November 2024 arXiv papers — page 40

Bo Hu, Siyu Liu, Beilin Ye, Yun Hao

Discovering explicit physical laws has traditionally depended on human intuition and domain expertise. Recent advances in artificial intelligence, particularly large language models (LLMs), offer a new route to accelerate this process by automating key steps from hypothesis generation to interpretable model construction. Here we develop an LLM-based multi-ag

Yuhao Zhou, Xiaohong Li, Jack M. Jenkins, Jie Hong

The frozen-field hydrodynamic (ffHD) model is a simplification of the full magnetohydrodynamical (MHD) equations under the assumption of a rigid magnetic field, which significantly reduces computational complexity and enhances efficiency. In this work, we combine the ffHD prescription with hyperbolic thermal conduction (TC) and the Transition Region Adaptive

Diego Chamorro, Manuel Fernando Cortez

In this paper, we study a Liouville-type theorem for the stationary fractional quasi-geostrophic equation in various dimensions. Indeed, our analysis focuses on dimensions n = 2, 3, 4 and we explore the uniqueness of weak solutions for this fractional system. We demonstrate here that, under some specific Lebesgue integrability information, the only admissibl

Haigang Li, Peihao Zhang

In this paper we investigate the stress concentration problem that occurs when two convex rigid particles are closely immersed in a fluid flow. The governing equations for the fluid flow are the stationary incompressible Navier-Stokes equations. We establish precise upper bounds for the gradients and second-order derivatives of the fluid velocity as the dist

Li Huang

ACTest is an open-source toolkit developed in the Julia language. Its central goal is to automatically establish analytic continuation testing datasets, which include a large number of spectral functions and the corresponding Green's functions. These datasets can be used to benchmark various analytic continuation methods and codes. In ACTest, the spectral fu

G. G. Plunk, M. Drevlak, E. Rodriguez, R. Babin

The first stellarator design was a simple tube of plasma twisted and closed on itself in the form of a figure-8. The line of such devices, however, was quickly ended over concerns related to plasma stability. We revisit the figure-8 concept, re-imagined as a modern optimized stellarator, and find the potential for a high degree of stability, as well as excep

Qianke Wang, Jun Liu, Dawei Lyu, Jian Wang

While the spatial mode of photons is widely used in quantum cryptography, its potential for quantum computation remains largely unexplored. Here, we showcase the use of the multi-dimensional spatial mode of photons to construct a series of high-dimensional quantum gates, achieved through the use of diffractive deep neural networks (D2NNs). Notably, our gates

Stavroula Makri

We study the configuration space of distinct, unordered points on compact orientable surfaces of genus $g$, denoted $S_g$. Specifically, we address the section problem, which concerns the addition of $n$ distinct points to an existing configuration of $m$ distinct points on $S_g$ in a way that ensures the new points vary continuously with respect to the init

Elona Shatri, Daniel Raymond, George Fazekas

In this paper, we explore the intersection of technology and cultural preservation by developing a self-supervised learning framework for the classification of musical symbols in historical manuscripts. Optical Music Recognition (OMR) plays a vital role in digitising and preserving musical heritage, but historical documents often lack the labelled data requi

Noa Edri Fraiman, Barak Sabbagh, Gilad Yossifon, Alexander Fish

Iontronics combines ions as charge carriers with electronic-like operations, enabling unique information processing, chemical regulation, and enhanced bio-integrability. Standard simulation tools encounter difficulties in effectively modeling the behavior of integrated iontronic components, highlighting the need for specialized design and simulation approach

Manuel Schwonberg, Claus Werner, Hanno Gottschalk, Carsten Meyer

Despite the recent progress in deep learning based computer vision, domain shifts are still one of the major challenges. Semantic segmentation for autonomous driving faces a wide range of domain shifts, e.g. caused by changing weather conditions, new geolocations and the frequent use of synthetic data in model training. Unsupervised domain adaptation (UDA) m

Han-Chuan Kou, Zhi-Han Zhang, Peng Li

We investigate the dissipative quench dynamics in a family of two-band fermionic systems by linearly ramping the staggered on-site energy. In the Lindblad formalism, we present an analytical solution in the presence of uniform loss or loss difference on bipartite lattices, which tells that dissipation exponentially suppresses the Kibble-Zurek (KZ) scaling be

Elona Shatri, Kalikidhar Palavala, George Fazekas

The generation of handwritten music sheets is a crucial step toward enhancing Optical Music Recognition (OMR) systems, which rely on large and diverse datasets for optimal performance. However, handwritten music sheets, often found in archives, present challenges for digitisation due to their fragility, varied handwriting styles, and image quality. This pape

