April 2024 arXiv papers — page 16

Keyang Ye, Qiming Hou, Kun Zhou

The advent of neural and Gaussian-based radiance field methods have achieved great success in the field of novel view synthesis. However, specular reflection remains non-trivial, as the high frequency radiance field is notoriously difficult to fit stably and accurately. We present a deferred shading method to effectively render specular reflection with Gauss

Thusitha Dayaratne, Carsten Rudolph, Tom Shirley, Sol Levi

Ensuring the reliability and security of smart inverters that provide the interface between distributed energy resources (DERs) and the power grid becomes paramount with the surge in integrating DERs into the (smart) power grid. Despite the importance of having updated firmware / software versions within a reasonable time frame, existing methods for establis

Haoyu Li, Li Ma

This paper addresses the following problem. \begin{equation} \left\{ \begin{array}{lr} -{\Delta}u=\lambda I_\alpha*_\Omega u+|u|^{2^*-2}u\mbox{ in }\Omega ,\nonumber u\in H_0^1(\Omega).\nonumber \end{array} \right. \end{equation} Here, $\Omega$ is a bounded domain in $\mathbb{R}^N$ with $N\geq3$, $2^*=\frac{2N}{N-2}$, $\lambda\in\mathbb{R}$, $\lambda\in(0,N)

T. Aguilar, A. Capelo-Astudillo, M. Conde-Correa, A. Duenas-Vidal

We provide an in-detail derivation through the $^3P_0$ pair creation model of the transition matrix for a baryon decaying into a meson-baryon system. The meson's analysis was conducted in Ref. [1] and we extend the same formalism to the baryon sector, focusing on the $\Delta(1232)\to \pi N$ strong decay width because all hadrons involved in the reaction are

Rhona L Hamilton, Moeri Horiuchi, Bowen Liu, Takuma Shirahata

The threshold pump power for modelocking decreased by 18% when the temperature was increased from 25 to 100 degrees C, where a SWCNT/PDMS coated tapered fiber was used as the saturable absorber in a fiber laser. Further, the pump power at which multi-pulse operation began decreased by 24%, and the pump power range over which fundamental modelocking could be

Chaewon Lee, Seon-Ho Lee, Chang-Su Kim

In recent interactive segmentation algorithms, previous probability maps are used as network input to help predictions in the current segmentation round. However, despite the utilization of previous masks, useful information contained in the probability maps is not well propagated to the current predictions. In this paper, to overcome this limitation, we pro

Joon Lee, Nicolas Macris, Jean Bernoulli Ravelomanana, Perrine Vantalon

The $k$-QSAT problem is a quantum analog of the famous $k$-SAT constraint satisfaction problem. We must determine the zero energy ground states of a Hamiltonian of $N$ qubits consisting of a sum of $M$ random $k$-local rank-one projectors. It is known that product states of zero energy exist with high probability if and only if the underlying factor graph ha

Xiaoshan Huang, Shane W. Davis, Yan-fei Jiang

The rising part of a tidal disruption event light curve provides unique insight into early emission and the onset of accretion. Various mechanisms are proposed to explain the pre-peak emission, including shocks from debris interaction and reprocessing of disk emission. We study the pre-peak emission and its influence on the gas circularization by a series of

Christian Peukert, Florian Abeillon, Jérémie Haese, Franziska Kaiser

Artificial intelligence (AI) systems rely heavily on human-generated data, yet the people behind that data are often overlooked. Human behavior can play a major role in AI training datasets, be it in limiting access to existing works or in deciding which types of new works to create or whether to create any at all. We examine creators' behavioral change when

Song Mei

U-Nets are among the most widely used architectures in computer vision, renowned for their exceptional performance in applications such as image segmentation, denoising, and diffusion modeling. However, a theoretical explanation of the U-Net architecture design has not yet been fully established. This paper introduces a novel interpretation of the U-Net arch

Yuan Wang, Huazhu Fu, Renuga Kanagavelu, Qingsong Wei

The performance of Federated Learning (FL) hinges on the effectiveness of utilizing knowledge from distributed datasets. Traditional FL methods adopt an aggregate-then-adapt framework, where clients update local models based on a global model aggregated by the server from the previous training round. This process can cause client drift, especially with signi

Eunji Ko, Seul Lee, Minseon Kim, Dongki Kim

The goal of protein representation learning is to extract knowledge from protein databases that can be applied to various protein-related downstream tasks. Although protein sequence, structure, and function are the three key modalities for a comprehensive understanding of proteins, existing methods for protein representation learning have utilized only one o

