, A. Sabio Vera

In high-energy particle physics, the study of particle-particle correlations in proton-proton and heavy-ion collisions constitutes a pivotal frontier in the effort to understand the fundamental dynamics of the strong force. To the best of our knowledge, we employ for the first time the BFKL dynamics implemented in a Monte Carlo code in momentum space to comp

N. Khorshid, M. Min, J. Polman, L. B. F. M. Waters

Understanding the formation history of planets is one of the goals of studying exoplanet atmospheres. The atmospheric composition of planets can provide insights into the formation pathways of planets. Even though the mapping of the atmospheric composition onto a formation pathway is not unambiguous, with the increasing sensitivity of modern instruments, we

Zhuohang Li, Cong Wang, Linwei Zhou, Yurou Guan

Perfluorocubane ($C_8F_8$) was successfully synthesized and found to accept and store electrons in its internal cubic cavity to form magnetic moments. However their inter-molecule spin-exchange coupling mechanism is yet to be revealed. In this study, we found the inter-molecule magnetic groundstates of $C_8F_8$ dimer and one-dimensional (1D) chain are tunabl

Yue Chen, Chen Huang, Yang Deng, Wenqiang Lei

Equipping a conversational search engine with strategies regarding when to ask clarification questions is becoming increasingly important across various domains. Attributing to the context understanding capability of LLMs and their access to domain-specific sources of knowledge, LLM-based clarification strategies feature rapid transfer to various domains in

E. Lascas Neto, R. Jorge, C. D. Beidler, J. Lion

In this work, we propose a method of optimising stellarator devices to favour the presence of an electron root solution of the radial electric field. Such a solution can help avoid heavy impurity accumulation, improve neoclassical thermal ion confinement and helium ash exhaust and possibly reduce turbulence. This study shows that an optimisation for such a r

Fotios Logothetis, Ignas Budvytis, Roberto Cipolla

In this work we present a novel multi-view photometric stereo (MVPS) method. Like many works in 3D reconstruction we are leveraging neural shape representations and learnt renderers. However, our work differs from the state-of-the-art multi-view PS methods such as PS-NeRF or Supernormal in that we explicitly leverage per-pixel intensity renderings rather tha

Angel F. Campoverde

There are two main ways of looking for new physics, direct searches and precision measurements. The latter are sensitive to a broader spectrum of models; they also can be sensitive to higher energy scales than what can be reached through direct searches. We will provide an update of several precision measurements carried out by the LHCb collaboration. In par

Olga Kellert, Carlos Gómez-Rodríguez, Mahmud Uz Zaman

TripAdvisor reviews and comparable data sources play an important role in many tasks in Natural Language Processing (NLP), providing a data basis for the identification and classification of subjective judgments, such as hotel or restaurant reviews, into positive or negative polarities. This study explores three important factors influencing variation in cro

Athanassios Z. Panagiotopoulos

Monte Carlo simulations in the grand canonical ensemble were used to obtain critical parameters and conditions leading to microphase separation for block copolymers with solvophilic and solvophobic segments. Solvent selectivity was systematically varied to distinguish between systems that undergo macrophase separation to ones that microphase separate in the

Liangliang Zhu, Zhebin Song, Xuesen Zhang, Meibin Qi

Independent component analysis (ICA) is a fundamental problem in the field of signal processing, and numerous algorithms have been developed to address this issue. The core principle of these algorithms is to find a transformation matrix that maximizes the non-Gaussianity of the separated signals. Most algorithms typically assume that the source signals are

Ashish Srivastava, Mohammed Nawfal

The K-Means clustering using LLoyd's algorithm is an iterative approach to partition the given dataset into K different clusters. The algorithm assigns each point to the cluster based on the following objective function \[\ \min \Sigma_{i=1}^{n}||x_i-\mu_{x_i}||^2\] The serial algorithm involves iterative steps where we compute the distance of each datapoint

