March 2025 arXiv papers — page 4

Karolina Podgórska, Damian Rybicki, Lan Maria Tran, Wojciech Tabiś

Europium-based materials are highly attractive due to their diverse range of physical properties. In these studies, we aimed to synthesize single crystals of the potentially topological semimetallic compound EuAgP, which up to this day has only been obtained in polycrystalline form. The flux method was employed for the syntheses, using fluxes such as: Bi, Sn

Qinyu Li, Yee Whye Teh, Razvan Pascanu

The canonical deep learning approach for learning requires computing a gradient term at each block by back-propagating the error signal from the output towards each learnable parameter. Given the stacked structure of neural networks, where each block builds on the representation of the block below, this approach leads to hierarchical representations. More ab

Prashanti Anderson, Ainesh Bakshi, Mahbod Majid, Stefan Tiegel

We consider the task of privately obtaining prediction error guarantees in ordinary least-squares regression problems with Gaussian covariates (with unknown covariance structure). We provide the first sample-optimal polynomial time algorithm for this task under both pure and approximate differential privacy. We show that any improvement to the sample complex

Wenyan Cong, Hanqing Zhu, Peihao Wang, Bangya Liu

World foundation models, which simulate the physical world by predicting future states from current observations and inputs, have become central to many applications in physical intelligence, including autonomous driving and robotics. However, these models require substantial computational resources for pretraining and are further constrained by available da

J. Josiek, M. Bernini-Peron, G. González-Torà, R. R. Lefever

Current leading theories of physics such as the Big Bang, the standard model of particle physics, and general relativity suggest that the universe should contain an equal amount of matter and antimatter. Yet observations have found a disproportionately large amount of matter, a phenomenon known as the baryon assymmetry problem. Since century-old established

Walter O. Krawec

In this work, we prove security of a quantum conference key agreement (QCKA) protocol augmented with a classical advantage distillation (CAD) protocol. We derive a proof of security, in the finite key setting, that is able to bound the secure key rate for any general, coherent, attack. We evaluate the performance of the system, showing our result can improve

Mesfin Taye

In this study, we advance the understanding of non-equilibrium systems by deriving thermodynamic relations for a heat engine operating under an exponentially decreasing temperature profile. Such thermal configurations closely mimic spatially localized heating such as laser-induced thermal gradients. Using exact analytical solutions, we show that this arrange

Philippe André, Michael Mattern, Doris Arzoumanian, Yoshito Shimajiri

Dense filaments are believed to be representative of the initial conditions of star formation in molecular clouds. We have used the MIRI instrument on JWST to image the massive filament NGC6334M at d~1.3 kpc with unprecedented resolution and dynamic range at 7.7 and 25.5 microns. Our observations reveal the fine structure of the filament in absorption agains

Vivek Sharma, Poulomi Sadhukhan

Fibrinogen, the monomeric unit of fibrin, the main constituent of blood clot, has a very complex structure. The fibrinogen builds the fibrin fiber and network through the half-staggered packing via knob-hole interaction and the $\alpha$C crosslinkers. Due to its rich structure, the elastic behavior also shows a unique nature of very high stretchability and m

Anna O. Schouten, Simon Ewing, David A. Mazziotti

The last several decades have seen significant advances in the theoretical modeling of materials within the fields of solid-state physics and materials science, but many methods commonly applied to this problem struggle to capture strong electron correlation accurately. Recent widespread interest in quantum materials -- where strong correlation plays a cruci

Kumar Sai Bondada, Daniel Jakubisin, R. Michael Buehrer

The main challenges of distributed MIMO systems lie in achieving highly accurate synchronization and ensuring the availability of accurate channel state information (CSI) at distributed nodes. This paper analytically examines the effects of synchronization offsets and CSI feedback delays on system capacity, providing insights into how these affect the cohere

Dawei Ge, Siyuan Liu, Qiang Qiu, Peng Li

We present the first single-channel 1.001-Tb/s DP-36QAM-PCS recirculating transmission over 73 loops of 146.77-km ultra-low-loss & low-IMI DNANF-5 fiber, achieving a record transmission distance of 10,714.28 km.

