December 2024 arXiv papers — page 156

Andriy Gusak, Serhii Abakumov

The concept of post-eutectic composition at a fixed undercooling is introduced as the most probable composition in zones of coupled growth. This composition corresponds to the minimum Gibbs free energy release rate in the steady state regime, aligning with Prigogine principle of minimum entropy production for steady states. Geometrically, this is represented

Yekun Ke, Yingyu Liang, Zhenmei Shi, Zhao Song

The application of transformer-based models on time series forecasting (TSF) tasks has long been popular to study. However, many of these works fail to beat the simple linear residual model, and the theoretical understanding of this issue is still limited. In this work, we propose the first theoretical explanation of the inefficiency of transformers on TSF t

Danylo Kolesnyk, Yelyzaveta Vodovozova

Modern approaches to generative modeling of continuous data using tensor networks incorporate compression layers to capture the most meaningful features of high-dimensional inputs. These methods, however, rely on traditional Matrix Product States (MPS) architectures. Here, we demonstrate that beyond a certain threshold in data and bond dimensions, a comb-sha

Matthew Lyle Olson, Neale Ratzlaff, Musashi Hinck, Shao-yen Tseng

Although capable of generating creative text, Large Language Models (LLMs) are poor judges of what constitutes "creativity". In this work, we show that we can leverage this knowledge of how to write creatively in order to better judge what is creative. We take a mechanistic approach that extracts differences in the internal states of an LLM when prompted to

S. Coriasco, L. Fatibene, S. Garruto, A. Orizzonte

We discuss the structure of covariant equations, relating analytical properties of solutions to algebraic properties of the corresponding differential operator, specifically of its principal symbol. The principal symbol and its globality is discussed for a general quasi-linear PDE system, regardless the algebraic structure the configuration space can have. W

Luigi Verdiani, Wolfgang Ziller

We study initial value problems for various geometric equations on a cohomogeneity manifold near a singular orbit. We show that when prescribing the Ricci curvature, or finding solutions to the Einstein and soliton equations, there exist solutions near the singular orbit, unique up to a finite number of constants. In part I we make a special assumption that

Michael Neubauer, Harmony Vargas

Let \(\mathcal{P}(n)\) be the set of partitions of the positive integer \(n\). For \(\alpha=(\alpha_1,...,\alpha_t) \in \mathcal{P}(n)\) define the diagonal sequence \(\delta(\alpha)=(d_k(\alpha))_{k \geq 1}\) via \( d_k(\alpha) = \big\lvert \{ i \, \rvert \, 1 \leq i \leq k \mbox{ and } \alpha_i + i- 1\geq k \} \big\rvert.\) We show that the set of all part

Tomer Jordi Chaffer, Justin Goldston, Gemach D. A. T. A.

Cooperation is vital to our survival and progress. Evolutionary game theory offers a lens to understand the structures and incentives that enable cooperation to be a successful strategy. As artificial intelligence agents become integral to human systems, the dynamics of cooperation take on unprecedented significance. The convergence of human-agent teaming, c

Rutwig Campoamor-Stursberg, Eduardo Fernandez-Saiz, Francisco J. Herranz

We revisit the nonlinear second-order differential equations $$ \ddot{x}(t)=a (x )\dot{x}(t)^2+b(t)\dot{x}(t) $$ where $a(x)$ and $b(t)$ are arbitrary functions on their argument from the perspective of Lie-Hamilton systems. For the particular choice $a(x)=3/x$ and $b(t)=1/t$, these equations reduce to the Buchdahl equation considered in the context of Gener

Sophie Hawkes, Christian Weinert, Teresa Almeida, Maryam Mehrnezhad

We show that perceptual hashing, crucial for detecting and removing image-based sexual abuse (IBSA) online, faces vulnerabilities from low-budget inversion attacks based on generative AI. This jeopardizes the privacy of users, especially vulnerable groups. We advocate to implement secure hash matching in IBSA removal tools to mitigate potentially fatal conse

Silvia Barbina, Enrique Casanovas

A free Steiner quasigroup is a free object in the variety of Steiner quasigroups. Free Steiner quasigroups are characterised by the existence of a levelled construction that starts with a free base - that is, a set of elements none of which is a product of the others, and which generate the quasigroup. Then each element in a free Steiner quasigroup $M$ can b

Manuel Sommer, Nora Fenske, Christian Heumann, Peter Scholz-Kreisel

Introduction Lifetime risks quantify health risks from radiation exposure and play an important role in radiation detriment and radon dose conversion. This study considers the lifetime risk of dying from lung cancer related to occupational radon exposure, focusing on lifetime excess absolute risk (LEAR), in addition to other lifetime risk measures. This arti

