November 2024 arXiv papers — page 108

Zhengyi Wang, Jonathan Lorraine, Yikai Wang, Hang Su

This work explores expanding the capabilities of large language models (LLMs) pretrained on text to generate 3D meshes within a unified model. This offers key advantages of (1) leveraging spatial knowledge already embedded in LLMs, derived from textual sources like 3D tutorials, and (2) enabling conversational 3D generation and mesh understanding. A primary

Claudio A. Buzzi, Douglas D. Novaes

For a given natural number $n$, the second part of Hilbert's 16th Problem asks whether there exists a finite upper bound for the maximum number of limit cycles that planar polynomial vector fields of degree $n$ can have. This maximum number of limit cycle, denoted by $H(n)$, is called the $n$th Hilbert number. It is well-established that $H(n)$ grows asympto

M. Antonello, L. Brinkmann, E. Garutti, R. Klanner

The gain-voltage dependence for SiPMs from V. Chmill et al., Study of the breakdown voltage of SiPMs, is reanalyzed and a non-linearity at the sub-percent level is observed. Simulations show that he non-linearity can be explained by the increase of the depletion depth of the avalanche region with over-voltage. A consequence of the non-linearity is that the v

Bozhou Zhuang, Sashank Rana, Brandon Jones, Danny Smyl

Numerical modeling errors are unavoidable in finite element analysis. The presence of model errors inherently reflects both model accuracy and uncertainty. To date there have been few methods for explicitly quantifying errors at points of interest (e.g. at finite element nodes). The lack of explicit model error approximators has been addressed recently with

Lena Stempfle, Arthur James, Julie Josse, Tobias Gauss

Inherently interpretable machine learning (IML) models offer valuable support for clinical decision-making but face challenges when features contain missing values. Traditional approaches, such as imputation or discarding incomplete records, are often impractical in scenarios where data is missing at test time. We surveyed 55 clinicians from 29 French trauma

Vahid Zolfaghari, Nenad Petrovic, Fengjunjie Pan, Krzysztof Lebioda

In this paper, we explore the integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) to enhance automated design and software development in the automotive industry. We present two case studies: a standardization compliance chatbot and a design copilot, both utilizing RAG to provide accurate, context-aware responses. We evaluat

Stefano Longhi

The behavior of systems far from equilibrium is often complex and unpredictable, challenging and sometimes overturning the physical intuition derived from equilibrium scenarios. One striking example of this is the Mpemba effect, which implies that non-equilibrium states can sometimes relax more rapidly when they are further from equilibrium. Despite a rich h

Carlos Floyd, Aaron R. Dinner, Suriyanarayanan Vaikuntanathan

Active nematics, formed from a liquid crystalline suspension of active force dipoles, are a paradigmatic active matter system whose study provides insights into how chemical driving produces the cellular mechanical forces essential for life. Recent advances in optogenetic control over molecular motors and cell-signaling pathways now allow experimenters to mi

Jinxiang Lai, Jie Zhang, Jun Liu, Jian Li

Multimodal LLMs (MLLMs) have emerged as an extension of Large Language Models (LLMs), enabling the integration of various modalities. However, Any-to-Any MLLMs are limited to generating pairwise modalities 'Text + X' within a single response, such as Text + {Image or Audio or Video}. To address this limitation, we introduce Spider, a novel efficient Any-to-M

Akari Haga, Akiyo Fukatsu, Miyu Oba, Arianna Bisazza

While current large language models have achieved a remarkable success, their data efficiency remains a challenge to overcome. Recently it has been suggested that child-directed speech (CDS) can improve training data efficiency of modern language models based on Transformer neural networks. However, it is not yet understood which specific properties of CDS a

Dafne Murillo, Sebastian Sardon

State capacity may shape whether natural resources generate prosperity, as it determines if windfalls are effectively turned into useful projects or wasted. We test this hypothesis studying the 2004-2011 mining boom in Peru, where mines' profits are redistributed as windfall transfers to local governments. Our empirical strategy combines geological data with

Shaokui Wei, Jiayin Liu, Hongyuan Zha

Backdoor attacks undermine the integrity of machine learning models by allowing attackers to manipulate predictions using poisoned training data. Such attacks lead to targeted misclassification when specific triggers are present, while the model behaves normally under other conditions. This paper considers a post-training backdoor defense task, aiming to det

Bor Plestenjak, Daniel A. Kiefer, Hauke Gravenkamp

Eigenvalues of parameter-dependent quadratic eigenvalue problems form eigencurves. The critical points on these curves, where the derivative vanishes, are of practical interest. A particular example is found in the dispersion curves of elastic waveguides, where such points are called zero-group-velocity (ZGV) points. Recently, it was revealed that the proble