C. Lovell, M. Lee, A. Vijayan, T. Harvey

The Lyman-break technique has been used to successfully identify high-redshift candidates in broad-band photometric data in the rest-frame optical and NIR using the dropout technique. We pioneer the application of this technique to new wavelength regimes, and search for dropouts in combined ALMA and JWST data. We find a candidate that is undetected in NIRCam

Sofia Guglielmini, Gerda Claeskens, Snigdha Panigrahi

The graphical lasso is a widely used algorithm for fitting undirected Gaussian graphical models. However, for inference on functionals of edge values in the learned graph, standard tools lack formal statistical guarantees, such as control of the type I error rate. We introduce a selective inference method for asymptotically valid inference after graphical la

Alok Abhishek, Lisa Erickson, Tushar Bandopadhyay

In this research, we introduce BEATS, a novel framework for evaluating Bias, Ethics, Fairness, and Factuality in Large Language Models (LLMs). Building upon the BEATS framework, we present a bias benchmark for LLMs that measure performance across 29 distinct metrics. These metrics span a broad range of characteristics, including demographic, cognitive, and s

E. Dartois, J. A. Noble, M. K. McClure, J. A. Sturm

Spectra of the nearly edge-on protoplanetary disks observed with the JWST have shown ice absorption bands of varying optical depths and peculiar profiles, challenging radiative transfer modelling and our understanding of dust and ice in disks. We build models including dust grain size, shape, and composition to reproduce JWST IFU spectroscopy of the large ed

Oliver Johnson

This is a response to the paper "Some statistical aspects of the Covid-19 response" by Wood et al, submitted to the discussion at the read paper meeting of the Royal Statistical Society on 10th April 2025.

Arshia Kermani, Veronica Perez-Rosas, Vangelis Metsis

This study presents a systematic comparison of three approaches for the analysis of mental health text using large language models (LLMs): prompt engineering, retrieval augmented generation (RAG), and fine-tuning. Using LLaMA 3, we evaluate these approaches on emotion classification and mental health condition detection tasks across two datasets. Fine-tuning

Josué Corujo, Paul Horn, Pablo Pérez-Lantero

Given $n>0$, let $S\subset [0,1]^2$ be a set of $n$ points, chosen uniformly at random. Let $R\cup B$ be a random partition, or coloring, of $S$ in which each point of $S$ is included in $R$ uniformly at random with probability $1/2$. Corujo et al.~(JOCO 2023) studied the random variable $M(n)$ equal to the number of points of $S$ that are covered by the rec

Adam Schmidt, Mert Asim Karaoglu, Soham Sinha, Mingang Jang

Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning, and subtask autonomy. Labeled data are essential to enabling algorithms in these downstream tasks since they allow us to quantify and train algorithms. This paper in

Jakub Adamczyk, Jakub Poziemski, Pawel Siedlecki

Small molecules play a critical role in the biomedical, environmental, and agrochemical domains, each with distinct physicochemical requirements and success criteria. Although biomedical research benefits from extensive datasets and established benchmarks, agrochemical data remain scarce, particularly with respect to species-specific toxicity. This work focu

Bonny Y. Wang, Yihao Zhou, William Chen, Nianyi Chen

We use the ASTRID cosmological simulation to forecast massive black hole (MBH) mergers detectable by Laser Interferometer Space Antenna (LISA) down to $z=0$. ASTRID directly models MBH dynamical friction, allowing a realistic tracking of their trajectory. It also incorporates relatively low-mass MBH seeds down to $5\times10^{4} M_{\odot}$, providing a more c

Ramy Takieldin, André Leroy

In this paper, we derive a formula for constructing a generator matrix for the intersection of any pair of linear codes over a finite field. Consequently, we establish a condition under which a linear code has a trivial intersection with another linear code (or its Galois dual). Furthermore, we provide a condition for reversibility and propose a generator ma

Stanislav Burov

We present a systematic method for constructing stochastic processes by modifying simpler, analytically solvable random walks on discrete lattices. Our framework integrates the Doob $h$-transformation with the Montroll defect theory, overcoming the strict constraints associated with each method alone. By combining these two approaches, we map random walks in

James B. Holliday, Darren Blount, Hoang Quan Nguyen, Samee U. Khan

Quantum computing holds transformative potential for optimizing large-scale drone fleet operations, yet its near-term limitations necessitate hybrid approaches blending classical and quantum techniques. This work introduces Quantum Unmanned Aerial Delivery Routing Optimization (QUADRO), a novel hybrid framework addressing the Energy-Constrained Capacitated U

Vikram Singh, Min Sun

Best subset selection in linear regression is well known to be nonconvex and computationally challenging to solve, as the number of possible subsets grows rapidly with increasing dimensionality of the problem. As a result, finding the global optimal solution via an exact optimization method for a problem with dimensions of 1000s may take an impractical amoun

