February 2024 arXiv papers — page 74

David Huber, Arran Schlosberg

The secondary market for Ethereum non-fungible tokens (NFTs) has resulted in over $1.8bn being paid to creators in the form of a sales tax commonly called creator royalties. This was despite royalty payments being enforced by no more than social contract alone. Predictably, such an incentive structure led to zero-royalty alternatives becoming abundant and pa

Tuukka Korhonen, Marek Sokołowski

We give an algorithm that given a graph $G$ with $n$ vertices and $m$ edges and an integer $k$, in time $O_k(n^{1+o(1)}) + O(m)$ either outputs a rank decomposition of $G$ of width at most $k$ or determines that the rankwidth of $G$ is larger than $k$; the $O_k(\cdot)$-notation hides factors depending on $k$. Our algorithm returns also a $(2^{k+1}-1)$-expres

Tatsuki Kuribayashi, Ryo Ueda, Ryo Yoshida, Yohei Oseki

The world's languages exhibit certain so-called typological or implicational universals; for example, Subject-Object-Verb (SOV) languages typically use postpositions. Explaining the source of such biases is a key goal of linguistics. We study word-order universals through a computational simulation with language models (LMs). Our experiments show that typolo

Viswakannan R. K., Subhadeep Roy

Through controlled numerical simulations in a one dimensional fiber bundle model with local stress concentration, we established an inverse correlation between the strength of the material and the cracks which grow inside it - both the maximum crack and the one that set in instability within the system, defined to be the critical crack. Through Pearson corre

Muhammad Qasim Khan, Wenzheng Dong, Leigh M. Norris, Lorenza Viola

Characterizing temporally correlated (``non-Markovian'') noise is a key prerequisite for achieving noise-tailored error mitigation and optimal device performance. Quantum noise spectroscopy can afford quantitative estimation of the noise spectral features; however, in its current form it is highly vulnerable to implementation non-idealities, notably, state-p

Hector Vargas Alvarez, Gianluca Fabiani, Ioannis G. Kevrekidis, Nikolaos Kazantzis

We use Physics-Informed Neural Networks (PINNs) to solve the discrete-time nonlinear observer state estimation problem. Integrated within a single-step exact observer linearization framework, the proposed PINN approach aims at learning a nonlinear state transformation map by solving a system of inhomogeneous functional equations. The performance of the propo

Mythili Surendran, Joshua Rollag, Christopher E. Stevens, Ching-Tai Fu

Rare earth dopants are one of the most extensively studied optical emission centers for a broad range of applications such as laser optoelectronics, sensing, lighting, and quantum information technologies due to their narrow optical linewidth and exceptional coherence properties. Epitaxial doped oxide thin films can serve as a promising and controlled host t

Maarten Löffler, Tamara Mchedlidze, David Orden, Josef Tkadlec

A pseudo-triangle is a simple polygon with exactly three convex vertices, and all other vertices (if any) are distributed on three concave chains. A pseudo-triangulation~$\mathcal{T}$ of a point set~$P$ in~$\mathbb{R}^2$ is a partitioning of the convex hull of~$P$ into pseudo-triangles, such that the union of the vertices of the pseudo-triangles is exactly~$

Soufiane Bouabbadi

Power systems are very large and complex, it can be influenced by many unexpected events this makes power system optimization problems difficult to solve, hence methods for solving these problems ought to be an active research topic. This review presents an overview of important mathematical comparaison of loss minimization algorithm and particle swarm optim

Ben Zindorf, Sougato Bose

Universal gate sets for quantum computation, when single and two qubit operations are accessible, include both Hermitian and non-Hermitian gates. Here we utilize the fact that any single-qubit operator may be implemented as two Hermitian gates, and thus a purely Hermitian universal set is possible. This implementation can be used to prepare high fidelity sin

Berkay Berabi, Alexey Gronskiy, Veselin Raychev, Gishor Sivanrupan

The automated program repair field has attracted substantial interest over the years, but despite significant research efforts, creating a system that works well for complex semantic bugs such as security vulnerabilities has proven difficult. A promising direction to solve this challenge is by leveraging large language models (LLMs), which are increasingly u

Aurélien Falco, Jérémy Leconte, Alexandre Mechineau, William Pluriel

With the new generation of space telescopes such as the James Webb Space Telescope (JWST), it is possible to better characterize the atmospheres of exoplanets. The atmospheres of Hot and Ultra Hot Jupiters are highly heterogeneous and asymmetrical. The difference between the temperatures on the day-side and the night-side is especially extreme in the case of

