February 2024 arXiv papers — page 35

Yuhao Wang, Lingjuan Miao, Zhiqiang Zhou, Lei Zhang

Infrared-visible image fusion (IVIF) has attracted much attention owing to the highly-complementary properties of the two image modalities. Due to the lack of ground-truth fused images, the fusion output of current deep-learning based methods heavily depends on the loss functions defined mathematically. As it is hard to well mathematically define the fused i

Paul Pollack, Akash Singha Roy

We provide a uniform bound on the partial sums of multiplicative functions under very general hypotheses. As an application, we give a nearly optimal estimate for the count of $n \le x$ for which the Alladi-Erd\H{o}s function $A(n) = \sum_{p^k \parallel n} k p$ takes values in a given residue class modulo $q$, where $q$ varies uniformly up to a fixed power o

Jinyong Ma, Jihua Zhang, Jake Horder, Andrey A. Sukhorukov

Quantum light sources are essential building blocks for many quantum technologies, enabling secure communication, powerful computing, precise sensing and imaging. Recent advancements have witnessed a significant shift towards the utilization of ``flat" optics with thickness at subwavelength scales for the development of quantum light sources. This approach o

Yiwen Zhang, Jiliang Cai, Peng Dong, Jiadian He

The significance of the superconducting diode effect lies in its potential application as a fundamental component in the development of next-generation superconducting circuit technology. The stringent operating conditions at low temperatures have posed challenges for the conventional semiconductor diode, primarily due to its exceptionally high resistivity.

Candice P. Chu

ChatGPT, the most accessible generative artificial intelligence (AI) tool, offers considerable potential for veterinary medicine, yet a dedicated review of its specific applications is lacking. This review concisely synthesizes the latest research and practical applications of ChatGPT within the clinical, educational, and research domains of veterinary medic

Cooper Finnigan, Dmitry K. Efimkin

Electron skew scattering by impurities is one of the major mechanisms behind the anomalous Hall effect in ferromagnetic nanostructures. It is particularly strong at the surface of topological insulators where electron dynamics is governed by the spin-1/2 Dirac equation. Motivated by recently discovered mappings between hydrodynamics and the spin-1 Dirac equa

Peng Wang, Yu Liu, Ziqi Liu, Ming-Yang Wang

The service provided by content delivery networks (CDNs) may overlook content locality, leaving room for potential performance improvement. In this study, we explore the feasibility of leveraging generated data as a replacement for fetching data in missing scenarios based on content locality. Due to sufficient local computing resources and reliable generatio

Hongru Wang, Boyang Xue, Baohang Zhou, Rui Wang

Conversational retrieval refers to an information retrieval system that operates in an iterative and interactive manner, requiring the retrieval of various external resources, such as persona, knowledge, and even response, to effectively engage with the user and successfully complete the dialogue. However, most previous work trained independent retrievers fo

Weile Chen, Haibo Du, Shihua Li

This paper proposes a new distributed finite-time differentiator (DFD) for multi-agent systems (MAS) under directed graph, which extends the differentiator algorithm from the centralized case to the distributed case by only using relative/absolute position information. By skillfully constructing a Lyapunov function, the finite-time stability of the closed-lo

Florian Hörsch, András Imolay, Ryuhei Mizutani, Taihei Oki

Consider a matroid equipped with a labeling of its ground set to an abelian group. We define the label of a subset of the ground set as the sum of the labels of its elements. We study a collection of problems on finding bases and common bases of matroids with restrictions on their labels. For zero bases and zero common bases, the results are mostly negative.

Y. Tokiwa, . P. Opletal, H. Sakai, S. Kambe

The normal-conducting state of the superconductor UTe$_2$ is studied by entropy analysis for magnetic fields along the $b$-axis, obtained from magnetization using the relation $(\partial M/\partial T)_B=(\partial S/\partial B)_T$. We observe a strong increase in entropy with magnetic field due to metamagnetic fluctuations (spatially uniform, $Q=0$). The fiel

Liling Sun, Qi Wu, Shu Cai, Yang Ding

The resistivity of a superconductor in its normal state plays a critical role in determining its superconducting ground state. However, measuring the resistivity of a material under high pressure has long presented a significant technical challenge due to pressure-induced changes in the crystallographic directions, especially for samples with anisotropic lay

Ting Lin

Understanding the internal spin structure of the nucleon remains a challenge in strong interaction physics. The unique capability of RHIC opened new avenues in studying the internal structure of the proton with unprecedented depth and precision. Significant progress has been made in the last few years through various measurements at STAR. The longitudinal sp