Sammy Florczak, Gabriel Groessbacher, Davide Ribezzi, Alessia Longoni

We introduce Generative, Adaptive, Context-Aware 3D Printing (GRACE), a novel approach combining 3D imaging, computer vision, and parametric modelling to create tailored, context-aware geometries using volumetric additive manufacturing. GRACE rapidly and automatically generates complex structures capable of conforming directly around features ranging from ce

A. Arhrib, S. Moretti, S. Semlali, C. H. Shepherd-Themistocleous

We study the discovery potential for a light Higgs boson via $gg \to H_{\text{SM-like}} \to hh \to b\bar{b}\gamma\gamma$ process at the Large Hadron Collider (LHC). Focusing on the 2-Higgs Doublet Model (2HDM) Type-I, which can accommodate light neutral Higgs states, of $\mathcal{O}(100)$ GeV or less in mass, while agreeing with theoretical and up-to-date ex

Elham Easy, Mengqi Fang, Mingxing Li, Eui-Hyeok Yang

Two-Dimensional (2D) transition metal dichalcogenides (TMDs) have been the subject of extensive attention thanks to their unique properties and atomically thin structure. Because of its unprecedented room-temperature magnetic properties, iron-doped MoS2 (Fe:MoS2) is considered the next-generation quantum and magnetic material. It is essential to understand F

Mohammed Sardar, Małgorzata J. Zimoń, Samuel Draycott, Alistair Revell

This article describes some common issues encountered in the use of Direct Numerical Simulation (DNS) turbulent flow data for machine learning. We focus on two specific issues; 1) the requirements for a fair validation set, and 2) the pitfalls in downsampling DNS data before training. We attempt to shed light on the impact these issues can have on machine le

Yujin Kang, Seunghyun Jeon, Junyong Shin, Yo-Seb Jeon

This paper addresses a data detection problem for multiple-input multiple-output (MIMO) communication systems with hardware impairments. To facilitate maximum likelihood (ML) data detection without knowledge of nonlinear and unknown hardware impairments, we develop novel likelihood function (LF) estimation methods based on data augmentation and boosting. The

Jun Liu, Mengqi Fang, Eui-Hyeok Yang, Xian Zhang

Two dimensional (2D) materials such as graphene and transition metal dichalcogenides (TMDC) have received extensive research interests and investigations in the past decade. In this research, we report the first experimental measurement of the in plane thermal conductivity of MoS2 monolayer under a large mechanical strain using optothermal Raman technique. T

Franz Baader, Jürgen Giesl

Motivated by an application where we try to make proofs for Description Logic inferences smaller by rewriting, we consider the following decision problem, which we call the small term reachability problem: given a term rewriting system $R$, a term $s$, and a natural number $n$, decide whether there is a term $t$ of size $\leq n$ reachable from $s$ using the

A. Shurgaia

Bogolyubov transformations are introduced into the nonrelativistic model of particle interaction with scalar mesons. Within the framework of the generalized Hamiltonian formalism developed by Dirac, a translation-invariant perturbation theory in inverse powers of the coupling constant is constructed. Transmission and reflection coefficients are obtained, the

Seyed Mohsen Hosseini, Mahdieh Soleymani Baghshah

A novel method for tackling the problem of imbalanced data in medical image segmentation is proposed in this work. In balanced cross entropy (CE) loss, which is a type of weighted CE loss, the weight assigned to each class is the in-verse of the class frequency. These balancing weights are expected to equalize the effect of each class on the overall loss and

Dhavalkumar Patel, Ganesh Raut, Satya Narayan Cheetirala, Girish N Nadkarni

Generative AI is transforming enterprise application development by enabling machines to create content, code, and designs. These models, however, demand substantial computational power and data management. Cloud computing addresses these needs by offering infrastructure to train, deploy, and scale generative AI models. This review examines cloud services fo

Jann Zosso

Guided by the Einstein equivalence principle that identifies the phenomenon of gravitation as a manifestation of the dynamics of spacetime in contrast to a localizable force, we review and explore its consequences on formulating a theory of gravity. The resulting space of metric theories of gravity may address open conceptual and observational puzzles throug

MD Rokibul Hasan

Organizations increasingly need to reassess their supply chain strategies in the rapidly modernizing world towards sustainability. This is particularly true in the United States, where supply chains are very extensive and consume a large number of resources. This research paper discusses how AI can support decision-making for sustainable supply chains with a

Mandev S. Gill, Guy Baele, Marc A. Suchard, Philippe Lemey

Scientific studies in many areas of biology routinely employ evolutionary analyses based on the probabilistic inference of phylogenetic trees from molecular sequence data. Evolutionary processes that act at the molecular level are highly variable, and properly accounting for heterogeneity in evolutionary processes is crucial for more accurate phylogenetic in

Neil He, Ming-Cheng Cheng, Yu Liu

The rising demand for high-performance computing (HPC) has made full-chip dynamic thermal simulation in many-core GPUs critical for optimizing performance and extending device lifespans. Proper orthogonal decomposition (POD) with Galerkin projection (GP) has shown to offer high accuracy and massive runtime improvements over direct numerical simulation (DNS).