Soufiane Hayou, Nikhil Ghosh, Bin Yu

In this paper, we show that Low Rank Adaptation (LoRA) as originally introduced in Hu et al. (2021) leads to suboptimal finetuning of models with large width (embedding dimension). This is due to the fact that adapter matrices A and B in LoRA are updated with the same learning rate. Using scaling arguments for large width networks, we demonstrate that using

Tobias Frank, Paulo E. Faria Junior, Klaus Zollner, Jaroslav Fabian

Rashba spin-orbit coupling is a quintessential spin interaction appearing in virtually any electronic heterostructure. Its paradigmatic spin texture in the momentum space forms a tangential vector field. Using first-principles investigations, we demonstrate that in twisted homobilayers and hetero-multilayers, the Rashba coupling can be predominantly radial,

Julien Delile, Srayanta Mukherjee, Anton Van Pamel, Leonid Zhukov

Large language models (LLMs) are transforming the way information is retrieved with vast amounts of knowledge being summarized and presented via natural language conversations. Yet, LLMs are prone to highlight the most frequently seen pieces of information from the training set and to neglect the rare ones. In the field of biomedical research, latest discove

F. A. Brito, Julio C. M. Rocha, A. S. Lemos, A. S. Pereira

In this work, we consider the dynamics of the self-induced collapse of the tachyon wave function in inflationary scenarios. We analyze the modifications on the power spectrum by considering the $\beta$-exponential potential, whose parameters have updated constraints by the Planck 2018 baseline data and recent results from the Atacama Cosmology Telescope (ACT

Sankhaneel Bisui, Sudipta Das, Tài Huy Hà, Jonathan Montaño

We provide explicit descriptions for the rational powers and Rees valuations of several classes of ideals invariant under natural actions of tori and products of general linear groups, in terms of polyhedra and lattice points. This allows us to show that a version of Musta\c{t}\u{a}-Takagi's summation formula for multiplier ideals also holds for the rational

Debolina Chatterjee, Jyotirmoy Sarkar

We study a system that experiences damaging external shocks at stochastic intervals, continuous degradation, and self-healing. The motivation for such a system comes from real-life applications based on micro-electro-mechanical systems (MEMS). The system fails if the cumulative damage exceeds a time-dependent threshold. We develop a preventive maintenance po

Jinhao Duan, Renming Zhang, James Diffenderfer, Bhavya Kailkhura

As Large Language Models (LLMs) are integrated into critical real-world applications, their strategic and logical reasoning abilities are increasingly crucial. This paper evaluates LLMs' reasoning abilities in competitive environments through game-theoretic tasks, e.g., board and card games that require pure logic and strategic reasoning to compete with oppo

Federico Bonetti, Michele Del Zotto, Ruben Minasian

Topological defects and operators give a far-reaching generalization of symmetries of quantum fields. An auxiliary topological field theory in one dimension higher than the QFT of interest, known as the SymTFT, provides a natural way for capturing such operators. This gives a new perspective on several applications of symmetries, but fails to capture continu

Sonja Hohloch

Assume $M$ to be $\mathbb R^2$ or a closed surface of genus $g \geq 1$ and $\omega$ a symplectic form on $M$. Let $\varphi: M \to M$ be a symplectomorphism with hyperbolic fixed point $x$ and transversely intersecting stable and unstable manifolds $W^s(\varphi, x)$ and $ W^u(\varphi, x)$. The intersection points $W^s(\varphi, x) \cap\ W^u(\varphi, x)=:{\math

Arnbjörg Soffía Árnadóttir, Josse van Dobben de Bruyn, Prem Nigam Kar, David E. Roberson

Sabidussi's theorem [Duke Math. J. 28, 1961] gives necessary and sufficient conditions under which the automorphism group of a lexicographic product of two graphs is a wreath product of the respective automorphism groups. We prove a quantum version of Sabidussi's theorem for finite graphs, with the automorphism groups replaced by quantum automorphism groups

Zhanhui Zhou, Jie Liu, Zhichen Dong, Jiaheng Liu

Large language models (LLMs) undergo safety alignment to ensure safe conversations with humans. However, this paper introduces a training-free attack method capable of reversing safety alignment, converting the outcomes of stronger alignment into greater potential for harm by accessing only LLM output token distributions. Specifically, our method achieves th

Alessandra Buonanno, Gustav Uhre Jakobsen, Gustav Mogull

Effective-one-body (EOB) waveforms employed by the LIGO-Virgo-KAGRA Collaboration have primarily been developed by resumming the post-Newtonian expansion of the relativistic two-body problem. Given the recent significant advancements in post-Minkowskian (PM) theory and gravitational self-force formalism, there is considerable interest in creating waveform mo

