November 2024 arXiv papers — page 5

Apurba Saha, Iftekhar Hakim Kaowsar, Mahdi Hasnat Siyam, M. Sohel Rahman

Two strings are considered to have parameterized matching when there exists a bijection of the parameterized alphabet onto itself such that it transforms one string to another. Parameterized matching has application in software duplication detection, image processing, and computational biology. We consider the problem for which a pattern $p$, a text $t$ and

Ikjun Hong, Chuchuan Hong, Theodore Anyika, Guodong Zhu

Achieving high-throughput, comprehensive analysis of single nanoparticles to determine their size, shape, and composition is essential for understanding particle heterogeneity with applications ranging from drug delivery to environmental monitoring. Existing techniques are hindered by low throughput, lengthy trapping times, irreversible particle adsorption,

Ying Li, Roger D. Johnson, Yogesh Singh, Radu Coldea

Through a combination of crystal symmetry analysis and density functional theory calculations we unveil a possible microscopic origin of the unexpected insulating behavior reported in the honeycomb Kitaev material Cu$_2$IrO$_3$. Our study suggests that this material hosts an instability towards charge ordering of the Ir ions, with alternating magnetic Ir$^{4

Stefan Franssen, Jeanne Nguyen, Aad van der Vaart

Semiparametric mixture models are parametric models with latent variables. They are defined kernel, $p_\theta(x | z)$, where z is the unknown latent variable, and $\theta$ is the parameter of interest. We assume that the latent variables are an i.i.d. sample from some mixing distribution $F$. A Bayesian would put a prior on the pair $(\theta, F)$. We prove c

Ivory Yang, Weicheng Ma, Soroush Vosoughi

The preservation and revitalization of endangered and extinct languages is a meaningful endeavor, conserving cultural heritage while enriching fields like linguistics and anthropology. However, these languages are typically low-resource, making their reconstruction labor-intensive and costly. This challenge is exemplified by Nushu, a rare script historically

Valerio Busillo, Crescenzo Tortora, Giovanni Covone, Leon V. E. Koopmans

Physical processes impact galaxy formation and evolution in diverse ways, requiring validation of their implementation in cosmological simulations through comparisons with real data across various galaxy types and properties. In this second paper of the CASCO series, we compare the structural properties and dark matter (DM) content of early-type galaxies fro

Md. Fahim Sultan, Tasmin Karim, Md. Shazzad Hossain Shaon, Mohammad Wardat

Software security is crucial in any field where breaches can exploit sensitive data, and lead to financial losses. As a result, vulnerability detection becomes an essential part of the software development process. One of the key steps in maintaining software integrity is identifying vulnerabilities in the source code before deployment. A security breach lik

Nitish Vikas Deshpande, Joseph Carlson, Miguel R. Castellanos, Robert W. Heath

Dynamic metasurface antennas (DMAs) beamform through low-powered components that enable reconfiguration of each radiating element. Previous research on a single-user multiple-input-single-output (MISO) system with a dynamic metasurface antenna at the transmitter has focused on maximizing the beamforming gain at a fixed operating frequency. The DMA, however,

Luca Collini, Siddharth Garg, Ramesh Karri

High-Level Synthesis (HLS) tools offer rapid hardware design from C code, but their compatibility is limited by code constructs. This paper investigates Large Language Models (LLMs) for automatically refactoring C code into HLS-compatible formats. We present a case study using an LLM to rewrite C code for NIST 800-22 randomness tests, a QuickSort algorithm,

Sumit Rout, Some Sankar Bhattacharya, Paweł Horodecki

Non-projective measurements play a crucial role in various information-processing protocols. In this work, we propose an operational task to identify measurements that are neither projective nor classical post-processing of data obtained from projective measurements. Our setup involves space-like separated parties with access to a shared state with bounded l

Jeffrey Gao, Paul C. Kainen

A permutation of the elements of a graph is a {\it construction sequence} if no edge is listed before either of its endpoints. The complexity of such a sequence is investigated by finding the delay in placing the edges, an {\it opportunity cost} for the construction sequence. Maximum and minimum cost c-sequences are provided for a variety of graphs and are u

Zixing Wang, Yi Zhang, Fulvio Forni

We tackle the problem of providing closed-loop stability guarantees with a scalable data-driven design. We combine virtual reference feedback tuning with dissipativity constraints on the controller for closed-loop stability. The constraints are formulated as a set of linear inequalities in the frequency domain. This leads to a convex problem that is scalable

Eduardo E. Quadros, Paulo J. Liebgott

In this work we establish every spherically symmetric non-Abelian Z(2) monopole generated by su(2) embeddings in the SU(4) Yang-Mills-Higgs model minimally broken to SO(4) by a symmetric second-rank tensor Higgs field. We find new monopole solutions associated with index 4 and index 10 embeddings. These solutions belong to su(2) multiplets that are higher di