Iovka Boneva, Jose Emilio Labra Gayo, Eric Prud'hommeaux, Katherine Thornton

We formally introduce an inheritance mechanism for the Shape Expressions language (ShEx). It is inspired by inheritance in object-oriented programming languages, and provides similar advantages such as reuse, modularity, and more flexible data modelling. Using an example, we explain the main features of the inheritance mechanism. We present its syntax and fo

Thinesh Thiyakesan Ponbagavathi, Alina Roitberg

Fine-grained understanding of human actions is essential for safe and intuitive human--robot interaction. We study the challenge of recognizing nearly symmetric actions, such as picking up vs. placing down a tool or opening vs. closing a drawer. These actions are common in close human-robot collaboration, yet they are rare and largely overlooked in mainstrea

Carlo Vanoni, Jaeuk Kim, Paul J. Steinhardt, Salvatore Torquato

Stealthy hyperuniform (SHU) many-particle systems are distinguished by a structure factor that vanishes not only at zero wavenumber (as in ``standard'' hyperuniform systems) but also across an extended range of wavenumbers near the origin. We generate disordered SHU packings of identical and `nonoverlapping' spheres in $d$-dimensional Euclidean space using a

Yubo Zhang, Pedro Botelho, Trevor Gordon, Gil Zussman

We consider a decentralized wireless network with several source-destination pairs sharing a limited number of orthogonal frequency bands. Sources learn to adapt their transmissions (specifically, their band selection strategy) over time, in a decentralized manner, without sharing information with each other. Sources can only observe the outcome of their own

U. de Freitas Carneiro da Graça, G. Gil da Silveira, C. Jahnke, A. Lessa

The Brazilian High-Energy Physics (HEP) community has expanded remarkably since its first involvement at CERN and Fermilab in the 1980s. Its recent organization under the Brazilian Network for High-Energy Physics (RENAFAE), since 2008, has further strengthened its scientific and technological goals, particularly in detector instrumentation, computing, and in

Martin Horák, Michal Šmejkal, Martin Kružík

Soft solids with surface energy exhibit complex mechanical behavior, necessitating advanced constitutive models to capture the interplay between bulk and surface mechanics. This interplay has profound implications for material design and emerging technologies. In this work, we set up variational models for bulk-surface elasticity and explore a novel class of

Hayley Ross, Kathryn Davidson, Najoung Kim

Recent work (Ross et al., 2025, 2024) has argued that the ability of humans and LLMs respectively to generalize to novel adjective-noun combinations shows that they each have access to a compositional mechanism to determine the phrase's meaning and derive inferences. We study whether these inferences can instead be derived by analogy to known inferences, wit

Yinzi Xin, Daniel Echeverri, Nemanja Jovanovic, Jonathan Lin

The Photonic Lantern Nuller (PLN) is an instrument concept designed to characterize exoplanets within a single beam-width from its host star. The PLN leverages the spatial symmetry of a mode-selective photonic lantern (MSPL) to create nulled ports, which cancel out on-axis starlight but allow off-axis exoplanet light to couple. The null-depths are limited by

Sergio Barrera Cabodevila, Xiaojian Du, Carlos A. Salgado, Bin Wu

We investigate the impact of quark production on bottom-up thermalization in heavy-ion collisions. First, we extend the parametric estimates of bottom-up thermalization in pure gluon systems by incorporating quark production in the weak-coupling (high-energy) limit. Our analysis reveals that quark production does not alter the qualitative features of the thr

Jingcheng Hu, Yinmin Zhang, Qi Han, Daxin Jiang

We introduce Open-Reasoner-Zero, the first open source implementation of large-scale reasoning-oriented RL training on the base model focusing on scalability, simplicity and accessibility. Through extensive experiments, we demonstrate that a minimalist approach, vanilla PPO with GAE ($\lambda=1$, $\gamma=1$) and straightforward rule-based rewards, without an

Jiacheng Lin, Tian Wang, Kun Qian

We propose Rec-R1, a general reinforcement learning framework that bridges large language models (LLMs) with recommendation systems through closed-loop optimization. Unlike prompting and supervised fine-tuning (SFT), Rec-R1 directly optimizes LLM generation using feedback from a fixed black-box recommendation model, without relying on synthetic SFT data from

Luke Whitehead, Andrew Casey, Richard P. Haley, Petri J. Heikkinen

We have designed and constructed a magnet surrounding a cylindrical volume of superfluid helium-3 to isolate a region of metastable, supercooled A-phase, entirely surrounded by bulk A-phase - isolating the 'bubble' from rough surfaces that can trigger the transition to the stable B-phase. We outline the design of the experimental cell and magnet, and show th

