October 2024 arXiv papers — page 61

Guillermo Arreaga-Garcia

Using a uniform partitioning of cubic cells, we cover the total volume of a $\Lambda$CDM cosmological simulation based on particles. We define a visualisation cell as a spatial extension of the cubic cell, so that we collect all simulation particles contained in this visualisation cell to create a series of Cartesian plots in which the over-density of matter

Antonio D. Montero-Dorta, Sergio Contreras, M. Celeste Artale, Facundo Rodriguez

The large-scale linear halo bias encodes the relation between the clustering of dark-matter (DM) halos and that of the underlying matter density field. Although the primary dependence of bias on halo mass is well understood in the context of structure formation, the physical origins of the multiple additional relations at fixed halo mass, commonly known as s

Andreas Løvendahl Eefsen, Nicholas Erup Larsen, Oliver Glozmann Bork Hansen, Thor Højhus Avenstrup

Accurate time series forecasting is a highly valuable endeavour with applications across many industries. Despite recent deep learning advancements, increased model complexity, and larger model sizes, many state-of-the-art models often perform worse or on par with simpler models. One of those cases is a recently proposed model, FITS, claiming competitive per

Samantha J. Alloo, David M. Paganin, Michelle K. Croughan, Jannis N. Ahlers

A key contribution to X-ray dark-field (XDF) is X-ray diffusion by sample structures smaller than the imaging system's spatial resolution. However, some XDF techniques report that resolvable sample edges also generate XDF. Speckle-based X-ray imaging (SBXI) extracts XDF by analyzing sample-imposed changes to a reference speckle pattern's visibility. We prese

Hongjia H. Chen, Hinke M. Osinga

Mathematical billiards is much like the real game: a point mass, representing the ball, rolls in a straight line on a (perfectly friction-less) table, striking the sides according to the law of reflection. A billiard trajectory is then completely characterised by the number of elastic collisions. The rules of mathematical billiards may be simple, but the pos

Ari Markowitz

We provide algorithms to decide whether a finitely generated subgroup of $\mathrm{SL}_2(\mathbb{R})$ is discrete, solve the constructive membership problem for finitely generated discrete subgroups of $\mathrm{SL}_2(\mathbb{R})$, and compute a fundamental domain for a finitely generated Fuchsian group. These algorithms have been implemented in Magma for grou

Rong-Xin Miao, Zi-Bing Xie

Due to the splitting problem, it is difficult to derive the holographic entanglement entropy for general higher derivative gravity. Inspired by double holography and renormalized entanglement entropy, we develop a method to derive the generalized gravitational entropy for the brane-world higher derivative (BWHD) gravity. Remarkably, this approach is independ

Shilin Lai

This paper sets up a framework to organize anticyclotomic Iwasawa theory in the context of the Gan-Gross-Prasad conjecture for unitary groups. We propose multiple main conjectures depending on archimedean weight interlacing conditions, generalizing phenomena in the anticyclotomic Iwasawa theory of elliptic curves. We also prove an abstract theorem in Galois

Kade M. Heckel, Adrian Weller

With the capability to write convincing and fluent natural language and generate code, Foundation Models present dual-use concerns broadly and within the cyber domain specifically. Generative AI has already begun to impact cyberspace through a broad illicit marketplace for assisting malware development and social engineering attacks through hundreds of malic

Qinsi Wang, Saeed Vahidian, Hancheng Ye, Jianyang Gu

Large language models (LLMs) with billions of parameters have sparked a new wave of exciting AI applications. However, their high computational costs and memory demands during inference pose significant challenges. Adaptive sparse activation inference, which activates only a small number of neurons for each token, offers a novel way to accelerate model infer

José A. Díaz-García, Francisco J. Caro-Lopera

This work studies the distribution of the nonsymmetric matrix $\mathbf{E}^{-1}\mathbf{H}$. This random product is of fundamental interest under the general multivariate linear hypothesis setting. Specifically when $\mathbf{H}$ and $\mathbf{E}$ are seen as the sums of squares and the sums of products due to the hypothesis and due to the error, respectively.