Paul G. Beckman, Michael O'Neil

We describe a fast algorithm for computing discrete Hankel transforms of moderate orders from $n$ nonuniform points to $m$ nonuniform frequencies in $O((m+n)\log\min(n,m))$ operations. Our approach combines local and asymptotic Bessel function expansions with nonuniform fast Fourier transforms. The order of each expansion is adjusted automatically according

Joyce Lai, Peter Seiler

Disturbance rejection in high-precision control applications can be significantly improved upon via online convex optimization (OCO). This includes classical techniques such as recursive least squares (RLS) and more recent, regret-based formulations. However, these methods can cause instabilities in the presence of model uncertainty. This paper introduces a

N. V. Okhotnikov, K. V. Lotov

In a plasma wakefield accelerator driven by a train of short particle bunches, it is possible to locally increase the acceleration rate by introducing a small negative gradient of the plasma density. A regime is possible in which the gradient affects only the relative phasing of the driver bunches and the wave, keeping the wave phase behind the driver stable

Haoxiang Zhang, Shi Chang, Arthur Leung, Kishanthan Thangarajah

The rise of Foundation Models (FMs) like Large Language Models (LLMs) is revolutionizing software development. Despite the impressive prototypes, transforming FMware into production-ready products demands complex engineering across various domains. A critical but overlooked aspect is performance engineering, which aims at ensuring FMware meets performance go

V. I. Korobov, F. A. Martynenko, A. P. Martynenko, A. V. Eskin

We study hadronic light-by-light scattering contribution to the energy interval (1S-2S) in muonium. Various amplitudes of interaction of a muon and an electron are constructed, in which the effect of hadronic scattering of light-by-light is determined using the transition form factor of two photons into a meson. Their contributions to the particle interactio

Fei Wan

Propensity Score Matching (PSM) stands as a widely embraced method in comparative effectiveness research. PSM crafts matched datasets, mimicking some attributes of randomized designs, from observational data. In a valid PSM design where all baseline confounders are measured and matched, the confounders would be balanced, allowing the treatment status to be c

Johan Bijnens, Nils Hermansson-Truedsson, Antonio Rodríguez-Sánchez

The dispersive approach to the hadronic light-by-light contribution to the muon $g-2$ involves an integral over three virtual photon momenta appearing in the light-by-light tensor. Building upon previous works, we systematically derive short-distance constraints in the region where two momenta are large compared to the third, the so-called Melnikov-Vainshtei

Yu-Kai Hung, Yun-Chien Huang, Ting-Yu Su, Yen-Ting Lin

Audience feedback is crucial for refining video content, yet it typically comes after publication, limiting creators' ability to make timely adjustments. To bridge this gap, we introduce SimTube, a generative AI system designed to simulate audience feedback in the form of video comments before a video's release. SimTube features a computational pipeline that

Ian Miguel, András Z. Salamon, Christopher Stone

Formulating an effective constraint model of a parameterised problem class is crucial to the efficiency with which instances of the class can subsequently be solved. It is difficult to know beforehand which of a set of candidate models will perform best in practice. This paper presents a system that employs graph rewriting to reformulate an input model for i

Tejbir Lohan, Chandan Maity

We consider the adjoint action of the symplectic Lie group $\mathrm{Sp}(2n,\mathbb{C})$ on its Lie algebra $\mathfrak{sp}(2n,\mathbb{C})$. An element $X \in \mathfrak{sp}(2n,\mathbb{C})$ is called $\mathrm{Ad}_{\mathrm{Sp}(2n,\mathbb{C})}$-real if $ -X = \mathrm{Ad}(g)X$ for some $g \in \mathrm{Sp}(2n,\mathbb{C})$. Moreover, if $ -X = \mathrm{Ad}(h)X $ for s

Yohan Potaux, Debajyoti Sarkar, Sergey N. Solodukhin

Following our previous work on hybrid quantum states in the RST model, we study its most interesting solution representing a completely regular spacetime with the structure of causal diamond, containing an apparent horizon and radiation at infinity. Adapting recent computations of radiation entropy in terms of the entropy of entanglement, we find that this e

Martin de Borbon, Dmitri Panov

Let $\mathcal{H}$ be a hyperplane arrangement in $\mathbb{CP}^n$. We define a quadratic form $Q$ on $\mathbb{R}^{\mathcal{H}}$ that is entirely determined by the intersection poset of $\mathcal{H}$. Using the Bogomolov-Gieseker inequality for parabolic bundles, we show that if $\mathbf{a} \in \mathbb{R}^{\mathcal{H}}$ is such that the weighted arrangement $(

