February 2025 arXiv papers — page 41

Riasat Ali, Xia Tiecheng, Rimsha Babar

The developments of the $f(R,~T)$ gravity theory, which is a logical expansion of general relativity according to Einstein, inspire us to examine this theory in greater detail and take up our study to obtain a modification of the Kiselev-like AdS black holes scenario. In this study, we employ the semi-classical Hamilton-Jacobi procedure to investigate the Ha

João Pedro Matos-Carvalho, Stefano Frizzo Stefenon, Valderi Reis Quietinho Leithardt, Kin-Choong Yow

Surface contamination on electrical grid insulators leads to an increase in leakage current until an electrical discharge occurs, which can result in a power system shutdown. To mitigate the possibility of disruptive faults resulting in a power outage, monitoring contamination and leakage current can help predict the progression of faults. Given this need, t

Ilja Kuzborskij, Yasin Abbasi Yadkori

We explore the low-rank structure of the weight matrices in neural networks at the stationary points (limiting solutions of optimization algorithms) with $L2$ regularization (also known as weight decay). We show several properties of such deep neural networks, induced by $L2$ regularization. In particular, for a stationary point we show alignment of the para

Giulia Piccirilli, Matteo Zennaro, Carlos García-García, David Alonso

Standard cosmological weak lensing analyses using cosmic shear are inevitably sensitive to small-scale, non-linear clustering from low-redshift structures. The need to adequately model the clustering of matter on this non-linear regime, accounting for both gravitational and baryonic effects, adds significant uncertainty to weak lensing studies, particularly

Johannes Lankeit, Michael Winkler

The basic chemotaxis-consumption model \[ u_t = \Delta u - \nabla \cdot(u\nabla v),\qquad\qquad v_t = \Delta v - uv \] is considered in general, possibly non-convex bounded domains of arbitrary spatial dimension. Global existence of weak solutions is shown, along with eventual smoothness of solutions and their stabilization in the large time limit.

Alexander E. Ulanov, Bastian Ruhnke, Thibault Wildi, Tobias Herr

Squeezed states of light are essential for emerging quantum technology in metrology and information processing. Chip-integrated photonics offers a route to scalable and efficient squeezed light generation, however, parasitic nonlinear processes and optical losses remain significant challenges. Here, we demonstrate single-mode quadrature squeezing in a photon

Hyosik Kang, Raquel Queiroz, Lukas Muechler

Single-photon emitters (SPEs) are crucial for quantum technologies such as quantum simulation, secure quantum communication, and precision measurements. Two-dimensional transition metal dichalcogenides (TMDCs) are promising SPE candidates due to their atomically thin nature and efficient photon extraction. However, their emission wavelengths limit compatibil

Mingxuan Li, Lunwei Zhang, Qiyin Huang, Tiemin Li

Incipient slip detection provides critical feedback for robotic grasping and manipulation tasks. However, maintaining its adaptability under diverse object properties and complex working conditions remains challenging. This article highlights the importance of completely representing spatio-temporal features of slip, and proposes a novel approach for incipie

Kaushik Kudtarkar, Yixin Chen, Ziqiang Cai, Preston Cunha

The quintessential hallmark distinguishing metasurfaces from traditional optical components is the engineering of subwavelength meta-atoms to manipulate light at will. Enabling this freedom, in a reverse manner, to control objects constituted by metasurfaces could expand our capability of optical manipulation to go beyond the predominant microscopic and sub-

Elliot Fox, Aude Gehrmann-De Ridder, Thomas Gehrmann, Nigel Glover

We compute the production rates for two, three, four and five jets in the hadronic decay of a Higgs boson in its two dominant decay modes to bottom quarks and gluons to third order in the QCD coupling constant. The five-, four- and three-jet rates are obtained from a next-to-next-to-leading order (NNLO) calculation of Higgs decay to three jets, while the two

Thomas Dooms, Daniel Wilhelm

Sparse auto-encoders (SAEs) have become a prevalent tool for interpreting language models' inner workings. However, it is unknown how tightly SAE features correspond to computationally important directions in the model. This work empirically shows that many RES-JB SAE features predominantly correspond to simple input statistics. We hypothesize this is caused

Akshay Verma, Richard Sear, Nicholas J. Restrepo, Neil F. Johnson

The sudden emergence of large-scale riots in otherwise unconnected cities across the UK in summer 2024 came as a shock for both government officials and citizens. Irrespective of these riots' specific trigger, a key question is how the capacity for such widespread city rioting might be foreseen through some precursor behavior that flags an emerging appetite