Adam Kabela, Zdeněk Ryjáček, Mária Skyvová, Petr Vrána

We show that every $3$-connected $\{K_{1,3},\Gamma_3\}$-free graph is Hamilton-connected, where $\Gamma_3$ is the graph obtained by joining two vertex-disjoint triangles with a path of length $3$. This resolves one of the two last open cases in the characterization of pairs of connected forbidden subgraphs implying Hamilton-connectedness. The proof is based

Simon Picard, Antonio Paolillo, Gilles Geeraerts, Joël Goossens

This work addresses the problem of exact schedulability assessment in uniprocessor mixed-criticality real-time systems with sporadic task sets. We model the problem by means of a finite automaton that has to be explored in order to check for schedulability. To mitigate the state explosion problem, we provide a generic algorithm which is parameterised by seve

Laura Tenjo-Patiño, Cristian E. Bello, Alcides Montoya Cañola

Quantum computing is a rapidly advancing field with the potential to drive scientific, educational, and technological development. However, it faces a significant shortage of qualified experts, creating an urgent demand for skilled professionals. In Latin America, quantum education remains in its early stages, further widening the regional talent and access

Vickie Chen, Brandon Wang, Joseph D. Peterson

The non-stretching approximation of polymer rheology simplifies a constitutive equation but fundamentally changes its behavior in fast flows, and the circumstances under which fast flows emerge cannot always be predicted a-priori. In this paper, we consider two simple flows for which shear rates are bounded in the original RP model but diverge to infinity in

Gustavo H. Cassemiro, C. David Hinostroza, Leandro Rodrigues de Faria, Daniel A. Mayoh

We studied the effects of point defects and Hg impurities in the electronic properties of bismuth iodide (Bi$_4$I$_4$). Our transport measurements after annealing at different temperatures show that the resistivity of Bi$_4$I$_4$ depends on its thermal history, suggesting that the formation of native defects and impurities can shape the temperature dependenc

Alexandru Malekshahian, Sam Spiro

The following game was introduced in a list of open problems from 1983 attributed to Erd\H{o}s: two players take turns claiming edges of a $K_n$ until all edges are exhausted. Player 1 wins the game if the largest clique that they claim at the end is strictly larger than the largest clique of their opponent; otherwise, Player 2 wins the game. Erd\H{o}s conje

Sergio E. Aguilar-Gutierrez

We study T$^2$-deformations in the DSSYK model \emph{after} performing ensemble averaging, to learn about the properties of its bulk dual geometry according to finite cutoff holography. We first derive the flow equation for generic holographic quantum mechanical systems dual to dilaton gravity theories without requiring AdS asymptotic boundaries, resulting i

Baptiste Desoubrie, Alain Vienne

The Pluto-Charon system is a binary system, characterised by its high mass ratio and its tidally locked synchronous orbit. Surrounding the central binary, four satellites - Styx, Nix, Kerberos and Hydra - follow near-circular and near equatorial orbits. Mutual tidal forces have probably a great influence on their long term dynamics. Several studies have poin

Harish K. Dureppagari, Chiranjib Saha, Harikumar Krishnamurthy, Xiao Feng Wang

The integration of non-terrestrial networks (NTN) into 5G new radio (NR) has opened up the possibility of developing a new positioning infrastructure using NR signals from Low-Earth Orbit (LEO) satellites. Compared to existing Global Navigation Satellite Systems (GNSS), LEO-based cellular positioning offers several advantages, such as a superior link budget,

Enrico M. Zucchelli, Brandon A. Jones

Bayesian estimation with an explicit transitional prior is required for a tracking algorithm to be embedded in most multi-target tracking frameworks. This paper describes a novel approach capable of tracking maneuvering spacecraft with an explicit transitional prior and in a Bayesian framework, with fewer than two observations passes per day. The algorithm s

Shuo Feng, Xuening Wang, Yifan, Shan

When novices fabricate, they start by choosing a workflow (e.g., laser cutting, 3D printing, etc.) and corresponding software from a narrow set they know. As they advance their design, another workflow might better suit their intent, but their models remain committed to the original workflow. This prohibits exploration, which fosters informed decision-making

Kexin Feng, Theodora Chaspari

This study investigates explainable machine learning algorithms for identifying depression from speech. Grounded in evidence from speech production that depression affects motor control and vowel generation, pre-trained vowel-based embeddings, that integrate semantically meaningful linguistic units, are used. Following that, an ensemble learning approach dec

Kexin Feng, Theodora Chaspari

This study investigates clinicians' perceptions and attitudes toward an assistive artificial intelligence (AI) system that employs a speech-based explainable ML algorithm for detecting depression. The AI system detects depression from vowel-based spectrotemporal variations of speech and generates explanations through explainable AI (XAI) methods. It further

E. A. Gallegos, R. Perca Gonzales, J. F. Jesus

We revisit the Keplerian-like parametrization of the two-body problem in Yukawa gravity studied in the literature. Some inconsistencies, which spoil Bertrand's theorem, observed in the $\eta$ parametrization of the true anomaly $\theta$ and in the formulae for the pericenter's advance are resolved. Moreover, inspired in this kind of study, we couple the Buck