Rodrigo Dutra Garcia, Gowri Ramachandran, Kealan Dunnett, Raja Jurdak

Modern distributed applications in healthcare, supply chain, and the Internet of Things handle a large amount of data in a diverse application setting with multiple stakeholders. Such applications leverage advanced artificial intelligence (AI) and machine learning algorithms to automate business processes. The proliferation of modern AI technologies increase

Alexander Fichtl, Juraj Vladika, Georg Groh

Knowledge-enhanced language models (KELMs) have emerged as promising tools to bridge the gap between large-scale language models and domain-specific knowledge. KELMs can achieve higher factual accuracy and mitigate hallucinations by leveraging knowledge graphs (KGs). They are frequently combined with adapter modules to reduce the computational load and risk

Zhuofan Wen, Shangtong Gui, Yang Feng

Inference acceleration of large language models (LLMs) has been put forward in many application scenarios and speculative decoding has shown its advantage in addressing inference acceleration. Speculative decoding usually introduces a draft model to assist the base LLM where the draft model produces drafts and the base LLM verifies the draft for acceptance o

Wojciech Adamczyk, Silvan Koch, Claudia Politi, Henry Fernandes Passagem

We demonstrate sub-Doppler cooling of calcium atoms using a two-photon transition from the ${^1}S_0$ ground state to the upper $4s5s~{^1}S_0$ state via the ${^1}P_1$ intermediate state. We achieve temperatures as low as $260~\mu\text{K}$ in a magneto-optical trap (MOT), well below the Doppler limit ($T_{\text{D}} = 0.8~\text{mK}$) of the ${^1}P_1$ state. We

Andrew Garber, Rohan Subramani, Linus Luu, Mark Bedaywi

A wide variety of goals could cause an AI to disable its off switch because "you can't fetch the coffee if you're dead" (Russell 2019). Prior theoretical work on this shutdown problem assumes that humans know everything that AIs do. In practice, however, humans have only limited information. Moreover, in many of the settings where the shutdown problem is mos

Oleksandr Gamayun, Yuri Zhuravlev

We consider finite-temperature deformation of the sine kernel Fredholm determinants acting on the closed contours. These types of expressions usually appear as static two-point correlation functions in the models of free fermions and can be equivalently presented in terms of Toeplitz determinants. The corresponding symbol, or the phase shift, is related to t

Shikhar Raj, Biplab Bose

Various biological phenomena, like cell differentiation and pattern formation in multicellular organisms, are explained using the bifurcation theory. Molecular network motifs like positive feedback and mutual repressor exhibit bifurcation and are responsible for the emergence of diverse cell types. Mathematical investigations of such problems usually focus o

F. Košuth, N. Potomová, Z. Pribulová, J. Kačmarčík

Point-contact Andreev reflection spectroscopy at low temperatures and high magnetic fields has been performed on a noncentrosymmetric La$_3$Se$_4$ superconductor with a critical temperature $T_c$ = 8 K. Two superconducting energy gaps $\Delta_1$ and $\Delta_2$ with $2\Delta_{1}/k_{B} T_{c}$ ~ 5.8 and $2\Delta_{2}/k_{B} T_{c}$ ~ 2.3, are directly observed in

Xinyi Li, Jialu Shi, Qiheng Xu

We consider large deviations of the cover time of the discrete torus $(\mathbb{Z}/N\mathbb{Z})^d$, $d \geq 3$ by simple random walk. We prove a lower bound on the probability that the cover time is smaller than $\gamma\in (0,1)$ times its expected value, with exponents matching the upper bound from [Goodman-den Hollander, Probab. Theory Related Fields (2014)

Yoshiki Nakamura, Ryoma Sin'ya

We investigate the equational theory for Kleene algebra terms with variable complements and constant complements -- (language) complement where it applies only to variables or constants -- w.r.t. languages. While the equational theory w.r.t. languages coincides with the language equivalence (under the standard language valuation) for Kleene algebra terms, th

Hiroshi Yano, Yota Maeda, Naoki Yamamoto

Deep learning has seen substantial achievements, with numerical and theoretical evidence suggesting that singularities of statistical models are considered a contributing factor to its performance. From this remarkable success of classical statistical models, it is naturally expected that quantum singular models will play a vital role in many quantum statist

Mohammed Riadh Berramdane, Alexandre Battiston, Michele Bardi, Nicolas Blet

Facing the thermal management challenges of Wide Bandgap (WBG) semiconductors, this study highlights the use of ARX parametric models, which provide accurate temperature predictions without requiring detailed understanding of component thickness disparities or material physical properties, relying solely on experimental measurements. These parametric models