Alberto Battistello, Guido Bertoni, Michele Corrias, Lorenzo Nava

We propose a novel approach for performing side-channel attacks on elliptic curve cryptography. Unlike previous approaches and inspired by the ``activity detection'' literature, we adopt a long-short-term memory (LSTM) neural network to analyze a power trace and identify patterns of operation in the scalar multiplication algorithm performed during an ECDSA s

Wilfrid Gangbo, David Jekel, Kyeongsik Nam, Aaron Z. Palmer

Motivated by parallels between mean field games and random matrix theory, we develop stochastic optimal control problems and viscosity solutions to Hamilton-Jacobi equations in the setting of non-commutative variables. Rather than real vectors, the inputs to the equation are tuples of self-adjoint operators from a tracial von Neumann algebra. The individual

Yen-Ju Lu, Ting-Yao Hu, Hema Swetha Koppula, Hadi Pouransari

In this work, we propose Mutual Reinforcing Data Synthesis (MRDS) within LLMs to improve few-shot dialogue summarization task. Unlike prior methods that require external knowledge, we mutually reinforce the LLM\'s dialogue synthesis and summarization capabilities, allowing them to complement each other during training and enhance overall performances. The di

Inbar Gat, Sigal Raab, Guy Tevet, Yuval Reshef

Generating motion for arbitrary skeletons is a longstanding challenge in computer graphics, remaining largely unexplored due to the scarcity of diverse datasets and the irregular nature of the data. In this work, we introduce AnyTop, a diffusion model that generates motions for diverse characters with distinct motion dynamics, using only their skeletal struc

Sneha Jha, Yaguang Zhang, J. V. Krogmeier, D Buckmaster

On-farm sensor data have allowed farmers to implement field management techniques and intensively track the corresponding responses. These data combined with historical records open the door for real-time field management improvements with the help of current advancements in computing power. However, despite these advances, the statistical design of experime

Alessandro Luongo, Varun Narasimhachar, Adithya Sireesh

Windowed arithmetic [Gidney, 2019] is a technique for reducing the cost of quantum arithmetic circuits with space--time tradeoffs using memory queries to precomputed tables. It can reduce the asymptotic cost of modular exponentiation from $O\left(n^3\right)$ to $O\left(n^3/\log^2 n\right)$ operations, resulting in the current state-of-the-art compilations of

Laura Andrianopoli

I will report on a top-down approach relating N=2, D=4 pure supergravity with non-trivial boundary behavior to a (2+1)-dimensional analog model which is able to describe the electronic properties of graphene-like materials. This is obtained, in a special asymptotic limit, by imposing an unconventional realization of supersymmetry in the D=3 boundary model.

Martin Van Waerebeke, Marco Lorenzi, Giovanni Neglia, Kevin Scaman

Machine Unlearning (MU) aims at removing the influence of specific data points from a trained model, striving to achieve this at a fraction of the cost of full model retraining. In this paper, we analyze the efficiency of unlearning methods and establish the first upper and lower bounds on minimax computation times for this problem, characterizing the perfor

Zifeng Zhuang, Diyuan Shi, Runze Suo, Xiao He

Complex high-dimensional spaces with high Degree-of-Freedom and complicated action spaces, such as humanoid robots equipped with dexterous hands, pose significant challenges for reinforcement learning (RL) algorithms, which need to wisely balance exploration and exploitation under limited sample budgets. In general, feasible regions for accomplishing tasks w

Prafulla Kumar Choubey, Xiangyu Peng, Shilpa Bhagavath, Caiming Xiong

Automated service agents require well-structured workflows to provide consistent and accurate responses to customer queries. However, these workflows are often undocumented, and their automatic extraction from conversations remains unexplored. In this work, we present a novel framework for extracting and evaluating dialog workflows from historical interactio

Yanran Shi, Bo Xie, Fengfan Ren, Xinyu Cai

Fractional quantum anomalous Hall effects realized in twisted bilayer MoTe$_2$ and multilayer-graphene-based moir\'e heterostructures have captured a tremendous growth of interest. In this work, we propose that rhombohedral multilayer graphene coupled with an artificial kagome superlattice potential is a new platform to realize various fractional topological

Xiaoyan Li, Shixin Xu, Faisal Habib, Neda Aminnejad

This study addresses the challenge of reconstructing unseen ECG signals from PPG signals, a critical task for non-invasive cardiac monitoring. While numerous public ECG-PPG datasets are available, they lack the diversity seen in image datasets, and data collection processes often introduce noise, complicating ECG reconstruction from PPG even with advanced ma

M. Bayer, E. Starkenburg, G. F. Thomas, N. Martin

Providing a detailed picture of the Sagittarius (Sgr) stream offers important constraints on the build-up of the Galactic halo as well as its gravitational potential at large radii. While several attempts have been made to model the structure of the Sgr stream, no model has yet been able to match all the features observed for the stream. Moreover, for severa