Jinqian Chen, Jihua Zhu, Qinghai Zheng, Zhongyu Li

Federated learning encounters substantial challenges with heterogeneous data, leading to performance degradation and convergence issues. While considerable progress has been achieved in mitigating such an impact, the reliability aspect of federated models has been largely disregarded. In this study, we conduct extensive experiments to investigate the reliabi

Kantaro Honda, Yosuke Takasu, Yuki Haruna, Yusuke Nishida

A two-body interaction or force between quantum particles is ubiquitous in nature, and the microscopic description in terms of the bare two-body interaction is the basis for quantitatively describing interacting few- and many-body systems. Alternatively, the effective description in terms of an effective two-body interaction successfully captures the essence

Ergon Cugler de Moraes Silva

This article explores the theoretical and computational aspects of the Infinite Monkey Theorem, investigating the number of attempts and the time required for a set of pseudorandom characters to assemble and recite Hamlets iconic phrase, To be, or not to be, that is the Question. Drawing inspiration from Emile Borel's original concept (1913), the study delve

Keir Darling, Lawrence M. Widrow

We study solutions of the collisionless Boltzmann equation (CBE) in a functional Koopman representation. This facilitates the use of linear spectral techniques characteristic of the analysis of Schrodinger-type equations. For illustrative purposes, we consider the classical phase mixing of a non-interacting distribution function in a quartic potential. Solut

Ashleigh Adams, Jennifer Elder, Nadia Lafrenière, Erin McNicholas

We perform a systematic study of permutation statistics and bijective maps on permutations using SageMath to search the FindStat combinatorial statistics database to identify apparent instances of the cyclic sieving phenomenon (CSP). Cyclic sieving occurs on a set of objects, a statistic, and a map of order $n$ when the evaluation of the statistic generating

Xinliang An, Hong Kiat Tan

Under spherical symmetry, we show that the weak cosmic censorship holds for the gravitational collapse of the Einstein-Maxwell-charged scalar field system. Namely, for this system, with generic initial data, the formed spacetime singularities are concealed inside black-hole regions. This generalizes Christodoulou's celebrated results to the charged case. Due

Peiheng Zhou, Ming Hu, Xiaofei Xie, Yihao Huang

Contrastive Language-Image Pre-training (CLIP) model, as an effective pre-trained multimodal neural network, has been widely used in distributed machine learning tasks, especially Federated Learning (FL). Typically, CLIP-based FL adopts Parameter-Efficient Fine-Tuning (PEFT) for model training, which only fine-tunes adapter parameters or soft prompts rather

Yu Lin, Zhiheng Li, Yubo Cui, Zheng Fang

3D single object tracking (SOT) is an important and challenging task for the autonomous driving and mobile robotics. Most existing methods perform tracking between two consecutive frames while ignoring the motion patterns of the target over a series of frames, which would cause performance degradation in the scenes with sparse points. To break through this l

Jieyong Wang, Chunyao Song, Yihao Wu

The topic-to-essay generation task is a challenging natural language generation task that aims to generate paragraph-level text with high semantic coherence based on a given set of topic words. Previous work has focused on the introduction of external knowledge, ignoring the insufficient generated text diversity. In order to improve the generation diversity,

Dylan Cope, Peter McBurney

In Emergent Communication (EC) agents learn to communicate with one another, but the protocols that they develop are specialised to their training community. This observation led to research into Zero-Shot Coordination (ZSC) for learning communication strategies that are robust to agents not encountered during training. However, ZSC typically assumes that no

Yuan Zhu, Yanqiang Wang, Yadong An, Hong Yang

This paper focuses on a real-time vehicle detection and urban traffic behavior analysis system based on Unmanned Aerial Vehicle (UAV) traffic video. By using UAV to collect traffic data and combining the YOLOv8 model and SORT tracking algorithm, the object detection and tracking functions are implemented on the iOS mobile platform. For the problem of traffic

Qianfan Wang, Yiwen Wang, Yixin Wang, Jifan Liang

In this paper, we propose a class of codes, referred to as random staircase generator matrix codes (SGMCs), which have staircase-like generator matrices. In the infinite-length region, we prove that the random SGMC is capacity-achieving over binary-input output-symmetric (BIOS) channels. In the finite-length region, we present the representative ordered stat

Liheng Lang, Qichen Lu, C. M. Dai, Xingbo Wei

The study of integrable systems has led to significant advancements in our understanding of many-body physics. We design a series of numerical experiments to analyze the integrability of a mass-imbalanced two-body system through energy level statistics and deep learning of wavefunctions. The level spacing distributions are fitted by a Brody distribution and

Douglas Scott

The cosmic neutrino background is like the cosmic microwave background, but less photon-y and more neutrino-ey. The CNB is also less talked about than the CMB, mostly because it's nearly impossible to detect directly. But if it could be detected, it would be interesting in several ways that are discussed.