Zhenjun Yu, Wenqiang Xu, Pengfei Xie, Yutong Li

We present ViTaM-D, a novel visual-tactile framework for reconstructing dynamic hand-object interaction with distributed tactile sensing to enhance contact modeling. Existing methods, relying solely on visual inputs, often fail to capture occluded interactions and object deformation. To address this, we introduce DF-Field, a distributed force-aware contact r

Fei Qin, Cullan Howlett, David Parkinson

The large-scale structure of the Universe and its evolution over time contains an abundance of cosmological information. One way to unlock this is by measuring the density and momentum power spectrum from the positions and peculiar velocities of galaxies, and fitting the cosmological parameters from these power spectrum. In this paper, we will explore the cr

Prajeet Bajpai, Yann Bugeaud

We establish an effective improvement on the Liouville inequality for approximation to complex non-real algebraic numbers by quadratic complex algebraic numbers.

P. Dalmas de Reotier, A. Yaouanc, D. Andreica, R. Gupta

We experimentally study the evolution of the magnetic moment $m$ and exchange interaction $J$ as a function of hydrostatic pressure in the zero-field helimagnetic phase of the strongly correlated electron system MnSi. The suppression of magnetic order at $\approx 1.5$~GPa is shown to arise from the $J$ collapse and not from a quantum fluctuations induced red

Paul Quincey

School and undergraduate students are almost always taught the equations of electromagnetism using a set of conventions that are described as the SI. More advanced students are often introduced to different conventions that produce different equations for the same relationships, using either the Gaussian or Heaviside-Lorentz systems. In general, the connecti

Xi Lin, Shixuan Zhao, Xinxu Wei, Amir Shmuel

3D microscopic cerebrovascular images are characterized by their high resolution, presenting significant annotation challenges, large data volumes, and intricate variations in detail. Together, these factors make achieving high-quality, efficient whole-brain segmentation particularly demanding. In this paper, we propose a novel Vessel-Pattern-Based Semi-Supe

Catalina Sáez-Carvajal, Nikolaus Vogt, Mónica Zorotovic, Javiera García-Veas

The orbital period of a cataclysmic variable stands as a crucial parameter for investigating the structure and physics of these binary systems, as well as understanding their evolution. We use photometric Gaia data for dwarf novae (DNe) in the quiescent state which are available for a number of years to determine new orbital periods and improve/modify previo

Shogo Sawaguchi, Temma Suzuki, Akihiro Miki, Kento Kawaharazuka

Numerous wearable robots have been developed to meet the demands of physical assistance and entertainment. These wearable robots range from body-enhancing types that assist human arms and legs to body-extending types that have extra arms. This study focuses specifically on wearable robots of the latter category, aimed at bodily extension. However, they have

Valentina Marulanda Acosta, Daniele Dequal, Matteo Schiavon, Aurelie Montmerle-Bonnefois

Future quantum networks will be composed of both terrestrial links for metropolitan and continent-scale connections and space-based links for global coverage and infrastructure resilience. However, the propagation of quantum signals through the atmosphere is severely impacted by the effects of turbulence. This is even more the case for entanglement-based qua

Ron Vatash, Amy Altshuler, Yael Roichman

A common and effective method for calculating the steady-state distribution of a process under stochastic resetting is the renewal approach that requires only the knowledge of the reset-free propagator of the underlying process and the resetting time distribution. The renewal approach is widely used for simple model systems such as a freely diffusing particl

T. Mondal, N. W. Prouse, P. de Perio, M. Hartz

Hyper-Kamiokande (Hyper-K) is a next-generation long baseline neutrino experiment. One of its primary physics goals is to measure neutrino oscillation parameters precisely, including the Dirac CP violating phase. As conventional $\nu_{\mu}$ beam generates from the J-PARC neutrino baseline contains only 1.5$\%$ of $\nu_{e}$ interaction of total, it is challen

Gao Chen, Hao Yan

In this paper, we compute the expansion of some harmonic functions and 1-forms on ALE Ricci-flat 4-manifolds.