Lilian Wanzare, Joel Okutoyi, Maurine Kang'ahi, Mildred Ayere

Kenyan Sign Language (KSL) is the primary language used by the deaf community in Kenya. It is the medium of instruction from Pre-primary 1 to university among deaf learners, facilitating their education and academic achievement. Kenyan Sign Language is used for social interaction, expression of needs, making requests and general communication among persons w

Solmaz Seyed Monir, Dongfang Zhao

The proliferation of fake news on digital platforms has underscored the need for robust and scalable detection mechanisms. Traditional methods often fall short in handling large and diverse datasets due to limitations in scalability and accuracy. In this paper, we propose NexusIndex, a novel framework and model that enhances fake news detection by integratin

Jan P. Williams, J. Nathan Kutz, Krithika Manohar

Model predictive control (MPC) is an industry standard control technique that iteratively solves an open-loop optimization problem to guide a system towards a desired state or trajectory. Consequently, an accurate forward model of system dynamics is critical for the efficacy of MPC and much recent work has been aimed at the use of neural networks to act as d

Muqsit Azeem, Debraj Chakraborty, Sudeep Kanav, Jan Kretinsky

Despite the advances in probabilistic model checking, the scalability of the verification methods remains limited. In particular, the state space often becomes extremely large when instantiating parameterized Markov decision processes (MDPs) even with moderate values. Synthesizing policies for such \emph{huge} MDPs is beyond the reach of available tools. We

Mikhail Semenov, Nayla El-Kork, Sergei N. Yurchenko, Jonathan Tennyson

A new phosphorous mononitride (${}^{31}$P${}^{14}$N, ${}^{31}$P${}^{15}$N) line list PaiN covering infrared, visible and ultraviolet regions is presented. The PaiN line list extending to the $A\,{}^{1}\Pi$ -- $X\,{}^{1}\Sigma^{+}$ vibronic band system, replaces the previous YYLT ExoMol line list for PN. A thorough analysis of high resolution experimental spe

Mahmud Hasan

Zero Trust Architecture (ZTA) represents a transformative approach to modern cybersecurity, directly addressing the shortcomings of traditional perimeter-based security models. With the rise of cloud computing, remote work, and increasingly sophisticated cyber threats, perimeter defenses have proven ineffective at mitigating risks, particularly those involvi

Abhiram Sripat

Mycorrhizal fungi form vast subterranean networks that are critical for plant nutrient uptake, carbon sequestration, and ecosystem resilience. Despite their ecological importance, optimizing these networks for precision agriculture, forestry,and carbon sequestration remains an open challenge, particularly when it comes to understanding the complex molecular

U. Al Khawaja, M. O. D. Alotaibi, L. Al Sakkaf

We investigate the interaction between two flat-top solitons within the cubic-quintic nonlinear Schr\"odinger equation framework. Our study results point towards a significant departure of flat-top solitons collisional characteristics from the conventional behaviors exhibited in the scattering dynamics of two bright solitons. Our investigation outlines speci

CMS Collaboration

Three rare decay processes of the Higgs boson to a $\rho$(770)$^0$, $\phi$(1020), or K$^{*}$(892)$^0$ meson and a photon are searched for using $\sqrt{s}$ = 13 TeV proton-proton collision data collected by the CMS experiment at the LHC. Events are selected assuming the mesons decay into a pair of charged pions, a pair of charged kaons, or a charged kaon and

Noura Chabar, M bark Amghar, Mohamed Amazioug

In this study, we propose a scheme to improve quantum correlations (QCs) between two magnons in a tripartite magnonical system. We use Gaussian interferometric power (GIP) to quantify QCs beyond entanglement. Additionally, Gaussian quantum steering is discussed. We investigate the enhancement of QCs via a squeezing parameter and an optical parametric amplifi

Shrenik Bhansali, Alwin Jin, Tyler Lizzo, Larry Heck

Large language models (LLMs) are essential in natural language processing (NLP) but are costly in data collection, pre-training, fine-tuning, and inference. Task-specific small language models (SLMs) offer a cheaper alternative but lack robustness and generalization. This paper proposes LEGO, a novel technique to extract SLMs from an LLM and recombine them.