Chao Tao, Dongsheng Kuang, Zhenyang Huang, Chengli Peng

In the later training stages, further improvement of the models ability to determine changes relies on how well the change detection (CD) model learns hard cases; however, there are two additional challenges to learning hard case samples: (1) change labels are limited and tend to pointer only to foreground targets, yet hard case samples are prevalent in the

Qi Deng

We propose a Conditional Singular Value Decomposition in the form of A_{mn} =H_{mk} B_{kl} M_{ln}^* for given general matrices A_{mn} and B_{kl} .

Jongkeun Choi, Minsuk Yang

We establish the existence, uniqueness, and various estimates for Green functions of mixed Dirichlet-conormal derivative problems for the stationary Stokes system with measurable coefficients in a two-dimensional Reifenberg flat domain with a rough separation.

Peiyan Zhang, Chaozhuo Li, Liying Kang, Feiran Huang

We investigate node representation learning on text-attributed graphs (TAGs), where nodes are associated with text information. Although recent studies on graph neural networks (GNNs) and pretrained language models (PLMs) have exhibited their power in encoding network and text signals, respectively, less attention has been paid to delicately coupling these t

Dante V. Gomez-Navarro

The Large-Scale Structure (LSS) of the Universe provides valuable information for modern cosmology. The future redshift surveys, as DESI (Dark Energy Spectroscopic Instrument), will measure millions of galaxies and quasars, which allows to measure the history expansion and the growth factor. In this work, we present the theoretical model of the matter power

Todd Morrill, Zhaoyuan Deng, Yanda Chen, Amith Ananthram

There are many settings where it is useful to predict and explain the success or failure of a dialogue. Circumplex theory from psychology models the social orientations (e.g., Warm-Agreeable, Arrogant-Calculating) of conversation participants and can be used to predict and explain the outcome of social interactions. Our work is novel in its systematic applic

Giang Ngo, Dang Nguyen, Dat Phan-Trong, Sunil Gupta

A common problem encountered in many real-world applications is level set estimation where the goal is to determine the region in the function domain where the function is above or below a given threshold. When the function is black-box and expensive to evaluate, the level sets need to be found in a minimum set of function evaluations. Existing methods often

Dante V. Gomez-Navarro

We live in the golden era of cosmology due to next redshift surveys will map a significant volume of the Universe across a wide range of redshifts. We analyze the clustering of the eBOSS luminous red galaxy sample (eBOSS LRG). We measure the multipole power spectra inferred from the NGC sample (107500 galaxies) and SGC sample (67316 galaxies) between redshif

Mohammad Hassany, Peter Brusilovsky, Jiaze Ke, Kamil Akhuseyinoglu

Worked examples (solutions to typical programming problems presented as a source code in a certain language and are used to explain the topics from a programming class) are among the most popular types of learning content in programming classes. Most approaches and tools for presenting these examples to students are based on line-by-line explanations of the

Job Feldbrugge

The reconstruction of density and velocity fields is of central importance to the interpretation of $N$-body simulations. We propose a phase-space extension of the Delaunay tessellation field estimator (DTFE) that tracks the dark matter fluid in phase-space. The new reconstruction scheme removes several artifacts from the conventional DTFE in multi-stream re

Wayne M. Saslow, Chen Sun

We consider the macroscopic dynamics of systems with charge and spin currents, using the methods of Onsager's irreversible thermodynamics. Applied to systems with spin-orbit interaction (SOI), we derive Onsager relations showing that, if electrical disequilibrium leads to spin currents, then magnetic disequilibrium leads to charge currents. We consider three

Marjorie K. Drake

Let $E \subset \mathbb{R}^n$ be a compact set, and $f:E \to \mathbb{R}$. How can we tell if there exists a convex extension $F \in C^{1,1}(\mathbb{R}^n)$ of $f$, i.e. satisfying $F|_E = f|_E$? Assuming such an extension exists, how small can one take the Lipschitz constant $\text{Lip}(\nabla F): = \sup_{x,y \in \mathbb{R}^n, x \neq y} \frac{|\nabla F(x) - \n

Pierre Colmez

We study the cohomology of the group of rational points of a linear algebraic group on adelic functional spaces, and we explore the relation with Emerton's completed cohomology.