Aikaterina Manoli, Janet V. T. Pauketat, Jacy Reese Anthis

Robots and other artificial intelligence (AI) systems are widely perceived as moral agents responsible for their actions. As AI proliferates, these perceptions may become entangled via the moral spillover of attitudes towards one AI to attitudes towards other AIs. We tested how the seemingly harmful and immoral actions of an AI or human agent spill over to a

Fabian Garmroudi, Michael Parzer, Takao Mori, Andrej Pustogow

Heusler compounds with six valence electrons per atom have attracted interest as thermoelectric materials owing to their semimetallic and semiconducting properties. Here, we theoretically and experimentally investigate electronic transport in Ru$_2$TiSi-based full-Heuslers. We show that electronic transport in this system can be well captured by a two-parabo

Joohyuk Park, Yongjeong Oh, Yongjune Kim, Yo-Seb Jeon

Semantic communications provide significant performance gains over traditional communications by transmitting task-relevant semantic features through wireless channels. However, most existing studies rely on end-to-end (E2E) training of neural-type encoders and decoders to ensure effective transmission of these semantic features. To enable semantic communica

Jakub Bielawski, Łukasz Cholewa, Fryderyk Falniowski

Precise description of population game dynamics introduced by revision protocols - an economic model describing the agent's propensity to switch to a better-performing strategy - is of importance in economics and social sciences in general. In this setting innovation or imitation of others is the force which drives the evolution of the economic system. As th

Jeong-Eun Heo, Miji Jeong

We report the detection of Raman-scattered C II lines at 7023 and 7054\r{A} in the symbiotic star V366 Carinae using GHOST at Gemini South. These faint features, originating from the C II doublet at ${\lambda}{\lambda}$ 1036 and 1037\r{A}, are rare and have been detected in only two other symbiotic stars: V1016 Cygni and RR Telescopii. Our findings showcase

Ehsan Nasiri, Long Wang

This paper addresses the challenge of teleoperating continuum instruments for minimally invasive surgery (MIS). We develop and adopt a novel task-priority-based kinematic formulation to quantitatively investigate teleoperation commands for continuum instruments under remote center of motion (RCM) constraints. Using redundancy resolution methods, we investiga

Léo Jimenez

In a recent article, Freitag, Moosa and the author showed that in differentially closed fields of characteristic zero, if two types are nonorthogonal, then their n+3 and m+3 Morley powers are not weakly orthogonal, where n and m are their respective Lascar ranks. In this short note, we prove that the bound is tight: there are such types with weakly orthogona

O. Pavón-Torres, J. R. Collantes-Collantes, M. A. Agüero-Granados

Nonlinear molecular excitations in DNA have traditionally been modelled using the nonlinear Schr\"odinger equation (NLSE). An alternative approach is based on the plane-base rotator model and the SU(2)/U(1) generalized spin coherent states, which leads to a cubic quintic NLSE. Higher-order nonlinearities are particularly useful for modelling complex interact

Andrew Jesson, Nicolas Beltran-Velez, David Blei

This work is about estimating when a conditional generative model (CGM) can solve an in-context learning (ICL) problem. An in-context learning (ICL) problem comprises a CGM, a dataset, and a prediction task. The CGM could be a multi-modal foundation model; the dataset, a collection of patient histories, test results, and recorded diagnoses; and the predictio

Aref Ayati, Mohammad Mahdi Hashemi, Mohsen Saffar, Hamid Reza Naji

Regarding the concepts of urban management, digital transformation, and smart cities, various issues are presented. Currently, we like to attend to location allocation problems that can be a new part of digital transformation in urban management (such as locating and placing facilities, locating and arranging centers such as aid and rescue centers, or even p

Tattwamasi Amrutam, David Gao, Srivatsav Kunnawalkam Elayavalli, Gregory Patchell

We prove that for every $n\geq 2$, the reduced group $C^*$-algebras of the countable free groups $C^*_r(\mathbb{F}_n)$ have strict comparison. Our method works in a general setting: for $G$ in a large family of non-amenable groups, including hyperbolic groups, free products, mapping class groups, right-angled Artin groups etc., we have $C^*_r(G)$ have strict