Djamel Himane

The smallest Euler brick, discovered by Paul Halcke, has edges $(177, 44, 240) $ and face diagonals $(125, 267, 244 ) $, generated by the primitive Pythagorean triple $ (3, 4, 5) $. Let $ (u,v,w) $ primitive Pythagorean triple, Sounderson made a generalization parameterization of the edges \begin{equation*} a = \vert u(4v^2 - w^2) \vert, \quad b = \vert v(4u

Lorenzo J. Díaz, Katrin Gelfert, Jinhua Zhang

We study the amount of nonhyperbolicity within a broad class of (nonhyperbolic) partially hyperbolic diffeomorphisms with a one-dimensional center. For that, we focus on the center Lyapunov exponent and the entropy of its level sets. We show that these entropies vary continuously and can be expressed in terms of restricted variational principles. In this stu

Benedict Clark, Rick Wilming, Artur Dox, Paul Eschenbach

The evolving landscape of explainable artificial intelligence (XAI) aims to improve the interpretability of intricate machine learning (ML) models, yet faces challenges in formalisation and empirical validation, being an inherently unsupervised process. In this paper, we bring together various benchmark datasets and novel performance metrics in an initial be

Damiano Anselmi

We study the impact of the expansion of the universe on a broad class of objects, including black holes, neutron stars, white dwarfs, and others. Using metrics that incorporate primordial inhomogeneities, the effects of a hypothetical "center of the universe" on inflation are calculated. Dynamic coordinates for black holes that account for expansions or cont

Michael Cramer Andersen

This study explores the age-old quest to construct a geometric model of a quantum particle. While static classical particle models have largely been dismissed, the focus has now shifted to intricate dynamic models that hold the promise of reconciling general relativity with quantum mechanics. We propose that matter particles can be described as radiation con

Ryan McGowan, Florian Naef, Brian O'Callaghan

We show that the $E_1$-equivalence $C^\bullet(S^2) \simeq H^\bullet(S^2)$ does not intertwine the inclusion of constant loops into the free loop space $S^2 \to LS^2$. That is, the isomorphism $HH_\bullet(H^\bullet(S^2)) \cong H^\bullet(LS^2)$ does not preserve the obvious maps to $H^\bullet(S^2)$ that exist on both sides. We give an explicit computation of t

Chung-Hsuan Hu, Zheng Chen, Erik G. Larsson

Federated learning (FL) has received significant attention in recent years for its advantages in efficient training of machine learning models across distributed clients without disclosing user-sensitive data. Specifically, in federated edge learning (FEEL) systems, the time-varying nature of wireless channels introduces inevitable system dynamics in the com

Yukiyoshi Nakkajima

For a flat $p$-adic formal family $S$ of log points over a complete discrete valuation ring with perfect residue field of mixed characteristics $(0,p)$ and for a simple normal crossing log scheme $X$ over an exact closed log subscheme of $S$ defined by an element of the maximal ideal of the dvr, we construct two fundamental filtered complexes in the converge

Dawid A. Hryniuk, Marzena H. Szymańska

We introduce a novel method of efficiently simulating the non-equilibrium steady state of large many-body open quantum systems with highly non-local interactions, based on a variational Monte Carlo optimization of a matrix product operator ansatz. Our approach outperforms and offers several advantages over comparable algorithms, such as an improved scaling o

Jukka Ruohonen

The European Union (EU) has been pursuing new cyber security policies in recent years. This paper presents a short reflection of four such policies. The focus is on potential incoherency, meaning a lack of integration, divergence between the member states, institutional dysfunction, and other related problems that should be at least partially avoidable by so

David Soler, Carlos Dafonte, Manuel Fernández-Veiga, Ana Fernández Vilas

The Messaging Layer security (MLS) and its underlying Continuous Group Key Agreement (CGKA) protocol allows a group of users to share a cryptographic secret in a dynamic manner, such that the secret is modified in member insertions and deletions. Although this flexibility makes MLS ideal for implementations in distributed environments, a number of issues nee