Peter Meisenheimer, Maya Ramesh, Sajid Husain, Isaac Harris

Spin waves in magnetic materials are promising information carriers for future computing technologies due to their ultra-low energy dissipation and long coherence length. Antiferromagnets are strong candidate materials due, in part, to their stability to external fields and larger group velocities. Multiferroic aniferromagnets, such as BiFeO$_3$ (BFO), have

Kira Goldner, Taylor Lundy

We initiate the study of multidimensional Bayesian utility maximization, focusing on the unit-demand setting where values are i.i.d. across both items and buyers. The seminal result of Hartline and Roughgarden '08 studies simple, information-robust mechanisms that maximize utility for $n$ i.i.d. agents and $m$ identical items via an approximation to social w

David Wärn

Given a span of spaces, one can form the homotopy pushout and then take the homotopy pullback of the resulting cospan. We give a concrete description of this pullback as the colimit of a sequence of approximations, using what we call the zigzag construction. We also obtain a description of loop spaces of homotopy pushouts. Using the zigzag construction, we r

Obai Bahwal, Oliver Kosut, Lalitha Sankar

Intelligent machine learning approaches are finding active use for event detection and identification that allow real-time situational awareness. Yet, such machine learning algorithms have been shown to be susceptible to adversarial attacks on the incoming telemetry data. This paper considers a physics-based modal decomposition method to extract features for

Matej Bubaš, Jordi Sancho-Parramon

Metal alloys hold the promise of providing hot carrier generation distributions superior to pure metals in applications such as sensing, catalysis and solar energy harvesting. Guidelines for finding the optimal alloy configuration for a target application require understanding the connection between alloy composition and hot carrier distribution. Here we pre

Christian Schlarmann, Naman Deep Singh, Francesco Croce, Matthias Hein

Multi-modal foundation models like OpenFlamingo, LLaVA, and GPT-4 are increasingly used for various real-world tasks. Prior work has shown that these models are highly vulnerable to adversarial attacks on the vision modality. These attacks can be leveraged to spread fake information or defraud users, and thus pose a significant risk, which makes the robustne

Chenghan Li, Or Sharir, Shunyue Yuan, Garnet K. Chan

Drawing inspiration from the domain of image super-resolution, we view the electron density as a 3D grayscale image and use a convolutional residual network to transform a crude and trivially generated guess of the molecular density into an accurate ground-state quantum mechanical density. We find that this model outperforms all prior density prediction appr

Durbar Roy, Sophia M, Kush K Dewangan, Abdur Rasheed

We study the mechanics of evaporation and precipitate formation in pure and bacteria-laden sessile whole blood droplets in the context of disease diagnostics. Using experimental and theoretical analysis, we show evaporation process has three stages based on evaporation rate. In the first stage, edge evaporation results in a gelated contact line along the per

Olivier Bordellès

We prove a totally explicit bound for short sums of certain non-negative arithmetic functions satisfying a general growth condition, and apply this result to derive two explicit estimates for the Erd\H{o}s-Hooley $\Delta$-function in short intervals.

Justus-Jonas Erker, Florian Mai, Nils Reimers, Gerasimos Spanakis

Search-based dialog models typically re-encode the dialog history at every turn, incurring high cost. Curved Contrastive Learning, a representation learning method that encodes relative distances between utterances into the embedding space via a bi-encoder, has recently shown promising results for dialog modeling at far superior efficiency. While high effici

Thomas Hales

In 1911, Alfred North Whitehead published a short book "Introduction to Mathematics" (IM) intended for students wanting an explanation of the fundamental ideas of mathematics. Whitehead's IM has enduring value because it was written not long after he and Bertrand Russell published their monumental three-volume work "Principia Mathematica" (PM) -- a publicati

Andrei V. Konstantinov, Stanislav R. Kirpichenko, Lev V. Utkin

A new model for generating survival trajectories and data based on applying an autoencoder of a specific structure is proposed. It solves three tasks. First, it provides predictions in the form of the expected event time and the survival function for a new generated feature vector on the basis of the Beran estimator. Second, the model generates additional da

Frances E. Rigby, Nikku Madhusudhan

Recent studies have suggested the possibility of Hycean worlds, characterised by deep liquid water oceans beneath H$_2$-rich atmospheres. These planets significantly widen the range of planetary properties over which habitable conditions could exist. We conduct internal structure modelling of Hycean worlds to investigate the range of interior compositions, o