Sonika Jangid, Pavan Kumar Meena, Niraj P. Atale, Rhea Stewart

Superconducting high-entropy alloys (HEAs) present a unique platform for studying the effect of disorder, composition, and crystal structure on superconducting pairing. In this study, we present a comprehensive bulk and microscopic investigation of the rarely observed equiatomic hexagonal HEA Nb-Mo-Ru-Re-Ir using magnetization, resistivity, heat capacity, an

Esteban Cisneros-Garibay, Henry Le Berre, Dimitrios Adam, Spencer H. Bryngelson

The cost of combustion simulations is often dominated by the evaluation of net production rates of chemical species and mixture thermodynamics (thermochemistry). Execution on computing accelerators (XPUs) like graphic processing units (GPUs) can greatly reduce this cost. However, established thermochemistry software is not readily portable to such devices or

James B. Holliday, Darren Blount, Eneko Osaba, Khoa Luu

In this paper, we explore the potential for quantum annealing to solve realistic routing problems. We focus on two NP-Hard problems, including the Traveling Salesman Problem with Time Windows and the Capacitated Vehicle Routing Problem with Time Windows. We utilize D-Wave's Quantum Annealer and Constrained Quadratic Model (CQM) solver within a hybrid framewo

Wesley A. Suttle, Jesse Milzman, Mustafa O. Karabag, Brian M. Sadler

Existing methods for deceptive path planning (DPP) address the problem of designing paths that conceal their true goal from a passive, external observer. Such methods do not apply to problems where the observer has the ability to perform adversarial interventions to impede the path planning agent. In this paper, we propose a novel Markov decision process (MD

Baptiste Courme, Chloé Vernière, Malo Joly, Daniele Faccio

Optimization approaches are ubiquitous in physics. In optics, they are key to manipulating light through complex media, enabling applications ranging from imaging to photonic simulators. In most demonstrations, however, the optimization process is implemented using classical coherent light, leading to a purely classical solution. Here we introduce the concep

Jian Wang, Xin Lan, Jizhe Zhou, Yuxin Tian

Under limited data setting, GANs often struggle to navigate and effectively exploit the input latent space. Consequently, images generated from adjacent variables in a sparse input latent space may exhibit significant discrepancies in realism, leading to suboptimal consistency regularization (CR) outcomes. To address this, we propose \textit{SQ-GAN}, a novel

E. R. Bezerra de Mello, H. F. Santana Mota, W. Oliveira dos Santos

In this paper we investigate the vacuum current associated with a charged bosonic field operator, induced by a cylindrical boundary in the idealized cosmic string spacetime. In this setup we assume that the cylindrical boundary is coaxial with the string, that by its turn carry a magnetic flux along its core. In order to develop this analysis, we calculate t

Annabella Meech, Alastair B. Claringbold, Eva-Maria Ahrer, James Kirk

The formation and migration history of a planet is expected to be imprinted in its atmosphere, in particular its carbon-to-oxygen (C/O) ratio and metallicity. The BOWIE-ALIGN programme is performing a comparative study of JWST spectra of four aligned and four misaligned hot Jupiters, with the aim of characterising their atmospheres and corroborating the link

Steve Awodey, Jacopo Emmenegger

A candidate for the effective 2-topos is proposed and shown to include the effective 1-topos as its subcategory of 0-types.

Zhiyuan Zhou, Pranav Atreya, You Liang Tan, Karl Pertsch

Scalable and reproducible policy evaluation has been a long-standing challenge in robot learning. Evaluations are critical to assess progress and build better policies, but evaluation in the real world, especially at a scale that would provide statistically reliable results, is costly in terms of human time and hard to obtain. Evaluation of increasingly gene

Sewoong Lee, Adam Davies, Marc E. Canby, Julia Hockenmaier

Sparse autoencoders (SAEs) are widely used in mechanistic interpretability research for large language models; however, the state-of-the-art method of using $k$-sparse autoencoders lacks a theoretical grounding for selecting the hyperparameter $k$ that represents the number of nonzero activations, often denoted by $\ell_0$. In this paper, we reveal a theoret

Adrian Skasberg Aasen, Andras Di Giovanni, Hannes Rotzinger, Alexey V. Ustinov

Quantum simulation, the study of strongly correlated quantum matter using synthetic quantum systems, has been the most successful application of quantum computers to date. It often requires determining observables with high precision, for example when studying critical phenomena near quantum phase transitions. Thus, readout errors must be carefully character