Eslam Abdelaleem

The quest for simplification in physics drives the exploration of concise mathematical representations for complex systems. This Dissertation focuses on the concept of dimensionality reduction as a means to obtain low-dimensional descriptions from high-dimensional data, facilitating comprehension and analysis. We address the challenges posed by real-world da

Fernando Abalos, Oscar Reula, David Hilditch

Systems of PDEs comprised of a combination of constraints and evolution equations are ubiquitous in physics. For both theoretical and practical reasons, such as numerical integration, it is desirable to have a systematic understanding of the well-posedness of the Cauchy problem for these systems. Presently we review the use of hyperbolic reductions, in which

Pietro Antonio Grassi, Ondrej Hulik

The BV formalism is a well-established method for analyzing symmetries and quantization of field theories. In this paper we use the BV formalism to derive partition functions of gauge invariant operators up to equations of motions and their redundancies of selected theories. We discuss various interpretations of the results, some dualities and relation to fi

Dániel T. R. Nagy, Csaba Czabán, Bence Bakó, Péter Hága

Recent progress in quantum machine learning has sparked interest in using quantum methods to tackle classical control problems via quantum reinforcement learning. However, the classical reinforcement learning environments often scale to high dimensional problem spaces, which represents a challenge for the limited and costly resources available for quantum ag

Srihari Kamesh Kompella, Kemal Davaslioglu, Yalin E. Sagduyu, Sastry Kompella

Radio frequency (RF) communication has been an important part of civil and military communication for decades. With the increasing complexity of wireless environments and the growing number of devices sharing the spectrum, it has become critical to efficiently manage and classify the signals that populate these frequencies. In such scenarios, the accurate cl

Alberto Espuny Díaz, Emma Hogan, Freddie Illingworth, Lukas Michel

We construct a set of $2^n$ points in $\mathbb{R}^n$ such that all pairwise Manhattan distances are odd integers, which improves the recent linear lower bound of Golovanov, Kupavskii and Sagdeev. In contrast to the Euclidean and maximum metrics, this shows that the odd-distance set problem behaves very differently to the equilateral set problem under the Man

Stuart Pernsteiner, Iavor S. Diatchki, Robert Dockins, Mike Dodds

We present Crux, a cross-language verification tool for Rust and C/LLVM. Crux targets bounded, intricate pieces of code that are difficult for humans to get right: for example, cryptographic modules and serializer / deserializer pairs. Crux builds on the same framework as the mature SAW-Cryptol toolchain, but Crux provides an interface where proofs are phras

Eka Puspita Arumaningtyas, Hasan Al Rasyid, Maria Giovanna Dainotti, Daisuke Yonetoku

The X-ray column density (NHX) of gamma-ray bursts (GRBs) can probe the local environment of their progenitors over a wide redshift range. Previous work has suggested an increasing trend as a function of redshift. The relevance of the current analysis relies on investigating the selection bias method, such as the effect of the X-ray spectrum in high-redshift

Stefano Marchesi, Antonio Iuliano, Elisa Prandini, Paolo Da Vela

We present the results of a multi-wavelength study of blazars selected from the 5th ROMABZCAT catalog. We selected from this sample a subsample of 2435 objects having at least one counterpart in one of the three main archival X-ray catalogs, which is, the fourth release of the XMM-Newton Survey Science Catalogue, the second release of the Chandra Source Cata

Vannkinh Nom, Souhail Bakkali, Muhammad Muzzamil Luqman, Mickaël Coustaty

Developing effective scene text detection and recognition models hinges on extensive training data, which can be both laborious and costly to obtain, especially for low-resourced languages. Conventional methods tailored for Latin characters often falter with non-Latin scripts due to challenges like character stacking, diacritics, and variable character width

Akhil Pandey Akella, Sagnik Ray Choudhury, David Koop, Hamed Alhoori

The reproducibility of scientific articles is central to the advancement of science. Despite this importance, evaluating reproducibility remains challenging due to the scarcity of ground truth data. Predictive models can address this limitation by streamlining the tedious evaluation process. Typically, a paper's reproducibility is inferred based on the avail

Dibyendu Das, Aditya Patankar, Nilanjan Chakraborty, C. R. Ramakrishnan

In this paper, we study the problem of methodically obtaining a sufficient set of kinesthetic demonstrations, one at a time, such that a robot can be confident of its ability to perform a complex manipulation task in a given region of its workspace. Although Learning from Demonstrations has been an active area of research, the problems of checking whether a

Matt Nicholl, Igor Andreoni

The detection of gravitational waves (GWs) has provided a new tool to study the Universe, with the scientific return enriched when combined with established probes: electromagnetic (EM) radiation and energetic particles. Since the groundbreaking detection in 2017 of merging neutron stars producing GW emission, a gamma-ray burst and an optical 'kilonova', the

