October 2024 arXiv papers — page 23

Enze Lv, Ning Xi, Yuliang Jin, Wei Li

Quantum critical points ubiquitously emerge in strongly correlated systems, with their influence persisting at finite temperatures and external fields. A paradigmatic example is the quantum Ising magnet, where transverse field $g$ controlling quantum fluctuations can expand the quantum critical point into an extended quantum critical regime. In this work, we

Saeed Mahloujifar, Luca Melis, Kamalika Chaudhuri

Empirical auditing has emerged as a means of catching some of the flaws in the implementation of privacy-preserving algorithms. Existing auditing mechanisms, however, are either computationally inefficient requiring multiple runs of the machine learning algorithms or suboptimal in calculating an empirical privacy. In this work, we present a tight and efficie

Monica Conti, Pietro Galimberti, Stefania Gatti, Andrea Giorgini

We study the Cahn-Hilliard equation with non-degenerate concentration-dependent mobility and logarithmic potential in two dimensions. We show that any weak solution is unique, exhibits propagation of uniform-in-time regularity, and stabilizes towards an equilibrium state of the Ginzburg-Landau free energy for large times. These results improve the state of t

Ashutosh Chaubey, Anoubhav Agarwaal, Sartaki Sinha Roy, Aayush Agrawal

Contextual advertising serves ads that are aligned to the content that the user is viewing. The rapid growth of video content on social platforms and streaming services, along with privacy concerns, has increased the need for contextual advertising. Placing the right ad in the right context creates a seamless and pleasant ad viewing experience, resulting in

Sam Armon, Joanne Beckford, Dillon Hanson, Naomi Krawzik

Classical parking functions are a generalization of permutations that appear in many combinatorial structures. Prime parking functions are indecomposable components such that any classical parking function can be uniquely described as a direct sum of prime ones. In this article, we extend the notion of primeness to three generalizations of classical parking

Yves Brihaye, Fabien Buisseret, Betti Hartmann, Oliver Layfield

We discuss boson stars and black holes with scalar hair in a model where the complex scalar field forming the boson star and the hair on the black hole, respectively, interacts with a real scalar field via a H\'enon-Heiles-type potential. We demonstrate that black holes and boson stars carrying only a real scalar field with cubic self-interaction are possibl

Gaspar Galaz, Jorge González-López, Viviana Guzmán, Hugo Messias

After over three decades of unsuccessful attempts, we report the first detection of molecular gas emission in Malin 1, the largest spiral galaxy observed to date, and one of the most iconic giant low surface brightness galaxies. Using ALMA, we detect significant $^{12}$CO(J=1-0) emission in the galaxy's central region and tentatively identify CO emission acr

Sami Baral, Eamon Worden, Wen-Chiang Lim, Zhuang Luo

The effectiveness of feedback in enhancing learning outcomes is well documented within Educational Data Mining (EDM). Various prior research has explored methodologies to enhance the effectiveness of feedback. Recent developments in Large Language Models (LLMs) have extended their utility in enhancing automated feedback systems. This study aims to explore th

Alex Kaltenbach, Michael Růžička

In this paper, we derive quasi-optimal $\textit{a priori}$ error estimates for the kinematic pressure for a Finite Element (FE) approximation of steady systems of $p$-Navier-Stokes type in the case of shear-thickening, $\textit{i.e.}$, in the case $p>2$, imposing a new mild Muckenhoupt regularity condition.

Shaoke Xi, Jiaqi Gao, Mengqi Liu, Jiamin Cao

With the growing performance requirements on networked applications, there is a new trend of offloading stateful network applications to SmartNICs to improve performance and reduce the total cost of ownership. However, offloading stateful network applications is non-trivial due to state operation complexity, state resource consumption, and the complicated re

Bowen Liu, Haoyang Li, Shuning Wang, Shuo Nie

Out-of-distribution (OOD) generalization in Graph Neural Networks (GNNs) has gained significant attention due to its critical importance in graph-based predictions in real-world scenarios. Existing methods primarily focus on extracting a single causal subgraph from the input graph to achieve generalizable predictions. However, relying on a single subgraph ca

Sroyon Sengupta

\textit{{\small We aim to get an algebraic generalization of Alladi-Johnson's (A-J) work on Duality between Prime Factors and the Prime Number Theorem for Arithmetic Progressions - II, using the Chebotarev Density Theorem (CDT). It has been proved by A-J, that for all positive integers $k,\ell$ such that $1\leq \ell\leq k$ and $(\ell,k)=1$,}} \begin{equation