Fernando Gómez-Ortiz, Louis Bastogne, Sriram Anand, Miao Yu

Skyrmions are stable topological textures that have garnered substantial attention within the ferroelectric community for their exotic functional properties. While previous studies have questioned the feasibility of [001]$_{\text{pc}}$ skyrmion tubes in rhombohedral BaTiO$_3$ due to the high energy cost of 180$^\circ$ domain walls, we demonstrate here their

Souvik Mondal, Murilo S. Baptista, Kapil Debnath

Optomechanical cavities, with nonlinear photon-phonon interactions, offer a more compact approach to chaos generation than conventional feedback-based optical systems. However, proper study on chaos synchronization of two optomechanical cavities connected by optical means is still unexplored. In this work, we theoretically investigate all-optical complete sy

Yangyuanchen Liu, Oscar Lopez-Pamies, John E. Dolbow

Over the past seven years, full-field analyses of a wide range of classical as well as modern quasi-static fracture experiments on nominally elastic brittle materials -- ranging from hard ceramics to soft elastomers -- have repeatedly identified the material strength surface as one of the key material properties that governs not only the nucleation of cracks

Ziyu Zhang, Binbin Huang, Hanqing Jiang, Liyang Zhou

We propose Quadratic Gaussian Splatting (QGS), a novel representation that replaces static primitives with deformable quadric surfaces (e.g., ellipse, paraboloids) to capture intricate geometry. Unlike prior works that rely on Euclidean distance for primitive density modeling--a metric misaligned with surface geometry under deformation--QGS introduces geodes

Agus Sudjianto, Aijun Zhang, Srinivas Neppalli, Tarun Joshi

This paper introduces a comprehensive framework for the evaluation and validation of generative language models (GLMs), with a focus on Retrieval-Augmented Generation (RAG) systems deployed in high-stakes domains such as banking. GLM evaluation is challenging due to open-ended outputs and subjective quality assessments. Leveraging the structured nature of RA

Balazs Plosz, Athanasios Lekosiotis, Mohammad Sabbah, Federico Belli

We report the generation of a multi-octave supercontinuum spanning from 350 nm to 1700 nm with exceptional spectral flatness and high conversion efficiency to both the visible and near infrared region, by pumping a methane-filled hollow-core antiresonant fiber with 1030 nm laser pulses. The dynamics exhibited signs of both modulational instability and stimul

Marta Ligero, Tim Lenz, Georg Wölflein, Omar S. M. El Nahhas

To date, the most common approach for radiology deep learning pipelines is the use of end-to-end 3D networks based on models pre-trained on other tasks, followed by fine-tuning on the task at hand. In contrast, adjacent medical fields such as pathology, which focus on 2D images, have effectively adopted task-agnostic foundational models based on self-supervi

Filippo Bolis, Emanuele Sobacchi, Fabrizio Tavecchio

Supermassive black holes in active galactic nuclei (AGNs) launch relativistic jets that shine through the entire electromagnetic spectrum. Blazars are a subclass of AGN where non-thermal radiation from the jet is strongly beamed, as the jet is directed nearly toward the observer. Multifrequency polarimetry is emerging as a powerful probe of blazar jets, espe

Thi Hoai Thuong Nguyen, Benjamin Boutin

This paper investigates the stability of both the semi-discrete and the implicit central scheme for the linear damped wave equation on the half-line, where the spatial boundary is characteristic for the limiting equation. The proposed schemes incorporate a discrete boundary condition designed to guarantee the uniform stability of the IBVP, regardless of the

Cheng-Wei Lin, Wan-Hsuan Hsieh, Kai-Xin Guan, Chan-Jan Hsu

The quality and size of a pretraining dataset significantly influence the performance of large language models (LLMs). While there have been numerous efforts in the curation of such a dataset for English users, there is a relative lack of similar initiatives for Traditional Chinese. Building upon this foundation of FineWeb, we introduce FineWeb-zhtw, a datas

Antonio Bucciarelli, Pierre-Louis Curien, Arturo De Faveri, Antonino Salibra

Building upon the classical article "Representing varieties of algebras by algebras'' by W. D. Neumann, we revisit the famous Birkhoff's HSP theorem in the light of infinitary algebra.

Prashant Batra

Many upper bounds for the moduli of polynomial roots have been proposed but reportedly assessed on selected examples or restricted classes only. Regarding quality measured in terms of worst-case relative overestimation of the maximum root-modulus we establish a simple, nearly optimal result.