Md Bokhtiar Al Zami, Shaba Shaon, Vu Khanh Quy, Dinh C. Nguyen

Industrial networks are undergoing rapid transformation driven by the convergence of emerging technologies that are revolutionizing conventional workflows, enhancing operational efficiency, and fundamentally redefining the industrial landscape across diverse sectors. Amidst this revolution, Digital Twin (DT) emerges as a transformative innovation that seamle

Xinmeng Hou, Lingyue Fu, Chenhao Meng, Kounianhua Du

Aspect-Opinion Pair Extraction (AOPE) and Aspect Sentiment Triplet Extraction (ASTE) have drawn growing attention in NLP. However, most existing approaches extract aspects and opinions independently, optionally adding pairwise relations, often leading to error propagation and high time complexity. To address these challenges and being inspired by transition-

Huiqi Zou, Pengda Wang, Zihan Yan, Tianjun Sun

A chatbot's personality design is key to interaction quality. As chatbots evolved from rule-based systems to those powered by large language models (LLMs), evaluating the effectiveness of their personality design has become increasingly complex, particularly due to the open-ended nature of interactions. A recent and widely adopted method for assessing the pe

Bartosz Sawicki, Michał Śmiałek, Bartłomiej Skowron

This article explores the evolving role of programming languages in the context of artificial intelligence. It highlights the need for programming languages to ensure human understanding while eliminating unnecessary implementation details and suggests that future programs should be designed to recognize and actively support user interests. The vision includ

Michele De Vita, Vasileios Belagiannis

Despite the remarkable progress in generative modelling, current diffusion models lack a quantitative approach to assess image quality. To address this limitation, we propose to estimate the pixel-wise aleatoric uncertainty during the sampling phase of diffusion models and utilise the uncertainty to improve the sample generation quality. The uncertainty is c

Dan Hu, Norbert Werner, Haiguang Xu, Qian Zheng

Context: The clusters Abell 3017 and Abell 3016 are located within a large-scale filament. A prominent X-ray bridge has been detected connecting the two clusters and a potential galaxy group between them. Aims: The aim of this work is to investigate the existence of a radio bridge in the filament between Abell 3017 and Abell 3016, to explore other diffuse ra

Mikhail A. Skvortsov, Oleg B. Zuev, Dina I. Fazlizhanova

We study how the supercurrent flow pattern is altered by inhomogeneities in superconducting films. Working in the vicinity of the critical temperature and assuming a model of short-range disorder in the quadratic term of the Ginzburg-Landau functional, we develop a perturbation theory in the inhomogeneity strength. Absorbing the ultraviolet divergences into

João Ferri, Ian L. Tashiro, L. Raul Abramo, Isabela Matos

Observations of gravitational waves (GWs) from dark sirens allow us to infer their locations and distances. Galaxies, on the other hand, have precise angular positions but no direct measurement of their distances -- only redshifts. The cross-correlation of GWs, which we limit here to binary black hole mergers (BBH), in spherical shells of luminosity distance

Tamojeet Roychowdhury, Thushara G. S. Pillai, Claudia Vilega-Rodrigues, Jens Kauffmann

Bok globules are small, dense clouds that act as isolated precursors for the formation of single or binary stars. Although recent dust polarization surveys, primarily with Planck, have shown that molecular clouds are strongly magnetized, the significance of magnetic fields in Bok globules has largely been limited to individual case studies, lacking a broader

Andrea Bulgarelli, Elia Cellini, Alessandro Nada

Non-equilibrium Markov Chain Monte Carlo (NE-MCMC) simulations provide a well-understood framework based on Jarzynski's equality to sample from a target probability distribution. By driving a base probability distribution out of equilibrium, observables are computed without the need to thermalize. If the base distribution is characterized by mild autocorrela

Zong-En Chen, Cheng-Wei Chiang, Feng-Yang Hsieh

Weak supervision combines the advantages of training on real data with the ability to exploit signal properties. However, training a neural network using weak supervision often requires an excessive amount of signal data, which severely limits its practical applicability. In this study, we propose addressing this limitation through data augmentation, increas

Jorge Miguel-Ramiro, Wolfgang Dür

Graph states are a fundamental entanglement resource for multipartite quantum applications which are in general challenging to transform efficiently. While fusion operations for merging entangled states are well-developed, no direct protocol exists for the reverse process, which we term fission. We introduce a simple, yet powerful, protocol that achieves thi