Weihang Guo, Zachary Kingston, Lydia E. Kavraki

Large Language Models (LLMs) have demonstrated remarkable ability in long-horizon Task and Motion Planning (TAMP) by translating clear and straightforward natural language problems into formal specifications such as the Planning Domain Definition Language (PDDL). However, real-world problems are often ambiguous and involve many complex constraints. In this p

Tudor Jianu, Baoru Huang, Hoan Nguyen, Binod Bhattarai

Endovascular surgical tool reconstruction represents an important factor in advancing endovascular tool navigation, which is an important step in endovascular surgery. However, the lack of publicly available datasets significantly restricts the development and validation of novel machine learning approaches. Moreover, due to the need for specialized equipmen

Ovais Iqbal Shah, Danish Raza Rizvi, Aqib Nazir Mir

Medical image segmentation is pivotal in healthcare, enhancing diagnostic accuracy, informing treatment strategies, and tracking disease progression. This process allows clinicians to extract critical information from visual data, enabling personalized patient care. However, developing neural networks for segmentation remains challenging, especially when pre

Aaron Landesman, Ishan Levy

We give an different proof of our result computing the stable homology of dihedral group Hurwitz spaces. This proof employs more elementary methods, instead of higher algebra.

Xander Byrne, Amy Bonsor, Laura K. Rogers, Christopher J. Manser

As a new generation of large-sky spectroscopic surveys comes online, the enormous data volume poses unprecedented challenges in classifying spectra. Modern unsupervised techniques have the power to group spectra based on their dominant features, circumventing the complete reliance on training data suffered by supervised methods. We outline the use of dimensi

Srinivasan Arunachalam, Sergey Bravyi, Arkopal Dutt

We show an improved inverse theorem for the Gowers-$3$ norm of $n$-qubit quantum states $|\psi\rangle$ which states that: for every $\gamma\geq 0$, if the $\textsf{Gowers}(|\psi \rangle,3)^8 \geq \gamma$ then the stabilizer fidelity of $|\psi\rangle$ is at least $\gamma^C$ for some constant $C>1$. This implies a constant-sample polynomial-time tolerant testi

Jhordan Silveira de Borba, Jonas Maziero

The field of quantum machine learning is a promising way to lead to a revolution in intelligent data processing methods. In this way, a hybrid learning method based on classic kernel methods is proposed. This proposal also requires the development of a quantum algorithm for the calculation of internal products between vectors of continuous values. In order f

Mathew A. Johnson, Jeffrey Oregero

In this paper, we study the nonlinear wave modulation of arbitrary amplitude periodic traveling wave solutions of the Camassa-Holm (CH) equation. Slow modulations of wave trains is often described through Whitham's theory of modulations, which at leading order models the slow evolution of the fundamental wave characteristics (such as the wave's frequency, ma

Qi Liu, Wei Wang, Andrea Santangelo, Lingda Kong

We report a time-resolved analysis of the accreting X-ray pulsar Cen X-3 using observations carried out by NuSTAR, which cover approximately two binary orbits in different intensity states. The pulse profile is relatively stable over the orbital phase and shows energy dependence. It has an obvious double-peaked shape in the energy band below 15 keV -- with t

Shenghao Xie, Wenqiang Zu, Mingyang Zhao, Duo Su

Autoregression in large language models (LLMs) has shown impressive scalability by unifying all language tasks into the next token prediction paradigm. Recently, there is a growing interest in extending this success to vision foundation models. In this survey, we review the recent advances and discuss future directions for autoregressive vision foundation mo

Katharina Brechtelsbauer, Johannes Mögerle, Hans Peter Büchler

Dysprosium atoms have proven to be a promising platform for quantum simulation due to their strong magnetic moment and high tunability of interactions. In this work, we propose Dysprosium atoms for simulating the one-dimensional spin-1 XXZ-Heisenberg model, which is known to have a rich phase diagram including the famous Haldane phase. To realize the model,

Felix Reidt

The ALICE collaboration prepares multiple upgrades to further extend the reach of heavy-ion physics at the LHC. For LHC Run 4 (2030-2033), a Forward Calorimeter (FoCal) system combines a high-granularity electromagnetic silicon-tungsten calorimeter with a conventional hadronic calorimeter leading to an excellent two-shower separation for neutral pion reconst

Tom Stoiber

Topological phases of gapped one-particle Hamiltonians with (anti)-unitary symmetries are classified by strong topological invariants according to the Altland-Zirnbauer table. Those indices are still well-defined in the regime of strong disorder when the spectral gap is replaced by a mobility gap, however, many questions regarding their robustness and existe