Nora Brambilla, Mathias Butenschoen, Xiang-Peng Wang

We perform a thorough investigation of the universality of the long distance matrix elements (LDMEs) of nonrelativistic QCD factorization based on a next-to-leading order (NLO) fit of $J/\psi$ color octet (CO) LDMEs to high transverse momentum $p_T$ $J/\psi$ and $\eta_c$ production data at the LHC. We thereby apply a novel fit-and-predict procedure to system

Omar El Assal, Carlos M. Mateo, Sebastien Ciron, David Fofi

One of the difficulties imposed on the manipulation of deformable objects is their characterization and the detection of representative keypoints for the purpose of manipulation. A keen interest was manifested by researchers in the last decade to characterize and manipulate deformable objects of non-fluid nature, such as clothes and ropes. Even though severa

Eysan Sans, Melisa Akdemir, Ayse Tiryakioglu, Ayse Peker-Dobie

Goodwin's model is a cornerstone in the study of dynamical systems within macroeconomics, explaining the interaction between employment ratio and wage share in a closed economy. Analogous to predator-prey dynamics in mathematical economics, the Goodwin model, despite its simplicity, effectively captures the periodic behavior of state variables over specific

Jia-Lu Zhang

In high-energy particle physics, extracting parton distribution functions (PDFs) from lattice quantum chromodynamics (QCD) calculations remains a significant challenge, particularly due to the divergent nature of perturbative expansions at high orders. The presence of renormalon singularities in the Borel plane further hinders the accurate determination of P

Tristan Ricoul

We prove a $p$-adic divisibility between the automorphic periods of a cuspidal automorphic representation of $\mathrm{GL}_3(\mathbb{Q})$ and the periods of its Arthur-Clozel's base change to some real quadratic field $E$. This generalizes earlier works of Tilouine-Urban and of Hida in the case of classical modular forms. The divisibility we prove involves a

Yuncheng Jiang, Chun-Mei Feng, Jinke Ren, Jun Wei

Ultrasound imaging is widely used in clinical diagnosis due to its non-invasive nature and real-time capabilities. However, traditional ultrasound diagnostics relies heavily on physician expertise and is often hampered by suboptimal image quality, leading to potential diagnostic errors. While artificial intelligence (AI) offers a promising solution to enhanc

Chris Parker, Martin van Beek

We describe all of the irreducible polynomial $\mathbb{F}_p\mathrm{SL}_2(p^r)$ representations which lift to $(\mathbb{Z}/p^s\mathbb{Z})\mathrm{SL}_2(p^r)$ representations for $s>1$, observing that they almost never do. We also show that two related indecomposable $\mathbb{F}_p \mathrm{SL}_2(p^r)$ representations cannot be lifted to $\mathbb{Z}/p^s\mathbb{Z}

Atasi Chakraborty, Anna Birk Hellenes, Rodrigo Jaeschke-Ubiergo, Tomas Jungwirth

The origin and efficiency of charge-to-spin conversion, known as the Edelstein effect (EE), has been typically linked to spin-orbit coupling mechanisms, which require materials with heavy elements within a non-centrosymmetric environment. Here we demonstrate that the high efficiency of spin-charge conversion can be achieved even without spin-orbit coupling i

Lei Qin

In this paper, we investigate the log-concavity property of the first eigenfunction to the weighted $p$-Laplace operator in class of bounded, convex and smooth domain. Moreover, we prove a Brunn-Minkowski-type inequality for the first eigenvalue to the weighted $p$-Laplace operator in the class of $C^2$ convex bodies in $\R^n$

Toru Sera

We establish higher order approximations in the Dynkin--Lamperti theorem, a limit theorem for the distribution of a killed subordinator immediately before its first passage time over a fixed level. For this purpose, we also study asymptotic expansions of potential densities for killed subordinators.

Kaifeng Gao, Jiaxin Shi, Hanwang Zhang, Chunping Wang

With the advance of diffusion models, today's video generation has achieved impressive quality. To extend the generation length and facilitate real-world applications, a majority of video diffusion models (VDMs) generate videos in an autoregressive manner, i.e., generating subsequent clips conditioned on the last frame(s) of the previous clip. However, exist

Naoki Masuda, Kazuyuki Aihara

Synchronous firing of neurons is thought to play important functional roles such as feature binding and switching of cognitive states. Although synchronization has mainly been investigated using model neurons with simple connection topology so far, real neural networks have more complex structures. Here we examine behavior of pulse-coupled leaky integrate-an

Luiz F. B. Caixeta, Matheus H. P. Gonçalves, M. H. R. Tragtenberg, Mauricio Girardi-Schappo

Slow-fast dynamics are intrinsically related to complex phenomena and are responsible for many of the homeostatic dynamics that keep biological systems healthy functioning. We study a discrete-time membrane potential model that can generate a diverse set of spiking behavior depending on the choice of slow-fast time scales, from fast spiking to bursting, or p