Xiyuan Gao

We explore spontaneous CP violation (SCPV) in the minimal non-supersymmetric SO(10) grand unified theory (GUT), with a scalar sector comprising a CP-even $45_H$, a $126_H$, and a complex $10_H$. All renormalizable couplings are real due to CP symmetry, and the Kobayashi-Maskawa phase arises solely from complex electroweak vacuum expectation values. The model

Arthur Alencastro Puls, Jan Kuske, Camilla Juul Hansen, Linda Lombardo

The third r-process peak (Os, Ir, Pt) is poorly understood due to observational challenges, with spectral lines located in the blue or near-ultraviolet region of stellar spectra. These challenges need to be overcome for a better understanding of the r-process in a broader context. To understand how the abundances of the third r-process peak are synthesised a

Pradip Kattel, Parameshwar R. Pasnoori, J. H. Pixley, Natan Andrei

We present a comprehensive analysis of boundary phenomena in a spin-$\frac{1}{2}$ anisotropic Heisenberg chain (XXZ-$\frac{1}{2}$) in the gapped antiferromagnetic phase, with a particular focus on the interplay between fractionalized spin-$\frac{1}{4} $ edge modes and a coupled spin-$\frac{1}{2}$ impurity at the edge. Employing a combination of Bethe Ansatz,

Amir-Reza Negari, Tyler D. Ellison, Timothy H. Hsieh

We establish a correspondence between the fault-tolerance of local stabilizer codes experiencing measurement and physical errors and the mixed-state phases of decohered resource states in one higher dimension. Drawing from recent developments in mixed-state phases of matter, this motivates a diagnostic of fault-tolerance, which we refer to as the spacetime M

Luis Alberto León Andonayre, Rahul Poddar

We introduce a nonperturbative approach to calculate the R\'enyi entropy of a single interval on the torus for single-character (meromorphic) conformal field theories. Our prescription uses the Wro\'nskian method of Mathur, Mukhi, and Sen [Nucl. Phys. B312, 15 (1989)], in which we construct differential equations for torus conformal blocks of the twist two-p

Euclid Collaboration, A. Ragagnin, A. Saro, S. Andreon

Cluster cosmology can benefit from combining multi-wavelength studies, which can benefit from characterising the correlation coefficients between different mass-observable relations. In this work, we aim to provide information on the scatter, the skewness, and the covariance of various mass-observable relations in galaxy clusters in cosmological hydrodynamic

Martin Hoferichter, Peter Stoffer, Maximilian Zillinger

Hadronic light-by-light (HLbL) scattering defines one of the critical contributions in the Standard-Model prediction of the anomalous magnetic moment of the muon. In this Letter, we present a complete evaluation using a dispersive formalism, in which the HLbL tensor is reconstructed from its discontinuities, expressed in terms of simpler hadronic matrix elem

Miguel Montero, Irene Valenzuela

We study D4 brane domain walls in the scale-separated 4d $\mathcal{N}$=1 AdS$_4$ DGKT scenario. Classically, these are BPS and satisfy a no-force condition since their tension equals their charge. We show that this property is not stable against quantum corrections and that these increase the brane tension-to-charge ratio, rendering the branes self-attractiv

Jakub Nadolny, Michał J. Michałowski, Massimiliano Parente, Martín Solar

Recent high-redshift ($z>4$) spatially resolved observations with the James Webb Space Telesescope have shown the evolution of the star formation rate (SFR) surface density ($\Sigma_{\rm SFR}$) and its main sequence in the $\Sigma_{\rm SFR}$-$M_*$ diagram ($\Sigma_{\rm SFR}{\rm MS}$). The $\Sigma_{\rm SFR}{\rm MS}$\ is already observed at cosmic morning ($z\

Ahmadullah Zahed

We bootstrap the leading order hadronic contribution to $a_\mu$ using unitarity, analytic properties, crossing symmetry and finite energy sum rules (FESR) from quantum chromodynamics (QCD), establishing a lower bound. Combining this lower bound with the remaining precisely calculated contributions from quantum electrodynamics and electroweak interactions, we

Jieming Lin, Torben Skrzypek, K. S. Stelle

We study compactifications of eleven- and ten-dimensional maximal supergravity on Calabi-Yau threefolds. We explicitly construct truncations to pure supergravity with eight supercharges in five and four dimensions and show that they are consistent, i.e. that every solution of the lower-dimensional equations of motion fully solves the higher-dimensional ones.