Diego Díaz, Pablo Paniagua, Cristián Larroulet

The consequences of natural disasters, such as earthquakes, are evident: death, coordination problems, destruction of infrastructure, and displacement of population. However, according to empirical research, the impact of a natural disaster on economic activity is mixed. Natural disasters could have significant economic effects, especially in developing econ

Kristina Radivojevic, DJ Adams, Griffin Laszlo, Felixander Kery

Social media platforms have witnessed a dynamic landscape of user migration in recent years, fueled by changes in ownership, policy, and user preferences. This paper explores the phenomenon of user migration from established platforms like X/Twitter to emerging alternatives such as Threads, Mastodon, and Truth Social. Leveraging a large dataset from X/Twitte

Emanuel Malvetti, Christian Arenz, Gunther Dirr, Thomas Schulte-Herbrüggen

We analyze convergence of gradient-descent methods on Riemannian manifolds. In particular, we study randomization of Riemannian gradient algorithms for minimizing smooth cost functions (of Morse-Bott type). We prove that randomized gradient descent methods, where the Riemannian gradient is replaced by a random projection of it, converge to a single local opt

Dandan Zhang, Zhiqiang Zhang, Nanguang Chen, Yun Wang

Time series data in real-world scenarios contain a substantial amount of nonlinear information, which significantly interferes with the training process of models, leading to decreased prediction performance. Therefore, during the time series forecasting process, extracting the local and global time series patterns and understanding the potential nonlinear f

Emel Altas, Bayram Tekin

We give a detailed canonical analysis of the $n$-dimensional $f$(Riemann) gravity, correcting the earlier results in the literature. We also write the field equations in the Fischer-Marsden form which is amenable to identifying the non-stationary energy on a spacelike hypersurface. We give pure $R^{2}$ and $R_{\mu\nu}R^{\mu\nu}$ theories as examples.

Giacomo Baldan, Alberto Guardone

This study investigates the flow evolution around a sinusoidal pitching NACA 0012 airfoil, defined by the National Advisory Committee for Aeronautics (NACA), undergoing deep dynamic stall using a wall-resolved large eddy simulation (LES) approach. Numerical results are assessed against experimental data from Lee and Gerontakos (2004) at Reynolds number Re =

Diego Sanmartin

Ensuring factual accuracy while maintaining the creative capabilities of Large Language Model Agents (LMAs) poses significant challenges in the development of intelligent agent systems. LMAs face prevalent issues such as information hallucinations, catastrophic forgetting, and limitations in processing long contexts when dealing with knowledge-intensive task

Younes Ben Mazziane, Othmane Marfoq

Count-Min Sketch with Conservative Updates (CMS-CU) is a memory-efficient hash-based data structure used to estimate the occurrences of items within a data stream. CMS-CU stores $m$ counters and employs $d$ hash functions to map items to these counters. We first argue that the estimation error in CMS-CU is maximal when each item appears at most once in the s

Maxence Brévard, Karim Rakhimov

We prove that, within any holomorphic family of endomorphisms of $\mathbb P^k(\mathbb C)$ in any dimension $k \geq 1$ and algebraic degree $d \geq 2$, the measurable holomorphic motion associated to dynamical stability in the sense of Berteloot-Bianchi-Dupont preserves the class of equilibrium states associated with weight functions $\psi$ satisfying $\sup\p

Janusz Morawiec, Thomas Zürcher

The following MW--problem was posed independently by Janusz Matkowski and Jacek Weso{\l}owski in different forms in 1985 and 2009, respectively: Are there increasing and continuous functions $\varphi\colon [0,1]\to [0,1]$, distinct from the identity on $[0,1]$, such that $\varphi(0)=0$, $\varphi(1)=1$ and $\varphi(x)=\varphi(\frac{x}{2})+\varphi(\frac{x+1}{2