Iris Breda, Glenn van de Ven, Sabine Thater, J. Falcón-Barroso

The processes driving the formation and evolution of late-type galaxies (LTGs) continue to be a debated subject in extragalactic astronomy. Investigating stellar kinematics, especially when combined with age estimates, provides crucial insights into the formation and subsequent development of galactic discs. Post-processing of exceptionally high-quality Inte

Ghanashyam Date

This is a brief note on a recently flagged issue \cite{CHK} regarding the precise characterization of quadrupolar truncation of the linearized gravitational waves in de Sitter space-time. An apparent inconsistency was noted while transforming the linearized solution truncated to quadrupolar contribution to the Bondi-Sachs form. A consistent truncation was id

M. M. A. Valiuddin, R. J. G. van Sloun, C. G. A. Viviers, P. H. N. de With

Advances in architectural design, data availability, and compute have driven remarkable progress in semantic segmentation. Yet, these models often rely on relaxed Bayesian assumptions, omitting critical uncertainty information needed for robust decision-making. Despite growing interest in probabilistic segmentation to address point-estimate limitations, the

Timo Jos Bogaarts, Felix Warmer

Neutron interactions in a fusion power plant play a pivotal role in determining critical design parameters such as coil-plasma distance and breeding blanket composition. Fast predictive neutronic capabilities are therefore crucial for an efficient design process. For this purpose, we have developed a new deterministic neutronics method, capable of quickly an

Daniel G. Figueroa, Joanes Lizarraga, Nicolás Loayza, Ander Urio

We study in detail the fully inhomogeneous non-linear dynamics of axion inflation, identifying three regimes: weak-, mild-, and strong-backreaction, depending on the duration of inflation. We use lattice techniques that explicitly preserve gauge invariance and shift symmetry, and which we validate against other computational methods of the linear dynamics an

Zhengrong Xie

The flux vector splitting (FVS) method has firstly been incorporated into the discontinuous Galerkin (DG) framework for reconstructing the numerical fluxes required for the spatial semi-discrete formulation, setting it apart from the conventional DG approaches that typically utilize the Lax-Friedrichs flux scheme or classical Riemann solvers. The control equ

Sahani Pathiraja, Philipp Wacker

It has long been posited that there is a connection between the dynamical equations describing evolutionary processes in biology and sequential Bayesian learning methods. This manuscript describes new research in which this precise connection is rigorously established in the continuous time setting. Here we focus on a partial differential equation known as t

Zi-Ao Ma, Tian Lan, Rong-Cheng Tu, Yong Hu

We present a systematic investigation of Multi-modal Retrieval Augmented Multi-modal Generation (M$^2$RAG), a novel task that enables foundation models to process multi-modal web content and generate multi-modal responses, which exhibits better information density and readability. Despite its potential impact, M$^2$RAG remains understudied, lacking comprehen

Mitra Koley, Nirmal Kotal, Dharm Veer

In this article, we study two fundamental questions on polyomino ideals which are radicality and primality. In order to study the question of radicality, we initiate the study of Knutson ideals among polyominoes. Knutson ideals were introduced by Conca and Varbaro after the work of Knutson on compatibly split ideals. Knutson ideals are known to have nice pro

Oluwadara Moronkeji, Fabio Sozio, Kamalendu Ghosh, Amira Meddeb

Elastomers filled with liquid inclusions -- as opposed to conventional solid fillers -- are a recent trend in the soft matter community because of their unique range of mechanical and physical properties. Such properties stem, in part, from the very large deformations that the underlying liquid inclusions are capable of undergoing. With the objective of adva

Juan Magalang, Javier Aguilar, Jose Perico Esguerra, Édgar Roldán

Antimicrobial resistance is a threat to public health with millions of deaths linked to drug resistant infections every year. To mitigate resistance, common strategies that are used are combination therapies and therapy switching. However, the stochastic nature of pathogenic mutation makes the optimization of these strategies challenging. Here, we propose a

ATLAS Collaboration

A search for decays of the Higgs boson into a $Z$ boson and a light resonance, with a mass of 0.5-3.5 GeV, is performed using the full 140 fb$^{-1}$ dataset of 13 TeV proton-proton collisions recorded by the ATLAS detector during Run 2 of the LHC. Leptonic decays of the $Z$ boson and hadronic decays of the light resonance are considered. The resonance can be

Clotilde Turpin, Olivier Rossel, Félix Schlosser-Perrin, Sam Ng

Objective: Direct cortical responses (DCR) and axono-cortical evoked potentials (ACEP) are generated by electrically stimulating the cortex either directly or indirectly through white matter pathways, potentially leading to different electrogenic processes. For ACEP, the slow conduction velocity of axons (median around 4 m.s$^{-1}$) is anticipated to induce