Ran Xu, Wenqi Shi, Yue Yu, Yuchen Zhuang

Developing effective biomedical retrieval models is important for excelling at knowledge-intensive biomedical tasks but still challenging due to the deficiency of sufficient publicly annotated biomedical data and computational resources. We present BMRetriever, a series of dense retrievers for enhancing biomedical retrieval via unsupervised pre-training on l

Xingyu Guo, Chen-Te Ma, Hui Zhang

We work the lattice fermions and non-Hermitian formulation in the 2D GNY model and demonstrate the numerical implementation for two flavors by the Hybrid Monte Carlo. Our approach has a notable advantage in dealing with chiral symmetry on a lattice by avoiding the Nielsen-Ninomiya theorem, due to the non-symmetrized finite-difference operator. We restore the

Kairui Feng, Dazhi Xi, Wei Ma, Cao Wang

The advents of Artificial Intelligence (AI)-driven models marks a paradigm shift in risk management strategies for meteorological hazards. This study specifically employs tropical cyclones (TCs) as a focal example. We engineer a perturbation-based method to produce ensemble forecasts using the advanced Pangu AI weather model. Unlike traditional approaches th

Yunxuan Mao, Bingqi Shen, Yifei Yang, Kai Wang

The joint optimization of the sensor trajectory and 3D map is a crucial characteristic of bundle adjustment (BA), essential for autonomous driving. This paper presents $\nu$-DBA, a novel framework implementing geometric dense bundle adjustment (DBA) using 3D neural implicit surfaces for map parametrization, which optimizes both the map surface and trajectory

Tingfang Chen, Zhonghua Sun, Conghui Xie, Hao Chen

Constacyclic codes over finite fields are an important class of linear codes as they contain distance-optimal codes and linear codes with best known parameters. They are interesting in theory and practice, as they have the constacyclic structure. In this paper, an infinite class of $q$-ary negacyclic codes of length $(q^m-1)/2$ and an infinite class of $q$-a

Ziling Heng, Mengjie Yang, Yang Ming

Linear codes are widely studied due to their applications in communication, cryptography, quantum codes, distributed storage and many other fields. In this paper, we use the trace and norm functions over finite fields to construct a family of linear codes. The weight distributions of the codes are determined in three cases via Gaussian sums. The codes are sh

Hanh Vo, Puttipong Pongtanapaisan, Thieu Nguyen

This paper employs various computational techniques to determine the bridge numbers of both classical and virtual knots. For classical knots, there is no ambiguity of what the bridge number means. For virtual knots, there are multiple natural definitions of bridge number, and we demonstrate that the difference can be arbitrarily far apart. We then acquired t

Jun Yu, Yutong Dai, Xiaokang Liu, Jin Huang

MTL is a learning paradigm that effectively leverages both task-specific and shared information to address multiple related tasks simultaneously. In contrast to STL, MTL offers a suite of benefits that enhance both the training process and the inference efficiency. MTL's key advantages encompass streamlined model architecture, performance enhancement, and cr

Chao Dong, Yifan Zhang, Ziye Jia, Yiyang Liao

The environment of low-altitude urban airspace is complex and variable due to numerous obstacles, non-cooperative aircrafts, and birds. Unmanned aerial vehicles (UAVs) leveraging environmental information to achieve three-dimension collision-free trajectory planning is the prerequisite to ensure airspace security. However, the timely information of surroundi

Josephine Munro, Sarah E. Dean, Neuton Li, Israel J. Vaughn

The Giant Magellan Telescope will use laser tomography adaptive optics to correct for atmospheric turbulence using artificial guide stars created in the sodium layer of the atmosphere (altitude ~95km). The sodium layer has appreciable thickness (~11km) and this results in the laser guide star being an elongated cylinder shape. Wavefront sensing with a Shack-

Ziling Heng, Keqing Cao

In this paper, we first generalize the class of linear codes by Ding and Ding (IEEE TIT, 61(11), pp. 5835-5842, 2015). Then we mainly study the augmented codes of this generalized class of linear codes. For one thing, we use Gaussian sums to determine the parameters and weight distributions of the augmented codes in some cases. It is shown that the augmented

Zhuohao Li, Guoyang Xie, Guannan Jiang, Zhichao Lu

Transformer recently emerged as the de facto model for computer vision tasks and has also been successfully applied to shadow removal. However, these existing methods heavily rely on intricate modifications to the attention mechanisms within the transformer blocks while using a generic patch embedding. As a result, it often leads to complex architectural des