Nian Li, Jianguo Wei

Transformer-based architectures for speaker verification typically require more training data than ECAPA-TDNN. Therefore, recent work has generally been trained on VoxCeleb1&2. We propose a backbone network based on self-attention, which can achieve competitive results when trained on VoxCeleb2 alone. The network alternates between neighborhood attention and

Gabriel O. Alves, Marcelo A. F. Santos, Gabriel T. Landi

We investigate a quantum thermometry scheme based collision model with Gaussian systems. A key open question of these schemes concerns the scaling of the Quantum Fisher Information (QFI) with the number of ancillae. In qubit-based implementations this question is difficult to assess, due to the exponentially growing size of the Hilbert space. Here we focus o

E. Carli, L. Levin, B. W. Stappers, E. D. Barr

The sensitivity of the MeerKAT radio interferometer is an opportunity to probe deeper into the population of rare and faint extragalactic pulsars. The TRAPUM (TRAnsients and PUlsars with MeerKAT) collaboration has conducted a radio-domain search for accelerated pulsars and transients in the Small Magellanic Cloud (SMC). This partially targeted survey, perfor

Chaim Goodman-Strauss

Through a series of elementary exercises, we explain the fractal structure of Pascal's triangle when written modulo $p$ using an 1852 theorem due to Kummer: A prime $p$ divides $\dfrac {n!}{i!j!} $ if and only if there is a carry in the addition $i+j=n$ when written in base $p$.

Hamidreza Movahedi, Andrew Weng, Sravan Pannala, Jason B. Siegel

The battery state of health (SOH) based on capacity fade and resistance increase is not sufficient for predicting Remaining Useful life (RUL). The electrochemical community blames the path-dependency of the battery degradation mechanisms for our inability to forecast the degradation. The control community knows that the path-dependency is addressed by full s

Pujian Mao, Bochen Zhou

We study the linearized gravity theory in the Newman-Unti gauge in the near horizon region of the de Sitter spacetime. The linearized Einstein equation involves the cosmological constant. The near horizon symmetry consists of near horizon supertranslation and near horizon superrotation. We compute the near horizon supertranslation charge and find the proper

Chun Tung Chou

Molecular communication is a bio-inspired communication paradigm where molecules are used as the information carrier. This paper considers a molecular communication network where the transmitter uses concentration modulated signals for communication. Our focus is to design receivers that can demodulate these signals. We want the receivers to use enzymatic cy

Zejun Huang, Chenxi Yang

An oriented graph is a digraph obtained from an undirected graph by choosing an orientation for each edge. Given a positive integer $n$ and an oriented graph $F$, the oriented Tur$\acute{\rm a}$n number $ex_{ori}(n,F)$ is the maximum number of arcs in an $F$-free oriented graph of order $n$. In this paper, we investigate the oriented Tur$\acute{\rm a}$n numb

Karl Dilcher, Larry Ericksen

We begin by considering a sequence of polynomials in three variables whose coefficients count restricted binary overpartitions with certain properties. We then concentrate on two specific subsequences that are closely related to the Chebyshev polynomials of both kinds, deriving combinatorial and algebraic properties of some special cases. We show that the ze

Christopher R. Kitching, Henri Kauhanen, Jordan Abbott, Deepthi Gopal

In this paper we study networks of nodes characterised by binary traits that change both endogenously and through nearest-neighbour interaction. Our analytical results show that those traits can be ranked according to the noisiness of their transmission using only measures of order in the stationary state. Crucially, this ranking is independent of network to

Giampiero Bardella, Simone Franchini, Pierpaolo Pani, Stefano Ferraina

Modern neuroscience has evolved into a frontier field that draws on numerous disciplines, resulting in the flourishing of novel conceptual frames primarily inspired by physics and complex systems science. Contributing in this direction, we recently introduced a mathematical framework to describe the spatiotemporal interactions of systems of neurons using lat