SHINE Collaboration

We report results from a 2018 pilot run to study the feasibility of nuclear fragmentation measurements with the NA61/SHINE experiment at the CERN SPS. These results are important for the interpretation of the production of light secondary cosmic-ray nuclei (Li, Be, and B) in the Galaxy. The specific focus here is on cross sections important for the productio

Federico Crippa, Danil Fedchenko

This paper considers the problem of ranking objects based on their latent merits using data from pairwise interactions. We allow for incomplete observation of these interactions and study what can be inferred about rankings in such settings. First, we show that identification of the ranking depends on a trade-off between the tournament graph and the interact

Scott Dietrich, Arash Akbari-Sharbaf, James H. Edgar, Alex Roubos

Microwave transmission line spectroscopy is used to observe the integer quantum Hall effect in two samples of monolayer graphene with different geometries that are resistively-coupled to a coplanar waveguide. We find plateaus in transmitted power that do not vary significantly with microwave frequency but are significantly different for two samples due to th

Cléa Chataigner, Afaf Taïk, Golnoosh Farnadi

Large language models (LLMs) are increasingly used as alternatives to traditional search engines given their capacity to generate text that resembles human language. However, this shift is concerning, as LLMs often generate hallucinations, misleading or false information that appears highly credible. In this study, we explore the phenomenon of hallucinations

Ágnes Kúsz

We introduce $\mathsf{WST}^{\beta_n}(K_n)$ as the weighted spanning tree of the complete graph $K_n$ w.r.t. the random electric network of conductances $\{\exp(-\beta_nU_{e})\}_{e\in E(K_n)}$ with $\mathrm{Unif}[0,1]$ i.i.d. $U_e$'s. Moving from $\beta_n\equiv 0$ to faster and faster growing $\beta_n$'s, the model interpolates between the \emph{uniform} and

Melissa Adrian, Jake A. Soloff, Rebecca Willett

Model selection is the process of choosing from a class of candidate models given data. For instance, methods such as the LASSO and sparse identification of nonlinear dynamics (SINDy) formulate model selection as finding a sparse solution to a linear system of equations determined by training data. However, absent strong assumptions, such methods are highly

Dongliang Guo, Mengxuan Hu, Zihan Guan, Junfeng Guo

Large pre-trained models have achieved notable success across a range of downstream tasks. However, recent research shows that a type of adversarial attack ($\textit{i.e.,}$ backdoor attack) can manipulate the behavior of machine learning models through contaminating their training dataset, posing significant threat in the real-world application of large pre

Stephen Bruce Sontz

The principal goal of this paper is to pass all quantum probability formulas to the projective space associated to the complex Hilbert space of a given quantum system, providing a more complete geometrization of quantum theory. Quantum events have consecutive and conditional probabilities, which have been used in the author's previous work to clarify `collap

Bowen Yan, Penghua Chen, Shawn X. Cui

We propose a novel construction of the Floquet 3D toric code and Floquet $X$-cube code through the coupling of spin chains. This approach not only recovers the coupling layer construction on foliated lattices in three dimensions but also avoids the complexity of coupling layers in higher dimensions, offering a more localized and easily generalizable framewor

Mikhail Khenner

A simple model and computation of Moir\'e-regulated composition evolution kinetics of bicomponent nanoclusters is presented. Assuming continuous adsorbate coverage on top of 2D bilayer and Moir\'e potential-driven nanocluster formation at fcc sites of Moir\'e landscape, these sites experience the influx of one component of a bicomponent adsorbate and the out

Ziad Ghanem

We establish the existence of non-stationary solutions to a symmetric system of second-order autonomous differential equations. Our technique is based on the equivariant degree theory and involves a novel characterization of orbit types of maximal kind in the Burnside Ring product of a finite number of basic degrees for the group $O(2) \times \Gamma \times \

Priscilla Canizares, Davide Murari, Carola-Bibiane Schönlieb, Ferdia Sherry

Hamilton's equations of motion form a fundamental framework in various branches of physics, including astronomy, quantum mechanics, particle physics, and climate science. Classical numerical solvers are typically employed to compute the time evolution of these systems. However, when the system spans multiple spatial and temporal scales numerical errors can a

Giuseppe Arbia, Vincenzo Nardelli

In the analysis of large spatial datasets, identifying and treating spatial outliers is essential for accurately interpreting geographical phenomena. While spatial correlation measures, particularly Local Indicators of Spatial Association (LISA), are widely used to detect spatial patterns, the presence of abnormal observations frequently distorts the landsca

Krishnaswami Alladi, Jason Johnson

In the first paper under this title (1977), the first author utilized a duality identity between the largest and smallest prime factors involving the Moebius function, to establish the following result as a consequence of the Prime Number Theorem for Arithmetic Progressions: If $k$ and $\ell$ are positive integers, with $1\le\ell\le k$ and $(\ell, k)=1$, the