Sandra Jeyakumar, Michael Kraus, Matthew J. Hole, David Pfefferlé

We present a novel family of particle discretisation methods for the nonlinear Landau collision operator. We exploit the metriplectic structure underlying the Vlasov-Maxwell-Landau system in order to obtain disretisation schemes that automatically preserve mass, momentum, and energy, warrant monotonic dissipation of entropy, and are thus guaranteed to respec

Soumya Chakrabarti, Chiranjeeb Singha

We report a family of self-similar exact solutions in General Relativity. The solutions are found in a Painleve-Gullstrand coordinate system but can also be transformed smoothly into a diagonal form. The solutions represent a gravitational collapse leading to three possible outcomes, depending on the parameter space : (i) a collapse followed by a bounce and

Wenjun Wu, Shuo Sun, Chi Sin Tang, Jing Wu

Flat bands and Dirac cones in materials are at the source of the exotic electronic and topological properties. The Lieb lattice is expected to host these electronic structures, arising from quantum destructive interference. Nevertheless, the experimental realization of a two-dimensional Lieb lattice remained challenging to date due to its intrinsic structura

Nicholas Loveday, Deryn Griffiths, Tennessee Leeuwenburg, Robert Taggart

Forecast verification is critical for continuous improvement in meteorological organizations. The Jive verification system was originally developed to assess the accuracy of public weather forecasts issued by the Australian Bureau of Meteorology. It started as a research project in 2015 and gradually evolved to be a Bureau operational verification system in

Jiayang Wu, Wensheng Gan, Han-Chieh Chao, Philip S. Yu

In recent years, geospatial big data (GBD) has obtained attention across various disciplines, categorized into big earth observation data and big human behavior data. Identifying geospatial patterns from GBD has been a vital research focus in the fields of urban management and environmental sustainability. This paper reviews the evolution of GBD mining and i

Shin'ichi Nojiri, S. D. Odintsov

We formulate the convenient and mimetic $f(Q)$ gravities in terms of the metric and four scalar fields with the $Q$ being the non-metricity scalar. As a result, it is shown that the obtained field equations are well-defined. By using the field equations, we show how the $f(Q)$ models which realise any given FLRW spacetime may be reconstructed. We construct c

Wenbin Guan, Zijiu Yang, Xiaohong Wu, Liqiong Chen

Presently, the task of few-shot object detection (FSOD) in remote sensing images (RSIs) has become a focal point of attention. Numerous few-shot detectors, particularly those based on two-stage detectors, face challenges when dealing with the multiscale complexities inherent in RSIs. Moreover, these detectors present impractical characteristics in real-world

Sing-Yuan Yeh, Hau-Tieng Wu, Ronen Talmon, Mao-Pei Tsui

Alternating Diffusion (AD) is a commonly applied diffusion-based sensor fusion algorithm. While it has been successfully applied to various problems, its computational burden remains a limitation. Inspired by the landmark diffusion idea considered in the Robust and Scalable Embedding via Landmark Diffusion (ROSELAND), we propose a variation of AD, called Lan

Masoumeh Nazari, Yaser Mike Banad, Sarah S. Sharif

This paper introduces tunable and switchable Perfect Absorbers (PAs) operating within the mid-infrared spectrum, specifically targeting the 3 to 5 um range at 0.25 um intervals. This spectrum is engineered for minimal atmospheric absorption and unique transmission characteristics. Our approach uses graphene-based nanophotonic aperiodic multilayer structures,

Shengyao Zhuang, Xueguang Ma, Bevan Koopman, Jimmy Lin

Utilizing large language models (LLMs) for zero-shot document ranking is done in one of two ways: (1) prompt-based re-ranking methods, which require no further training but are only feasible for re-ranking a handful of candidate documents due to computational costs; and (2) unsupervised contrastive trained dense retrieval methods, which can retrieve relevant

Walid Saad, Omar Hashash, Christo Kurisummoottil Thomas, Christina Chaccour

Building future wireless systems that support services like digital twins (DTs) is challenging to achieve through advances to conventional technologies like meta-surfaces. While artificial intelligence (AI)-native networks promise to overcome some limitations of wireless technologies, developments still rely on AI tools like neural networks. Such tools strug

Yeon-Ji Song, Jaein Kim, Suhyung Choi, Jin-Hwa Kim

Human perception involves decomposing complex multi-object scenes into time-static object appearance (i.e., size, shape, color) and time-varying object motion (i.e., position, velocity, acceleration). For machines to achieve human-like intelligence in real-world interactions, understanding these physical properties of objects is essential, forming the founda