Chengzhe Piao, Taiyu Zhu, Stephanie E Baldeweg, Paul Taylor

Accurate prediction of future blood glucose (BG) levels can effectively improve BG management for people living with diabetes, thereby reducing complications and improving quality of life. The state of the art of BG prediction has been achieved by leveraging advanced deep learning methods to model multi-modal data, i.e., sensor data and self-reported event d

Jinxu Zhang

Understanding the contents of multimodal documents is essential to accurately extract relevant evidence and use it for reasoning. Existing document understanding models tend to generate answers with a single word or phrase directly, ignoring the source document's evidence and lacking interpretability. In this work, we address the lack of step-wise capabiliti

Julio Careaga, Víctor Osores

A three-dimensional model of polydisperse reactive sedimentation is developed by means of a multilayer shallow water approach. The model consists of a variety of solid particles of different sizes and densities, and substrates diluted in water, which produce biochemical reactions while the sedimentation process occurs. Based on the Masliyah-Lockett-Bassoon s

Yang He, Long Cheng, Heming Wang, Yu Zhang

Optical frequency division based on bulk or fiber optics provides unprecedented spectral purity for microwave oscillators. To extend the applications of this approach, the big challenges are to develop miniaturized optical frequency division oscillators without trading off phase noise performance. In this paper, we report a chip-scale electro-optical frequen

Akira Yamada

In 2012, we obtained Oppenheim's inequality for positive semidefinite matrices and its equality condition by the reproducing kernel method. In this paper, as a continuation, we give a reproducing kernel proof of the block matrix version of the Oppenheim-Schur's inequality and its equality condition in the positive definite case.

Arshiya Taj Abdul, Augustinos D. Saravanos, Evangelos A. Theodorou

This paper presents a novel distributed robust optimization scheme for steering distributions of multi-agent systems under stochastic and deterministic uncertainty. Robust optimization is a subfield of optimization which aims to discover an optimal solution that remains robustly feasible for all possible realizations of the problem parameters within a given

Rizky Reza Fauzi, Jerremy Joelnathan Stevanlim

An insurance company is required to prepare a certain amount of money, called reserve, as a mean to pay its policy holders claims in the future. There are several types of reserve, one of them is IBNR reserve, for which the payments are made not in the same calendar year as the events that trigger the claims. Wuthrich and Merz (2015) developed a Bayesian Cha

Rahul Karmakar, Himanshu, Srikanth Sastry, Sanat K Kumar

Vitrimers are polymer networks that can undergo bond exchange reactions. They dynamically rearrange their structures while maintaining their overall integrity, thus resulting in unique properties such as self-healing, reprocessability, shape memory and adaptability. Here, we show that the introduction of dynamic bonds directly impacts the polymer density. Fo

Yiping Song, Juhua Zhang, Zhiliang Tian, Yuxin Yang

As sufficient data are not always publically accessible for model training, researchers exploit limited data with advanced learning algorithms or expand the dataset via data augmentation (DA). Conducting DA in private domain requires private protection approaches (i.e. anonymization and perturbation), but those methods cannot provide protection guarantees. D

Nikolaos Roidos, Andreas Savas-Halilaj

We study the curve shortening flow on Riemann surfaces with finitely many conformal conical singularities. If the initial curve is passing through the singular points, then the evolution is governed by a degenerate quasilinear parabolic equation. In this case, we establish short time existence, uniqueness, and regularity of the flow. We also show that the ev

D. F. G. Coelho, R. J. Cintra

This report elaborates on approximations for the discrete Fourier transform by means of replacing the exact Cooley-Tukey algorithm twiddle-factors by low-complexity integers, such as $0, \pm \frac{1}{2}, \pm 1$.