Adrián García Riber, Rubén García-Benito, Francisco Serradilla

Using sonification on scientific data analysis provides additional dimensions to visualization, potentially increasing researchers' analytical capabilities and fostering inclusion and accessibility. This research explores the potential of multimodal Integral Field Spectroscopy (IFS) applied to galaxy analysis through the development and evaluation of a tool

Oren Bergman, Francesco Mignosa

We revisit the 3d ${\cal N}=5$ Chern-Simons-Matter theory with orthosymplectic gauge group and its gravity dual from the perspective of generalized symmetries. We derive the corresponding 4d symmetry topological field theory from the gravity dual and relate the allowed boundary conditions to the different variants of the 3d theory. Concentrating on a specifi

Kamran Salehi Vaziri

We propose a new approach for constructing the late-time conformal boundary of quantum field theory in de Sitter spacetime. A boundary theory which consists of a continuous family of primary operators residing on unitary irreducible representations, the principal series. These boundary operators exhibit two-point functions that include contact terms alongsid

Sonja M. Koehler, Hao Jiao, Rahul Kannan

Recent observations from the James Webb Space Telescope (JWST) have uncovered an unexpectedly large abundance of massive, UV-bright galaxies at high redshifts, presenting a significant challenge to established galaxy formation models within the standard $\Lambda$CDM cosmological framework. Cosmic strings, predicted by a wide range of particle physics theorie

Sungwoo Hong, Maxim Perelstein, Taewook Youn

We study a scenario where a dark sector, described by a Conformal Field Theory (CFT), interacts with the Standard Model through the neutrino portal. In this setup, conformal invariance breaks below the electroweak scale, causing the theory to transition into a confined (hadronic) phase. One of the hadronic excitations in this phase can act as dark matter. In

Arturo de Giorgi, Maria Ramos

We study the $\textit{complete}$ parameter space of a bulk axion in flat and warped extra spacetime dimensions. We characterize in detail the regimes where no single KK mode is produced along the canonical QCD axion line, and instead, it is maximally deviated along with several other axions that constitute a multiple solution to the strong CP problem. In bot

Martin Hoferichter, Peter Stoffer, Maximilian Zillinger

In this work, we present an evaluation of subleading effects in the hadronic light-by-light contribution to the anomalous magnetic moment of the muon. Using a recently derived optimized basis, we first study the matching of axial-vector contributions to short-distance constraints at the level of the scalar basis functions, finding that also the tails of the

Shukang Yin, Chaoyou Fu, Sirui Zhao, Chunjiang Ge

Recent years have seen the success of Multimodal Large Language Models (MLLMs) in the domain of vision understanding. The success of these models can largely be attributed to the dominant scaling law, which states that larger parameter sizes and data volumes contribute to better performance. Notably, data scaling has been primarily driven by automatic data p

Yuze He, Wang Zhao, Shaohui Liu, Yubin Hu

We introduce AlphaTablets, a novel and generic representation of 3D planes that features continuous 3D surface and precise boundary delineation. By representing 3D planes as rectangles with alpha channels, AlphaTablets combine the advantages of current 2D and 3D plane representations, enabling accurate, consistent and flexible modeling of 3D planes. We deriv

Rakesh Arul, Zhao Jiang, Xinjuan Li, Fiona M. Bell

Photon upconversion, combining several low-energy photons to generate one high-energy photon is of wide interest for biomedical, catalytic and photonic applications. Lanthanide-doped nanoparticles (LnNP) are a unique type of upconversion nanoconverter, which can realize ultralarge anti-Stokes shift (>1000 nm) and high photostability, without photo-bleaching

Sebastian J. Morris, Christopher J. Ho, Simon M. Fischer, Jiří Etrych

We study the collapse of an attractive Bose-Einstein condensate, where an unstable system evolves towards a singularity, by numerically solving the underlying cubic-quintic nonlinear Schr\"odinger equation. We find good agreement between our simulations and the atom-loss measurements with a $^{39}$K condensate. Our simulations reveal an interplay of weak col

Jan-Philipp Christ, Pit Bermes, Fabian Grusdt

We consider the ground state properties of a lattice Bose polaron, a quasiparticle arising from the interaction between an impurity confined to an optical lattice and a surrounding homogeneous Bose-Einstein condensate hosting phononic modes. We present an extension of Wegner's and Wilson's flow equation approach, the operator valued flow equation approach, w

Zhiqiang Shen, Ammar Sherif, Zeyuan Yin, Shitong Shao

Recent advances in dataset distillation have led to solutions in two main directions. The conventional batch-to-batch matching mechanism is ideal for small-scale datasets and includes bi-level optimization methods on models and syntheses, such as FRePo, RCIG, and RaT-BPTT, as well as other methods like distribution matching, gradient matching, and weight tra

Yi Zhang, Johan Comparat, Gabriele Ponti, Andrea Merloni

The circumgalactic medium (CGM), as the gas repository for star formation, might contain the answer to the mysterious galaxy quenching and bimodal galaxy population origin. We measured the X-ray emission of the hot CGM around star-forming and quiescent galaxies. We detect extended X-ray emission from the hot CGM around star-forming galaxies with $\log(M_*/M_