Clémence Gaunand, Yannick De Wilde, Adrien François, Veneta Grigorova-Moutiers

Understanding heat transfers in fibrous materials, particularly conduction, is a major challenge due to their heterogeneous and multiscale nature, and the unknown contribution of fiber-to-fiber contacts. In most previous modeling studies, the existence of thermal contact resistance is not considered, and the computational complexity limits the size of simula

Filippo Fagioli, Asia Mainenti

The aim of this paper is to gain a better understanding of weak and strong positivity for exterior forms on complex vector spaces. We prove a dimensionality reduction argument for positive forms, which allows us to restrict to the case of $(2,2)$-forms in $\mathbb{C}^4$. In this setting, we find criteria for weak positivity based on the associated Hermitian

Julia Domingues Lemos, Fabio Pereira dos Santos

Turbulent flow remains a challenging subject, despite extensive efforts to find analytical descriptions. Modeling small scales of motion is crucial for saving time and resources in numerical simulations, particularly in industrial applications. Here we attempt to model small scales of motion by creating closures for a Shell model of turbulence, more specific

Haolan Wang, Zhenghao Liu, Xinze Li, Xiaocui Yang

Tabular data contains rich structural semantics and plays a crucial role in organizing and manipulating information. Recent methods employ Multi-modal Large Language Models (MLLMs) to address table-related tasks across various modalities of table representations. However, existing studies mainly focus on exploring the table understanding ability of MLLMs usi

Mateusz Raczyński, Julia Kucharek, Kacper Oreszczuk, Aleksander Rodek

Recent studies have demonstrated that using h-BN as a substrate for the growth of transition metal dichalcogenides can significantly reduce excitonic linewidths. However, many other optical parameters still require optimization. In this work, we present a detailed study of the low-temperature photoluminescence efficiency of MBE-grown MoSe$_2$ monolayers on h

Yu Zhou, Jesús Bautista, Weijia Yao, Héctor García de Marina

Inverse kinematics is a fundamental technique for motion and positioning control in robotics, typically applied to end-effectors. In this paper, we extend the concept of inverse kinematics to guiding vector fields for path following in autonomous mobile robots. The desired path is defined by its implicit equation, i.e., by a collection of points belonging to

Hemanthkumar B., Sumanth Bharadwaj H. S

Recently, several mathematicians have investigated various partition functions with the goal of discovering Ramanujan-type congruences. One such function is $\overline{B}_{2^\alpha}(n)$, which represents the number of $2^\alpha-$regular overpartition pairs of $n$. In this context, we establish Ramanujan-type congruences modulo powers of $2$ for this function

Yuan-Fei Wei, Zhi-Ming Tang, Xue-Ren Huang, Ming-Lu Bu

We present systematic relativistic many-body calculations of multipole transition properties for singly charged aluminum ion (Al II) using a method that combines the configuration interaction and many-body perturbation theory (CI+MBPT). Our calculations cover the 103 lowest energy levels in Al II. For five key low-lying configurations (3s2 1S0, 3s3p 3P0, 3s3

Rohan Chakravarthy, Jonathan Agil, Arijit Sharma, Jung Bog Kim

We demonstrate the effect of Zeeman and hyperfine optical pumping and transverse laser cooling of a dysprosium (Dy) atomic beam on the $4f^{10}6s^2(J = 8) \rightarrow 4f^{10}6s6p(J = 9)$ transition at 421.291 nm. For $^{163}$Dy, an electro-optic modulator is used to generate five frequency sidebands required to pump the atoms to the $F = 10.5$ ground state h

John D. Norton

1. Strong and weak notions of erasure are distinguished according to whether the single erasure procedure does or does not leave the environment in the same state independently of the pre-erasure state. 2. Purely thermodynamic considerations show that strong erasure cannot be dissipationless. 3. The main source of entropy creation in erasure processes at mol

Federico Scarì, Nitin Jonathan Myers, Chen Quan, Arkady Zgonnikov

Accurate environmental perception is critical for advanced driver assistance systems (ADAS). Light detection and ranging (LiDAR) systems play a crucial role in ADAS; they can reliably detect obstacles and help ensure traffic safety. Existing research on LiDAR sensing has demonstrated that adapting the LiDAR's resolution and range based on environmental chara

Zhuoran Li, Chunming Hu, Junfan Chen, Zhijun Chen

Word order difference between source and target languages is a major obstacle to cross-lingual transfer, especially in the dependency parsing task. Current works are mostly based on order-agnostic models or word reordering to mitigate this problem. However, such methods either do not leverage grammatical information naturally contained in word order or are c