James McCrum, Terence P Kee

Conways Game of Life is a cellular automaton noted for its rich, complex, and emergent behavior, which seems qualitatively lifelike it exists within a wider space of different rule-sets of cellular automata none of which have been found to display behaviors that seem as rich as Conways selected example We present here a set of three quantitative tests for li

Majdi Hassan, Nikhil Shenoy, Jungyoon Lee, Hannes Stark

Predicting low-energy molecular conformations given a molecular graph is an important but challenging task in computational drug discovery. Existing state-of-the-art approaches either resort to large scale transformer-based models that diffuse over conformer fields, or use computationally expensive methods to generate initial structures and diffuse over tors

Yingheng Wang, Zichen Wang, Gil Sadeh, Luca Zancato

Self-supervised training of language models (LMs) has seen great success for protein sequences in learning meaningful representations and for generative drug design. Most protein LMs are based on the Transformer architecture trained on individual proteins with short context lengths. Such protein LMs cannot extrapolate to longer proteins and protein complexes

Hanqing Jiang, Liyang Zhou, Zhuang Zhang, Yihao Yu

This paper presents an accurate and robust Structure-from-Motion (SfM) pipeline named LiVisSfM, which is an SfM-based reconstruction system that fully combines LiDAR and visual cues. Unlike most existing LiDAR-inertial odometry (LIO) and LiDAR-inertial-visual odometry (LIVO) methods relying heavily on LiDAR registration coupled with Inertial Measurement Unit

Beatrice Donelli, Stefano Gherardini, Raffaele Marino, Francesco Campaioli

We present a cooperative protocol to charge quantum spin networks up to the highest-energy configuration, in terms of the network's magnetization. The charging protocol leverages spin-spin interactions and the crossing of a phase transition's critical point. Exploiting collective dynamics of the spin network, the cooperative protocol guarantees a precision a

Kimihiro Hasegawa, Wiradee Imrattanatrai, Zhi-Qi Cheng, Masaki Asada

Multimodal systems have great potential to assist humans in procedural activities, where people follow instructions to achieve their goals. Despite diverse application scenarios, systems are typically evaluated on traditional classification tasks, e.g., action recognition or temporal action segmentation. In this paper, we present a novel evaluation dataset,

Aaron Landesman, Ishan Levy

We compute the average number of surjections from class groups of quadratic function fields over $\mathbb F_q(t)$ onto finite odd order groups $H$, once $q$ is sufficiently large. These yield the first known moments of these class groups, as predicted by the Cohen--Lenstra heuristics, apart from the case $H = \mathbb Z/3\mathbb Z$. The key input to this resu

Antonio Rago, Stylianos Loukas Vasileiou, Francesca Toni, Tran Cao Son

Gradual semantics (GS) have demonstrated great potential in argumentation, in particular for deploying quantitative bipolar argumentation frameworks (QBAFs) in a number of real-world settings, from judgmental forecasting to explainable AI. In this paper, we provide a novel methodology for obtaining GS for statement graphs, a form of structured argumentation

Andrea Vaiuso, Marcello Righi, Oier Coretti, Moreno Apicella

Unmanned Aerial Vehicles (UAVs) have become widely used in various fields and industrial applications thanks to their low operational cost, compact size and wide accessibility. However, the noise generated by drone propellers has emerged as a significant concern. This may affect the public willingness to implement these vehicles in services that require oper

Michael Scheutzow, Michael Grinfeld

We consider the deterministic and stochastic versions of a first order non-autonomous differential equation which allows us to discuss the persistence of rivers ("fleuves") under noise.

W. Oliveira dos Santos, E. R. Bezerra de Mello

In this paper we analyze the vacuum bosonic current associated with a massive charged scalar field propagating in a $(D+1)$-dimensional anti-de Sitter (AdS) bulk in the presence of an idealized carrying-magnetic-flux cosmic string and also a brane. We assume that the string is perpendicular to the brane which is parallel to the AdS boundary. The brane divide

Silvia Preda, Matteo Semplice

We propose a level set method to reconstruct unknown surfaces from point clouds, without assuming that the connections between points are known. We consider a variational formulation with a curvature constraint that minimizes the surface area weighted by the distance of the surface from the point cloud. More precisely we solve an equivalent advection-diffusi

Ian T Vidamour, Guru Venkat, Charles Swindells, David Griffin

We describe 'RingSim', a phenomenological agent-based model that allows numerical simulation of magnetic nanowire networks with areas of hundreds of micrometers squared for durations of hundreds of seconds; a practical impossibility for general-purpose micromagnetic simulation tools. In RingSim, domain walls (DWs) are instanced as mobile agents which respond

Carter Blair, Kate Larson, Edith Law

Aligning AI agents with human values is challenging due to diverse and subjective notions of values. Standard alignment methods often aggregate crowd feedback, which can result in the suppression of unique or minority preferences. We introduce Interactive-Reflective Dialogue Alignment, a method that iteratively engages users in reflecting on and specifying t

Veronica Kelsey, Peter Rowley

In the spirit of Conway we define a groupoid starting from projective planes of order $q$, where $q$ is odd. The associated group of these groupoids is then investigated.