Tao Liu, Juhao Wu

This paper systematically investigates the analytic properties of the ratio $f(s)/f(1-s) = X(s)$ based on the Davenport-Heilbronn functional equation $f(s) = X(s)f(1-s)$. We propose a novel method to analyze the distribution of non-trivial zeros through the monotonicity of the ratio $|f(s)/f(1-s)|$. Rigorously proving that non-trivial zeros can only lie on t

Viviana Stasino, Pasquale Mastrovito, Carlo Cosenza, Anna Levochkina

Besides noticeable challenges in implementing low-error single- and two-qubit quantum gates in superconducting quantum processors, the readout technique and analysis are a key factor in determining the efficiency and performance of quantum processors. Being able to efficiently implement quantum algorithms involving entangling gates and asses their output is

Zirui Chen, Xing Hu, Puhua Sun, Xin Xia

Third-party libraries are essential in software development as they prevent the need for developers to recreate existing functionalities. However, vulnerabilities within these libraries pose significant risks to dependent projects. Upgrading dependencies to secure versions is not feasible to neutralize vulnerabilities without patches or in projects with spec

Yizhou Huang, Yihua Cheng, Kezhi Wang

Understanding human motion is crucial for accurate pedestrian trajectory prediction. Conventional methods typically rely on supervised learning, where ground-truth labels are directly optimized against predicted trajectories. This amplifies the limitations caused by long-tailed data distributions, making it difficult for the model to capture abnormal behavio

G. Weaver, M. J. Selfridge, J. M. Setchfield, F. Dresbach

We present the results of a novel classification scheme for all items, objects, concepts, and crucially -- things -- in the known and unknown universe. Our definitions of meat, soup and vegetable are near-exhaustive and represent a new era of scientific discovery within the rapidly-developing field of Arbitrary Classification. While the definitions of vegeta

Francesco Pio Ramunno, Paolo Massa, Vitaliy Kinakh, Brandon Panos

The spatial properties of the solar magnetic field are crucial to decoding the physical processes in the solar interior and their interplanetary effects. However, observations from older instruments, such as the Michelson Doppler Imager (MDI), have limited spatial or temporal resolution, which hinders the ability to study small-scale solar features in detail

Yuelei Li, Hyunjin Kim, Fangneng Zhan, Ri-Zhao Qiu

Objects produce different sounds when hit, and humans can intuitively infer how an object might sound based on its appearance and material properties. Inspired by this intuition, we propose Visual Acoustic Fields, a framework that bridges hitting sounds and visual signals within a 3D space using 3D Gaussian Splatting (3DGS). Our approach features two key mod

Avijit Bera, Leonel Medina Varela, Vinu Sooriyaarachchi, Mustapha Ishak

Intrinsic alignment (IA) of galaxies is a challenging source of contamination in the Cosmic shear (GG) signals. The galaxy intrinsic ellipticity-gravitational shear (IG) correlation is generally the most dominant component of such contamination for cross-correlating redshift bins. The self-calibration (SC) method is one of the most effective techniques to mi

Aurel Bulgac, Ibrahim Abdurrahman, Matthew Kafker, Ionel Stetcu

In nuclei with an odd nucleon number the non-vanishing spin number density is the source of a pseudo-magnetic field, which favors the splitting of the nucleon Cooper pairs. Such an pseudo-magnetic field is generated always in the dynamics of any nucleus, but its effects on Cooper pairs is significantly enhanced in the dynamic evolution of nuclei with an odd

Yixuan Li, Yu Tian, Yipo Huang, Wei Lu

The rapid and unrestrained advancement of generative artificial intelligence (AI) presents a double-edged sword. While enabling unprecedented creativity, it also facilitates the generation of highly convincing content, undermining societal trust. As image generation techniques become increasingly sophisticated, detecting synthetic images is no longer just a

Jian-He Zheng, Jin-Ping Zhu, Wenbin Lu, Bing Zhang

When a relativistic jet is launched following the core-collapse of a star, its interaction with the stellar envelope leads to the formation of a hot cocoon, which produces various viewing-angle-dependent observational phenomena following the breakout from the surface. We study the observational signatures of fast X-ray transient (FXT) EP240414a, which may or

Lars Andersson, Bernardo Araneda

Hermitian non-K\"ahler Einstein 4-manifolds have a quasi-locally conserved charge associated to spin-lowering via Killing spinors, and corresponding to a parameter of the moduli space. This charge is evaluated for all explicitly known examples of gravitational instantons. Generic gravitational perturbations are shown to admit a closed 2-form that measures th