Jichen Li, Lijia Xie, Hanting Huang, Bo Zhou

Strategic mining attacks, such as selfish mining, exploit blockchain consensus protocols by deviating from honest behavior to maximize rewards. Markov Decision Process (MDP) analysis faces scalability challenges in modern digital economics, including blockchain. To address these limitations, reinforcement learning (RL) provides a scalable alternative, enabli

Vijay Gopal Thirupakuzi Vangipuram, Chenxi Hu, Abdul Mukit Majumder, Christopher Chae

Orthorhombic-structured II-IV nitrides provide a promising opportunity to expand the material platform while maintaining compatibility with the wurtzite crystal structure of the traditional III-nitride material system. Among them, MgSiN$_{2}$ stands out due to its close compatibility with GaN and AlN and its theoretically predicted ultrawide direct band gap

Liang Ze Wong

In this short position paper, we introduce tensor completions and artifacts and make the case that they are a useful theoretical framework for understanding certain types of hallucinations and generalizations in language models.

Uli Sauerland, Celia Matthaei, Felix Salfner

We argue that human language learning proceeds in a manner that is different in nature from current approaches to training LLMs, predicting a difference in learning biases. We then present evidence from German plural formation by LLMs that confirm our hypothesis that even very powerful implementations produce results that miss aspects of the logic inherent t

Fernando Al Assal, Ben Lowe

A sequence of distinct closed surfaces in a hyperbolic 3-manifold M is asymptotically geodesic if their principal curvatures tend uniformly to zero. When M has finite volume, we show such sequences are always asymptotically dense in the 2-plane Grassmann bundle of M. When M has infinite volume and is geometrically finite, we show such sequences do not exist.

Sudipta Saha, Md. Kawsar Alam

Considerable attention has been directed towards the prognosis of lung diseases primarily due to their high prevalence. Despite advancements in detection technologies, current methods such as computed tomography, chest radiographs, bold proteomic patterns, nuclear magnetic resonance, and positron emission tomography still face limitations in detecting diseas

Aritra Bal, Markus Klute, Benedikt Maier, Melik Oughton

We introduce 1P1Q, a novel quantum data encoding scheme for high-energy physics (HEP), where each particle is assigned to an individual qubit, enabling direct representation of collision events without classical compression. We demonstrate the effectiveness of 1P1Q in quantum machine learning (QML) through two applications: a Quantum Autoencoder (QAE) for un

Xi Cen

This paper refines the main results from our previous study on sparse bounds of generalized commutators of multilinear fractional singular integral operators in \cite{CenSong2412}. The key improvements are: 1. We replace pointwise domination with the $(m+1)$-linear fractional sparse form ${\mathcal A}_{\eta,\mathcal{S},\tau,{\vec{r}},s'}^\mathbf{b,k,t}$, adv

A. Boselli, M. Fossati, Y. Roehlly, P. Amram

The Virgo Environmental Survey Tracing Ionised Gas Emission (VESTIGE) is a blind narrow-band Halpha+[NII] imaging survey of the Virgo cluster carried out with MegaCam at the CFHT telescope. The survey provides deep narrow-band images for 385 galaxies hosting star forming HII regions. We identify individual HII regions and measure their main physical properti

Hao Gu, Wei Li, Lujun Li, Qiyuan Zhu

Mixture-of-Experts (MoE) architectures in large language models (LLMs) achieve exceptional performance, but face prohibitive storage and memory requirements. To address these challenges, we present $D^2$-MoE, a new delta decompression compressor for reducing the parameters of MoE LLMs. Based on observations of expert diversity, we decompose their weights int

Zhenghao Liu, Xingsheng Zhu, Tianshuo Zhou, Xinyi Zhang

With the rapid advancement of Multi-modal Large Language Models (MLLMs), their capability in understanding both images and text has greatly improved. However, their potential for leveraging multi-modal contextual information in Retrieval-Augmented Generation (RAG) remains largely underexplored. To address this gap, this paper introduces Multi-Modal Retrieval

Bart van der Vecht, Atak Talay Yücel, Hana Jirovská, Stephanie Wehner

Recently, a first-of-its-kind operating system for programmable quantum network nodes was developed, called QNodeOS. Here, we present an extension of QNodeOS called Qoala, which introduces (1) a unified program format for hybrid interactive classical-quantum programs, providing a well-defined target for compilers, and (2) a runtime representation of a progra

Laurence Hirsch, Robin Hirsch, Bayode Ogunleye

Text clustering holds significant value across various domains due to its ability to identify patterns and group related information. Current approaches which rely heavily on a computed similarity measure between documents are often limited in accuracy and interpretability. We present a novel approach to the problem based on a set of evolved search queries.