ALICE Collaboration

The momentum-differential invariant cross sections of ${\pi^{0}}$ and $\eta$ mesons are reported for pp collisions at $\sqrt{s}$ = 13 TeV at midrapidity ($|y|<0.8$). The measurement is performed in a broad transverse-momentum range of $0.2<p_{\rm T}<200$ GeV/$c$ and $0.4 < p_{\rm T} < 60$ GeV/$c$ for the ${\pi^{0}}$ and $\eta$, respectively, extending the $p

Josipa Majstorović, Léon Vidal, Philippe Lognonné

In the light of the recent advances in lunar space missions a great interest into using Moon as a future environment for gravitational waves (GWs) detectors has been initiated. Moon offers a unique environment for such detectors due to constrained noise sources, since unlike Earth it does not have ocean and atmosphere. In this paper, we further explore the i

Anindya Sundar Das, Guansong Pang, Monowar Bhuyan

Visual anomaly detection targets to detect images that notably differ from normal pattern, and it has found extensive application in identifying defective parts within the manufacturing industry. These anomaly detection paradigms predominantly focus on training detection models using only clean, unlabeled normal samples, assuming an absence of contamination;

Mohammad Ali S. Afshar, Jafar Sadeghi

Non-commutative black holes(NCBH), due to the non-commutativity of spacetime coordinates, lead to a modification of the spacetime metric. By replacing the Dirac delta function with a Gaussian distribution, the mass is effectively smeared, eliminating point-like singularities. Our objective is to investigate the impact of this change on spacetime geodesics, i

Tamas Vaszary

Carleman linearization is a technique that embeds systems of ordinary differential equations with polynomial nonlinearities into infinite dimensional linear systems in a procedural way. In this paper we generalize the method for systems of partial differential equations with quadratic nonlinearities, while maintaining the original structure of Carleman linea

León Salas, Matthew Liska, Sera Markoff, Koushik Chatterjee

The Event Horizon Telescope Collaboration (EHTC) observed the Galactic centre source Sagittarius A* (Sgr A*) and used emission models primarily based on single ion temperature (1T) general relativistic magnetohydrodynamic (GRMHD) simulations. This predicted emission is strongly dependent on a modelled prescription of the ion-to-electron temperature ratio. Th

Nadaniela Egidi, Josephin Giacomini, Paolo Leonesi, Pierluigi Maponi

Motion Magnification (MM) is a collection of relative recent techniques within the realm of Image Processing. The main motivation of introducing these techniques in to support the human visual system to capture relevant displacements of an object of interest; these motions can be in object color and in object location. In fact, the goal is to opportunely pro

Wei-Yang Zhang, Feng-Lian Dong, Zhi-Wei Wei, Yan-Ru Wang

The distributed recursion (DR) algorithm is an effective method for solving the pooling problem that arises in many applications. It is based on the well-known P-formulation of the pooling problem, which involves the flow and quality variables; and it can be seen as a variant of the successive linear programming (SLP) algorithm, where the linear programming

Junwen Wang, Zhonghao Wang, Oscar MacCormac, Jonathan Shapey

Despite significant advancements, segmentation based on deep neural networks in medical and surgical imaging faces several challenges, two of which we aim to address in this work. First, acquiring complete pixel-level segmentation labels for medical images is time-consuming and requires domain expertise. Second, typical segmentation pipelines cannot detect o

Hao WU, Hanwen Zhang

We study the differentially private top-$k$ selection problem, aiming to identify a sequence of $k$ items with approximately the highest scores from $d$ items. Recent work by Gillenwater et al. (ICML '22) employs a direct sampling approach from the vast collection of $d^{\,\Theta(k)}$ possible length-$k$ sequences, showing superior empirical accuracy compare

Jonas Serych, Michal Neoral, Jiri Matas

In this work, we present MFTIQ, a novel dense long-term tracking model that advances the Multi-Flow Tracker (MFT) framework to address challenges in point-level visual tracking in video sequences. MFTIQ builds upon the flow-chaining concepts of MFT, integrating an Independent Quality (IQ) module that separates correspondence quality estimation from optical f

David Angeli, Davide Martini, Giacomo Innocenti, Alberto Tesi

Despite modular conditions to guarantee stability for large-scale systems have been widely studied, few methods are available to tackle the case of networks with multiple equilibria. This paper introduces small-gain like sufficient conditions for 2-contraction of large-scale interconnected systems on the basis of a family of upper-bounds to the $L_2$ gains t

Arianna Crippa, Yahui Chai, Omar Costa Hamido, Paulo Itaborai

We aim to apply a quantum computing technique to compose artworks. The main idea is to revisit three paintings of different styles and historical periods: ''Narciso'', painted circa 1597-1599 by Michelangelo Merisi (Caravaggio), ''Les fils de l'homme'', painted in 1964 by Rene Magritte and ''192 Farben'', painted in 1966 by Gerard Richter. We utilize the out