Ivan Zelich

We introduce the notion of indivisible sequences and show that to any indivisible sequence $\{S, \Psi: S \to R\}$ we can associate faithfully flat ring maps $R \to R'$ that are not descendable. As a corollary, we obtain the first example of a faithfully flat ring map between $\aleph_{n-1}$-countable rings that has descendability exponent $n$, and indeed a fa

Xiaoyan Xing, Konrad Groh, Sezer Karaoglu, Theo Gevers

We introduce LumiNet, a novel architecture that leverages generative models and latent intrinsic representations for effective lighting transfer. Given a source image and a target lighting image, LumiNet synthesizes a relit version of the source scene that captures the target's lighting. Our approach makes two key contributions: a data curation strategy from

Hui Ren, Joanna Materzynska, Rohit Gandikota, David Bau

We explore whether pre-training on datasets with paintings is necessary for a model to learn an artistic style with only a few examples. To investigate this, we train a text-to-image model exclusively on photographs, without access to any painting-related content. We show that it is possible to adapt a model that is trained without paintings to an artistic s

Zicheng Lin, Tian Liang, Jiahao Xu, Qiuzhi Lin

Mathematical reasoning tasks pose significant challenges for large language models (LLMs) because they require precise logical deduction and sequence analysis. In this work, we introduce the concept of critical tokens -- elements within reasoning trajectories that significantly influence incorrect outcomes. We present a novel framework for identifying these

Stefan Smeu, Dragos-Alexandru Boldisor, Dan Oneata, Elisabeta Oneata

Good datasets are essential for developing and benchmarking any machine learning system. Their importance is even more extreme for safety critical applications such as deepfake detection - the focus of this paper. Here we reveal that two of the most widely used audio-video deepfake datasets suffer from a previously unidentified spurious feature: the leading

Hang Ye, Xiaoxuan Ma, Hai Ci, Wentao Zhu

Achieving realistic animated human avatars requires accurate modeling of pose-dependent clothing deformations. Existing learning-based methods heavily rely on the Linear Blend Skinning (LBS) of minimally-clothed human models like SMPL to model deformation. However, they struggle to handle loose clothing, such as long dresses, where the canonicalization proce

Joseph Heyward, João Carreira, Dima Damen, Andrew Zisserman

Following the successful 2023 edition, we organised the Second Perception Test challenge as a half-day workshop alongside the IEEE/CVF European Conference on Computer Vision (ECCV) 2024, with the goal of benchmarking state-of-the-art video models and measuring the progress since last year using the Perception Test benchmark. This year, the challenge had seve

Sarah Kiden, Bernd Stahl, Beverley Townsend, Carsten Maple

This report presents a comprehensive response to the United Nation's Interim Report on Governing Artificial Intelligence (AI) for Humanity. It emphasizes the transformative potential of AI in achieving the Sustainable Development Goals (SDGs) while acknowledging the need for robust governance to mitigate associated risks. The response highlights opportunitie

C. Özen, Y. Alhassid

Level densities are often parametrized using the back-shifted Bethe formula (BBF) for nuclei that possess experimental data for s-wave neutron resonance average spacings and a complete discrete level sequence at low excitation energies. However, these parametrizations require the additional modeling of the dependence of the spin-cutoff parameter on excitatio

Xuhao Hu, Dongrui Liu, Hao Li, Xuanjing Huang

Safety concerns of Multimodal large language models (MLLMs) have gradually become an important problem in various applications. Surprisingly, previous works indicate a counterintuitive phenomenon that using textual unlearning to align MLLMs achieves comparable safety performances with MLLMs aligned with image text pairs. To explain such a phenomenon, we disc

Haoxiang Chen, Weiluo Ren, Xiang Li, Ji Chen

One-dimensional (1D) systems and models provide a versatile platform for emergent phenomena induced by strong electron correlation. In this work, we extend the newly developed real space neural network quantum Monte Carlo methods to study the quantum phase transition of electronic and magnetic properties. Hydrogen chains of different interatomic distances ar

Siddhi Raut, Eric M. Schlegel, Thomas G. Pannuti, Brannon W. Jones

We present an analysis of two epochs of ACIS observations of the SA(s)c spiral galaxy NGC 3938 with the Chandra X-ray Observatory. The total exposure time of the observations was 95 ksec with a limiting unabsorbed luminosity of approximately 10^{38}$ ergs/sec assuming a distance of 22 Mpc. A total of 47 discrete merged sources from both epochs were detected