Angelique Taylor, Tauhid Tanjim, Huajie Cao, Jalynn Blu Nicoly

How might healthcare workers (HCWs) leverage augmented reality head-mounted displays (AR-HMDs) to enhance teamwork? Although AR-HMDs have shown immense promise in supporting teamwork in healthcare settings, design for Emergency Department (ER) teams has received little attention. The ER presents unique challenges, including procedural recall, medical errors,

Kevin Michalewicz, Mauricio Barahona, Barbara Bravi

Understanding the intertwined contributions of amino acid sequence and spatial structure is essential to explain protein behaviour. Here, we introduce INFUSSE (Integrated Network Framework Unifying Structure and Sequence Embeddings), a deep learning framework for the prediction of single-residue properties that combines fine-tuning of sequence embeddings der

Louisa Conwill, Megan K. Levis, Karla Badillo-Urquiola, Walter J. Scheirer

HCI is increasingly taking inspiration from religious traditions as a basis for ethical technology designs. Such ethically-inspired designs can be especially important for social communications technologies, which are associated with numerous societal concerns. If religious values are to be incorporated into real-world designs, there may be challenges when d

Yuxiao Wen, Yanjun Han, Zhengyuan Zhou

We study regret minimization in repeated first-price auctions (FPAs), where a bidder observes only the realized outcome after each auction -- win or loss. This setup reflects practical scenarios in online display advertising where the actual value of an impression depends on the difference between two potential outcomes, such as clicks or conversion rates, w

K. I. Tkachenko, P. Fabrykiewicz, A. K. Ovsianikov, M. Meven

Neutron diffraction experiments of TmFeO$_3$ single crystals were performed in the external magnetic fields. The field along $c$-axis increases temperature of spin-reorientation transition $T_{SR}$ from phase ${\Gamma}4$ to ${\Gamma}2$. Application of the field along $b$-axis led to the decrease of $T_{SR}$ and to the formation of new phases. Based on the te

Søren Fournais, Yannick Guedes Bonthonneau, Léo Morin, Nicolas Raymond

The two-dimensional magnetic Laplacian is considered. We calculate the leading term of the splitting between the first two eigenvalues of the operator in the semiclassical limit under the assumption that the magnetic field does not vanish and has two symmetric magnetic wells with respect to the coordinate axes. This is the first result of quantum tunneling b

Soumen Sinha, Tanisha Rana, Susmita Ghosh, Rahul Roy

In this article, we propose a novel approach for plant hierarchical taxonomy classification by posing the problem as an open class problem. It is observed that existing methods for medicinal plant classification often fail to perform hierarchical classification and accurately identifying unknown species, limiting their effectiveness in comprehensive plant ta

Simon Boeder, Fabian Gigengack, Benjamin Risse

Occupancy estimation has become a prominent task in 3D computer vision, particularly within the autonomous driving community. In this paper, we present a novel approach to occupancy estimation, termed GaussianFlowOcc, which is inspired by Gaussian Splatting and replaces traditional dense voxel grids with a sparse 3D Gaussian representation. Our efficient mod

Callum Simpson, Gerard Hall, John S. Duncan, Yujiang Wang

MRI-based delineation of brain tissue removed by epilepsy surgery can be challenging due to post-operative brain shift. In consequence, most studies use manual approaches which are prohibitively time-consuming for large sample sizes, require expertise, and can be prone to errors. We propose RAMPS (Resections And Masks in Preoperative Space), an automated pip

Sabyasachi Chakraborty, Rohit Sarma Sarkar, Sonjoy Majumder

The recent advancements in out-of-time-ordered correlator (OTOC) measurements have provided a promising pathway to explore quantum chaos and information scrambling. However, despite recent advancements, their experimental realization remains challenging due to the complexity of implementing backward time evolution. Here, we present a scalable quantum circuit

Asaf Nachmias, Yuval Peres

A rooted network consists of a connected, locally finite graph G, equipped with edge conductances and a distinguished vertex o. A nonnegative function on the vertices of G which vanishes at o, has Laplacian 1 at o, and is harmonic at all other vertices is called a potential. We prove that every infinite recurrent rooted network admits a potential tending to

Golshid Shekoufandeh, Paul Boersma, Antal van den Bosch

We test and study the variation in speech recognition of fine-tuned versions of the Whisper model on child, elderly and non-native Dutch speech from the JASMIN-CGN corpus. Our primary goal is to evaluate how speakers' age and linguistic background influence Whisper's performance. Whisper achieves varying Word Error Rates (WER) when fine-tuned on subpopulatio