Stefano Di Giovacchino

We develop resonance-based low-regularity numerical integrators for stochastic Schr"odinger equations with additive $Q$-Wiener noise, covering both the linear equation with rough potential and the cubic nonlinear case. For the linear problem, we prove strong and almost sure convergence, achieving first-order accuracy in $H^\sigma$ for solutions in $H^{\sigma

Linus Nwankwo, Bjoern Ellensohn, Vedant Dave, Peter Hofer

To ensure the efficiency of robot autonomy under diverse real-world conditions, a high-quality heterogeneous dataset is essential to benchmark the operating algorithms' performance and robustness. Current benchmarks predominantly focus on urban terrains, specifically for on-road autonomous driving, leaving multi-degraded, densely vegetated, dynamic and featu

Rui-zhi Yang, Felix Aharonian

Recent cosmic ray (CR) measurements have revealed unexpected anomalies in secondary CRs, namely deviations from the predictions of the so-called standard Galactic CR paradigm regarding the composition and energy spectra of the products of interactions of primary (accelerated) CRs with interstellar gas: (i) antiparticles (positrons and antiprotons), (ii) ligh

Yahya Ladghami, Brahim Asfour, Amine Bouali, Taoufik Ouali

This paper presents a detailed study of the thermodynamics of charged BTZ black holes using the conformal holographic extended thermodynamics formalism and Tsallis statistics. The cornerstone of our thermodynamic framework is the re-scaling of CFT by the conformal factor, which is considered a thermodynamic parameter. Here, the AdS radius is distinct from th

Grigorii Khvatskii, Nuno Moniz, Khoa Doan, Nitesh V Chawla

The unique characteristics of text data make classification tasks a complex problem. Advances in unsupervised and semi-supervised learning and autoencoder architectures addressed several challenges. However, they still struggle with imbalanced text classification tasks, a common scenario in real-world applications, demonstrating a tendency to produce embeddi

Alex Kalbach, Ted Chinburg

This is an expository paper intended to introduce the polynomial time lattice basis reduction algorithm first described by Arjen Lenstra, Hendrik Lenstra, and L\'aszl\'o Lov\'asz in 1982. We begin by introducing the shortest vector problem, which motivates the underlying components of the LLL algorithm. Then, we introduce the details of the algorithm itself,

Chiara Tarantini, David C. Larbalestier

High critical current density Jc is generally the most important property of any superconductor used for applications. The critical current Ic is most frequently measured by transport 4 probe V-I techniques and the measured Ic is then divided by the cross-sectional area to give the critical current density Jc. This method is normally error-free. Occasionally

Shu Yu, Chaochao Lu

In open-world environments like Minecraft, existing agents face challenges in continuously learning structured knowledge, particularly causality. These challenges stem from the opacity inherent in black-box models and an excessive reliance on prior knowledge during training, which impair their interpretability and generalization capability. To this end, we i

Dimitrios G. Patsatzis, Mario di Bernardo, Lucia Russo, Constantinos Siettos

We present GoRINNs: numerical analysis-informed (shallow) neural networks for the solution of inverse problems of non-linear systems of conservation laws. GoRINNs is a hybrid/blended machine learning scheme based on high-resolution Godunov schemes for the solution of the Riemann problem in hyperbolic Partial Differential Equations (PDEs). In contrast to othe

Matin Mortaheb, Priyanka Kaswan, Sennur Ulukus

Federated learning (FL) is a collaborative approach where multiple clients, coordinated by a parameter server (PS), train a unified machine-learning model. The approach, however, suffers from two key challenges: data heterogeneity and communication overhead. Data heterogeneity refers to inconsistencies in model training arising from heterogeneous data at dif

seyed Mohammad Hosseindokht, SamanehAlsadat Saeedinia

Global stability of the systems has always been vital of importance; however, this concept has not yet been sufficiently developed for the nonlinear systems. This paper extends the Jacobian matrix so that this method be able to seek the criteria to ensure global stability for a special class of nonlinear systems. In this regard, we propose a new analysis met