Andrei Ruskuc, Chun-Ju Wu, Emanuel Green, Sophie L. N. Hermans

Quantum networks that distribute entanglement among remote nodes will unlock transformational technologies in quantum computing, communication, and sensing. However, state-of-the-art networks utilize only a single optically-addressed qubit per node; this constrains both the quantum communication bandwidth and memory resources, greatly impeding scalability. S

Andrew Lee, Cory H. Colbert

We consider the embedding function $c_b(a)$ describing the problem of symplectically embedding an ellipsoid $E(1,a)$ into the smallest possible scaling by $\lambda>1$ of the polydisc $P(1,b)$. In particular, we calculate rigid-flexible values, i.e. the minimum $a$ such that for $E(1,a')$ with $a'>a$, the embedding problem is determined only by volume. For $1

Yiling Yang, Engui Fan, Yue Liu

In this paper, we establish the orbital stability of the 1-soliton solution for the derivative nonlinear Schr\"odinger equation under perturbations in $L^2(\mathbb{R})$. We demonstrate this stability by utilizing the B\"acklund transformation associated with the Lax pair and by applying the first conservation quantity in $L^2(\mathbb{R}).$

Ha Anh Vu

This research presents a machine-learning approach for tumor detection in medical images using convolutional neural networks (CNNs). The study focuses on preprocessing techniques to enhance image features relevant to tumor detection, followed by developing and training a CNN model for accurate classification. Various image processing techniques, including Ga

Ran Finkelstein, Richard Bing-Shiun Tsai, Xiangkai Sun, Pascal Scholl

Enhancing the precision of measurements by harnessing entanglement is a long-sought goal in the field of quantum metrology. Yet attaining the best sensitivity allowed by quantum theory in the presence of noise is an outstanding challenge, requiring optimal probe-state generation and readout strategies. Neutral atom optical clocks, leading systems for measuri

C. Mielke, V. Sazgari, I. Plokhikh, S. Shin

The kagome lattice has emerged as a promising platform for hosting unconventional chiral charge order at high temperatures. Notably, in LaRu$_{3}$Si$_{2}$, a room-temperature charge-ordered state with a propagation vector of ($\frac{1}{4}$,~0,~0) has been recently identified. However, understanding the interplay between this charge order and superconductivit

Ran Xu, Wenqi Shi, Yue Yu, Yuchen Zhuang

We present RAM-EHR, a Retrieval AugMentation pipeline to improve clinical predictions on Electronic Health Records (EHRs). RAM-EHR first collects multiple knowledge sources, converts them into text format, and uses dense retrieval to obtain information related to medical concepts. This strategy addresses the difficulties associated with complex names for the

Cristian Vega, Stanislav Boldyrev, Vadim Roytershteyn

In a strongly magnetized, magnetically dominated relativistic plasma, Alfv\'enic turbulence can extend to scales much smaller than the particle inertial scales. It leads to an energy cascade somewhat analogous to inertial- or kinetic-Alfv\'en turbulent cascades existing in non-relativistic space and astrophysical plasmas. Based on phenomenological modeling a

Mykola Sereda, Tucker Allen, Nadine C. Bradbury, Khaled Z. Ibrahim

We extend our recently developed sparse-stochastic fragmented exchange formalism for ground-state hybrid DFT (ngH-DFT) to calculate absorption spectra within linear-response time-dependent Generalized Kohn-Sham DFT (LR-GKS-TDDFT), for systems consisting of thousands of valence electrons within a grid-based/plane-wave representation. A mixed deterministic/fra

Giovanni Di Giannatale, Alberto Bottino, Stephan Brunner, Moahan Murugappan

In this work, we explore the triangularity effects on turbulent transport employing global gyrokinetic simulations performed with the ORB5 code. Numerous experiments on the Tokamak \`a Configuration Variable (TCV) and, more recently, on the DIII-D machine, have demonstrated superior confinement properties in L-mode of negative triangularity (NT) over positiv

Marcin Briański, Daniel Kráľ, Kristýna Pekárková

The notion of branch-depth for matroids was introduced by DeVos, Kwon and Oum as the matroid analogue of the tree-depth of graphs. The contraction-deletion-depth, another tree-depth like parameter of matroids, is the number of recursive steps needed to decompose a matroid by contractions and deletions to single elements. Any matroid with contraction-deletion

Eric Dannetun, Riccardo Formenti, Bo Y. Gao, Juliann Geraci

Principal symmetric ideals were recently introduced by Harada, Seceleanu, and Sega, with a focus on their homological properties. They are ideals generated by the orbit of a single polynomial under permutations of variables in a polynomial ring. In this paper we seek to determine when a product of two principal symmetric ideals is principal symmetric and whe

Olli Saari, Hua-Yang Wang, Yuanhong Wei

We provide sparse estimates for gradients of solutions to divergence form elliptic partial differential equations in terms of the source data. We give a general result of Meyers (or Gehring) type, a result for linear equations with VMO coefficients and a result for linear equations with Dini continuous coefficients. In addition, we provide an abstract theore