S. Syritsyn, M. Engelhardt, S. Krieg, J. Negele

Proton and neutron electric and magnetic form factors are the primary characteristics of their spatial structure and have been studied extensively over the past half-century. At large values of the momentum transfer $Q^2$ they should reveal transition from nonperturbative to perturbative QCD dynamics as well as effects of quark orbital angular momenta and di

Yi-Kai Zhang, De-Chuan Zhan, Han-Jia Ye

Large Language Models (LLMs) have demonstrated human-like instruction-following abilities, particularly those exceeding 100 billion parameters. The combined capability of some smaller, resource-friendly LLMs can address most of the instructions that larger LLMs excel at. In this work, we explore how to route the best-performing LLM for each instruction to ac

Lars Röhrig, Kevin Kröninger, Romain Madar, Stéphane Monteil

This paper presents a novel tagging technique to measure the beauty-quark partial decay-width ratio $R_b$ and its forward-backward asymmetry $A_\text{FB}^b$ at the FCC-ee, using $\mathcal{O}(10^{12})$ $Z$-boson decays. The method is based on the exclusive reconstruction of a selected list of $b$-hadron decay modes in $Z\to b\bar{b}$ events at the $Z$ pole, w

Jose Manuel Torralba, Alberto Meza, S. Venkatesh Kumaran, Amir Mostafaei

The development of high-entropy alloys (HEAs) has marked a paradigm shift in alloy design, moving away from traditional methods that prioritize a dominant base metal enhanced by minor elements. HEAs instead incorporate multiple alloying elements with no single dominant component, broadening the scope of alloy design. This shift has led to the creation of div

Andraž Repar, Nada Lavrač, Senja Pollak

Automated terminology extraction refers to the task of extracting meaningful terms from domain-specific texts. This paper proposes a novel machine learning approach to terminology extraction, which combines features from traditional term extraction systems with novel contextual features derived from contextual word embeddings. Instead of using a predefined l

Peyman Afshani, Maike Buchin, Anne Driemel, Marena Richter

We propose sublinear algorithms for probabilistic testing of the discrete and continuous Fr\'echet distance - a standard similarity measure for curves. We assume the algorithm is given access to the input curves via a query oracle: a query returns the set of vertices of the curve that lie within a radius $\delta$ of a specified vertex of the other curve. The

V. O. Kozlov, I. A. Smirnov, M. S. Kuznetsova, E. V. Kolobkova

The lead halide perovskite nanocrystals embedded into a glass matrix exhibit strong interaction with light and demonstrate exceptional optical and spin related features along with long-term chemical and physical stability. We apply the spin noise spectroscopy technique which offers a number of specific opportunities to study the spin system of CsPbI$_3$ nano

Elia Zonta, Ivana Jovanovic Buha, Michele Spinola, Christoph Weißinger

The Doyle-Fuller-Newman model is arguably the most ubiquitous electrochemical model in lithium-ion battery research. Since it is a highly nonlinear model, its input-output relations are still poorly understood. Researchers therefore often employ sensitivity analyses to elucidate relative parametric importance for certain use cases. However, some methods are

Daopeng Yin, Liquan Mei

This paper presents stability and accuracy analysis of a high-order explicit time stepping scheme introduced by \cite[Section 2.2]{Buvoli2019}, which exhibits superior stability compared to classical Adams-Bashforth. A conjecture that is supported by several numerical phenomena in \cite[Figure 2.5]{Buvoli2018}, the method appears to remain stable when the ac

Víctor Navarro-Fernández, Christian Seis

We study a passive scalar equation on the two-dimensional torus, where the advecting velocity field is given by a cellular flow with a randomly moving center. We prove that the passive scalar undergoes mixing at a deterministic exponential rate, independent of any underlying diffusivity. Furthermore, we show that the velocity field enhances dissipation and w

Suchona Akter, Mohammad R. Momeni

Two-dimensional layered bronze (HB) materials are a new class of mixed-valence hybrid organic-inorganic metal oxides that demonstrate great potential as advanced functional materials for next-generation electronics. Recently, new hybrid vanadium bronze materials, (EV)V8O20 and (MV)V8O20, EV = ethyl viologen and MV = methyl viologen, have been introduced, wit

Eldar Knar

In the context of scientific policy and science management, this study examines the system of nonuniform wage distribution for researchers. A nonlinear mathematical model of optimal remuneration for scientific workers has been developed, considering key and additive aspects of scientific activity: basic qualifications, research productivity, collaborative pr