Amir A. Khodahami, Azizollah Azizi

We investigate the potential for generating an AMPS firewall from the replica wormhole topology, which describes the post-Page time spacetime in the evaporation process of a black hole. Our analysis reveals that this topology gives rise to a Dirac delta force experienced by infalling particles at the event horizon, consistent with the AMPS firewall hypothesi

Haoran Wang, Aman Rangapur, Xiongxiao Xu, Yueqing Liang

Existing claim verification datasets often do not require systems to perform complex reasoning or effectively interpret multimodal evidence. To address this, we introduce a new task: multi-hop multimodal claim verification. This task challenges models to reason over multiple pieces of evidence from diverse sources, including text, images, and tables, and det

Dhandeep Challagundla, Ignatius Bezzam, Riadul Islam

While general-purpose computing follows Von Neumann's architecture, the data movement between memory and processor elements dictates the processor's performance. The evolving compute-in-memory (CiM) paradigm tackles this issue by facilitating simultaneous processing and storage within static random-access memory (SRAM) elements. Numerous design decisions tak

Nataliya Sevryugina, Serena Costanzo, Stephen de Bruyn Kops, Colm-cille Caulfield

Computational Fluid Dynamics (CFD) is an indispensable method of fluid modelling in engineering applications, reducing the need for physical prototypes and testing for tasks such as design optimisation and performance analysis. Depending on the complexity of the system under consideration, models ranging from low to high fidelity can be used for prediction,

Ekaterina Tarasevich, Maxim Gladush

Theoretical methods based on the density matrix are powerful tools to describe open quantum systems. However, such methods are complicated and intricate to be used analytically. Here we present an object-oriented framework for constructing the equation of motion of the correlation matrix at a given order in the quantum chain of BBGKY hierarchy used to descri

Xiaoling Yi, Ryan Antonio, Joren Dumoulin, Jiacong Sun

Deep neural networks (DNNs) face significant challenges when deployed on resource-constrained extreme edge devices due to their computational and data-intensive nature. While standalone accelerators tailored for specific application scenarios suffer from inflexible control and limited programmability, generic hardware acceleration platforms coupled with RISC

Hee Seung Kim, Hyeok-Jun Yang, Karlo Penc, SungBin Lee

Chiral spin liquids, which break time-reversal symmetry, are of great interest due to their topological properties and fractionalized excitations (anyons). In this work, we investigate chiral spin liquids (CSL) on the kagome lattice arising from the competition between the third-nearest-neighbor Heisenberg interaction across hexagons ($J_d$) and a staggered

Anneke Reinold, Lucas Berger, Marcin Raczkowski, Zhiying Zhao

We report on a comprehensive thermodynamic study of a quasi-two-dimensional (quasi-2D) quantum magnet Cu$_2$(OH)$_3$Br which in the 2D layer can be viewed as strongly coupled alternating antiferromagnetic and ferromagnetic chains. In an applied magnetic field transverse to the ordered spins below $T_N=9.3$ K, a field-induced phase transition from the 3D orde

Zi-Xuan Huang, Jia-Wei Chen, Zhi-Peng Zhang, Chia-Mu Yu

Visual prompting (VP) is a new technique that adapts well-trained frozen models for source domain tasks to target domain tasks. This study examines VP's benefits for black-box model-level backdoor detection. The visual prompt in VP maps class subspaces between source and target domains. We identify a misalignment, termed class subspace inconsistency, between

Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe, Florian Hinterwimmer

Fine-tuning large language models (LLMs) with limited data poses a practical challenge in low-resource languages, specialized domains, and constrained deployment settings. While pre-trained LLMs provide strong foundations, effective adaptation under data scarcity requires focused and efficient fine-tuning techniques. This paper presents a structured and prac

Eva Katharina Bauer, Simon Bultmann, Sven Behnke

The human gait is a complex interplay between the neuronal and the muscular systems, reflecting an individual's neurological and physiological condition. This makes gait analysis a valuable tool for biomechanics and medical experts. Traditional observational gait analysis is cost-effective but lacks reliability and accuracy, while instrumented gait analysis,

Harry Prieto

We establish the existence of the Bernstein polynomial in one indeterminate $t$, and provide a method for its explicit computation. The Bernstein polynomial is associated with finitely generated modules over the Weyl algebra, known as $D$-modules, and is notoriously difficult to compute directly. Our approach is constructive, offering a systematic method to