Alexander Neef, Sebastian Hammer, Yuxuan Yao, Shubham Sharma

Charge transport in organic semiconductors is limited by dynamical disorder. Design rules for new high-mobility materials have therefore focused on limiting its two foundations: structural fluctuations and the transfer integral gradient. However, it has remained unclear how these goals should be translated into molecular structures. Here we show that a speci

Zhenghong Zhou, Jie An, Jiebo Luo

Precise camera pose control is crucial for video generation with diffusion models. Existing methods require fine-tuning with additional datasets containing paired videos and camera pose annotations, which are both data-intensive and computationally costly, and can disrupt the pre-trained model distribution. We introduce Latent-Reframe, which enables camera c

Shuning Chang, Pichao Wang, Jiasheng Tang, Fan Wang

Diffusion Transformers (DiT) are renowned for their impressive generative performance; however, they are significantly constrained by considerable computational costs due to the quadratic complexity in self-attention and the extensive sampling steps required. While advancements have been made in expediting the sampling process, the underlying architectural i

Georgios Karakatsoulis

The Mixture Cure (MC) models constitute an appropriate and easily interpretable method when studying a time-to-event variable in a population comprised of both susceptible and cured individuals. In literature, those models usually assume that the latter are unobservable. However, there are cases in which a cured individual may be identified. For example, whe

Mojtaba Eshghie, Gustav Andersson Kasche

In this paper, we introduce the Sarv, a novel non-monolithic blockchain-based data structure designed to represent hierarchical relationships between digitally representable components. Sarv serves as an underlying infrastructure for a wide range of applications requiring hierarchical data management, such as supply chain tracking, asset management, and circ

K. Raya, A. Bashir, J. Rodríguez-Quintero

Several aspects of the internal structure of pseudoscalar mesons, accessible through generalized parton distributions in their zero-skewness limit, are examined. These include electromagnetic and gravitational form factors related to charge and mass densities; and distributions in the impact parameter space. To this end, we employ an algebraically viable fra

Asaad Daher, Leonardo Tinti, Amaresh Jaiswal, Radoslaw Ryblewski

We extend the derivation of second-order relativistic viscous hydrodynamics to incorporate the effects of baryon current, a non-vanishing chemical potential, and a realistic equation of state. Starting from a microscopic quantum theory, we employ a quasiparticle approximation to describe the evolution of hydrodynamic degrees of freedom and establish its conn

Victor Charpentier, Ignacio Andrade-Silva, Trevor J. Jones, Tom Marzin

Deployable structures, essential across various engineering applications ranging from umbrellas to satellites, are evolving to include soft, morphable designs where geometry drives transformation. However, a major challenge for soft materials lies in achieving reliable actuation and stable shape retention in their deployed state. Drawing inspiration from bio

Juan A. Delgado-Notario, David López-Díaz, David McCloskey, José M. Caridad

We study the photothermal conversion in plasmonic nanohelices, unveiling how helical nanostructures made from metals with a notable interband activity, such as cobalt (Co) and nickel (Ni), exhibit a remarkable temperature rise $\Delta$T up to $\approx$1000 K under illumination. Such outstanding $\Delta$T values exclusively occur at wavelengths close to their

Yuchen Wan, Zaile Li, L. Jeff Hong

Robust ranking and selection (R&S) is an important and challenging variation of conventional R&S that seeks to select the best alternative among a finite set of alternatives. It captures the common input uncertainty in the simulation model by using an ambiguity set to include multiple possible input distributions and shifts to select the best alternative wit

Dan Maoz

Using the Zwicky Transient Facility (ZTF), Burdge et al. (2020) discovered systems of eclipsing double white dwarfs (EDWDs) having orbital periods <1 hr. From the properties of 3 of the discovered systems, I estimate a merger rate of DWDs, per WD in the Galaxy, of $R_{\rm merge, WD}\approx8\times 10^{-12}$yr$^{-1}$, or a rate per unit stellar mass in the Gal

Akshat Choube, Rahul Majethia, Sohini Bhattacharya, Vedant Das Swain

Longitudinal passive sensing studies for health and behavior outcomes often have missing and incomplete data. Handling missing data effectively is thus a critical data processing and modeling step. Our formative interviews with researchers working in longitudinal health and behavior passive sensing revealed a recurring theme: most researchers consider imputa

Eda Alici

Flavour-changing neutral current (FCNC) interactions between the Higgs boson and the top quark are subject to significant suppression within the Standard Model (SM). Consequently, these interactions can only attain an observable level through the influence of Beyond the Standard Model (BSM) physics effects. It is therefore of great importance to investigate