Erwan Mahe, Sara Tucci-Piergiovanni

Order fairness in distributed ledgers refers to properties that relate the order in which transactions are sent or received to the order in which they are eventually finalized, i.e., totally ordered. The study of such properties is relatively new and has been especially stimulated by the rise of Maximal Extractable Value (MEV) attacks in blockchain environme

Leonardo Colombo, Manuel de León, María Emma Eyrea Irazú, Asier López-Gordón

Bi-Hamiltonian structures can be utilised to compute a maximal set of functions in involution for certain integrable systems, given by the eigenvalues of the recursion operator relating both Poisson structures. We show that the recursion operator relating two compatible Jacobi structures cannot produce a maximal set of functions in involution. However, as we

Sebastian Steindl, Ulrich Schäfer, Bernd Ludwig

Data scarcity is one of the main problems when it comes to real-world applications of transformer-based models. This is especially evident for task-oriented dialogue (TOD) systems, which require specialized datasets, that are usually not readily available. This can hinder companies from adding TOD systems to their services. This study therefore investigates

F. M. Belchior, R. V. Maluf, A. Yu. Petrov, P. J. Porfírio

In this paper, we investigate black hole solutions in Einstein-Kalb-Ramond (EKR) bumblebee gravity sourced by a global monopole characterized by the charge $\eta$. This modified theory of gravity possesses the notable feature of incorporating local Lorentz symmetry breaking (LSB) via a spontaneous symmetry-breaking mechanism. We solve the field equations for

Juan C. Petit, Matthias Sperl

We present a jamming diagram for 2D bidisperse granular systems, capturing two distinct jamming transitions. The first occurs as large particles form a jammed structure, while the second, emerging at a critical small-particle concentration, $X_{\mathrm{S}}^{*} \approx 0.21$, and size ratio, $\delta^{*} \approx 0.25$, involves small particles jamming into the

Federico Vasile, Elisa Maiettini, Giulia Pasquale, Nicolò Boccardo

Most control techniques for prosthetic grasping focus on dexterous fingers control, but overlook the wrist motion. This forces the user to perform compensatory movements with the elbow, shoulder and hip to adapt the wrist for grasping. We propose a computer vision-based system that leverages the collaboration between the user and an automatic system in a sha

Konstantina Bairaktari, Jiayun Wu, Zhiwei Steven Wu

Conformal prediction is a powerful distribution-free framework for constructing prediction sets with coverage guarantees. Classical methods, such as split conformal prediction, provide marginal coverage, ensuring that the prediction set contains the label of a random test point with a target probability. However, these guarantees may not hold uniformly acros

Arghavan Sanei, Jinghui Cheng

Previous work established that open source software (OSS) projects can benefit from the involvement of UX professionals, who offer user-centric perspectives and contributions to improve software usability. However, their participation in OSS issue discussions (places where design and implementation decisions are often made) is relatively scarce since those p

Chengyin Xu, Kaiyuan Chen, Xiao Li, Ke Shen

The escalating scale and cost of Large Language Models (LLMs) training necessitate accurate pre-training prediction of downstream task performance for comprehensive understanding of scaling properties. This is challenged by: 1) the emergence phenomenon, where unpredictable capabilities appearing suddenly at critical model scales; and 2) uneven task difficult

Ying-Ao Wang, Yunyi Zhang, Ye Zhang

In this paper, we introduce a unified framework, inspired by classical regularization theory, for designing and analyzing a broad class of linear regression approaches. Our framework encompasses traditional methods like least squares regression and Ridge regression, as well as innovative techniques, including seven novel regression methods such as Landweber

Yanmeng Wang, Wenkai Ji, Jian Zhou, Fu Xiao

Federated learning (FL) has emerged as a promising distributed learning paradigm for training deep neural networks (DNNs) at the wireless edge, but its performance can be severely hindered by unreliable wireless transmission and inherent data heterogeneity among clients. Existing solutions primarily address these challenges by incorporating wireless resource

Zhenheng Tang, Xiang Liu, Qian Wang, Peijie Dong

Motivated by reducing the computational and storage costs of LLMs, model compression and KV cache compression have attracted much attention from researchers. However, current methods predominantly emphasize maintaining the performance of compressed LLMs, as measured by perplexity or simple accuracy on tasks of common sense knowledge QA and basic arithmetic r

Tom Sander, Pierre Fernandez, Saeed Mahloujifar, Alain Durmus

Benchmark contamination poses a significant challenge to the reliability of Large Language Models (LLMs) evaluations, as it is difficult to assert whether a model has been trained on a test set. We introduce a solution to this problem by watermarking benchmarks before their release. The embedding involves reformulating the original questions with a watermark