Arup Chattopadhyay, Teun D. H. van Nuland, Chandan Pradhan

Given $H$ self-adjoint, $V$ symmetric and relatively $H$-bounded, and $f:\mathbb{R}\to\mathbb{C}$ satisfying mild conditions, we show that the Gateaux derivative $$\frac{d^n}{dt^n}f(H+tV)|_{t=0}$$ exists in the operator norm topology, for every natural $n$, give a new explicit formula for this derivative in terms of multiple operator integrals, and establish

Tianqing Liu, Xiaohui Yuan

Count time series data are frequently analyzed by modeling their conditional means and the conditional variance is often considered to be a deterministic function of the corresponding conditional mean and is not typically modeled independently. We propose a semiparametric mean and variance joint model, called random rounded count-valued generalized autoregre

Yi Lu, Chuanyu Wang, Soumya K. Kanungo, F. Barry Dunning

We simulate the the Su-Schrieffer-Heeger (SSH) model using Rydberg-atom synthetic dimensions constructed, in a single atom, from a ladder of six neighboring $n\:^3S_1$ Rydberg states in which adjacent states are coupled with two-photon transitions using microwave fields. Alternating strong/weak tunneling rates, controlled by adjusting the microwave amplitude

Jiajie Yuan, Linxiao Wu, Yulu Gong, Zhou Yu

This paper combines Struts and Hibernate two architectures together, using DAO (Data Access Object) to store and access data. Then a set of dual-mode humidity medical image library suitable for deep network is established, and a dual-mode medical image assisted diagnosis method based on the image is proposed. Through the test of various feature extraction me

Xiaoxue Zhao, Yijun Yu, Yexing Li, Dong Li

The continuous emergence of novel services and massive connections involve huge energy consumption towards ultra-dense radio access networks. Moreover, there exist much more number of controllable parameters that can be adjusted to reduce the energy consumption from a network-wide perspective. However, a network-level energy-saving intent usually contains mu

Cheng Zhang, Arthur Azevedo de Amorim, Marco Gaboardi

TopKAT is the algebraic theory of Kleene algebra with tests (KAT) extended with a top element. Compared to KAT, one pleasant feature of TopKAT is that, in relational models, the top element allows us to express the domain and codomain of a relation. This enables several applications in program logics, such as proving under-approximate specifications or reach

Steven Shave, Richard Kasprowicz, Abdullah M. Athar, Denise Vlachou

The Connectivity Map (CMap) is a large publicly available database of cellular transcriptomic responses to chemical and genetic perturbations built using a standardized acquisition protocol known as the L1000 technique. Databases such as CMap provide an exciting opportunity to enrich drug discovery efforts, providing a 'known' phenotypic landscape to explore

Khaled Saab, Tao Tu, Wei-Hung Weng, Ryutaro Tanno

Excellence in a wide variety of medical applications poses considerable challenges for AI, requiring advanced reasoning, access to up-to-date medical knowledge and understanding of complex multimodal data. Gemini models, with strong general capabilities in multimodal and long-context reasoning, offer exciting possibilities in medicine. Building on these core

Mu-Tian Wang, Hui-Gen Liu

TOI-1338 is the first circumbinary planet system discovered by TESS. It has one transiting planet at P$\sim$95 day and an outer non-transiting planet at P$\sim$215 day complemented by RV observation. Here we present a global photo-dynamical modeling of the TOI-1338 system that self-consistently accounts for the mutual gravitational interactions between all k

Saeed Damadi, Soroush Zolfaghari, Mahdi Rezaie, Jinglai Shen

The core of a good model is in its ability to focus only on important information that reflects the basic patterns and consistencies, thus pulling out a clear, noise-free signal from the dataset. This necessitates using a simplified model defined by fewer parameters. The importance of theoretical foundations becomes clear in this context, as this paper relie

Justin Zhao, Timothy Wang, Wael Abid, Geoffrey Angus

Low Rank Adaptation (LoRA) has emerged as one of the most widely adopted methods for Parameter Efficient Fine-Tuning (PEFT) of Large Language Models (LLMs). LoRA reduces the number of trainable parameters and memory usage while achieving comparable performance to full fine-tuning. We aim to assess the viability of training and serving LLMs fine-tuned with Lo

Xinyu Ma, Xuebo Liu, Derek F. Wong, Jun Rao

Multimodal machine translation (MMT) is a challenging task that seeks to improve translation quality by incorporating visual information. However, recent studies have indicated that the visual information provided by existing MMT datasets is insufficient, causing models to disregard it and overestimate their capabilities. This issue presents a significant ob

Mingyao Chen, Huimin Liu, Xu He, Minjuan Li

The interaction of atomic orbitals at the interface of perovskite oxide heterostructures has been investigated for its profound impact on the band structures and electronic properties, giving rise to unique electronic states and a variety of tunable functionalities. In this study, we conducted an extensive investigation of the optical and electronic properti