Jonathan Hayase, Ema Borevkovic, Nicholas Carlini, Florian Tramèr

Recent work has shown it is possible to construct adversarial examples that cause an aligned language model to emit harmful strings or perform harmful behavior. Existing attacks work either in the white-box setting (with full access to the model weights), or through transferability: the phenomenon that adversarial examples crafted on one model often remain e

Susana Valdez-Alvarado, Alejandro Cruz-Osorio, J. M. Dávila, L. Arturo Ureña-López

We investigated the possibility that compact stars could be described by a fermion-boson star with a quartic self-interaction in the boson sector. Specifically, by varying the polytropic constant $K$ and adiabatic index $\Gamma$ in the polytropic equation of state, the boson mass $\mu$, and the self-interaction parameter $\Lambda$, we construct equilibrium c

Zengqing Wu, Run Peng, Shuyuan Zheng, Qianying Liu

Large Language Models (LLMs) have increasingly been utilized in social simulations, where they are often guided by carefully crafted instructions to stably exhibit human-like behaviors during simulations. Nevertheless, we doubt the necessity of shaping agents' behaviors for accurate social simulations. Instead, this paper emphasizes the importance of spontan

Qisen Yang, Zekun Wang, Honghui Chen, Shenzhi Wang

Psychological measurement is essential for mental health, self-understanding, and personal development. Traditional methods, such as self-report scales and psychologist interviews, often face challenges with engagement and accessibility. While game-based and LLM-based tools have been explored to improve user interest and automate assessment, they struggle to

Andrzej A. Zdziarski, Swadesh Chand, Srimanta Banerjee, Michal Szanecki

We perform a detailed study of the black hole spin of Cyg X-1, using accurate broad-band X-ray data obtained in the soft spectral state by simultaneous NICER and NuSTAR observations, supplemented at high energies by INTEGRAL data. We use the relativistic disk model kerrbb together with different models of the Comptonization high energy tail and the relativis

Zhijun Guo, Alvina Lai, Johan Hilge Thygesen, Joseph Farrington

Large language models (LLMs) have attracted significant attention for potential applications in digital health, while their application in mental health is subject to ongoing debate. This systematic review aims to evaluate the usage of LLMs in mental health, focusing on their strengths and limitations in early screening, digital interventions, and clinical a

Himanshu Chaudhary, Ujjal Debnath, Shibesh Kumar Jas Pacif, Niyaz Uddin Molla

This study investigates the accelerated cosmic expansion within the Ho\v{r}ava-Lifshitz Model. To constrain the cosmological parameters of this model, we incorporate 17 Baryon Acoustic Oscillation points, 31 Cosmic Chronometer points, 40 Type Ia Supernovae points, 24 quasar Hubble diagram points, and 162 Gamma Ray Bursts points, along with the latest Hubble

J. E. Griffin

Modern regression applications can involve hundreds or thousands of variables which motivates the use of variable selection methods. Bayesian variable selection defines a posterior distribution on the possible subsets of the variables (which are usually termed models) to express uncertainty about which variables are strongly linked to the response. This can

Mariaelena Boglione, Umberto D'Alesio, Carlo Flore, Josè Osvaldo Gonzalez-Hernandez

The Bayesian reweighting procedure is extended to the case of multiple independent extractions of transverse momentum dependent parton distributions (TMDs). By exploiting the data on transverse single spin asymmetries, $A_N$, for inclusive pion production in polarized proton-proton collisions measured at RHIC, we perform a simultaneous reweighting of the qua

Ying Xu, Michael Lanier, Anindya Sarkar, Yevgeniy Vorobeychik

Graphs are commonly used to model complex networks prevalent in modern social media and literacy applications. Our research investigates the vulnerability of these graphs through the application of feature based adversarial attacks, focusing on both decision time attacks and poisoning attacks. In contrast to state of the art models like Net Attack and Meta A

Ganesh Sapkota, Sanjay Madria

In this paper, we have proposed a new strategy of using the landmark anchor node instead of a radio-based anchor node to obtain the virtual coordinates (landmarkID, DISTANCE) of moving troops or defense forces that will help in tracking and maneuvering the troops along a safe path within a GPS-denied battlefield environment. The proposed strategy implements

L. I. Petrova

It is shown with the help of skew-symmetric forms that the mathematical physics equations, on which no additional conditions are imposed, have quantum properties. And this is due to the integrability properties of differential equations, which depends on the consistency of derivatives with respect to different variables and the consistency of equations, if t