David Cimasoni, Livio Ferretti, Iuliia Popova

The Levine-Tristram signature admits an n-variable extension for n-component links: it was first defined as an integer valued function on $(S^1\setminus\{1\})^n$, and recently extended to the full torus $T^n$. The aim of the present article is to study and use this extended signature. First, we show that it is constant on the connected components of the comp

Krzysztof A. Meissner, Roger Penrose

According to conformal cyclic cosmology (CCC), the currently conventional description of the entire history of the universe (but without an initial inflationary phase) provides but one cosmic aeon of an unending sequence of such aeons, where the future conformal infinity of each aeon joins essentially smoothly to the conformally stretched big bang of the nex

Cosimo Laneve, Alvise Spanò, Dalila Ressi, Sabina Rossi

We present an empirical evaluation of Large Language Models in code understanding associated with non-trivial, semantic-preserving program transformations such as copy propagation or constant folding. Our findings show that LLMs fail to judge semantic equivalence in approximately 41\% of cases when no context is provided and in 29\% when given a simple gener

Umberto Michelucci, Francesca Venturini

Machine learning is vital in high-stakes domains, yet conventional validation methods rely on averaging metrics like mean squared error (MSE) or mean absolute error (MAE), which fail to quantify extreme errors. Worst-case prediction failures can have substantial consequences, but current frameworks lack statistical foundations for assessing their probability

Veronica Castle, Merdeka Miles, Rafael Perez-Vicente, Rodrigo Fernandez-Gonzalez

Tissue boundaries pattern embryos, suppress tumours, and provide directional cues. Tissue boundaries are associated with supracellular cables formed by actin and the molecular motor non-muscle myosin II. Actomyosin cables generate tension that prevents cell mixing. Whether other cellular behaviours contribute to the formation of linear interfaces between cel

Zhengren Wang, Rui Ling, Chufan Wang, Yongan Yu

Modern code generation has made significant strides in functional correctness and execution efficiency. However, these systems often overlook a critical dimension in real-world software development: maintainability. To handle dynamic requirements with minimal rework, we propose MaintainCoder as a pioneering solution. It integrates the Waterfall model, design

Bruno Deprez, Wei Wei, Wouter Verbeke, Bart Baesens

Financial institutions are required by regulation to report suspicious financial transactions related to money laundering. Therefore, they need to constantly monitor vast amounts of incoming and outgoing transactions. A particular challenge in detecting money laundering is that money launderers continuously adapt their tactics to evade detection. Hence, dete

Lorenzo Tronchin, Tommy Löfstedt, Paolo Soda, Valerio Guarrasi

The advancement of generative AI, particularly in medical imaging, confronts the trilemma of ensuring high fidelity, diversity, and efficiency in synthetic data generation. While Generative Adversarial Networks (GANs) have shown promise across various applications, they still face challenges like mode collapse and insufficient coverage of real data distribut

N. S. Gonchar

The state of economic theory and accumulated facts from the different branches of the economic science require to analyze the concept of the description of economy systems. The economic reality generates the problems the solution of that is only possible by a new paradigm of the description of economy system. The classical mathematical economics is based on

Vasco C. Braz, Nuno A. M. Araújo

When amorphous molecular powders are exposed to high humidity levels or temperatures, the particle viscosity increases due to plasticization, promoting the formation of sinter bridges between pairs of particles in contact. Over time, these bridges facilitate particle agglomeration, eventually leading to the formation of a macroscopic cake that alters the mec

Samuel J George

This study investigates the factors that contribute to the forward movement of student desks throughout the school day. We hypothesize that desk movement is influenced not only by classroom floor type but also by the physical characteristics of students, such as height and age. Furthermore, we explore how the subject taught in the classroom (e.g., Science vs

Dominick M. Rowan, John D. Roberts

In an effort to reduce drain on grant funds and decrease unused space in publications, we have developed a Python package for inserting advertisements into the space left empty by corner plots. This novel technique can allow authors to reduce or eliminate publication charges for journals such as MNRAS and ApJ. In order to offset publication costs entirely, w

Karthik Muthineni, Alexander Artemenko, Artjom Grudnitsky, Josep Vidal

The sixth-generation (6G) cellular technology will be deployed with a key feature of Integrated Sensing and Communication (ISAC), allowing the cellular network to map the environment through radar sensing on top of providing communication services. In this regard, the entire network can be considered as a sensor with a broader Field of View (FoV) of the envi