Christopher Wiedeman, Chuang Niu, Mengzhou Li, Bruno De Man

Ultra-high resolution images are desirable in photon counting CT (PCCT), but resolution is physically limited by interactions such as charge sharing. Deep learning is a possible method for super-resolution (SR), but sourcing paired training data that adequately models the target task is difficult. Additionally, SR algorithms can distort noise texture, which

Cem Uluoglakci, Tugba Taskaya Temizel

Hallucinations pose a significant challenge to the reliability and alignment of Large Language Models (LLMs), limiting their widespread acceptance beyond chatbot applications. Despite ongoing efforts, hallucinations remain a prevalent challenge in LLMs. The detection of hallucinations itself is also a formidable task, frequently requiring manual labeling or

Mehdi Golafshan, Ivan Mitrofanov

We investigate unipotent dynamics on a torus and apply these techniques to the following problem. Let \(d\) be a positive integer, and let \(a > 0\) be a real number. For an integer \(b \geqslant 5\), such that \(a\) and \(b\) are multiplicatively independent, consider the sequence \((\mathbf{w}_n)\), where \(\mathbf{w}_n\) is the most significant digit of \

Jeremy Glick, William Huntington, Daniel Heinzen

We demonstrate an approach for producing a high flux beam of $^7$Li$^4$He dimers by performing post-nozzle seeding of a lithium beam into a supersonic helium expansion. The molecular beam has a longitudinal temperature of 13(6) mK and a continuous flux on the order of $10^{11}$ dimers/s. Monte Carlo simulations of molecular formation based on ab-initio quant

Seyed Morteza Hamzeh Pahnehkolaei, Amirreza Kachabi, Milad Heydari Sipey, Davood Domiri Ganji

In this paper, effect of physical parameters in presence of magnetic field on heat transfer and flow of third grade non-Newtonian Nanofluid in a porous medium with annular cross sectional analytically has been investigated. The viscosity of Nanofluid categorized in 3 model include constant model and variable models with temperature that in variable category

Ievgen Makedonskyi, Igor Makhlin

The first part of this paper concerns type C. We present new explicitly defined families of algebro-combinatorial structures of three kinds: combinatorial bases in representations, Newton--Okounkov bodies of flag varieties and toric degenerations of flag varieties. All three families are parametrized by the same family of polytopes: the marked chain-order po

Takafumi Mase

The theory of degree growth and algebraic entropy plays a crucial role in the field of discrete integrable systems. However, a general method for calculating degree growth for lattice equations (partial difference equations) is not yet known. Here we propose a method to rigorously compute the exact degree of each iterate for lattice equations. Halburd's meth

Haytham Al Ewaidat, Youness El Brag, Ahmad Wajeeh Yousef E'layan, Ali Almakhadmeh

Purpose Medical imaging diagnosis faces challenges, including low-resolution images due to machine artifacts and patient movement. This paper presents the Frequency-Guided U-Net (GFNet), a novel approach for medical image segmentation that addresses challenges associated with low-resolution images and inefficient feature extraction. Approach In response to c

Nicola Cotumaccio

Pattern matching queries on strings can be solved in linear time by Knuth-Morris-Pratt (KMP) algorithm. In 1973, Weiner introduced the suffix tree of a string [FOCS 1973] and showed that the seemingly more difficult problem of computing matching statistics can also be solved in liner time. Pattern matching queries on graphs are inherently more difficult: und

Tristan Maxson, Tibor Szilvasi

Machine learning interatomic potentials (MLIPs) are an emerging modeling technique that promises to provide electronic structure theory accuracy for a fraction of its cost, however, the transferability of MLIPs is a largely unknown factor. Recently, it has been proposed (J. Chem. Phys., 2023, 158, 084111) that MLIPs trained on solely liquid water data cannot

Animesh Datta, Ankit Sharma, Matinehsadat Hosseinigheidari, Uttam Singisetti

To investigate the transport properties in random alloys, it is important to model the alloy disorder using supercells. Though traditional methods like Virtual Crystal Approximation (VCA) are computationally efficient, the local disorder in the system is not accurately captured as artificial translational symmetry is imposed on the system. However, in the ca

Jaime E. Pineda, Olli Sipilä, Dominique M. Segura-Cox, Maria Teresa Valdivia-Mena