Chen Zhao, Feng Mi, Xintao Wu, Kai Jiang

The fairness-aware online learning framework has emerged as a potent tool within the context of continuous lifelong learning. In this scenario, the learner's objective is to progressively acquire new tasks as they arrive over time, while also guaranteeing statistical parity among various protected sub-populations, such as race and gender, when it comes to th

Goonmeet Bajaj, Srinivasan Parthasarathy, Valerie L. Shalin, Amit Sheth

Grounding is a challenging problem, requiring a formal definition and different levels of abstraction. This article explores grounding from both cognitive science and machine learning perspectives. It identifies the subtleties of grounding, its significance for collaborative agents, and similarities and differences in grounding approaches in both communities

Mirjam Weilenmann, Costantino Budroni, Miguel Navascues

We study what can or cannot be certified in communication scenarios where the assumption of independence and identical distribution (iid) between experimental rounds fails. In this respect, we prove that membership tests for non-convex sets of correlations cannot be formulated in the non-iid regime. Similarly, it is impossible to self-test non-extreme quantu

Hongjin Su, Shuyang Jiang, Yuhang Lai, Haoyuan Wu

Recently the retrieval-augmented generation (RAG) has been successfully applied in code generation. However, existing pipelines for retrieval-augmented code generation (RACG) employ static knowledge bases with a single source, limiting the adaptation capabilities of Large Language Models (LLMs) to domains they have insufficient knowledge of. In this work, we

Marco Grandis

This note is about the smash product of pointed topological spaces, without relying on some convenient subcategory. We deal with its partial associativity properties and their connection with the function spaces, introducing a property of regular associativity related to the colax monoidal structure of the product. We also study a large class of triples of p

Xinran Wang, Nicolas Rojas

This paper introduces a Cosserat rod based mathematical model for modeling a self-controllable variable curvature soft continuum robot. This soft continuum robot has a hollow inner channel and was developed with the ability to perform variable curvature utilizing a growing spine. The growing spine is able to grow and retract while modifies its stiffness thro

Xinqun Mei, Guofang Wang, Liangjun Weng

In this paper, we investigate the existence of admissible (and strictly convex) smooth solutions to the prescribed $L_p$ quotient type curvature problem with $p>1$. For cases where $p=k-l+1$ and $p> k-l+1$, we obtain an admissible solution without any additional conditions, which is strictly spherically convex under a convexity condition. Under the same conv

Ganna Kudryavtseva, Ajda Lemut Furlani

We show that the universal $X$-generated $F$-inverse monoid $F(G)$, where $G$ is an $X$-generated group, introduced by Auinger, Szendrei and the first-named author, arises as a quotient inverse monoid of the Margolis-Meakin expansion $M(G, X\cup \overline{G})$ of $G$, with respect to the extended generating set $X\cup \overline{G}$, where $\overline{G}$ is a

Valentine Soto

The bounded derived category of a finite dimensional algebra of finite global dimension is equivalent the stable category of $\mathbb{Z}$-graded modules over its trivial extension \cite{Happel}. In particular, given two derived equivalent finite dimensional algebras $\Lambda_{1}$ and $\Lambda_{2}$ of finite global dimension, their trivial extensions are stab

Thomas Cass, William F. Turner

Random developments of a path into a matrix Lie group $G_N$ have recently been used to construct signature-based kernels on path space. Two examples include developments into GL$(N;\mathbb{R})$ and $U(N;\mathbb{C})$, the general linear and unitary groups of dimension $N$. For the former, [MLS23] showed that the signature kernel is obtained via a scaling limi

Craig R. Walton, Jessica K. Rigley, Alexander Lipp, Robert Law

Earth's surface is deficient in available forms of many elements considered limiting for prebiotic chemistry. In contrast, many extraterrestrial rocky objects are rich in these same elements. Limiting prebiotic ingredients may, therefore, have been delivered by exogenous material; however, the mechanisms by which exogeneous material may be reliably and non-d

Siheng Xiong, Yuan Yang, Faramarz Fekri, James Clayton Kerce

Compared with static knowledge graphs, temporal knowledge graphs (tKG), which can capture the evolution and change of information over time, are more realistic and general. However, due to the complexity that the notion of time introduces to the learning of the rules, an accurate graph reasoning, e.g., predicting new links between entities, is still a diffic

Samira Elghaayda, Xiang Zhou, Mostafa Mansour

We obtain analytical expressions for distance-based quantum resources and examine their distribution in the proximity of a Schwarzschild black hole (SBH) within a curved background. For an observer in free fall and their stationary counterpart sharing the Gisin state, the quantum resources are degraded at an infinite Hawking temperature. The extent of this d