Hyeonho Jeong, Chun-Hao Paul Huang, Jong Chul Ye, Niloy Mitra

While recent foundational video generators produce visually rich output, they still struggle with appearance drift, where objects gradually degrade or change inconsistently across frames, breaking visual coherence. We hypothesize that this is because there is no explicit supervision in terms of spatial tracking at the feature level. We propose Track4Gen, a s

Christie Djidjev

As cyber threats continue to evolve in sophistication and scale, the ability to detect anomalous network behavior has become critical for maintaining robust cybersecurity defenses. Modern cybersecurity systems face the overwhelming challenge of analyzing billions of daily network interactions to identify potential threats, making efficient and accurate anoma

Anton Baumann, Rui Li, Marcus Klasson, Santeri Mentu

Vision-language models (VLMs), such as CLIP and SigLIP, have found remarkable success in classification, retrieval, and generative tasks. For this, VLMs deterministically map images and text descriptions to a joint latent space in which their similarity is assessed using the cosine similarity. However, a deterministic mapping of inputs fails to capture uncer

V. A. Baturin, S. V. Ayukov, A. V. Oreshina, A. B. Gorshkov

Hydrogen is the main chemical component of the solar plasma, and H-ionization determines basic properties of the first adiabatic exponent $\Gamma_1$. Hydrogen ionization remarkably differs from the ionization of other chemicals. Due to the large number concentration, H-ionization causes a very deep lowering of $\Gamma_1$, and the lowering profile appears to

Silas Ruhrberg Estévez, Alex Grafton, Lynn Thomson, Joana Warnecke

Neonates in intensive care require continuous monitoring. Current measurement devices are limited for long-term use due to the fragility of newborn skin and the interference of wires with medical care and parental interactions. Camera-based vital sign monitoring has the potential to address these limitations and has become of considerable interest in recent

Meilong Xu, Saumya Gupta, Xiaoling Hu, Chen Li

Accurately modeling multi-class cell topology is crucial in digital pathology, as it provides critical insights into tissue structure and pathology. The synthetic generation of cell topology enables realistic simulations of complex tissue environments, enhances downstream tasks by augmenting training data, aligns more closely with pathologists' domain knowle

Zifan Lin, Sara Seager, Benjamin P. Weiss

The interior composition and structure of Uranus are ambiguous. It is unclear whether Uranus is composed of fully differentiated layers dominated by an icy mantle or has smooth compositional gradients. The Uranus Orbiter and Probe (UOP), the next NASA Flagship mission prioritized by the Planetary Science and Astrobiology Survey 2023-2032, will constrain the

Jebish Purbey, Drishti Sharma, Siddhant Gupta, Khawaja Murad

This paper presents the system description of our entry for the COLING 2025 RegNLP RIRAG (Regulatory Information Retrieval and Answer Generation) challenge, focusing on leveraging advanced information retrieval and answer generation techniques in regulatory domains. We experimented with a combination of embedding models, including Stella, BGE, CDE, and Mpnet

Balázs Bárány, Michał Rams

In this paper, we study the smoothness of the density function of absolutely continuous measures supported on random self-similar sets on the line. We show that the natural projection of a measure with symbolic local dimension greater than 1 at every point is absolutely continuous with H\"older continuous density almost surely. In particular, if the similari

Yinqiu Liu, Guangyuan Liu, Ruichen Zhang, Dusit Niyato

Large Language Models (LLMs) have significantly advanced communications fields, such as Telecom Q\&A, mathematical modeling, and coding. However, LLMs encounter an inherent issue known as hallucination, i.e., generating fact-conflicting or irrelevant content. This problem critically undermines the applicability of LLMs in communication systems yet has not be

Alfonso Annarelli, Dario Alfè, Andrea Zen

Quantum Monte Carlo (QMC) methods represent a powerful family of computational techniques for tackling complex quantum many-body problems and performing calculations of stationary state properties. QMC is among the most accurate and powerful approaches to the study of electronic structure, but its application is often hindered by a steep learning curve, henc

Rolf Schneider

The Gauss image problem for convex bodies asks for the existence of a convex body that "links" two given measures on the unit sphere in a certain way. We treat here a corresponding question for pseudo-cones, that is, for unbounded closed convex sets strictly contained in their recession cones.