Artur O. Lopes, Victor Vargas

We will show the central limit theorem for the general one-dimensional lattice where the space of symbols is a compact metric space. We consider the CLT for Lipschitz-Gibbs probabilities and in the proof we use several properties of the Ruelle operator defined on our setting; this will require fixing an {\em a priori probability}. An important issue in the p

Job Guidos, Lucas Kolanz, Davide Lazzati

We present a novel implementation of a soft sphere, discrete elements code to simulate the dynamics of self-gravitating granular materials. The code is used to study the outcome of sub-sonic collisions between self-gravitating rubble piles with masses ranging from $\sim6\times10^{21}$ to $\sim6\times10^{22}$ g. These masses are representative of asteroids an

Luis Enrique Rosas-Hernandez, Jose Luis Cabellos, Angiolo Huamán, Bernardo Mendoza

Atoms within moir\'e bilayers relax in-plane to minimize elastic energy [e.g., Cazeaux et al., J. Elast. 154, 443 (2023)]; such relaxation brings their space group symmetries down to P1. Here, the ab initio second harmonic generation (SHG) of twisted and atomistically optimized hBN bilayers was determined at four twist angles ($\theta=38.21^{\circ}$, $60.00^

Bardia Safaei, Vishal M. Patel

Pre-trained vision-language models (VLMs) like CLIP have demonstrated impressive zero-shot performance on a wide range of downstream computer vision tasks. However, there still exists a considerable performance gap between these models and a supervised deep model trained on a downstream dataset. To bridge this gap, we propose a novel active learning (AL) fra

Sacha Cerf, Benjamin Dayan, Umberto De Ambroggio, Marc Kaufmann

To find a shortest path between two nodes $s_0$ and $s_1$ in a given graph, a classical approach is to start a Breadth-First Search (BFS) from $s_0$ and run it until the search discovers $s_1$. Alternatively, one can start two Breadth-First Searches, one from $s_0$ and one from $s_1$, and alternate their layer expansions until they meet. This bidirectional B

Yudai Kazuno, Masao Mori, Yuka Kaneda, Koki Otaki

We present the findings of a comprehensive and detailed analysis of merger tree data from ultra-high-resolution cosmological $N$-body simulations. The analysis, conducted with a particle mass resolution of $5 \times 10^3 h^{-1} M_{\odot}$ and a halo mass resolution of $10^7 h^{-1} M_{\odot}$, provides sufficient accuracy to suppress numerical artefacts. This

Adrian Iordache, Bogdan Alexe, Radu Tudor Ionescu

We propose a novel teacher-student framework to distill knowledge from multiple teachers trained on distinct datasets. Each teacher is first trained from scratch on its own dataset. Then, the teachers are combined into a joint architecture, which fuses the features of all teachers at multiple representation levels. The joint teacher architecture is fine-tune

Guanjie Wang, Qifeng Liao

It is known that standard stochastic Galerkin methods face challenges when solving partial differential equations (PDEs) with random inputs. These challenges are typically attributed to the large number of required physical basis functions and stochastic basis functions. Therefore, it becomes crucial to select effective basis functions to properly reduce the

Marco Braga, Pranav Kasela, Alessandro Raganato, Gabriella Pasi

Personalization in Information Retrieval (IR) is a topic studied by the research community since a long time. However, there is still a lack of datasets to conduct large-scale evaluations of personalized IR; this is mainly due to the fact that collecting and curating high-quality user-related information requires significant costs and time investment. Furthe

Mohammad Ikbal Hossain, Muhammad Imam Hussain, Ayesha Arobee, Md Nasim Fardous Zim

This study explores the intersection of technological innovation and environmental sustainability in the context of Bitcoin mining. With Bitcoin's growing adoption, concerns surrounding the energy consumption and environmental impact of mining activities have intensified. The study examines the core process of Bitcoin mining, focusing on its energy-inten

Ganna Kudryavtseva

We extend the equivalence by Cockett and Garner between restriction monoids and ample categories to the setting of Boolean range semigroups which are non-unital one-object versions of range categories. We show that Boolean range semigroups are equivalent to ample topological categories where the range map $r$ is open, and \'etale Boolean range semigroups are

Muhammad Bilal, Ameer Hamza, Nadia Malik

Objective: This review aims to analyze the application of natural language processing (NLP) techniques in cancer research using electronic health records (EHRs) and clinical notes. This review addresses gaps in the existing literature by providing a broader perspective than previous studies focused on specific cancer types or applications. Methods: A compreh