Jianping Jiang, Weiye Xiao, Zhengyu Lin, Huaizhong Zhang

Human beings are social animals. How to equip 3D autonomous characters with similar social intelligence that can perceive, understand and interact with humans remains an open yet foundamental problem. In this paper, we introduce SOLAMI, the first end-to-end Social vision-Language-Action (VLA) Modeling framework for Immersive interaction with 3D autonomous ch

Hung Kwan Fok, Marco Pignatari, Benoît Côté, Reto Trappitsch

Presolar grains are stardust particles that condensed in the ejecta or in the outflows of dying stars and can today be extracted from meteorites. They recorded the nucleosynthetic fingerprint of their parent stars and thus serve as valuable probes of these astrophysical sites. The most common types of presolar silicon carbide grains (called mainstream SiC gr

Lukas Schmidbauer, Elisabeth Lobe, Ina Schaefer, Wolfgang Mauerer

Many of the envisioned use-cases for quantum computers involve optimisation processes. While there are many algorithmic primitives to perform the required calculations, all eventually lead to quantum gates operating on quantum bits, with an order as determined by the structure of the objective function and the properties of target hardware. When the structur

Ruiqi Bai, Yijiao Zhang, Hanbo Yang, Zhongyi Zhu

Information from related source studies can often enhance the findings of a target study. However, the distribution shift between target and source studies can severely impact the efficiency of knowledge transfer. In the high-dimensional regression setting, existing transfer approaches mainly focus on the parameter shift. In this paper, we focus on the high-

K. Kumarasinghe, A. Rahman, M. Tomlinson, D. Le

We report a systematic study of the normal-state and superconducting properties of single crystal Pb$_{1-x}$Sn$_{x}$TaSe$_{2}$ $(0\leq x \leq 0.23)$. Sn doping enhances the superconducting temperature $T_{c}$ up to 5.1 K while also significantly increasing impurity scattering in the crystals. For $x=0$ and 0.018, the specific heat jump at $T_{c}$ exceeds the

Julian De Vuyst, Stefan Eccles, Philipp A. Hoehn, Josh Kirklin

Modular crossed product algebras have recently assumed an important role in perturbative quantum gravity as they lead to an intrinsic regularization of entanglement entropies by introducing quantum reference frames (QRFs) in place of explicit regulators. This is achieved by imposing certain boost constraints on gravitons, QRFs and other fields. Here, we revi

Daixuan Cheng, Shaohan Huang, Ziyu Zhu, Xintong Zhang

Adapting general multimodal large language models (MLLMs) to specific domains, such as scientific and industrial fields, is highly significant in promoting their practical applications. This paper systematically investigates domain adaptation of MLLMs via post-training, focusing on data synthesis, training pipeline, and task evaluation. (1) Data Synthesis: U

Benjamin Antieau, Noah Riggenbach

We define an $\infty$-category $\mathrm{CycSyn}$ of $p$-typical cyclotomic synthetic spectra and prove that the motivic filtration on $\mathrm{THH}(R;\mathbf{Z}_p)$, defined by Bhatt, Morrow, and Scholze when $R$ is quasisyntomic and by Hahn, Raksit, and Wilson in the chromatically quasisyntomic case, naturally admits the structure of a $p$-typical cyclotomi

Libor Šmejkal

Magnetoelectric multiferroics are highly sought after for applications in low-power electronics and for advancing fundamental research, including axion insulators and dark matter detection. However, achieving a combination of ferroic spin and electric orders, along with their controllable switching, remains a significant challenge in conventional ferromagnet

Giuseppe Arrò, Hui Li, William H. Matthaeus

We present a new scale decomposition method to investigate turbulence in wavenumber-frequency space. Using 3D magnetohydrodynamic turbulence simulations, we show that magnetic fluctuations with time scales longer than the nonlinear time exhibit an inverse cascade toward even smaller frequencies. Low frequency magnetic fluctuations support turbulence, acting

Rikhav Shah, Nikhil Srivastava, Edward Zeng

The eigenvalues and eigenvectors of nonnormal matrices can be unstable under perturbations of their entries. This renders an obstacle to the analysis of numerical algorithms for non-Hermitian eigenvalue problems. A recent technique to handle this issue is pseudospectral shattering [BGVKS23], showing that adding a random perturbation to any matrix has a regul

Soikot Sarkar, Sajid Muhaimin Choudhury

The hybrid metal-dielectric nanostructures (HMDN) are promising candidates to address the ohmic loss by conventional nanostructures in photovoltaic applications by strong confinement and high scattering directivity. In this study, we present a c-Si/TiO$_2$ heterojunction thin film solar cell (TFSC) where a pair of triangular HMDN comprised of Ag and AZO was