Mingi Jeong, Arihant Chadda, Ziang Ren, Luyang Zhao

This paper introduces the first publicly accessible labeled multi-modal perception dataset for autonomous maritime navigation, focusing on in-water obstacles within the aquatic environment to enhance situational awareness for Autonomous Surface Vehicles (ASVs). This dataset, collected over 4 years and consisting of diverse objects encountered under varying e

Bowen Xu, Shaoyu Wu, Kai Liu, Lulu Hu

With the proliferation of large language models (LLMs), the comprehensive alignment of such models across multiple tasks has emerged as a critical area of research. Existing alignment methodologies primarily address single task, such as multi-turn dialogue, coding, mathematical problem-solving, and tool usage. Although there is a large amount of high-quality

Jiquan Yuan, Fanyi Yang, Jihe Li, Xinyan Cao

In recent years, image generation technology has rapidly advanced, resulting in the creation of a vast array of AI-generated images (AIGIs). However, the quality of these AIGIs is highly inconsistent, with low-quality AIGIs severely impairing the visual experience of users. Due to the widespread application of AIGIs, the AI-generated image quality assessment

Peng-Liang Du, Wei Du, Bing-Qing Zhang, Zhen-Ping Yi

From $\sim$ 5000 deg$^{2}$ of the combination of the Beijing-Arizona Sky Survey (BASS) and Mayall $z$-band Legacy Survey (MzLS) which is also the northern sky region of the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, we selected a sample of 31,825 candidates of low surface brightness galaxies (LSBGs) with the mean effective surface br

Ruisi Zhang, Rachel Selina Rajarathnam, David Z. Pan, Farinaz Koushanfar

Physical design watermarking on contemporary integrated circuit (IC) layout encodes signatures without considering the dense connections and design constraints, which could lead to performance degradation on the watermarked products. This paper presents ICMarks, a quality-preserving and robust watermarking framework for modern IC physical design. ICMarks emb

Pengcheng Chen, Yuxuan Yang, Bin Lyu, Zhen Yang

In this paper, we propose a movable antenna (MA) enhanced scheme for wireless powered mobile edge computing (WP-MEC) system, where the hybrid access point (HAP) equipped with multiple MAs first emits wireless energy to charge wireless devices (WDs), and then receives the offloaded tasks from the WDs for edge computing. The MAs deployed at the HAP enhance the

Josh Andres, Chris Danta, Andrea Bianchi, Sungyeon Hong

Generative AI capabilities are rapidly transforming how we perceive, interact with, and relate to machines. This one-day workshop invites HCI researchers, designers, and practitioners to imaginatively inhabit and explore the possible futures that might emerge from humans combining generative AI capabilities into everyday technologies at massive scale. Worksh

Shuo-Hui Li, Yao-Wen Zhang, Ding Pan

It is a long-standing challenge to accurately and efficiently compute thermodynamic quantities of many-body systems at thermal equilibrium. The conventional methods, e.g., Markov chain Monte Carlo, require many steps to equilibrate. The recently developed deep learning methods can perform direct sampling, but only work at a single trained temperature point a

Tom Shachar, Ritam Sinha, Michael Smolkin

It is known that for RG flows confined to a two-dimensional defect, where the bulk maintains its conformal nature, the coefficient of the Euler density in the defect's Weyl anomaly (termed b) cannot increase as the flow progresses from the ultraviolet to the infrared, a principle known as the b-theorem. In this paper, we investigate whether this theorem stil

Jie Liu, Yue Cai, Kang-Jie Ma, Lei Tan

We study the entanglement generation of two giant atoms within a one-dimensional bidirectional-chiral waveguide quantum electrodynamics (QED) system, where the initial state of the two giant atoms are $|e_a,g_b\rangle $. Here, each giant atom is coupled to the waveguide through three connection points, with the configurations divided into five types based on

Lingbo Huang, Yushi Chen, Xin He

Recently, deep learning models have achieved excellent performance in hyperspectral image (HSI) classification. Among the many deep models, Transformer has gradually attracted interest for its excellence in modeling the long-range dependencies of spatial-spectral features in HSI. However, Transformer has the problem of quadratic computational complexity due

Parshin Shojaee, Kazem Meidani, Shashank Gupta, Amir Barati Farimani

Mathematical equations have been unreasonably effective in describing complex natural phenomena across various scientific disciplines. However, discovering such insightful equations from data presents significant challenges due to the necessity of navigating extremely large combinatorial hypothesis spaces. Current methods of equation discovery, commonly know