Eric Battenberg, RJ Skerry-Ryan, Daisy Stanton, Soroosh Mariooryad

Autoregressive (AR) Transformer-based sequence models are known to have difficulty generalizing to sequences longer than those seen during training. When applied to text-to-speech (TTS), these models tend to drop or repeat words or produce erratic output, especially for longer utterances. In this paper, we introduce enhancements aimed at AR Transformer-based

Rajat, Paramjeet Banger, Sandeep Gautam

We study the collective excitation spectrum of a Raman-induced spin-orbit-coupled spin-1 Bose-Einstein condensate confined in a quasi-one-dimensional harmonic trap while varying either the Raman coupling or quadratic Zeeman term by using the Bogoliubov approach. A few low-lying modes, which can be used to delineate the phase boundaries, are identified by exc

Junlong Chen, Jens Grubert, Per Ola Kristensson

As more applications of large language models (LLMs) for 3D content for immersive environments emerge, it is crucial to study user behaviour to identify interaction patterns and potential barriers to guide the future design of immersive content creation and editing systems which involve LLMs. In an empirical user study with 12 participants, we combine quanti

Divyam R. Kakani, Dineshkumar Subendran, Shivam J. Singh

The comparative study of Proportional-Integral (PI) and Proportional-Integral-Derivative (PID) controllers applied to level and flow control in coupled tank systems is presented in this research work. The coupled tank system, characterized by its nonlinear behavior, was selected due to its relevance in chemical processing industries where precision in liquid

Emiliano Liwski, Fatemeh Mohammadi

We study the realization spaces of matroids and hyperplane arrangements. First, we define the notion of naive dimension for the realization space of matroids and compare it with the expected dimension and the algebraic dimension, exploring the conditions under which these dimensions coincide. Next, we introduce the family of inductively connected matroids an

Chukwudubem Okafor, Jacob Herrin, Catalin R. Picu, Tommy Sewell

Meso-scale calculations of pore collapse and hotspot formation in energetic crystals provide closure models to macro-scale hydrocodes for predicting the shock sensitivity of energetic materials. To this end, previous works obtained atomistics-consistent material models for two common energetic crystals, HMX and RDX, such that pore collapse calculations adher

R. Flores-Calderón, C. Hooley

We present a model in which a Hatsugai-Kohmoto interaction is added to a system of fermions with a Weyl point in their non-interacting dispersion relation, and analyze its behavior as a function of the chemical potential. We show that the model exhibits a Weyl-Mott point -- a single isolated Green's function zero -- and that this implies an emergent non-Ferm

Yang Li, Gábor Székelyhidi

We study singularities along the Lagrangian mean curvature flow with tangent flows given by multiplicity one special Lagrangian cones that are smooth away from the origin. Some results are: uniqueness of all such tangent flows in dimension two; uniqueness in any dimension when the link of the cone is connected; the existence of nontrivial special Lagrangian

Jonathan Dechert, Svetlana Gurevich, Stefan Heusler

Visual models play a crucial role in both science and science communication. However, the distinction between mere analogies and mathematically sound graphical representations is not easy and can be misunderstood not only by laypeople but also within academic literature itself. Moreover, even when the graphical representation exactly corresponds to the mathe

F. Iraci, A. Chalumeau, C. Tiburzi, J. P. W. Verbiest

Radio pulsars allow the study of the ionised interstellar medium and its dispersive effects, a major noise source in gravitational wave searches using pulsars. In this paper, we compare the functionality and reliability of three commonly used schemes to measure temporal variations in interstellar propagation effects in pulsar-timing data. We carry out extens

Ibrahima Dione

When solving rank-deficient or discrete ill-posed problems by regularization methods, the choice of the regularization parameter is crucial. It is also of interest, the regularization norm used in the selection of the solution. In this work, we propose a stabilization of the existing regularization methods to address the delicate task of choosing this parame

Harsh Aggarwal, Nirmal Raj

In direct searches of dark matter, multi-scatter signatures are now being sought to probe scattering cross sections that are large enough to make the detector optically thick to incident particles. We provide some significant updates to the multi-scatter program. Using considerations of energy deposition, we derive the reaches in cross section and mass of va

Amogh Akella

In this paper, we explore how to leverage large language models (LLMs) to solve mathematical problems efficiently and accurately. Specifically, we demonstrate the effectiveness of classifying problems into distinct categories and employing category-specific problem-solving strategies to improve the mathematical performance of LLMs. We design a simple yet int