Henry Leung

Bulk cone singularities are singularities in boundary two-point functions at points separated by a null geodesic in the bulk, but not in the boundary. In this work, we describe a new type of bulk cone singularities in a family of Vaidya-like spacetimes that are labeled by the radius $r_+$ of the resulting black hole. We find a sharp transition in the causal

Parjanya Prashant, Seyedeh Baharan Khatami, Bruno Ribeiro, Babak Salimi

We consider the task of out-of-distribution (OOD) generalization, where the distribution shift is due to an unobserved confounder ($Z$) affecting both the covariates ($X$) and the labels ($Y$). This confounding introduces heterogeneity in the predictor, i.e., $P(Y | X) = E_{P(Z | X)}[P(Y | X,Z)]$, making traditional covariate and label shift assumptions unsu

Guiran Liu, Binrong Zhu

This study investigated the dynamic connectivity patterns between EEG and fMRI modalities, contributing to our understanding of brain network interactions. By employing a comprehensive approach that integrated static and dynamic analyses of EEG-fMRI data, we were able to uncover distinct connectivity states and characterize their temporal fluctuations. The r

Wenjia Wang, Liang Pan, Zhiyang Dou, Jidong Mei

Simulating stylized human-scene interactions (HSI) in physical environments is a challenging yet fascinating task. Prior works emphasize long-term execution but fall short in achieving both diverse style and physical plausibility. To tackle this challenge, we introduce a novel hierarchical framework named SIMS that seamlessly bridges highlevel script-driven

Simon Pepin Lehalleur, Richárd Rimányi

We study the geometry of the algebraic set of tuples of composable matrices which multiply to a fixed matrix, using tools from the theory of quiver representations. In particular, we determine its codimension $C$ and the number $\theta$ of its top-dimensional irreducible components. Our solution is presented in three forms: a Poincar\'e series in equivariant

Felix Willenborg, Dennis Philipp, Claus Lämmerzahl

The Taub-NUT spacetime offers many curious insights into the solutions of Einstein's electrovacuum equation. In the Bonnor interpretation, this spacetime possesses so-called Misner strings, which induce phenomena strikingly analogous to Dirac strings in the context of magnetic monopoles. The study of scattering in the latter case leads to a quantization of t

Livio Robaldo, Gianluca Pozzato

This paper presents a new ontology that implements the well-known Deontic Traditional Scheme in RDFs and SPARQL, fit to handle irresolvable conflicts, i.e., situations in which two or more statements prescribe conflicting obligations, prohibitions, or permissions, with none of them being "stronger" than the other one(s). In our view, this paper marks a signi

Gesa Sarnighausen, Tram Thi Ngoc Nguyen, Thorsten Hohage, Mangalika Sinha

Traction force microscopy is a method widely used in biophysics and cell biology to determine forces that biological cells apply to their environment. In the experiment, the cells adhere to a soft elastic substrate, which is then deformed in response to cellular traction forces. The inverse problem consists in computing the traction stress applied by the cel

Emma T. Chickles, Kevin B. Burdge, Joheen Chakraborty, Vik S. Dhillon

Type Ia supernovae, critical for studying cosmic expansion, arise from thermonuclear explosions of white dwarfs, but their precise progenitor pathways remain unclear. Growing evidence supports the ``double-degenerate'' scenario, where two white dwarfs interact. The absence of other companion types capable of explaining the observed Ia rate, along with observ

António Girão, Toby Insley

We prove that for each integer $r\geq 2$, there exists a constant $C_r>0$ with the following property: for any $0<\varepsilon \leq 1/2$ and any graph $G$ with clique number at most $r,$ there is a partition of $V(G)$ into at most $(1/\varepsilon)^{C_r}$ sets $S_1, \dots, S_t,$ such that $G[S_i]$ has maximum degree at most $\varepsilon |S_i|$ for each $1 \leq

Daniel Alcalde Puente, Matteo Rizzi

This work introduces a self-learning protocol that incorporates measurement and feedback into variational quantum circuits for efficient quantum state preparation. By combining projective measurements with conditional feedback, the protocol learns state preparation strategies that extend beyond unitary-only methods, leveraging measurement-based shortcuts to

Alina Marcu

Quantifying the gap between synthetic and real-world imagery is essential for improving both transformer-based models - that rely on large volumes of data - and datasets, especially in underexplored domains like aerial scene understanding where the potential impact is significant. This paper introduces a novel methodology for scene complexity assessment usin

Samuel Cailleaux, Quentin Ficheux, Nicolas Roch, Denis M. Basko

When a small system is coupled to a bath, it is generally assumed that the state of the bath remains unaffected by the system due to the bath's large number of degrees of freedom. Here we show theoretically that this assumption can be easily violated for photonic baths typically used in experiments involving superconducting circuits. We analyze the dynamics