Enrique Garcia-Ceja

Being able to assess the confidence of individual predictions in machine learning models is crucial for decision making scenarios. Specially, in critical applications such as medical diagnosis, security, and unmanned vehicles, to name a few. In the last years, complex predictive models have had great success in solving hard tasks and new methods are being pr

Eric Ströher

We study the electric Helmholtz equation $\Delta u + Vu + \lambda u =f$ and show that, for certain potentials, the solution $u$ given by the limited absorption principle obeys a Sommerfeld radiation condition. We use a non-spherical approach based on the solution $K$ of the eikonal equation $|\nabla K|^2=1 + \frac{p}{\lambda}$ to improve previous results in

Finn Feindt, Inge Diehl, Karsten Hansen, Stephan Lachnit

Silicon Photomultipliers (SiPMs) are state-of-the-art photon detectors used in particle physics, medical imaging, and beyond. They are sensitive to individual photons in the optical wavelength regime and achieve time resolutions of a few tens of picoseconds, which makes them interesting candidates for timing detectors in tracking systems for particle physics

Sara Pollock, Leo Rebholz, Xuemin Tu, Menyging Xiao

We analyze and test a simple-to-implement two-step iteration for the incompressible Navier-Stokes equations that consists of first applying the Picard iteration and then applying the Newton iteration to the Picard output. We prove that this composition of Picard and Newton converges quadratically, and our analysis (which covers both the unique solution and n

Chang Won Lee, Steven L. Waslander

Multi-object tracking (MOT) methods have seen a significant boost in performance recently, due to strong interest from the research community and steadily improving object detection methods. The majority of tracking methods follow the tracking-by-detection (TBD) paradigm, blindly trust the incoming detections with no sense of their associated localization un

Hugo Lebeau, Florent Chatelain, Romain Couillet

The performance of spectral clustering relies on the fluctuations of the entries of the eigenvectors of a similarity matrix, which has been left uncharacterized until now. In this letter, it is shown that the signal $+$ noise structure of a general spike random matrix model is transferred to the eigenvectors of the corresponding Gram kernel matrix and the fl

Yuhei Yamada, Shingo Maeda

Stimuli-responsive gels are the gels that vary the volume depending on environmental conditions. It has been reported that the stimuli-responsive gel with an inhomogeneous structure exhibits faster volume change than the gel without it. It is understood as a difference in the transfer dynamics of the solvent, though, there are few models for discussing the e

Jonas Köppl, Benedikt Jahnel

We provide a class of examples of interacting particle systems on $\mathbb{Z}^d$, for $d\in\{1,2\}$, that admit a unique translation-invariant stationary measure, which is not the long-time limit of all translation-invariant starting measures, due to the existence of time-periodic orbits in the associated measure-valued dynamics. This is the first such examp

S. Schlagenhauf, M. Mugrauer, C. Ginski, S. Buder

Stellar multiplicity is a key aspect of exoplanet diversity, as the presence of more than one star in a planetary system can have both devastating and positive effects on its formation and evolution. In this paper, we present the results of a Lucky Imaging survey of 212 exoplanet host stars performed with AstraLux at CAHA 2.2 m. The survey includes data from

Felix J. Dorfner, Liv Jürgensen, Leonhard Donle, Fares Al Mohamad

Introduction: With the rapid advances in large language models (LLMs), there have been numerous new open source as well as commercial models. While recent publications have explored GPT-4 in its application to extracting information of interest from radiology reports, there has not been a real-world comparison of GPT-4 to different leading open-source models

Zihao Yang, Hui Tian, Yingjie Zhu, Yu Xu

Stellar coronal mass ejections (CMEs) from host stars are an important factor that affects the habitability of exoplanets. Although their solar counterparts have been well observed for decades, it is still very difficult to find solid evidence of stellar CMEs. Using the spectral line profile asymmetry caused by the Doppler shift of erupting plasma, several s

Sergi Batlle-Porro, Dumitru Calugaru, Haoyu Hu, Roshan Krishna Kumar

Ever since the initial experimental observation of correlated insulators and superconductivity in the flat Dirac bands of magic angle twisted bilayer graphene, a search for the microscopic description that explains its strong electronic interactions has begun. While the seemingly disagreeing electronic transport and scanning tunneling microscopy experiments