Martina Favero, Jere Koskela

The coalescent is a foundational model of latent genealogical trees under neutral evolution, but suffers from intractable sampling probabilities. Methods for approximating these sampling probabilities either introduce bias or fail to scale to large sample sizes. We show that a class of cost functionals of the coalescent with recurrent mutation and a finite n

Aymen Sekhri, Seyed Ali Amirshahi, Mohamed-Chaker Larabi

Augmented Reality (AR) is a major immersive media technology that enriches our perception of reality by overlaying digital content (the foreground) onto physical environments (the background). It has far-reaching applications, from entertainment and gaming to education, healthcare, and industrial training. Nevertheless, challenges such as visual confusion an

Xavier Bekaert, Laura Donnay, Yannick Herfray

We construct wavefunctions for unitary irreducible representations (UIRs) of the Bondi-Metzner-Sachs (BMS) group, i.e. BMS particles, and show that they describe quantum superpositions of (Poincar\'e) particles propagating on inequivalent gravity vacua. This follows from reconsidering McCarthy's classification of BMS group UIRs through a unique, Lorentz-inva

Yupei Li, Hanqian Li, Lucia Specia, Björn W. Schuller

Machine-generated music (MGM) has emerged as a powerful tool with applications in music therapy, personalised editing, and creative inspiration for the music community. However, its unregulated use threatens the entertainment, education, and arts sectors by diminishing the value of high-quality human compositions. Detecting machine-generated music (MGMD) is,

Zhenyu Hou, Pengfan Du, Yilin Niu, Zhengxiao Du

This study explores the scaling properties of Reinforcement Learning from Human Feedback (RLHF) in Large Language Models (LLMs). Although RLHF is considered an important step in post-training of LLMs, its scaling potential is still largely unknown. We systematically analyze key components in the RLHF framework--model size, data composition, and inference bud

Jiahe Shen, Roger Van Peski

We compute the joint distribution of singular numbers for all principal corners of a $p$-adic Hermitian (resp. alternating) matrix with additive Haar distribution, the non-archimedean analogue of the GUE (resp. aGUE) corners process. In the alternating case we find that it is a Hall-Littlewood process, explaining -- and recovering as a corollary -- results o

Vittorio D'Esposito, Giuseppe Fabiano, Domenico Frattulillo, Flavio Mercati

Motivated by the expectation that relativistic symmetries might acquire quantum features in Quantum Gravity, we take the first steps towards a theory of ''Doubly'' Quantum Mechanics, a modification of Quantum Mechanics in which the geometrical configurations of physical systems, measurement apparata, and reference frame transformations are themselves quantiz

Bimarsha Khanal, Paras Poudel, Anish Chapagai, Bijan Regmi

Plant diseases significantly impact our food supply, causing problems for farmers, economies reliant on agriculture, and global food security. Accurate and timely plant disease diagnosis is crucial for effective treatment and minimizing yield losses. Despite advancements in agricultural technology, a precise and early diagnosis remains a challenge, especiall

Alexandre Eremenko, Sergei Merenkov

We study Carath\'eodory convergence for open, simply connected surfaces spread over the sphere and, in particular, provide examples demonstrating that in the Speiser class the conformal type can change when two singular values collide.

Namgyu Kang, Jaemin Oh, Youngjoon Hong, Eunbyung Park

The numerical approximation of partial differential equations (PDEs) using neural networks has seen significant advancements through Physics-Informed Neural Networks (PINNs). Despite their straightforward optimization framework and flexibility in implementing various PDEs, PINNs often suffer from limited accuracy due to the spectral bias of Multi-Layer Perce

Quang-Trung Luu, Minh-Thanh Nguyen, Tuan-Anh Do, Michel Kieffer

Network slicing is a critical feature in 5G and beyond communication systems, enabling the creation of multiple virtual networks (i.e., slices) on a shared physical network infrastructure. This involves efficiently mapping each slice component, including virtual network functions (VNFs) and their interconnections (virtual links), onto the physical network. T

S. A. Belov, T. Goffrey, T. D. Arber, D. Y. Kolotkov

Context. Observations of slow magnetoacoustic waves in solar coronal loops suggest that, in hot coronal plasma, heat conduction may be suppressed in comparison with the classical thermal transport model. Aims. We link this suppression with the effect of the non-local thermal transport that appears when the plasma temperature perturbation gradient becomes com

A. Sowa, J. Fransson

A regular coherent state (CS) is a special type of quantum state for boson particles placed in a single site. The defining feature of the CS is that it is an eigenmode of the annihilation operator. The construction easily generalizes to the case of a finite number of sites. However, the challenge is altogether different when one considers an infinite array o