Pengyuan Shi, Xiaoyu Wang, Lihao Zhang, Wenqin Song

Magnetoresistance (MR) oscillations serve as a hallmark of intrinsic quantum behavior, traditionally observed only in conducting systems. Here we report the discovery of MR oscillations in an insulating system, the vertical junctions of CrPS$_4$ which is a two dimensional (2D) A-type antiferromagnetic semiconductor. Systematic investigations of MR peaks unde

Sergio E. Aguilar-Gutierrez, Andrew Svesko, Manus R. Visser

We revisit the formalism of $\text{T}\overline{\text{T}}$ deformations for quantum theories that are holographically dual to two-dimensional dilaton-gravity theories with Dirichlet boundary conditions. To better understand the microscopics of de Sitter space, we focus on deformations for which the dual bulk geometry flows from Anti-de Sitter to de Sitter spa

Sudeshna Ganguly, Katsuya Yonehara, Chandrashekhara M Bhat, A. Kent Triplett

Long and short baseline neutrino oscillation experiments, such as DUNE, ANNIE, SBND, demand high precision in reducing systematic errors, particularly those related to neutrino-nucleus interaction cross-sections. The stroboscopic approach offers a method to capture distinct neutrino energy spectra, aiding in the separation of flux and cross-section uncertain

Dmitrii Korshunov

We consider a natural distance function on the period space of a hyperk\"ahler manifold associated to non-holonomic constraints imposed by twistor lines. These metrics were introduced by Verbitsky in the context of the global Torelli theorem for hyperk\"aler manifolds. We show that they are Finsler and explicitly describe their Finsler norms. To achieve this

Mohammad A. Alhejji

A separable version of Ky Fan's majorization relation is proven for a sum of two operators that are each a tensor product of two positive semi-definite operators. In order to prove it, upper bounds are established for the relevant largest eigenvalue sums in terms of the optimal values of certain linear programs. The objective function of these linear program

Rudy Arthur

Community detection, as well as the identification of other structures like core periphery and disassortative patterns, is an important topic in network analysis. While most methods seek to find the best partition of the network according to some criteria, there is a body of results that suggest that a single network can have many good but distinct partition

Vipin Gunda, Archit Mehta

We introduce a modified Weighted Cascade model that integrates asymmetric budgets and product scores, providing new insights into the Generalized Asymmetric Influence Maximization problem, which we establish as NP-hard. Our simulations demonstrate that players with higher budgets possess a distinct advantage in networks characterized by larger diameters, whe

Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux, Arian Hosseini

The dominant paradigm for RLHF is online and on-policy RL: synchronously generating from the large language model (LLM) policy, labelling with a reward model, and learning using feedback on the LLM's own outputs. While performant, this paradigm is computationally inefficient. Inspired by classical deep RL literature, we propose separating generation and lear

Shrihan Agarwal, Aleksandra Ćiprijanović, Brian D. Nord

Modeling strong gravitational lenses is computationally expensive for the complex data from modern and next-generation cosmic surveys. Deep learning has emerged as a promising approach for finding lenses and predicting lensing parameters, such as the Einstein radius. Mean-variance Estimators (MVEs) are a common approach for obtaining aleatoric (data) uncerta

A. E. Lynas-Gray, O. L. Polyansky, J. Tennyson, S. N. Yurchenko

Improved opacities are needed for modelling the atmospheres and evolution of cool carbon-rich stars and extra-solar planets; in particular, contributions made by the astrophysically important propadienediylidene (C$_3$) molecule need, at a minimum, to be determined using a line list which includes all significant transitions in the energy range of interest.

V. P. Goncharov

The large-scale dynamics of heat spots in a thin layer of incompressible rotating fluid under the action of Coriolis and gravity is considered to obtain a simple model of synoptic turbulence. The derivation of equations describing the evolution of the spots is based on the use of the variational principle, perturbation theory, and the assumption of geostroph

Rana Shahout, Cong Liang, Shiji Xin, Qianru Lao

Augmented Large Language Models (LLMs) enhance the capabilities of standalone LLMs by integrating external data sources through API calls. In interactive LLM applications, efficient scheduling is crucial for maintaining low request completion times, directly impacting user engagement. However, these augmentations introduce scheduling challenges due to the ne