Felix Ahrens, Elena Ferri, Guerino Avallone, Carlo Barone

Noise at the quantum limit over a broad bandwidth is a fundamental requirement for future cryogenic experiments for neutrino mass measurements, dark matter searches and Cosmic Microwave Background (CMB) measurements as well as for fast high-fidelity read-out of superconducting qubits. In the last years, Josephson Parametric Amplifiers (JPA) have demonstrated

David Xu

We prove that convex-cocompact representations of finitely generated groups in the group of isometries of the infinite-dimensional hyperbolic space form an open set in the space of representations, allowing us to deform these convex-cocompact representations. We then use bending to obtain convex-cocompact representations of surface groups that are not conjug

Maya Banks, Michael K. Brown, Tara Gomes, Prashanth Sridhar

We give an overview of a Macaulay2 package for computing with the multigraded BGG correspondence. This software builds on the package BGG due to Abo-Decker-Eisenbud-Schreyer-Smith-Stillman, which concerns the standard graded BGG correspondence. In addition to implementing the multigraded BGG functors, this package includes an implementation of differential m

Elhadji C. Faye, Mame Diarra Fall, Nicolas Dobigeon

This paper introduces a Bayesian framework for image inversion by deriving a probabilistic counterpart to the regularization-by-denoising (RED) paradigm. It additionally implements a Monte Carlo algorithm specifically tailored for sampling from the resulting posterior distribution, based on an asymptotically exact data augmentation (AXDA). The proposed algor

Matthew Shu, Nishant Balepur, Shi Feng, Jordan Boyd-Graber

Flashcard schedulers rely on 1) student models to predict the flashcards a student knows; and 2) teaching policies to pick which cards to show next via these predictions. Prior student models, however, just use study data like the student's past responses, ignoring the text on cards. We propose content-aware scheduling, the first schedulers exploiting flashc

Shayan Hundrieser, Benjamin Eltzner, Stephan F. Huckemann

Fr\'echet means, conceptually appealing, generalize the Euclidean expectation to general metric spaces. We explore how well Fr\'echet means can be estimated from independent and identically distributed samples and uncover a fundamental limitation: In the vicinity of a probability distribution $P$ with nonunique means, independent of sample size, it is not po

Xiaoyu Tian, Junru Gu, Bailin Li, Yicheng Liu

A primary hurdle of autonomous driving in urban environments is understanding complex and long-tail scenarios, such as challenging road conditions and delicate human behaviors. We introduce DriveVLM, an autonomous driving system leveraging Vision-Language Models (VLMs) for enhanced scene understanding and planning capabilities. DriveVLM integrates a unique c

Savannah P. Hays, Lianrui Zuo, Yihao Liu, Anqi Feng

Deep learning (DL) has led to significant improvements in medical image synthesis, enabling advanced image-to-image translation to generate synthetic images. However, DL methods face challenges such as domain shift and high demands for training data, limiting their generalizability and applicability. Historically, image synthesis was also carried out using d

Arnab Kumar Mallik

The deposition of micron particles finds importance in meteorology and several engineering applications such as deposition of dust in gas lines, carbon deposition in engine exhaust, designing effective air-cleaning systems and estimating deposition of inhaled drug or atmospheric pollutants to determine its consequences on human health. Although the existing

Julian Zapata-Hall

Within college basketball, the decision to foul or not with a 3-point lead (the "foul up 3" dilemma) significantly impacts teams. A single fouling decision can directly determine the outcome of a game or even an entire season. Within this research project, I take a novel look at the "foul up 3" dilemma. As opposed to using time as a blocking factor, as previ

Francesco Preti, József Zsolt Bernád

Quantitative characterization of two-qubit entanglement purification protocols is introduced. Our approach is based on the concurrence and the hit-and-run algorithm applied to the convex set of all two-qubit states. We demonstrate that pioneering protocols are unable to improve the estimated initial average concurrence of almost uniformly sampled density mat

Ángel González-Prieto, Javier Martínez, Vicente Muñoz

In this paper, we study the geometry of the moduli space of representations of the fundamental group of the complement of a torus link into an algebraic group G, an algebraic variety known as the G-character variety of the torus link. These torus links are a family of links in the 3-dimensional sphere formed by stacking several copies of torus knots. We deve

Nathan van Beusekom, Marc van Kreveld, Max van Mulken, Marcel Roeloffzen

Detecting location-correlated groups in point sets is an important task in a wide variety of applications areas. In addition to merely detecting such groups, the group's shape carries meaning as well. In this paper, we represent a group's shape using a simple geometric object, a line segment. Specifically, given a radius $r$, we say a line segment is represe