Jiansong Li, Jiaxin Geng, Yun Ling, Heping Wang

In this paper, we obtain some exact $L_2$ Bernstein-Markov inequalities for generalized Hermite and Gegenbauer weight. More precisely, we determine the exact values of the extremal problem $$M_n^2(L_2(W_\lambda),{\rm D}):=\sup_{0\neq p\in\mathcal{P}_n}\frac{\int_I\left|{\rm D} p(x)\right|^2W_\lambda(x){\rm d}x}{\int_I| p(x)|^2W_\lambda(x){\rm d}x},\ \lambda>

C. L. Pereira, F. Braga-Ribas, B. Sicardy, B. E. Morgado

Comets offer valuable insights into the early Solar System's conditions and processes. Stellar occultations enables detailed study of cometary nuclei typically hidden by their coma. Observing the star's light passing through the coma helps infer dust's optical depth near the nucleus and determine dust opacity detection limits. 29P/Schwassmann-Wachmann 1, a C

Jingtao Fan, Xiaofan Zhou, Suotang Jia

As an important effect induced by the particle-lattice interaction, the Peierls transition, a hot topic in condensed matter physics, is usually believed to occur in the one-dimensional fermionic systems. We here study a bosonic version of the one-dimensional Ising-Kondo lattice model, which describes itinerant bosons interact with the localized magnetic mome

Toshihiko Ota

Recent high-precision cosmological data tighten the bound to neutrino masses and start rising a tension to the results of lab-experiment measurements, which may hint new physics in the role of neutrinos during the structure formation in the universe. A scenario with massless sterile neutrinos was proposed to alleviate the cosmological bound and recover the c

Paulo Sérgio Almeida

We define am axiomatic timeless framework for asynchronous distributed systems, together with well-formedness and consistency axioms, which unifies and generalizes the expressive power of current approaches. 1) It combines classic serialization per-process with a global visibility. 2) It defines a physical realizability well-formedness axiom to prevent physi

Hao Ai, Yu-xi Liu

To demonstrate supremacy of quantum computing, increasingly large-scale superconducting quantum computing chips are being designed and fabricated. However, the complexity of simulating quantum systems poses a significant challenge to computer-aided design of quantum chips, especially for large-scale chips. Harnessing the scalability of graph neural networks

Mikita Balesni, Tomek Korbak, Owain Evans

Large language models can use chain-of-thought (CoT) to externalize reasoning, potentially enabling oversight of capable LLM agents. Prior work has shown that models struggle at two-hop question-answering without CoT. This capability is so basic that if it was a fundamental limitation, it would imply that many complex agentic tasks would similarly require Co

Haochen Huang, Pengyu Shi, Nina Elkina, Henrik Schulz

It is known that in an unbounded fluid, the inline configuration of a freely rising bubble pair is often unstable with respect to lateral disturbances. This work numerically examines the stability of this configuration in the presence of a nearby vertical wall. The focus is on moderately inertial regimes, where two bubbles rising initially in line typically

Xue-Jing Zhang, Erik Koch, Eva Pavarini

The surprising inversion of the orbital- and magnetic-order transition temperatures in the RVO3 series with increasing the rare-earth radius makes the series unique among orbitally-ordered materials. Here, augmenting dynamical mean-field theory with a decomposition of the order parameter into irreducible tensors, we show that this anomalous behavior emerges

A. V. Karpova, S. V. Zharikov, D. A. Zyuzin, A. Yu. Kirichenko

Context. Spider pulsars are millisecond pulsars in tight binary systems, in which a low-mass companion star is heated and ablated by the pulsar wind. Their observations allow one to study stellar evolution with formation of millisecond pulsars and physics of superdense matter in neutron stars. However, spiders are rare due to difficulties of their discovery

Irem Topal, Alexander Cherevko, Yuri Bugay, Maxim Shishlenin

Cerebral aneurysms and arteriovenous malformations are life-threatening hemodynamic pathologies of the brain. While surgical intervention is often essential to prevent fatal outcomes, it carries significant risks both during the procedure and in the postoperative period, making the management of these conditions highly challenging. Parameters of cerebral blo

Daniela Kaufmann, Jérémy Berthomieu

Formal verification techniques based on computer algebra have proven highly effective for circuit verification. The circuit, given as an and-inverter graph, is encoded as a set of polynomials that automatically generates a Gr\"obner basis with respect to a lexicographic term ordering. Correctness of the circuit can be derived by computing the polynomial rema