J. Greenfield, C. Bell, F. Faramarzi, C. Kim

We report on the fabrication and characterization of superconducting magnesium diboride (MgB$_2$) thin films intended for quantum-limited devices based non-linear kinetic inductance (NLKI) such as parametric amplifiers with either elevated operating temperatures or expanded frequency ranges. In order to characterize the MgB$_2$ material properties, we have f

Holger Gies, Marta Picciau

We investigate a class of quantum field theories with relativistic Luttinger fermions and local self-interaction in scalar channels. For an understanding of possible low-energy phases, we first classify the set of mass terms arising from scalar fermion bilinears. For large flavor numbers, we show that each of our models features a coupling branch in which th

Koen Ponse, Aske Plaat, Niki van Stein, Thomas M. Moerland

Accurate economic simulations often require many experimental runs, particularly when combined with reinforcement learning. Unfortunately, training reinforcement learning agents in multi-agent economic environments can be slow. This paper introduces EconoJax, a fast simulated economy, based on the AI economist. EconoJax, and its training pipeline, are comple

Priyanka Mondal, Daria I. Markina, Lennard Hopf, Lukas Krelle

Semiconducting CrSBr is a layered A-type antiferromagnet, with individual layers antiferromagnetically coupled along the stacking direction. Due to its unique orthorhombic crystal structure, CrSBr exhibits highly anisotropic mechanical and optoelectronic properties acting itself as a quasi-1D material. CrSBr demonstrates complex coupling phenomena involving

Salvatore Federico, Sebastian Holthausen, Nina J. Husemann, Patrizio Neff

We recall in this note that the induced tangent stiffness tensor $\mathbb{H}^{\text{ZJ}}_{\tau}(\tau)$ appearing in a hypoelastic formulation based on the Zaremba-Jaumann corotational derivative and the rate constitutive equation for the Kirchhoff stress tensor $\tau$ is minor and major symmetric if the Kirchhoff stress $\tau$ is derived from an elastic pote

G. Maciejewski, J. Golonka, M. Fernandez, J. Ohlert

Statistical studies show that stars of GK spectral types, with masses below 1.1 Sun mass, are depleted in hot Jupiters. This finding is evidence of tidal orbital decay during the main-sequence lifetime. Theoretical considerations show that in some configurations, the tidal energy dissipation can be boosted by non-linear effects in dynamical tides, which are

F. M. Watson, W. R. B. Lionheart, J. Hellier

In complex-valued coherent inverse problems such as synthetic aperture radar (SAR), one may often have prior information only on the magnitude image which shows the features of interest such as strength of reflectivity. In contrast, there may be no more prior knowledge of the phase beyond it being a uniform random variable. However, separately regularising t

Jiaxuan Gong, Hendrik Roch, Chun Shen

We develop a generative model for the nuclear matter equation of state at zero net baryon density using the Gaussian Process Regression method. We impose first-principles theoretical constraints from lattice QCD and hadron resonance gas at high- and low-temperature regions, respectively. By allowing the trained Gaussian Process Regression model to vary freel

Aaron Haag, Bertram Fuchs, Altay Kacan, Oliver Lohse

IEC 61131-3 Structured Text (ST) is a widely used programming language for programmable logic controllers (PLCs) in automation systems. However, generating ST code with LLMs poses unique challenges due to limited data in public training datasets and the complexity of ST language syntax. This paper proposes an approach to fine-tune LLMs for the generation of

Rokas Silkinis, Marek Maciaszek, Vytautas Žalandauskas, Marianne Etzelmüller Bathen

In this work, we present a first-principles density functional theory (DFT) computational investigation of the luminescence and absorption lineshapes associated with the neutral carbon-oxygen interstitial pair (CiOi) defect in silicon. We obtain the lineshapes of the defect in the dilute limit using a computational methodology that constructs dynamical matri

Llorenç Escolà-Farràs, Léo Colisson Palais, Florian Speelman

We introduce a quantum cloning game in which $k$ separate collaborative parties receive a classical input, determining which of them has to share a maximally entangled state with an additional party (referee). We provide the optimal winning probability of such a game for every number of parties $k$, and show that it decays exponentially when the game is play

Qia Shen, Jiaxin Chen, Bin Rong, Yaqi Rong

Nonlinear Hall effect (NLHE) offers a novel means of uncovering symmetry and topological properties in quantum materials, holding promise for exotic (opto)electronic applications such as microwave rectification and THz detection. The BCD-independent NLHE could exhibit a robust response even at room temperature, which is highly desirable for practical applica