Xiangpeng Yang, Linchao Zhu, Hehe Fan, Yi Yang

Recent advancements in diffusion models have significantly improved video generation and editing capabilities. However, multi-grained video editing, which encompasses class-level, instance-level, and part-level modifications, remains a formidable challenge. The major difficulties in multi-grained editing include semantic misalignment of text-to-region contro

Benedikt Remlein, Massimiliano Esposito, Francesco Avanzini

At the microscopic scale, open chemical reaction networks are described by stochastic reactions that follow mass-action kinetics and are coupled to chemostats. We show that closed chemical reaction networks -- with specific stoichiometries imposed by mass-action kinetics -- behave like open ones in the limit where the abundances of a subset of species become

Fabian Richter, Ulrich Bangert, Friedemann Landmesser, Nicolai Gölz

Time-domain interferometry is an important principle in Fourier transform (FT) and nonlinear femto- to attosecond spectroscopy. To optimize the resolution and sensitivity of this approach, various interferometer stabilization schemes have been developed. Among them, acousto-optical phase modulation (AOPM) of the interferometer arms combined with phase-synchr

Shijie Lin, Boxiang Yun, Wei Shen, Qingli Li

Medical Hyperspectral Imaging (MHSI) offers potential for computational pathology and precision medicine. However, existing CNN and Transformer struggle to balance segmentation accuracy and speed due to high spatial-spectral dimensionality. In this study, we leverage Mamba's global context modeling to propose a dual-stream architecture for joint spatial-spec

Simon Geisler, Tom Wollschläger, M. H. I. Abdalla, Vincent Cohen-Addad

To circumvent the alignment of large language models (LLMs), current optimization-based adversarial attacks usually craft adversarial prompts by maximizing the likelihood of a so-called affirmative response. An affirmative response is a manually designed start of a harmful answer to an inappropriate request. While it is often easy to craft prompts that yield

Xuanliang Zhang, Dingzirui Wang, Keyan Xu, Qingfu Zhu

Question answering on the hybrid context of tables and text (TATQA) is a critical task, with broad applications in data-intensive domains. However, existing TATQA datasets are limited to English, leading to several drawbacks: (i) They overlook the challenges of multilingual TAT-QA and cannot assess model performance in the multilingual setting. (ii) They do

Bo Wang, Hashem Ashrafiuon, Sergey G. Nersesov

This paper investigates extremum seeking control for a torque-controlled antenna pointing system without direct angular measurements. We consider a two-degree-of-freedom (2-DOF) antenna system that receives an unknown signal from its environment, where the signal strength varies with the antenna orientation. It is assumed that only real-time measurements of

Michael V. Davidovich

We consider the linear and nonlinear response of a weighted graphene sheet under the normal incidence of a plane electromagnetic wave in the form of a quasi-monochromatic pulse of long duration with a sharp edge and harmonic filling. The generation of odd harmonics in the reflected and transmitted spectra is obtained. The coefficient of transformation of the

Yanguang Chen

The law of allometric growth originated from biology has been widely used in urban research for a long time. Some conditional research conclusions based on biological phenomena have been erroneously transmitted in the field of urban geography, leading to some misunderstandings. One of the misunderstandings is that allometric analysis must be based on average

Arianna Poli, Simone Fratini, Jennifer Coulter, Andrew J. Millis

We study the interplay of electron-electron and electron-disorder scattering in correlated Fermi liquids by the disordered Hubbard model using dynamical mean-field theory with an IPT-CPA solver. We find significant violations of Matthiessen's rule (additivity of scattering mechanisms) which we explain in terms of the screening of the disorder potential by in

Yufei Lu, Yuetao Li, Zhizhou Jia, Qun Hao

In this letter, we propose a color-assisted robust framework for accurate LiDAR odometry and mapping (LOAM). Simultaneously receiving data from both the LiDAR and the camera, the framework utilizes the color information from the camera images to colorize the LiDAR point clouds and then performs iterative pose optimization. For each LiDAR scan, the edge and p

Boyan Li, Jiayi Zhang, Ju Fan, Yanwei Xu

Text-to-SQL, which enables natural language interaction with databases, serves as a pivotal method across diverse industries. With new, more powerful large language models (LLMs) emerging every few months, fine-tuning has become incredibly costly, labor-intensive, and error-prone. As an alternative, zero-shot Text-to-SQL, which leverages the growing knowledg

Ritika Dhundhwal, Haoran Duan, Lucas Brauch, Soroush Arabi

For practical superconducting quantum processors, orders of magnitude improvement in coherence is required, motivating efforts to optimize hardware design and explore new materials. Among the latter, the coherence of superconducting transmon qubits has been shown to improve by forming the qubit capacitor pads from $\alpha$-tantalum, avoiding the meta-stable