L. Zibecchi, I. Andruchow, E. Ej. Marchesini, S. A. Cellone

We present the results of the optical monitoring of 18 southern blazars in the V and R Johnson-Cousins bands. Our main objective is to study the variations in the optical flux and theis relationship with the colour and spectral variabilities. The optical observations were acquired with the 2.15 m "Jorge Sahade" telescope, CASLEO, Argentina.The whole campaign

Manuel Burger, Fedor Sergeev, Malte Londschien, Daphné Chopard

Notable progress has been made in generalist medical large language models across various healthcare areas. However, large-scale modeling of in-hospital time series data - such as vital signs, lab results, and treatments in critical care - remains underexplored. Existing datasets are relatively small, but combining them can enhance patient diversity and impr

Fangkai Jiao, Geyang Guo, Xingxing Zhang, Nancy F. Chen

Preference optimization techniques, such as Direct Preference Optimization (DPO), are frequently employed to enhance the reasoning capabilities of large language models (LLMs) in domains like mathematical reasoning and coding, typically following supervised fine-tuning. These methods rely on high-quality labels for reasoning tasks to generate preference pair

Samuel Blitz, Robert J. Scherrer, Oem Trivedi

Certain holographic dark energy (HDE) models allow for the possibility of a ``long freeze,'' in which the scale factor evolves to a constant in the long-time limit. Here we extend previous calculations by adding a nonrelativistic matter component. The addition of a matter component tends to destroy the long freeze behavior, driving the universe to recollapse

Lingxiao Wang, Jiaxing Zhao

The correlation function observed in high-energy collision experiments encodes critical information about the emitted source and hadronic interactions. While the proton-proton interaction potential is well constrained by nucleon-nucleon scattering data, these measurements offer a unique avenue to investigate the proton-emitting source, reflecting the dynamic

Pol Puigdemont, Enrico Russo, Axel Wassington, Abhijit Das

Graph Neural Networks (GNNs) have shown significant promise in various domains, such as recommendation systems, bioinformatics, and network analysis. However, the irregularity of graph data poses unique challenges for efficient computation, leading to the development of specialized GNN accelerator architectures that surpass traditional CPU and GPU performanc

Yisol Choi, Sangkyung Kwak, Sihyun Yu, Hyungwon Choi

We present BootComp, a novel framework based on text-to-image diffusion models for controllable human image generation with multiple reference garments. Here, the main bottleneck is data acquisition for training: collecting a large-scale dataset of high-quality reference garment images per human subject is quite challenging, i.e., ideally, one needs to manua

Ahmed Heakl, Chaimaa Abi, Rania Hossam, Abdulrahman Mahmoud

The transition from x86 to ARM architecture is becoming increasingly common across various domains, primarily driven by ARM's energy efficiency and improved performance across traditional sectors. However, this ISA shift poses significant challenges, mainly due to the extensive legacy ecosystem of x86 software and lack of portability across proprietary ecosy

Jason Kayembe, Iness Ben Guirat, Jan Tobias Muehlberg

This paper explores the intersection of privacy, cybersecurity, and environmental impacts, specifically energy consumption and carbon emissions, in cloud-based office solutions. We hypothesise that solutions that emphasise privacy and security are typically "greener" than solutions that are financed through data collection and advertising. To test our hypoth

Harris Abdul Majid, Pietro Sittoni, Francesco Tudisco

Foundation models have demonstrated remarkable success across various scientific domains, motivating our exploration of their potential in solar physics. In this paper, we present Solaris, the first foundation model for forecasting the Sun's atmosphere. We leverage 13 years of full-disk, multi-wavelength solar imagery from the Solar Dynamics Observatory, spa

Koki Hashimoto

This paper presents two types of results related to hyperarithmetic analysis. First, we introduce new variants of the dependent choice axiom, namely $\mathrm{unique}~\Pi^1_0(\mathrm{resp.}~\Sigma^1_1)\text{-}\mathsf{DC}_0$ and $\mathrm{finite}~\Pi^1_0(\mathrm{resp.}~\Sigma^1_1)\text{-}\mathsf{DC}_0$. These variants imply $\mathsf{ACA}_0^+$ but do not imply $

Kathrin Seßler, Maurice Fürstenberg, Babette Bühler, Enkelejda Kasneci

The manual assessment and grading of student writing is a time-consuming yet critical task for teachers. Recent developments in generative AI, such as large language models, offer potential solutions to facilitate essay-scoring tasks for teachers. In our study, we evaluate the performance and reliability of both open-source and closed-source LLMs in assessin

Kai Han, Jin Wang, Yunhui Shi, Hanqin Cai

Deep unfolding networks have gained increasing attention in the field of compressed sensing (CS) owing to their theoretical interpretability and superior reconstruction performance. However, most existing deep unfolding methods often face the following issues: 1) they learn directly from single-channel images, leading to a simple feature representation that

Dries Vandenabeele, Nikolaus Doppelhammer, Sambhu Radhakrishnan, Vinod Chandran C.