Yassine Sekhmani, Bidyut Hazarika, P. Phukon, Alexandre Landry

This paper mainly aims to solve the Anti deSitter Black Holes (AdS BH) under the Barrow entropy under polytropic gas fluid, especially the Chaplygin Gas. First, we develop this last polytropic model in detail to then obtain the possible solutions and thermodynamic conditions on the Energy-Momentum and the Barrow Entropy for spacetimes of spatial dimension $D

Peter Verleijsdonk, Collin Drent, Stella Kapodistria, Willem van Jaarsveld

We consider the key practical challenge of multi-asset maintenance optimization in settings where degradation parameters are heterogeneous and unknown, and must be inferred from degradation data. To address this, we propose scalable methods suitable for complex asset networks. Degradation is modeled as a stochastic shock process, and real-time data are conti

Renan Maneli Mezabarba, Rodrigo Santos Monteiro, Thales Fernando Vilamaior Paiva

This paper uses a net-theoretic approach to convergence spaces, aimed to simplify the description of continuous convergence in order to apply it in problems concerning Homotopy Theory. We present methods for handling homotopies of limit spaces, define fundamental groupoids, and prove a generalized version of the Seifert-van Kampen Theorem for limit spaces.

Adam J. Finley

During the solar cycle, the Sun's magnetic field polarity reverses due to the emergence, cancellation, and advection of magnetic flux towards the rotational poles. Flux emergence events occasionally cluster together, although it is unclear if this is due to the underlying solar dynamo or simply by chance. Regardless of the cause, we aim to characterise how t

Théo Voldoire, Nicolas Chopin, Guillaume Rateau, Robin J. Ryder

Assuming X is a random vector and A a non-invertible matrix, one sometimes need to perform inference while only having access to samples of Y = AX. The corresponding likelihood is typically intractable. One may still be able to perform exact Bayesian inference using a pseudo-marginal sampler, but this requires an unbiased estimator of the intractable likelih

Shenghui Chen, Ruihan Zhao, Sandeep Chinchali, Ufuk Topcu

Strategic coordination between autonomous agents and human partners under incomplete information can be modeled as turn-based cooperative games. We extend a turn-based game under incomplete information, the shared-control game, to allow players to take multiple actions per turn rather than a single action. The extension enables the use of multi-step intent,

Cailean Osborne, Farbod Daneshyan, Runzhi He, Hengzhi Ye

Companies, including market rivals, have long collaborated on the development of open source software (OSS), resulting in a tangle of co-operation and competition known as "open source co-opetition". While prior work investigates open source co-opetition in OSS projects that are hosted by vendor-neutral foundations, we have a limited understanding thereof in

Yushi Hamaguchi, Alex S. L. Tse

We introduce an infinite-horizon, continuous-time portfolio selection problem faced by an agent with periodic S-shaped preference and present bias. The inclusion of a quasi-hyperbolic discount function leads to time-inconsistency and we characterize the optimal portfolio for a pre-committing, naive and sophisticated agent respectively. In the more theoretica

Maryam Dialameh, Hossein Rajabzadeh, Moslem Sadeghi-Goughari, Jung Suk Sim

Precise segmentation of papillary thyroid microcarcinoma (PTMC) during ultrasound-guided radiofrequency ablation (RFA) is critical for effective treatment but remains challenging due to acoustic artifacts, small lesion size, and anatomical variability. In this study, we propose DualSwinUnet++, a dual-decoder transformer-based architecture designed to enhance

Stefanos Pasios, Nikos Nikolaidis

Simulators are indispensable for research in autonomous systems such as self-driving cars, autonomous robots, and drones. Despite significant progress in various simulation aspects, such as graphical realism, an evident gap persists between the virtual and real-world environments. Since the ultimate goal is to deploy the autonomous systems in the real world,

Juan G. Lechuz-Sierra, Ana Elvira H. Martin, Ashok M. Sundaram, Ruben Martinez-Cantin

One of the first tasks we learn as children is to grasp objects based on our tactile perception. Incorporating such skill in robots will enable multiple applications, such as increasing flexibility in industrial processes or providing assistance to people with physical disabilities. However, the difficulty lies in adapting the grasping strategies to a large

Efim Khazanov

A formula for the wavefront of a wave reflected from a diffraction grating with an arbitrary surface profile, as well as with arbitrary non-equidistant and non-parallel grooves was obtained. It was shown that the wavefront of the reflected wave can change significantly when the grating is rotated by 180 degrees around the normal. Surface imperfection and gro

Robin W. Spencer, Samuel M. Otterstrom

Recent studies of human migration have focused on modern issues of international economics, politics, urbanization, or commuting. Here we make use of very large anonymized genealogies which offer quantitative metrics and models before census data became available. In European and North American data from 1400 to 1950 we find two distinct patterns of lifetime