Mahjabeen Fatima, Saleem Ayaz Khan, Syed Rizwan

The work reports nonmagnetic behavior (0.04 $\mu$B) in two-dimensional (2D) V2C-OF MXene and ferromagnetism in MnO$_2$ adsorbed V2C-OF MXene. The density functional theory (DFT) calculations were carried out to study the magnetic moments of V$_2$C-OF and MnO$_2$@V$_2$C-OF MXene. The MXene, which is derived from the exfoliation of its parent V$_2$AlC MAX phas

Nataliya A. Balabanova, Manh Hong Duong, Christian Hilbe

The theory of direct reciprocity explores how individuals cooperate when they interact repeatedly. In repeated interactions, individuals can condition their behaviour on what happened earlier. One prominent example of a conditional strategy is Tit-for-Tat, which prescribes to cooperate if and only if the co-player did so in the previous round. The evolutiona

Dimitrios Samakovlis, Stefano Albini, Rubén Rodríguez Álvarez, Denisa-Andreea Constantinescu

Breakthroughs in ultra-low-power chip technology are transforming biomedical wearables, making it possible to monitor patients in real time with devices operating on mere {\mu}W. Although many studies have examined the power performance of commercial microcontrollers, it remains unclear which ones perform best across diverse application profiles and which ha

V. Domínguez Tubío, M. Badás Aldecocea, J. van Dam, A. S. Sørensen

Satellite-based quantum repeaters are a promising means to reach global distances in quantum networking due to the polynomial decrease of optical transmission with distance in free space, in contrast to the exponential decrease in optical fibers. We propose a satellite-based quantum repeater architecture with trapped individual atomic qubits, which can serve

Basdouri Imed, Jean Lerbet, Bouzid Mosbahi

In this paper, we introduce the concepts of quasi-centroid and quasi-derivation for Zinbiel algebras. Utilizing the classification results of Zinbiel algebras established previously, we describe the quasi-centroids and quasi-derivations of low-dimensional Zinbiel algebras. Additionally, we explore certain properties of quasi-centroids in the context of Zinbi

Vincent Jugé

Since AVL trees were invented in 1962, two major open questions about rebalancing operations, which found positive answers in other balanced binary search trees, were left open: can these operations be performed top-down (with a fixed look-ahead), and can they use an amortised constant number of write operations per update? We propose an algorithm that answe

Linyu Peng, Hiroaki Yoshimura

In this paper, we propose the concept of $(\pm)$-discrete Dirac structures over a manifold, where we define $(\pm)$-discrete two-forms on the manifold and incorporate discrete constraints using $(\pm)$-finite difference maps. Specifically, we develop $(\pm)$-discrete induced Dirac structures as discrete analogues of the induced Dirac structure on the cotange

Christopher Smith

In the first part of this talk, after a brief presentation of the strong CP puzzle, the construction of axion models and their main phenomenological features are described. In the second part, the possibility to mix the Peccei-Quinn symmetry with baryon and lepton numbers is discussed, showing that the axion could ultimately play a role in other puzzles of t

Luigi Foschini, Alberto Vecchiato, Alfio Bonanno

According to the asymptotically safe gravity, black holes may have characteristics different from those described according to general relativity if the running of the gravitational constant coupling happens at low energies. Particularly, they should be more compact, with a smaller event horizon, which in turn affects the other quantities dependent on it, li

Saiqi Liu, Chen Lin

The distillability conjecture of two-copy 4 by 4 Werner states is one of the main open problems in quantum information. We prove two special cases of the conjecture. The first case occurs when two 4 by 4 matrices A, B are both unitarily equivalent to block diagonal matrices with 2 by 2 blocks. The second case occurs when B is unitarily equivalent to either -

Jose L. Movilla, Josep Planelles, Juan I. Climente

The effect of polaron formation on the ground state of excitons, trions and biexcitons confined in CsPbBr$_3$ nanocrystals is studied in the framework of effective mass Hamiltonians, using a Haken-like (Bajaj) potential for carrier-phonon coupling. The binding energy of trions agrees well with that observed in experiments, with position-dependent dielectric

Ogutu B. Osoro, Edward J. Oughton, Fabion Kauker

Broadband Internet access is an important way to help achieve the Sustainable Development Goals. Currently, fixed fiber infrastructure is essential for providing universal broadband, but has received relatively little research attention in low-income countries compared to other more cost-efficient wireless technologies. Yet, pushing out fiber broadband netwo

Lorenzo Fabris, Marco Tezzele, Ciro Busiello, Mauro Sicchiero

In this work, we focus on the early design phase of cruise ship hulls, where the designers are tasked with ensuring the structural resilience of the ship against extreme waves while reducing steel usage and respecting safety and manufacturing constraints. At this stage the geometry of the ship is already finalized and the designer choose the thickness of the