Jinwon Ko, Dongkwon Jin, Chang-Su Kim

A novel algorithm, called semantic line combination detector (SLCD), to find an optimal combination of semantic lines is proposed in this paper. It processes all lines in each line combination at once to assess the overall harmony of the lines. First, we generate various line combinations from reliable lines. Second, we estimate the score of each line combin

Zhi-Qi Cheng, Xiang Li, Jun-Yan He, Junyao Chen

Emotional Text-to-Speech (E-TTS) synthesis has garnered significant attention in recent years due to its potential to revolutionize human-computer interaction. However, current E-TTS approaches often struggle to capture the intricacies of human emotions, primarily relying on oversimplified emotional labels or single-modality input. In this paper, we introduc

Huy Quang Pham, Thang Kien-Bao Nguyen, Quan Van Nguyen, Dan Quang Tran

Optical Character Recognition - Visual Question Answering (OCR-VQA) is the task of answering text information contained in images that have just been significantly developed in the English language in recent years. However, there are limited studies of this task in low-resource languages such as Vietnamese. To this end, we introduce a novel dataset, ViOCRVQA

Ranyang Zhou, Jacqueline T. Liu, Nakul Kochar, Sabbir Ahmed

RowHammer stands out as a prominent example, potentially the pioneering one, showcasing how a failure mechanism at the circuit level can give rise to a significant and pervasive security vulnerability within systems. Prior research has approached RowHammer attacks within a static threat model framework. Nonetheless, it warrants consideration within a more nu

Jungwoo Lee, Younggun Cho

This paper proposes a photorealistic real-time dense 3D mapping system that utilizes a learning-based image enhancement method and mesh-based map representation. Due to the characteristics of the underwater environment, where problems such as hazing and low contrast occur, it is hard to apply conventional simultaneous localization and mapping (SLAM) methods.

Zhiming Chang, Boyang Liu, Yifei Xia, Youming Guo

Monitoring space objects is crucial for space situational awareness, yet reconstructing 3D satellite models from ground-based telescope images is challenging due to atmospheric turbulence, long observation distances, limited viewpoints, and low signal-to-noise ratios. In this paper, we propose a novel computational imaging framework that overcomes these obst

James Paolo Rili

A neural network is used to train, predict, and evaluate a model to calculate the energies of 3-dimensional systems composed of Ti and O atoms. Python classes are implemented to quantify atomic interactions through symmetry functions and to specify prediction algorithms. The hyperparameters of the model are optimised by minimising validation RMSE, which then

Xinzijian Liu, Yanbo Han, Zhuoyuan Li, Jiahao Fan

In the AI-for-science era, scientific computing scenarios such as concurrent learning and high-throughput computing demand a new generation of infrastructure that supports scalable computing resources and automated workflow management on both cloud and high-performance supercomputers. Here we introduce Dflow, an open-source Python toolkit designed for scient

Xinping Zhou, Yuandeng Shen, Yihua Yan, Ke Yu

This paper presents three distinct wave trains that occurred on 2023 April 21: a broad quasi-periodic fast-propagating (QFP) wave train and a bi-directional narrow QFP wave train. The broad QFP wave train expands outward in a circular wavefront, while bi-directional narrow QFP wave trains propagate in the northward and southward directions, respectively. The

Sifan Long, Xiaowei Guo, Xiaokang Fan, Canqun Yang

Solving Fluid-Structure Interaction (FSI) problems using traditional methods is a big challenge in the field of numerical simulation. As a powerful multi-physical field coupled library, preCICE has a bright application prospect for solving FSI, which supports many open/closed source software and commercial CFD solvers to solve FSI problems in the form of a b

Tong Yang, Mingying Zhong

We study the diffusion limit of the strong solution to the Vlasov-Maxwell-Boltzmann (VMB) system with initial data near a global Maxwellian. By introducing a new decomposition of the solution to identify the essential components for generating the initial layer, we prove the convergence and establish the opitmal convergence rate of the classical solution to

Chenghong Wang, Lina Qiu, Johes Bater, Yukui Luo

Secure collaborative analytics (SCA) enable the processing of analytical SQL queries across multiple owners' data, even when direct data sharing is not feasible. Although essential for strong privacy, the large overhead from data-oblivious primitives in traditional SCA has hindered its practical adoption. Recent SCA variants that permit controlled leakages u

Yunori Nishikawa, Tomoki Yoshioka

We consider quantum entanglement in strongly correlated quantum impurity systems for states manifesting interesting properties such as multi-level Kondo effect and dual nature between itineracy and localization etc.. For this purpose, we set up a system consisting of one or two quantum impurities arbitrarily selected from the system as a subsystem, and inves