Michael Beukman, Samuel Coward, Michael Matthews, Mattie Fellows

In unsupervised environment design, reinforcement learning agents are trained on environment configurations (levels) generated by an adversary that maximises some objective. Regret is a commonly used objective that theoretically results in a minimax regret (MMR) policy with desirable robustness guarantees; in particular, the agent's maximum regret is bounded

Dimitri Papageorgiou, Jan Kronqvist, Asha Ramanujam, James Kor

When faced with a limited budget of function evaluations, state-of-the-art black-box optimization (BBO) solvers struggle to obtain globally, or sometimes even locally, optimal solutions. In such cases, one may pursue solution polishing, i.e., a computational method to improve (or ``polish'') an incumbent solution, typically via some sort of evolutionary algo

Zehra Melce Hüsünbeyi, Tatjana Scheffler

We propose an ontology enhanced model for sentence based claim detection. We fused ontology embeddings from a knowledge base with BERT sentence embeddings to perform claim detection for the ClaimBuster and the NewsClaims datasets. Our ontology enhanced approach showed the best results with these small-sized unbalanced datasets, compared to other statistical

Mohammad Heydari, Zahra Rezvani

Data is becoming more complex, and so are the approaches designed to process it. Enterprises have access to more data than ever, but many still struggle to glean the full potential of insights from what they have. This research explores the challenges and experiences of Iranian developers in implementing the MLOps paradigm within enterprise settings. MLOps,

Shuowei Jin, Xueshen Liu, Yongji Wu, Haizhong Zheng

Large language models (LLMs) have achieved remarkable success in natural language tasks, but their inference incurs substantial computational and memory overhead. To improve efficiency, parallel decoding methods like Skeleton-of-Thought (SoT) decompose prompts into sub-problems for concurrent processing. However, these methods significantly compromise answer

Nadezhda Chirkova, Vassilina Nikoulina

Zero-shot cross-lingual knowledge transfer enables a multilingual pretrained language model, finetuned on a task in one language, make predictions for this task in other languages. While being broadly studied for natural language understanding tasks, the described setting is understudied for generation. Previous works notice a frequent problem of generation

N. Vazquez von Bibow, E. N. Millán, C. J. Ruestes

While the mechanical behavior of noble nanoporous metals has been the subject of numerous studies, less is known about their recently developed refractory-based counterparts. Here we report on the mechanical properties, deformation mechanisms and topological changes of nanoporous tantalum, a prototypical refractory metal, by means of atomistic simulations of

A. L. Mota, F. C. Sá Barreto

Correlation identities are obtained for $Z_3$ lattice gauge theory where the bonds of the plaquettes are decorated by generalized three-state Ising variables. Making use of correlation inequalities we obtain the area decay of the Wilson loop observable in a range of the coupling parameter larger than those obtained from mean field theory considerations.

Puxuan Yu, Daniel Cohen, Hemank Lamba, Joel Tetreault

In search settings, calibrating the scores during the ranking process to quantities such as click-through rates or relevance levels enhances a system's usefulness and trustworthiness for downstream users. While previous research has improved this notion of calibration for low complexity learning-to-rank models, the larger data demands and parameter count spe

Hao Tang, Darren Key, Kevin Ellis

We give a model-based agent that builds a Python program representing its knowledge of the world based on its interactions with the environment. The world model tries to explain its interactions, while also being optimistic about what reward it can achieve. We define this optimism as a logical constraint between a program and a planner. We study our agent on

Hui Zhou, Ken Raffenetti, Yanfei Guo, Thomas Gillis

As HPC system architectures and the applications running on them continue to evolve, the MPI standard itself must evolve. The trend in current and future HPC systems toward powerful nodes with multiple CPU cores and multiple GPU accelerators makes efficient support for hybrid programming critical for applications to achieve high performance. However, the sup

Samuel Warren, Yuchen Wang, Carlos L. Benavides-Riveros, David A. Mazziotti

We present an exact ansatz for the eigenstate problem of mixed fermion-boson systems that can be implemented on quantum devices. Based on a generalization of the electronic contracted Schr\"odinger equation (CSE), our approach guides a trial wave function to the ground state of any arbitrary mixed Hamiltonian by directly measuring residuals of the mixed CSE

Mohammad Heydari, Babak Teimourpour

The rise of the Internet and the exponential increase in data have made manual data summarization and analysis a challenging task. Instagram social network is a prominent social network widely utilized in Iran for information sharing and communication across various age groups. The inherent structure of Instagram, characterized by its text-rich content and g