Abbé M. Whitford, Hugo Rivera-Morales, Cullan Howlett, Mariana Vargas-Magaña

In the early Universe, neutrinos decouple quickly from the primordial plasma and propagate without further interactions. The impact of free-streaming neutrinos is to create a temporal shift in the gravitational potential that impacts the acoustic waves known as baryon acoustic oscillations (BAOs), resulting in a non-linear spatial shift in the Fourier-space

Shuang-Yi Li, Jie Xu, Rui-Xiang Shi, Li-Sheng Geng

Inspired by the newly reported $B\to D^*(\to D\pi)\ell\bar{\nu}_\ell$ differential decay rates by the Belle and Belle II Collaborations, we revisit the $V_{cb}$ puzzle in semi-leptonic $B\to D^*$ decays, considering the latest lattice QCD~(LQCD) simulations and light-cone sum rule~(LCSR) results. We examine the commonly used Caprini-Lellouch-Neubert~(CLN), B

Michael Poon, Hanno Rein, Dang Pham

Planet obliquity is the alignment or misalignment of a planet spin axis relative to its orbit normal. In a multiplanet system, this obliquity is a valuable signature of planet formation and evolutionary history. The young $\beta$ Pictoris system hosts two coplanar super-Jupiters and upcoming JWST observations of this system will constrain the obliquity of th

Yan Cui, Bo Xia

In the present paper, we show that the global solution to (partially) damped Klein-Gordon equation on the three dimensional Euclidean space with small data decays exponentially. The key ingredients in the proof are: Morawetz-type estimates for solutions with small data and Ruiz's unique continuation principle for wave equations.

Alessandro Passantino

We show that the set of Hilbert functions $P(m)=\chi(mK_\mathcal{F})$ of 2-dimensional foliated canonical models with fixed $K_\mathcal{F}^2$, $K_\mathcal{F} \cdot K_X$ and $i_\mathbb{Q}(\mathcal{F})$ is finite. As a consequence, we deduce that two results on the effective birationality and boundedness of foliated canonical models with fixed Hilbert function

Patrick Salfeld, Rebecca Waldecker

In previous work, all finite simple groups that act with fixity 4 have been classified. In this article we investigate which ones of these groups act faithfully on a compact Riemann surface of genus at least 2 with fixity four in total and in such a way that fixity 4 is exhibited on at least one orbit. This is an extended version of the submitted article, in

Xiao Zhang, Ruoxi Jiang, Rebecca Willett, Michael Maire

We introduce nested diffusion models, an efficient and powerful hierarchical generative framework that substantially enhances the generation quality of diffusion models, particularly for images of complex scenes. Our approach employs a series of diffusion models to progressively generate latent variables at different semantic levels. Each model in this serie

Tianshuo Peng, Mingsheng Li, Jiakang Yuan, Hongbin Zhou

Recent advancements in Large Multi-modal Models (LMMs) underscore the importance of scaling by increasing image-text paired data, achieving impressive performance on general tasks. Despite their effectiveness in broad applications, generalist models are primarily trained on web-scale datasets dominated by natural images, resulting in the sacrifice of special

Zhi-Fu Gao, Luiz C. Garcia de Andrade

In the Standard Model\,(SM) of particle physics, photon-torsion mixing is extended to include the Einstein-Cartan portal to dark-photon-axion-torsion mixing beyond the Standard Model\,(BSM), mediated by torsion. The Barbero-Immirzi(BI) parameter, of the order of $10^{-31}$, is more stringent than those obtained by Aliberti and Lambiase using matter-antimatte

Aleksandr S. Petrov, Dmitry Svintsov

Thermoelectric effects in $p-n$ junctions are widely used for energy generation with thermal gradients, creation of compact Peltier refrigerators and, most recently, for sensitive detection of infrared and terahertz radiation. It is conventionally assumed that electrons and holes creating thermoelectric current are in equilibrium and share the common quasi-F

Yiren Song, Shengtao Lou, Xiaokang Liu, Hai Ci

Diffusion models have revolutionized generative modeling with their exceptional ability to produce high-fidelity images. However, misuse of such potent tools can lead to the creation of fake news or disturbing content targeting individuals, resulting in significant social harm. In this paper, we introduce Anti-Reference, a novel method that protects images f

Arash E. Zaghi

Quantum mechanics has transformed our understanding of reality, yet deep philosophical puzzles remain unresolved. Is there a consistent way to describe quantum measurement, the emergence of space and time, and the role of observers within one coherent ontology? This paper introduces Relational Quantum Dynamics (RQD), an interpretation that places relationshi

Vincil Bishop, Steven Simske

The paper presents a systematic methodology for analyzing software developer productivity by refining contribution rate metrics to distinguish meaningful development efforts from anomalies. Using the Mean-High Model Contribution Rate (mhMCR) method, the research introduces a statistical framework that focuses on continuous contributions, mitigating distortio