The development of Hydrated Silicate Ionic Liquids, which are hypo-hydrated room temperature melts of alkali silicates, has created new opportunities for synthesizing porous silicates. Their discovery also allows to reinterpret the role of an ionic liquid for zeolite synthesis and offer unique opportunities to study crystallization in situ. The reduced compl

J. L. Li, Y. Z. Niu, L. P. Qin, X. Q. Li

We propose a postselected amplification (PSA) scheme for phase shift measurement of optical coherent states when passing through the Mach-Zehnder-interferometer (MZI). Different from the usual weak-value-amplification (WVA) formulation, the which-path states of the MZI ($\left| 1 \right\rangle $ and $\left| 2 \right\rangle $) cannot be described as sub-syste

L. B. De Toni, L. F. Ziebell, R. Gaelzer

This study explores the dynamic evolution of dust electrical potential and plasma particle number densities with a focus on the charging of dust grains through electron and ion absorption, as described by the orbital motion limited (OML) theory. The initial model, which does not account for plasma particle sources and sinks, predicts that dust grains could e

Hümeyra Husseini-Wüsthoff, Sabine Riethdorf, Andreas Schneeweiss, Andreas Trumpp

Detection and differentiation of circulating tumor cells (CTCs) and non-CTCs in blood draws of cancer patients pose multiple challenges. While the gold standard relies on tedious manual evaluation of an automatically generated selection of images, machine learning (ML) techniques offer the potential to automate these processes. However, human assessment rema

Xiaozhong Ji, Xiaobin Hu, Zhihong Xu, Junwei Zhu

The study of talking face generation mainly explores the intricacies of synchronizing facial movements and crafting visually appealing, temporally-coherent animations. However, due to the limited exploration of global audio perception, current approaches predominantly employ auxiliary visual and spatial knowledge to stabilize the movements, which often resul

Letian Chen, Yun Tian, Xu Hu, Suya Chen

Understanding the evolution of electrified solid-liquid interfaces during electrochemical reactions is crucial. However, capturing the dynamic behavior of the interfaces with high temporal resolution and accuracy over long timescales remains a major challenge for both experimental and computational techniques. Here, we present a constant potential reactor fr

Ljubica Davidović

We give a review of brackets and interior products in bosonic string theory, in different representations, used in formulation of a theory and derived in a transformation of related mathematical structures. We consider the C-bracket, defined in double string theory, in a context of Poisson algebra of symmetry generator, and show its connection to prior brack

K. Dinar, J. Delgado-Notario, C. Bray, K. Maussang

It has recently been shown that Terahertz sensors can effectively detect the spin resonances of Dirac fermions in graphene. The associated photovoltaic measurement technique allows for the investigation of the intrinsic spin-orbit coupling in graphene as well as its topological properties from microwave to Terahertz frequencies. In this work, using graphene/

Jingchao Peng, Thomas Bashford-Rogers, Zhuang Shao, Haitao Zhao

Infrared (IR) imaging offers advantages in several fields due to its unique ability of capturing content in extreme light conditions. However, the demanding hardware requirements of high-resolution IR sensors limit its widespread application. As an alternative, visible light can be used to synthesize IR images but this causes a loss of fidelity in image deta

Niranjan Rajesh, Georgin Jacob, SP Arun

Despite the rapid pace at which deep networks are improving on standardized vision benchmarks, they are still outperformed by humans on real-world vision tasks. One solution to this problem is to make deep networks more brain-like. Although there are several benchmarks that compare the ability of deep networks to predict brain responses on natural images, th

Jingchao Peng, Thomas Bashford-Rogers, Jingkun Chen, Haitao Zhao

Exposure correction methods aim to adjust the luminance while maintaining other luminance-unrelated information. However, current exposure correction methods have difficulty in fully separating luminance-related and luminance-unrelated components, leading to distortions in color, loss of detail, and requiring extra restoration procedures. Inspired by princip

Débora A. F. Albanez, Maicon J. Benvenutti, Samuel Little, Jing Tian

In this study, we conduct a parameter error analysis for the 3D modified Leray-$\alpha$ model using both analytical and numerical approaches. We first prove the global well-posedness and continuous dependence of initial data for the assimilated system. Furthermore, given sufficient conditions on the physical parameters and norms of the true solution, we demo