Yao Wang, Yijun Yu, Yexing Li, Dong Li

With recent advancements in the sixth generation (6G) communication technologies, more vertical industries have encountered diverse network services. How to reduce energy consumption is critical to meet the expectation of the quality of diverse network services. In particular, the number of base stations in 6G is huge with coupled adjustable network paramete

Yixuan Li, Dan C. Baciu, Marcos Novak, George Legrady

Over the past year, the emergence of advanced text-to-image Generative AI models has significantly impacted the art world, challenging traditional notions of creativity and the role of artists. This study explores how artists interact with these technologies, using a 5P model (Purpose, People, Process, Product, and Press) based on Rhodes' creativity framewor

Jordan Meadows, Tamsin James, Andre Freitas

Language models (LMs) can hallucinate when performing complex mathematical reasoning. Physics provides a rich domain for assessing their mathematical capabilities, where physical context requires that any symbolic manipulation satisfies complex semantics (\textit{e.g.,} units, tensorial order). In this work, we systematically remove crucial context from prom

Brendan Hertel, Nhu Tran, Meriem Elkoudi, Reza Azadeh

In this paper, we present our work in progress towards creating a library of motion primitives. This library facilitates easier and more intuitive learning and reusing of robotic skills. Users can teach robots complex skills through Learning from Demonstration, which is automatically segmented into primitives and stored in clusters of similar skills. We prop

Dongqi Sun, Qiang E

A weak reducing pair in a Heegaard splitting M = V \cup_S W is a pair of disjoint essential disks D \in V and E \in W. The weakly reducible Heegaard splitting contains at least one weak reducing pair. Critical Heegaard splitting is a special case of weakly reducible Heegaard splitting which contains at least two weak reducing pairs satisfying some special co

David Hall, Stephen Hausler, Sutharsan Mahendren, Peyman Moghadam

Neural fields provide a continuous scene representation of 3D geometry and appearance in a way which has great promise for robotics applications. One functionality that unlocks unique use-cases for neural fields in robotics is object 6-DoF registration. In this paper, we provide an expanded analysis of the recent Reg-NF neural field registration method and i

Mohamed-Ali Belabbas, Jehyung Ko

We investigate global dynamic feedback stabilization from a topological viewpoint. In particular, we consider the general case of dynamic feedback systems, whereby the total space (which includes the state space of the system and of the controller) is a fibre bundle, and derive conditions on the topology of the bundle that are necessary for various notions o

Genival da Silva

In this manuscript we prove the existence of solutions to a fully nonlinear system of (degenerate) elliptic equations of Lane-Emden type and discuss a inhomogeneous generalization.

Jose Figueroa, Gaston Giribet, Anibal Neira-Gallegos, Julio Oliva

We study solutions of Einstein equations with negative cosmological constant in five dimensions that describe black holes whose event horizons are homogeneous, anisotropic spaces. We focus on the case where the constant-time slices of the horizon are the Nil geometry, the Thurston geometry associated to the Heisenberg group. For such spaces, we analyze the s

Bing Su, Ke Zhu

We propose a panel ARMA-GARCH model to capture the dynamics of large panel data with $N$ individuals over $T$ time periods. For this model, we provide a two-step estimation procedure to estimate the ARMA parameters and GARCH parameters stepwisely. Under some regular conditions, we show that all of the proposed estimators are asymptotically normal with the co

Alfredo González Lezcano, Imtak Jeon, Augniva Ray

Quantum study of supersymmetric theories on Euclidean two dimensional anti-de Sitter space (EAdS$_2$) requires complexified spectrum. For a chiral multiplet, we showed that the spectrum of the Dirac operator acquires a universal shift of $\text{i}/2$ from the real spectrum to make the supersymmetry between boson and fermion manifest, where both the bosonic a

Yongjin Yang, Sihyeon Kim, SangMook Kim, Gyubok Lee

Incorporating unanswerable questions into EHR QA systems is crucial for testing the trustworthiness of a system, as providing non-existent responses can mislead doctors in their diagnoses. The EHRSQL dataset stands out as a promising benchmark because it is the only dataset that incorporates unanswerable questions in the EHR QA system alongside practical que

Fanjun Bu, Alexandra Bremers, Mark Colley, Wendy Ju

Human-robot interaction requires to be studied in the wild. In the summers of 2022 and 2023, we deployed two trash barrel service robots through the wizard-of-oz protocol in public spaces to study human-robot interactions in urban settings. We deployed the robots at two different public plazas in downtown Manhattan and Brooklyn for a collective of 20 hours o