A. Mazoun, S. Bocquet, J. J. Mohr, M. Garny

We use galaxy cluster abundance measurements from the South Pole Telescope (SPT) enhanced by Multi-Component Matched Filter (MCMF) confirmation and complemented with mass information obtained using weak-lensing data from Dark Energy Survey Year~3 (DES Y3) and targeted Hubble Space Telescope (HST) observations for probing deviations from the cold dark matter

Riccardo Caniato, Tristan Rivière

We prove that stationary Yang$-$Mills fields in dimensions 5 belonging to the variational class of weak connections are smooth away from a closed singular set $S$ of vanishing 1-dimensional Hausdorff measure. Our proof is based on an $\varepsilon$-regularity theorem, which generalizes to this class of weak connections the existing previous $\varepsilon$-regu

J. Yu. Panteleeva, E. Epelbaum, A. M. Gasparyan, J. Gegelia

The gravitational form factors of the deuteron are calculated in the framework of non-relativistic chiral effective field theory. Non-relativistic reduction of the matrix element of the energy-momentum tensor operator for spin-one systems is worked out, and the gravitational form factors of the deuteron are extracted from the three-point function of the ener

Jessica Gronsbell, Jianhui Gao, Zachary R. McCaw, Yaqi Shi

From structural biology to epidemiology, predictions from machine learning (ML) models increasingly complement costly gold-standard data, enabling faster, more affordable, and scalable scientific inquiry. In response, prediction-based (PB) inference has emerged to support statistical analysis that combines a large volume of predicted data with a small amount

Emanuele Frittaion, Takako Nemoto, Michael Rathjen

Choice and independence of premise principles play an important role in characterizing Kreisel's modified realizability and G\"odel's Dialectica interpretation. In this paper we show that a great many intuitionistic set theories are closed under the corresponding rules for finite types over $\mathbb{N}$. It is also shown that the existence property (or exist

Ali Lotfi, Ian McQuillan, Steven Rayan

L-systems can be made to model and create simulations of many biological processes, such as plant development. Finding an L-system for a given process is typically solved by hand, by experts, in a massively time-consuming process. It would be significant if this could be done automatically from data, such as from sequences of images. In this paper, we are in

Bo Li, Chuan Chen, Zhong Wang

In disordered Hermitian systems, localization of energy eigenstates prohibits wave propagation. In non-Hermitian systems, however, wave propagation is possible even when the eigenstates of Hamiltonian are exponentially localized by disorders. We find in this regime that non-Hermitian wave propagation exhibits novel universal scaling behaviors without Hermiti

Miantao Liu, Yu-Zhe Liu, Shengda Liu

This paper provides a new categorification of the Lebesgue integral with variable upper limits by using normed modules over finite-dimensional $\Bbbk$-algebras $\mathit{\Lambda}$ and the category $\mathscr{A}^p_{\mathit{\Lambda}}$ associated with $\mathit{\Lambda}$. The integration process is redefined through the introduction of an integral partially ordere

Prajwal Singh, Ashish Tiwari, Gautam Vashishtha, Shanmuganathan Raman

Neural radiance fields (NeRF) have revolutionized photorealistic rendering of novel views for 3D scenes. Despite their growing popularity and efficiency as 3D resources, NeRFs face scalability challenges due to the need for separate models per scene and the cumulative increase in training time for multiple scenes. The potential for incrementally encoding mul

Araceli Guzmán-Tristán, Antonio Rieser

We propose a pair of completely data-driven algorithms for unsupervised classification and dimension reduction, and we empirically study their performance on a number of data sets, both simulated data in three-dimensions and images from the COIL-20 data set. The algorithms take as input a set of points sampled from a uniform distribution supported on a metri

Subhajit Sahu

Community detection involves grouping nodes in a graph with dense connections within groups, than between them. We previously proposed efficient multicore (GVE-LPA) and GPU-based ($\nu$-LPA) implementations of Label Propagation Algorithm (LPA) for community detection. However, these methods incur high memory overhead due to their per-thread/per-vertex hashta

J. C. Verde, N. Coton, M. V. Ramallo

Media and membranes composed of micrometric-diameter pores are well known in academia and industry to be capable of efficacious nanofiltration of fluids once the pore inner surfaces are coated with nanostructures. Given the large mismatch between the two very different scales of these hybrid systems, it could be expected that trapping of nanoimpurities would

Yingtian Chen, Hui Li, Oleg Y. Gnedin

Globular cluster (GC) streams, debris of stars that tidally stripped from their progenitor GCs, have densities that correlate positively with the GC mass loss rate. In this work, we employ a novel particle spray algorithm that can accurately reproduce the morphology of streams of various orbital types, enabling us to uncover the relationship between the GC m