Stepan Margaryan

We will study some important properties of Boolean functions based on newly introduced concepts called Special Decomposition of a Set and Special Covering of a Set. These concepts enable us to study important problems concerning Boolean functions represented in conjunctive normal form including the satisfiability problem. Studying the relationship between th

Dmitry A. Mylnikov, Mikhail A. Kashchenko, Ilya V. Safonov, Kostya S. Novoselov

Mid-infrared (mid-IR) photodetectors play a crucial role in various applications, including the development of biomimetic vision systems that emulate neuronal function. However, current mid-IR photodetector technologies are limited by their cost and efficiency. In this work, we demonstrate a new type of photodetector based on a tunnel structure made of two-d

Roberta Favata, Davide Piccioni, Alberto Parola, Federico Becca

We explore the ground-state properties of a one-dimensional model with two orbitals per site, where, in addition to atomic energies $\pm M$, intra- and inter-orbital hoppings, the intra-orbital Hubbard ($U$) and nearest-neighbor density-density ($V$) repulsions are included. Our results are primarily based on a Jastrow-Slater wave function and variational Mo

Weijie Sun, Mitsuo Oka, Marit Øieroset, Drew L. Turner

Electrons are accelerated to high, non-thermal energies during explosive energy-release events in space, such as magnetic reconnection. However, the properties and acceleration mechanisms of relativistic electrons directly associated with reconnection X-line are not well understood. This study utilizes Magnetospheric Multiscale (MMS) measurements to analyze

Boquan Fan, Yuchen Wang, Weicheng Zhan

We study the radial symmetry properties of stationary and uniformly rotating solutions of the 2D Euler equation in the unit disc, both in the smooth setting and the patch setting. In the patch setting, we prove that every uniformly rotating patch with angular velocity $\Omega\le 0$ or $\Omega \ge 1/2$ must be radial, where both bounds are sharp. The conclusi

Mithun Pal, Alexander Eber, Lukas Fürst, Emily Hruska

Sustained mutual coherence between two combs over extended periods is a prerequisite for dual-comb spectroscopy (DCS), particularly in achieving high-resolution molecular spectroscopy and precise spectral measurements. However, achieving long coherence times remains a challenge for Yb-doped frequency combs. This work introduces an experimental approach for p

Emin Aliyev, Arash Mobaraki, Hâldun Sevinçli, Seymur Jahangirov

Owing to the promising optoelectronic and thermoelectric properties of two-dimensional (2D) group III-VI materials (MXs), their nanoribbons (NRs) have attracted notable attention as an emerging class of quasi-one-dimensional (quasi-1D) nanostructures. Due to the fact that the most stable 2D monolayer polymorph of MXs is the 1H phase, to date, existing studie

Wei Sun, Wenxuan Wang, Changhong Yang, Ying Liu

Multiferroic materials, characterized by the coexisting of ferroelectric polarization (breaking spatial inversion symmetry) and magnetism (breaking time-reversal symmetry), with strong magnetoelectric coupling, are highly sought after for advanced technological applications. Novel altermagnets, distinct from conventional magnets, have recently been revealed

Yilie Huang, Yanwei Jia, Xun Yu Zhou

We study continuous-time mean--variance portfolio selection in markets where stock prices are diffusion processes driven by observable factors that are also diffusion processes, yet the coefficients of these processes are unknown. Based on the recently developed reinforcement learning (RL) theory for diffusion processes, we present a general data-driven RL a

Zipeng Qi, Hao Chen, Haotian Zhang, Zhengxia Zou

In this paper, we propose a novel semantic splatting approach based on Gaussian Splatting to achieve efficient and low-latency. Our method projects the RGB attributes and semantic features of point clouds onto the image plane, simultaneously rendering RGB images and semantic segmentation results. Leveraging the explicit structure of point clouds and a one-ti

Mehwish Mehmood, Shahzaib Iqbal, Tariq Mahmood Khan, Ivor Spence

The analysis of retinal images for the diagnosis of various diseases is one of the emerging areas of research. Recently, the research direction has been inclined towards investigating several changes in retinal blood vessels in subjects with many neurological disorders, including dementia. This research focuses on detecting diseases early by improving the pe

Damien de Mijolla, Wen Yang, Philippa Duckett, Christopher Frye

Prompting and fine-tuning have emerged as two competing paradigms for augmenting language models with new capabilities, such as the use of tools. Prompting approaches are quick to set up but rely on providing explicit demonstrations of each tool's usage in the model's prompt, thus coupling tool use to the task at hand and limiting generalisation. Fine-tuning