Electron fraction and cosmic-ray ionization rates (CRIR) in star-forming regions are important quantities in astrochemical modeling and are critical to the degree of coupling between neutrals, ions, and electrons, which regulates the dynamics of the magnetic field. However, these are difficult quantities to estimate. We aim to derive the electron fraction an

Yunqi Zhang, Shaileshh Bojja Venkatakrishnan

Popular blockchains today have hundreds of thousands of nodes and need to be able to support sophisticated scaling solutions$\unicode{x2013}$such as sharding, data availability sampling, and layer-2 methods. Designing secure and efficient peer-to-peer (p2p) networking protocols at these scales to support the tight demands of the upper layer crypto-economic p

Jianyou Wang, Kaicheng Wang, Xiaoyue Wang, Weili Cao

Effective information retrieval (IR) in settings with limited training data, particularly for complex queries, remains a challenging task. This paper introduces IR2, Information Regularization for Information Retrieval, a technique for reducing overfitting during synthetic data generation. This approach, representing a novel application of regularization tec

J. Wijnen, T. Vermeij, J. P. M. Hoefnagels, M. G. D. Geers

The role of heterogeneity in the plastic flow of thin ferrite specimens is investigated in this study. This is done through a recently introduced quasi-2D experimental-numerical framework that allows for a quantitative comparison of the deformation fields of metal microstructures between experiments and simulations at a high level of detail and complexity. T

Z. I. Shaikh, I. Y. Vasko, I. H. Hutchinson, S. R. Kamaletdinov

We present a statistical analysis of electrostatic solitary waves observed aboard Magnetospheric Multiscale spacecraft in the Earth's magnetosheath. Applying single-spacecraft interferometry to several hundred solitary waves collected in about two minute intervals, we show that almost all of them have the electrostatic potential of positive polarity and prop

Andrew Frohmader, Alexander Heaton

We consider Vinberg $\theta$-groups associated to a cyclic quiver on $k$ nodes. Let $K$ be the product of the general linear groups associated to each node. Then $K$ acts naturally on $\oplus \text{Hom}(V_i, V_{i+1})$ and by Vinberg's theory the polynomials are free over the invariants. We therefore consider the harmonics as a representation of $K$, and give

Maliheh Izadi, Jonathan Katzy, Tim van Dam, Marc Otten

Transformer-based language models for automatic code completion have shown great promise so far, yet the evaluation of these models rarely uses real data. This study provides both quantitative and qualitative assessments of three public code language models when completing real-world code. We first developed an open-source IDE extension, Code4Me, for the onl

Tomislav Maric, Mohammed Elwardi Fadeli, Alessandro Rigazzi, Andrew Shao

Combining machine learning (ML) with computational fluid dynamics (CFD) opens many possibilities for improving simulations of technical and natural systems. However, CFD+ML algorithms require exchange of data, synchronization, and calculation on heterogeneous hardware, making their implementation for large-scale problems exceptionally challenging. We provide

Anton Petrunin

We consider the following question: When does a Riemannian manifold admit an embedding with a uniformly thick tubular neighborhood in another Riemannian manifold of large dimension?

Omama Hamad, Ali Hamdi, Khaled Shaban

Effective feature representations play a critical role in enhancing the performance of text generation models that rely on deep neural networks. However, current approaches suffer from several drawbacks, such as the inability to capture the deep semantics of language and sensitivity to minor input variations, resulting in significant changes in the generated

Ekaterina Khestanova, Vanik Shahnazaryan, Valerii K. Kozin, Valeriy I. Kondratyev

Integration of 2D semiconductors with photonic crystal slabs provides an attractive approach to achieve strong light--matter coupling and exciton-polariton formation in a planar chip-compatible geometry. However, for the development of practical devices, it is crucial that the polariton excitations in the structure are easily tunable and exhibit strong nonli

Jiabao Ji, Bairu Hou, Alexander Robey, George J. Pappas

Aligned large language models (LLMs) are vulnerable to jailbreaking attacks, which bypass the safeguards of targeted LLMs and fool them into generating objectionable content. While initial defenses show promise against token-based threat models, there do not exist defenses that provide robustness against semantic attacks and avoid unfavorable trade-offs betw

Alexander V. Mikhailov, Pol Vanhaecke

It is well-known that a formal deformation of a commutative algebra ${\mathcal A}$ leads to a Poisson bracket on ${\mathcal A}$ and that the classical limit of a derivation on the deformation leads to a derivation on ${\mathcal A}$, which is Hamiltonian with respect to the Poisson bracket. In this paper we present a generalisation of it for formal deformatio