Ashish Khisti, M. Reza Ebrahimi, Hassan Dbouk, Arash Behboodi

We consider multi-draft speculative sampling, where the proposal sequences are sampled independently from different draft models. At each step, a token-level draft selection scheme takes a list of valid tokens as input and produces an output token whose distribution matches that of the target model. Previous works have demonstrated that the optimal scheme (w

Jiahua Liu, Zeyuan Cui, Wenhan Ge, Pengxiang Zhan

CAPTCHAs protect against resource misuse and data theft by distinguishing human activity from automated bots. Advances in machine learning have made traditional image and text-based CAPTCHAs vulnerable to attacks, leading modern CAPTCHAs, such as GeeTest and Akamai, to incorporate behavioral analysis like mouse trajectory detection. Existing bypass technique

Agustina Czenky, Jacob Kesten, Abiel Quinonez, Chelsea Walton

A classical result in quantum topology is that oriented 2-dimensional topological quantum field theories (2-TQFTs) are fully classified by commutative Frobenius algebras. In 2006, Turaev and Turner introduced additional structure on Frobenius algebras, forming what are called extended Frobenius algebras, to classify 2-TQFTs in the unoriented case. This work

Justo Ospino, Daniel Suárez-Urango, Laura M. Becerra, Héctor Hernández

Understanding the role of pressure anisotropy and dissipation is crucial for modelling compact objects' internal structure and observable properties. In this work, we reinterpret local pressure anisotropy in relativistic stellar structures as an additional contribution to the energy density. This perspective enables the formulation of anisotropic equations o

Jiri Mekyska, Zoltan Galaz, Katarina Safarova, Vojtech Zvoncak

Even though the computerised assessment of developmental dysgraphia (DD) based on online handwriting processing has increasing popularity, most of the solutions are based on a setup, where a child writes on a paper fixed to a digitizing tablet that is connected to a computer. Although this approach enables the standard way of writing using an inking pen, it

Paul Howard, Eleftherios Tachtsis

We continue the study of the Erd\H{o}s-Dushnik-Miller theorem (A graph with an uncountable set of vertices has either an infinite independent set or an uncountable clique) in set theory without the axiom of choice. We show that there are three inequivalent versions of this theorem and we give some results about the positions of these versions in the deductiv

Jiaofen Nan, Gaodeng Fan, Kaifan Zhang, Chen Zhao

In the field of medical image analysis, image registration is a crucial technique. Despite the numerous registration models that have been proposed, existing methods still fall short in terms of accuracy and interpretability. In this paper, we present MsMorph, a deep learning-based image registration framework aimed at mimicking the manual process of registe

Somi Aktar, Niyaz Uddin Molla, Farook Rahaman, G. Mustafa

We investigate the astrophysical consequences of black holes in quadratic gravity, characterized by the parameters $S_0$, $S_2$, $m_0$ and $m_2$, in addition to the black hole mass $M$. To evaluate the physical validity of the fundamental quadratic gravity black hole solutions, we analyze their gravitational lensing properties in the strong field regime. Spe

Thomas Iadecola, Srimoyee Sen, Lars Sivertsen

A connection has recently been proposed between periodically driven systems known as Floquet insulators in continuous time and static fermion theories in discrete time. This connection has been established in a $(1+1)$-dimensional free theory, where an explicit mapping between the spectra of a Floquet insulator and a discrete-time Dirac fermion theory has be

Katherine Howitt, Sathvik Nair, Allison Dods, Robert Melvin Hopkins

Humans develop their grammars by making structural generalizations from finite input. We ask how filler-gap dependencies, which share a structural generalization despite diverse surface forms, might arise from the input. We explicitly control the input to a neural language model (NLM) to uncover whether the model posits a shared representation for filler-gap

M. E. Limes, L. Rathbun, E. L. Foley, T. Kornack

Pump and probe scalar atomic magnetometers show incredible potential for real-world, traditionally difficult measurement environments due to their high dynamic range and linearity. Previously, it has been assumed these scalar magnetometer have a flat response across their bandwidth, and flat noise floor. Here we show that standard fitting routines, used to e

Dylan J. Altschuler, Han Huang, Konstantin Tikhomirov

A seminal result of Lee asserts that the Ramsey number of any bipartite $d$-degenerate graph $H$ satisfies $\log r(H) = \log n + O(d)$. In particular, this bound applies to every bipartite graph of maximal degree $\Delta$. It remains a compelling challenge to identify conditions that guarantee that an $n$-vertex graph $H$ has Ramsey number linear in $n$, ind