Samiran Gode, Abhijeet Nayak, Débora N. P. Oliveira, Michael Krawez

Effective robot navigation in unseen environments is a challenging task that requires precise control actions at high frequencies. Recent advances have framed it as an image-goal-conditioned control problem, where the robot generates navigation actions using frontal RGB images. Current state-of-the-art methods in this area use diffusion policies to generate

Yuyou Gan, Yong Yang, Zhe Ma, Ping He

With the continuous development of large language models (LLMs), transformer-based models have made groundbreaking advances in numerous natural language processing (NLP) tasks, leading to the emergence of a series of agents that use LLMs as their control hub. While LLMs have achieved success in various tasks, they face numerous security and privacy threats,

Sina Taamoli, Negin Nezhad, Bahram Mobasher, Faezeh Manesh

The role of internal and environmental factors in the star formation activity of galaxies is still a matter of debate, particularly at higher redshifts. Leveraging the most recent release of the COSMOS catalog, COSMOS2020, and density measurements from our previous study we disentangle the impact of environment and stellar mass on the star formation rate (SF

N. S. Manton

An extension of the Standard Model is proposed, where the Higgs field is valued in the complex projective plane ${\mathbb{CP}}^2$, rather than ${\mathbb{C}}^2$. Its geometry is consistent with $U(2) \simeq (SU(2) \times U(1))/ \mathbb{Z}_2$ electroweak gauge symmetry. The leading terms in the Lagrangian, beyond those of the Standard Model, are much more tigh

Federico P. Cortese, Antonio Pievatolo

Thermal comfort is essential for well-being in urban spaces, especially as cities face increasing heat from urbanization and climate change. Existing thermal comfort models usually overlook temporal dynamics alongside spatial dependencies. We address this problem by introducing a spatio-temporal jump model that clusters data with persistence across both spat

Vincent Chanal, Samuel Humpage, Markus Millinger

Technical carbon dioxide removal through bioenergy with carbon capture or direct air capture plays a role in virtually all climate mitigation scenarios. Both of these technologies rely on the use of chemical solvents or sorbents in order to capture CO$_2$. Lately, concerns have surfaced about the cost and energy implications of producing solvents and sorbent

Nataliya A. Balabanova, Manh Hong Duong

Vaccination is widely recognised as one of the most effective forms of public health interventions. Individuals decisions regarding vaccination creates a complex social dilemma between individual and collective interests, where each person's decision affects the overall public health outcome. In this paper, we study the adaptive dynamics for the evolutionary

Ning Wang, Jianming Cai, Chao Lei

Magnetic imaging with ultra-high spatial resolution is crucial to exploring the magnetic textures of emerging quantum materials. We propose a novel magnetic imaging protocol that achieves Angstrom-scale resolution by combining spin defects in van der Waals materials and terahertz scattering scanning near-field optical microscopy (THz s-SNOM). Spin defects in

Gagan Aggarwal, Anupam Gupta, Andres Perlroth, Grigoris Velegkas

We study a setting where agents use no-regret learning algorithms to participate in repeated auctions. \citet{kolumbus2022auctions} showed, rather surprisingly, that when bidders participate in second-price auctions using no-regret bidding algorithms, no matter how large the number of interactions $T$ is, the runner-up bidder may not converge to bidding trut

Hongjian Wang, Aaditya Ramdas

We present two sharp, closed-form empirical Bernstein inequalities for symmetric random matrices with bounded eigenvalues. By sharp, we mean that both inequalities adapt to the unknown variance in a tight manner: the deviation captured by the first-order $1/\sqrt{n}$ term asymptotically matches the matrix Bernstein inequality exactly, including constants, th

Jérôme Kieffer, Julien Orlans, Nicolas Coquelle, Samuel Debionne

We present here a real-time analysis of diffraction images acquired at high frame-rate (925 Hz) and its application to macromolecular serial crystallography. The software uses a new signal separation algorithm, able to distinguish the amorphous (or powder diffraction) component from the diffraction signal originating from single crystals. It relies on the ab

Xiao-Jun Gao

In this paper, we investigate the strong gravitational lensing effects and optical appearances around a spherically symmetric regular black hole, whose metric is derived from a non-singular collapsing dust ball model in asymptotically safe gravity. In this regular black hole spacetime, we obtain the analytical expression of the light deflection angle via cal

Yunuo Wang, Ningning Yang, Jialin Li

Generative Adversarial Networks (GANs) have surfaced as a revolutionary element within the domain of low-dose computed tomography (LDCT) imaging, providing an advanced resolution to the enduring issue of reconciling radiation exposure with image quality. This comprehensive review synthesizes the rapid advancements in GAN-based LDCT denoising techniques, exam