H. Umehata, C. C. Steidel, I. Smail, A. M. Swinbank

In the present-day universe, the most massive galaxies are ellipticals located in the cores of galaxy clusters, harboring the heaviest super-massive black holes (SMBHs). However the mechanisms that drive the early growth phase and subsequent transformation of these morphology and kinematics of galaxies remain elusive. Here we report (sub)kiloparsec scale obs

Mattia Cielo, Gianpiero Mangano, Ofelia Pisanti, David Wands

Sudden phase transitions during inflation can give rise to strongly enhanced primordial density perturbations on scales much smaller than those directly probed by cosmic microwave background anisotropies. In this paper, we study the effect of the incoming quantum state on the steepest growth found in the primordial power spectrum using a simple model of an i

Yahan Yang, Soham Dan, Dan Roth, Insup Lee

With the ubiquity of Large Language Models (LLMs), guardrails have become crucial to detect and defend against toxic content. However, with the increasing pervasiveness of LLMs in multilingual scenarios, their effectiveness in handling multilingual toxic inputs remains unclear. In this work, we introduce a comprehensive multilingual test suite, spanning seve

Zhongyang Li

In 2003, Kahn conjectured a characterization of the critical percolation probability $p_c$ in terms of vertex cut sets (\cite{JK03}). Later, Lyons and Peres (2016) conjectured a similar characterization of $p_c$ , but in terms of edge cut sets (\cite{LP16}). Both conjectures were subsequently proven by Tang (\cite{pt23}) for bond percolation and site percola

Jonghong Jeon

Artificial Intelligence (AI) has rapidly evolved over the past decade and has advanced in areas such as language comprehension, image and video recognition, programming, and scientific reasoning. Recent AI technologies based on large language models and foundation models are approaching or surpassing artificial general intelligence. These systems demonstrate

Nancy Thomas, Saba Rahimi, Annita Vapsi, Cathy Ansell

Amidst escalating climate change, hurricanes are inflicting severe socioeconomic impacts, marked by heightened economic losses and increased displacement. Previous research utilized nighttime light data to predict the impact of hurricanes on economic losses. However, prior work did not provide a thorough analysis of the impact of combining different techniqu

Raman Dutt, Pedro Sanchez, Ondrej Bohdal, Sotirios A. Tsaftaris

In this work, we present compelling evidence that controlling model capacity during fine-tuning can effectively mitigate memorization in diffusion models. Specifically, we demonstrate that adopting Parameter-Efficient Fine-Tuning (PEFT) within the pre-train fine-tune paradigm significantly reduces memorization compared to traditional full fine-tuning approac

Enrico Bothmann, Lois Flower, Christian Gütschow, Stefan Höche

Sherpa is a general-purpose Monte Carlo event generator for the simulation of particle collisions in high-energy collider experiments. We summarise new developments, essential features, and ongoing improvements within the Sherpa 3 release series. Physics improvements include higher-order electroweak corrections, simulations of photoproduction and hard diffra

Katrin Halbig, Timm Oertel, Dieter Weninger

Strict inequalities in mixed-integer linear optimization can cause difficulties in guaranteeing convergence and exactness. Utilizing that optimal vertex solutions follow a lattice structure we propose a rounding rule for strict inequalities that guaranties exactness. The lattice used is generated by $\Delta$-regularity of the constraint matrix belonging to t

José M. Arrieta, Juliana Fernandes, Phillipo Lappicy

We consider a scalar parabolic partial differential equation on the interval with nonlinear boundary conditions that are asymptotically sublinear. As the parameter crosses critical values (e.g. the Steklov eigenvalues), it is known that there are large equilibria that arise through a bifurcation from infinity (i.e., such equilibria converge, after rescaling,

Jefferson Zhou, Kahn Rhrissorrakrai

Prostate cancer is the second most common form of cancer, though most patients have a positive prognosis with many experiencing long-term survival with current treatment options. Yet, each treatment carries varying levels of intensity and side effects, therefore determining the severity of prostate cancer is an important criteria in selecting the most approp

Amir Algom, Snir Ben Ovadia, Federico Rodriguez Hertz, Mario Shannon

Motivated by a question of M. Hochman, we construct examples of hyperbolic IFSs $\Phi$ on $[0,1]$ where linear and non-linear behaviour coexist. Namely, for every $2\leq r \leq \infty$ we exhibit the existence of a $C^r$-smooth IFS such that $f'\equiv c(\Phi)$ on the attractor and $f''\equiv 0$ for every $f \in \Phi$, yet $\Phi$ is not $C^t$-smooth for any $