Jiahui Zhang, Runbo Jiang, Kangming Li, Pengyu Chen

The keyhole phenomenon has been widely observed in laser materials processing, including laser welding, remelting, cladding, drilling, and additive manufacturing. Keyhole-induced defects, primarily pores, dramatically affect the performance of final products, impeding the broad use of these laser-based technologies. The formation of these pores is typically

Youngeun Kim, Yuhang Li, Priyadarshini Panda

Prompt-based Continual Learning (PCL) has gained considerable attention as a promising continual learning solution as it achieves state-of-the-art performance while preventing privacy violation and memory overhead issues. Nonetheless, existing PCL approaches face significant computational burdens because of two Vision Transformer (ViT) feed-forward stages; o

Alexander Schmidt, Prathmesh Madhu, Andreas Maier, Vincent Christlein

Image enhancement algorithms are very useful for real world computer vision tasks where image resolution is often physically limited by the sensor size. While state-of-the-art deep neural networks show impressive results for image enhancement, they often struggle to enhance real-world images. In this work, we tackle a real-world setting: inpainting of images

Qi Pang, Shengyuan Hu, Wenting Zheng, Virginia Smith

Advances in generative models have made it possible for AI-generated text, code, and images to mirror human-generated content in many applications. Watermarking, a technique that aims to embed information in the output of a model to verify its source, is useful for mitigating the misuse of such AI-generated content. However, we show that common design choice

Liang Wu, Krystian Ganko, Shimin Wang, Richard D. Braatz

Establishing an execution time certificate in deploying model predictive control (MPC) is a pressing and challenging requirement. As nonlinear MPC (NMPC) results in nonlinear programs, differing from quadratic programs encountered in linear MPC, deriving an execution time certificate for NMPC seems an impossible task. Our prior work \cite{wu2023direct} intro

Heng Li, Maximillian Marin, Maha Reda Farhat

Motivation: The gene content regulates the biology of an organism. It varies between species and between individuals of the same species. Although tools have been developed to identify gene content changes in bacterial genomes, none is applicable to collections of large eukaryotic genomes such as the human pangenome. Results: We developed pangene, a computat

Ilan Price, Nicholas Daultry Ball, Samuel C. H. Lam, Adam C. Jones

Inducing and leveraging sparse activations during training and inference is a promising avenue for improving the computational efficiency of deep networks, which is increasingly important as network sizes continue to grow and their application becomes more widespread. Here we use the large width Gaussian process limit to analyze the behaviour, at random init

Maurizio Firrotta

We extend the Veneziano and Shapiro-Virasoro amplitudes to four arbitrarily excited states in bosonic string theory. We use the formalism of coherent string states based on the Di Vecchia-Del Giudice-Fubini construction. Within the same formalism, we also analyze the three string scattering finding the covariant version of the three reggeon interaction. Then

Subigya Nepal, Arvind Pillai, Weichen Wang, Tess Griffin

MoodCapture presents a novel approach that assesses depression based on images automatically captured from the front-facing camera of smartphones as people go about their daily lives. We collect over 125,000 photos in the wild from N=177 participants diagnosed with major depressive disorder for 90 days. Images are captured naturalistically while participants

Shenao Zhang, Sirui Zheng, Shuqi Ke, Zhihan Liu

Reinforcement learning (RL) has become the de facto standard practice for sequential decision-making problems by improving future acting policies with feedback. However, RL algorithms may require extensive trial-and-error interactions to collect useful feedback for improvement. On the other hand, recent developments in large language models (LLMs) have showc

Tokuhiro Eto, Yoshikazu Giga

We consider a minimizing movement scheme of Chambolle type for the mean curvature flow equation with prescribed contact angle condition in a smooth bounded domain in $\mathbb{R}^d$ ($d\geq2$). We prove that an approximate solution constructed by the proposed scheme converges to the level-set mean curvature flow with prescribed contact angle provided that the

Dragos Ghioca

In the goundbreaking paper [BD11] (which opened a wide avenue of research regarding unlikely intersections in arithmetic dynamics), Baker and DeMarco prove that for the family of polynomials $f_\lambda(x):=x^d+\lambda$ (parameterized by $\lambda\in\mathbb{C}$), given two starting points $a$ and $b$ in $\mathbb{C}$, if there exist infinitely many $\lambda\in\