Fred Espen Benth, Nils Detering, Luca Galimberti

In this paper, we present a framework for learning the solution map of a backward parabolic Cauchy problem. The solution depends continuously but nonlinearly on the final data, source, and force terms, all residing in Banach spaces of functions. We utilize Fr\'echet space neural networks (Benth et al. (2023)) to address this operator learning problem. Our ap

Jan Hansen-Palmus, Michael Truong Le, Oliver Hausdörfer, Alok Verma

Large Language Models (LLMs) have pushed the frontier of artificial intelligence but are comprised of hundreds of billions of parameters and operations. For faster inference latency, LLMs are deployed on multiple hardware accelerators through various Model Parallelism strategies. Our paper looks into the details on one such strategy - Tensor Parallel - and p

A. Gogoi, J. C. Mandal

This paper compares the HLLEM and HLL-CPS schemes for Euler equations and proposes improvements for all Mach number flows. Enhancements to the HLLEM scheme involve adding anti-diffusion terms in the face normal direction and modifying anti-diffusion coefficients for linearly degenerate waves near shocks. The HLL-CPS scheme is improved by adjusting anti-diffu

Thomas Kahle, Lukas Kühne, Leonie Mühlherr, Bernd Sturmfels

We develop novel tools for computing the likelihood correspondence of an arrangement of hypersurfaces in a projective space. This uses the module of logarithmic derivations. This object is well-studied in the linear case, when the hypersurfaces are hyperplanes. We here focus on nonlinear scenarios and their applications in statistics and physics.

Michael A. Heroux, Sameer Shende, Lois Curfman McInnes, Todd Gamblin

In this paper, we discuss the need for an integrated software stack that unites artificial intelligence (AI) and modeling and simulation (ModSim) tools to advance scientific discovery. The authors advocate for a unified AI/ModSim software ecosystem that ensures compatibility across a wide range of software on diverse high-performance computing systems, promo

P. Cortes-Zuleta, I. Boisse, M. Ould-Elhkim, T. G. Wilson

We report the discovery of a super-Earth candidate orbiting the nearby mid M dwarf Gl\,725A using the radial velocity (RV) method. The planetary signal has been independently identified using high-precision RVs from the SOPHIE and SPIRou spectrographs, in the optical and near-infrared domains, respectively. We modelled the stellar activity signal jointly wit

Tom F. O'Hara, David P. Reid, Gregory L. Marsden, Karen L. Aplin

The triboelectric charging of granular materials remains a poorly understood phenomenon with a wide range of scientific and industrial applications, from volcanic lightning to pharmaceutical manufacturing. The Faraday cup is the most commonly used apparatus for studying triboelectric charging, yet current methods of interpreting measurements are overly simpl

Sebastiano Boscarino, Seung Yeon Cho

Implicit-explicit Runge-Kutta (IMEX-RK) time discretization methods are very popular when solving stiff kinetic equations. In [21], an asymptotic analysis shows that a specific class of high-order IMEX-RK schemes can accurately capture the Navier-Stokes limit without needing to resolve the small scales dictated by the Knudsen number. In this work, we extend

Tiantian Zhao

It has been shown that many first-order methods satisfy the perturbed Fenchel duality inequality, which yields a unified derivation of convergence. More first-order methods are discussed in this paper, e.g., dual averaging and bundle method. We show primal-dual convergence of them on convex optimization by proving the perturbed Fenchel duality property. We a

Zikai Zhou, Shitong Shao, Lichen Bai, Shufei Zhang

Text-to-image diffusion model is a popular paradigm that synthesizes personalized images by providing a text prompt and a random Gaussian noise. While people observe that some noises are ``golden noises'' that can achieve better text-image alignment and higher human preference than others, we still lack a machine learning framework to obtain those golden noi

Matthew Burfitt, Tyrone Cutler

Path homology plays a central role in digraph topology and GLMY theory more general. Unfortunately, the computation of the path homology of a digraph $G$ is a two-step process, and until now no complete description of even the underlying chain complex has appeared in the literature. In this paper we introduce an inductive method of constructing elements of t

Souvik Banerjee, Suman Das, Arnab Kundu, Michael Sittinger

Based on previous works, in this article we systematically analyze the implications of the explicit normal modes of a probe scalar sector in a BTZ background with a Dirichlet wall, in an asymptotically AdS-background. This is a Fuzzball-inspired geometric model, at least in an effective sense. We demonstrate explicitly that in the limit when the Dirichlet wa