Alexandre Pannier

We establish Burkholder-Davis-Gundy-type inequalities for stochastic Volterra integrals with a completely monotone convolution kernel, which may exhibit singular behaviour at the origin. When the supremum is taken over a finite interval, the upper bound depends linearly on the $L^\gamma$-norm of the kernel, for any $\gamma>2$. We demonstrate the utility of t

Sourav Saha, Suchana Datta, Dwaipayan Roy, Mandar Mitra

A large number of approaches to Query Performance Prediction (QPP) have been proposed over the last two decades. As early as 2009, Hauff et al. [28] explored whether different QPP methods may be combined to improve prediction quality. Since then, significant research has been done both on QPP approaches, as well as their evaluation. This study revisits Hauff

Sergii Kutnii

Grand unification possibilities in Nambu-Jona-Lasinio-like models are studied. To address the problem of vector boson masses and nonrenormalizability of the theory, algebraic formalism encompassing the effective action, Schwinger-Keldysh path integral, and Bogoliubov-Parasiuk-Hepp-Zimmerman renormalization is constructed. A new NJL-like model: the theory of

Maria-Magdalena Wolf, Niklas Krauss, Arwed Schmidt, Frank Diermeyer

Implementing a teleoperation system with its various actors and interactions is challenging and requires an overview of the necessary functions. This work collects all tasks that arise in a control center for an automated vehicle fleet from literature and assigns them to the two roles Remote Operator and Fleet Manager. Focusing on the driving-related tasks o

Nuwan Weeraratne, Lyn Hunt, Jason Kurz

PCA is widely used in health and care research to analyze complex HD datasets, such as patient health records, genetic data, and medical imaging. By reducing dimensionality, PCA helps identify key patterns and trends, which can aid in disease diagnosis, treatment optimization, and the discovery of new biomarkers. However, the primary goal of any dimensional

Sovik Roy, Anushree Pandey, Tushar Kanti Dey, Surajit Sen

Teleportation, a novel scheme, initially posited by Bennett \textit{et.al}, has been studied here in the context of sending a single qutrit from Alice to Bob using two qutrit entangled channels as resources. In this paper we have considered two special two qutrit entangled states, which belong to $SU(3)$ group, as useful resources for teleportation. For the

Gui-Xin Liu, Ting-Long Wang, Yi-Fan Jiang

Recently there has been considerable excitement surrounding the promising realization of high-spin Kitaev material, such as the quasi-2D compound CrI$_3$ and CrGeTe$_3$. However, the stability of quantum spin liquids (QSL) against single ion anisotropy (SIA) in these materials and the global quantum phase diagram of the extended spin-3/2 Kitaev model with fi

Dun Yuan, Hao Zhou, Di Wu, Xue Liu

Large language models (LLMs) have made significant progress in general-purpose natural language processing tasks. However, LLMs are still facing challenges when applied to domain-specific areas like telecommunications, which demands specialized expertise and adaptability to evolving standards. This paper presents a novel framework that combines knowledge gra

Mario Alberto Vallejo Reyes

This study analyzes representative Mexican folk vocal melodies using MIDI feature extraction, examining ambitus, pitch-class entropy, and interval distribution. It also explores the relationship between these features and song popularity, as measured by Spotify plays. The study employs MATLAB and the MIDI Toolbox for extracting musical features and performin

Vito Squicciarini, Irina Mirova, Francis D. Anderson, Zhiyuan He

High angular resolution holds the key to extending our knowledge in several domains of astronomical research. In addition to the development of new instruments, advancements in post-processing algorithms can enhance the performances attainable in an observation, turning archival observations into a treasure. We developed a machine-learning tool, named zoom-i

Hamed Farahani, R. A. Serota

We study decades-long historic distributions of accumulated S\&P500 returns, from daily returns to those over several weeks. The time series of the returns emphasize major upheavals in the markets -- Black Monday, Tech Bubble, Financial Crisis and Covid Pandemic -- which are reflected in the tail ends of the distributions. De-trending the overall gain, we co

Jonathan Dumas, Sébastien Finet, Nathalie Grisey, Ibtissam Hamdane

This paper examines the relationship between system imbalance and several explanatory variables within the French electricity system. The factors considered include lagged imbalance values, observations of renewable energy sources (RES) generation and consumption, and forecasts for RES generation and consumption. The study analyzes the distribution of system

Antonio Maglio

This thesis focuses on developing "stacky" versions of contact structures, extending the classical notion of contact structures on manifolds. A fruitful approach is to study contact structures using line bundle-valued $1$-forms. Specifically, we introduce the notions of $0$ and $+1$-shifted contact structures on Lie groupoids. To define the kernel of a line