Joshua Ott, Edward Balaban, Mykel Kochenderfer

We consider the problem of an autonomous agent equipped with multiple sensors, each with different sensing precision and energy costs. The agent's goal is to explore the environment and gather information subject to its resource constraints in unknown, partially observable environments. The challenge lies in reasoning about the effects of sensing and movemen

Peng Shi

The study shows that errors exist in the derivation of equilibrium equations in terms of displacement. It is discovered that when the equilibrium equations in terms of displacement are derived, the variation of the differential order of displacement may cause the variation of the stress state in an elastomer. For plane stress problems, the Lame-Navier equati

Sifan Long, Fengxiao Tang, Yangfan Li, Tiao Tan

The sixth generation mobile communication standard (6G) can promote the development of Industrial Internet and Internet of Things (IoT). To achieve comprehensive intelligent development of the network and provide customers with higher quality personalized services. This paper proposes a network performance optimization and intelligent operation network archi

Bao-Feng Feng, Heng-Chun Hu, Han-Han Sheng, Wei Yin

In the present paper, an integrable semi-discretization of the modified Camassa-Holm (mCH) equation with cubic nonlinearity is presented. The key points of the construction are based on the discrete Kadomtsev-Petviashvili (KP) equation and appropriate definition of discrete reciprocal transformations. First, we demonstrate that these bilinear equations and t

Tomoki Fukuma, Koki Noda, Toshihide Ubukata Kousuke Hoso, Yoshiharu Ichikawa

The proliferation of social media has led to information overload and increased interest in opinion mining. We propose "Question-Answering Network Analysis" (QANA), a novel opinion mining framework that utilizes Large Language Models (LLMs) to generate questions from users' comments, constructs a bipartite graph based on the comments' answerability to the qu

Yujin Jeong, Dominik Rothenhäusler

Many existing approaches for estimating parameters in settings with distributional shifts operate under an invariance assumption. For example, under covariate shift, it is assumed that $p(y|x)$ remains invariant. We refer to such distribution shifts as sparse, since they may be substantial but affect only a part of the data generating system. In contrast, in

Daniel Bochen Tan, Murphy Yuezhen Niu, Craig Gidney

Quantum error correction is necessary for large-scale quantum computing. A promising quantum error correcting code is the surface code. For this code, fault-tolerant quantum computing (FTQC) can be performed via lattice surgery, i.e., splitting and merging patches of code. Given the frequent use of certain lattice-surgery subroutines (LaS), it becomes crucia

Nawaj KC, Josh Pollitz

This article is concerned with nonzero modules of finite length and finite projective dimension over a local ring. We show the Loewy length of such a module is larger than the regularity of the ring whenever the ring is strict Cohen-Macaulay, establishing a conjecture of Corso--Huneke--Polini--Ulrich for such rings. In fact, we show the stronger result that

Logan Hyslop

In this paper, motivated by studying special values of zeta functions attached to finite type F_p-schemes, we introduce a category of ``arithmetic C(S^1,R)-modules'' attached to any Dedekind ring R, and compute the 0th K-group of this category. Specializing to the case of R=Z_l for some prime l neq p (resp. R=Z_p), we prove that there is a natural functorial

Han-Yu Wang, Xiao-Cheng Bai, Wen-Feng Wu, Zhi Zeng

CsV3Sb5, a notable compound within the kagome family, is renowned for its topological and superconducting properties, as well as its detection of local magnetic field and anomalous Hall effect in experiments. However, the origin of this local magnetic field is still veiled. In this study, we employ the first-principles calculations to investigate the atomic

Jonas Hielscher, Simon Parkin

Security awareness campaigns in organizations now collectively cost billions of dollars annually. There is increasing focus on ensuring certain security behaviors among employees. On the surface, this would imply a user-centered view of security in organizations. Despite this, the basis of what security awareness managers do and what decides this are unclear

Tadahisa Funaki

We consider the Glauber-Kawasaki dynamics on a $d$-dimensional periodic lattice of size $N$, that is, a stochastic time evolution of particles performing random walks with interaction subject to the exclusion rule (Kawasaki part), in general, of non-gradient type, together with the effect of the creation and annihilation of particles (Glauber part) whose rat

Woojin Lee, Babar Shahzaad, Balsam Alkouz, Athman Bouguettaya

We propose a novel failure-aware reactive UAV delivery service composition framework. A skyway network infrastructure is presented for the effective provisioning of services in urban areas. We present a formal drone delivery service model and a system architecture for reactive drone delivery services. We develop radius-based, cell density-based, and two-phas