Run Yang, Runpeng Dai, Siran Gao, Xiaocheng Tang

Accurate spatial-temporal prediction of network-based travelers' requests is crucial for the effective policy design of ridesharing platforms. Having knowledge of the total demand between various locations in the upcoming time slots enables platforms to proactively prepare adequate supplies, thereby increasing the likelihood of fulfilling travelers' requests

Simon Barthelmé, Fabienne Castell, Alexandre Gaudillière, Clothilde Melot

Exact eigendecomposition of large matrices is very expensive, and it is practically impossible to compute exact eigenvalues. Instead, one may set a more modest goal of approaching the empirical distribution of the eigenvalues, recovering the overall shape of the eigenspectrum. Current approaches to spectral estimation typically work with \emph{moments} of th

Qiyuan Zhang, Fuyuan Lyu, Zexu Sun, Lei Wang

As enthusiasm for scaling computation (data and parameters) in the pretraining era gradually diminished, test-time scaling (TTS), also referred to as ``test-time computing'' has emerged as a prominent research focus. Recent studies demonstrate that TTS can further elicit the problem-solving capabilities of large language models (LLMs), enabling significant b

Justin Lien, Hiroyasu Ando

The Linear Inverse Model (LIM) is a class of data-driven methods that construct approximate linear stochastic models to represent complex observational data. The stochastic forcing can be modeled using either Gaussian white noise or Ornstein-Uhlenbeck colored noise; the corresponding models are called White-LIM and Colored-LIM, respectively. Although LIMs ar

LHC collaboration

By observing collider neutrino interactions of different flavours, the SND@LHC and Faser experiments have shown that the LHC can make interesting contributions to neutrino physics. This document summarizes why the SND@LHC Collaboration intends to continue taking data at the High Luminosity LHC (HL-LHC). The upgraded detector will instrument the regions of bo

Luke Shaw

A numerical integrator for $\dot{x}=f(x)$ is called \emph{stable} if, when applied to the 1D Dahlquist test equation $\dot{x}=\lambda x,\lambda\in\mathbb{C}$ with fixed timestep $h>0$, the numerical solution remains bounded as the number of steps tends to infinity. It is well known that no explicit integrator may remain stable beyond certain limits in $\lamb

Yanzeng Zhang, Xian-Zhu Tang

Hot-cold ablative mixing plasmas are ubiquitous in astrophysical and laboratory systems, where a cold/dense plasma is roughly in pressure balance with a hot/dilute plasma. Examples include the plasma thermal quench during major disruptions in tokamaks, interaction between a central hot-spot and the solid liner in an inertial confinement fusion (ICF) capsule,

Naveen Namashivayam

Compute nodes on modern heterogeneous supercomputing systems comprise CPUs, GPUs, and high-speed network interconnects (NICs). Parallelization is identified as a technique for effectively utilizing these systems to execute scalable simulation and deep learning workloads. The resulting inter-process communication from the distributed execution of these parall

Daichi Otsuka, Shinichi Mae, Ryosuke Yamada, Hirokatsu Kataoka

In the recent years, the research community has witnessed growing use of 3D point cloud data for the high applicability in various real-world applications. By means of 3D point cloud, this modality enables to consider the actual size and spatial understanding. The applied fields include mechanical control of robots, vehicles, or other real-world systems. Alo

Saab Mansour, Leonardo Perelli, Lorenzo Mainetti, George Davidson

In e-commerce, behavioral data is collected for decision making which can be costly and slow. Simulation with LLM powered agents is emerging as a promising alternative for representing human population behavior. However, LLMs are known to exhibit certain biases, such as brand bias, review rating bias and limited representation of certain groups in the popula

Damian Rybicki, Kamila Komędera, Janusz Przewoźnik, Łukasz Gondek

A thorough study of EuZn$_2$P$_2$ single crystals, which were grown from Sn flux, was performed using both bulk (heat capacity, ac susceptibility, dc magnetization, electrical resistivitivity, magnetoresistance) and microscopic (M\"ossbauer spectroscopy) techniques. Electrical resistance and magnetic susceptibility were measured also under high pressure cond

Dingyun Yao, Chao Zhang, Z. Y. Xie, Zhijie Fan

The classical Heisenberg model is one of the most fundamental models in statistical and condensed matter physics. Extensive theoretical and numerical studies suggest that, in two dimensions, this model does not exhibit a finite-temperature phase transition but instead manifests asymptotic freedom. However, some research has also proposed the possibility of a