July 2023 arXiv papers — page 47

Ming-Wei Li, Zhong-Lv Huang, Xiao-Gang He

Due to finite masses and mixing, for neutrinos propagation in space-time, there is a chiral oscillation between left- and right- chiral neutrinos, besides the usual oscillation between different generations. The probability of chiral oscillation is suppressed by a factor of $m^2/E^2$ making the effect small for relativistic neutrinos. However, for non-relati

Clinton J. Wang, Polina Golland

One little-explored frontier of image generation and editing is the task of interpolating between two input images, a feature missing from all currently deployed image generation pipelines. We argue that such a feature can expand the creative applications of such models, and propose a method for zero-shot interpolation using latent diffusion models. We apply

Zihao Li, Changkun Jiang, Jianqiang Li

Automatic protein function prediction (AFP) is classified as a large-scale multi-label classification problem aimed at automating protein enrichment analysis to eliminate the current reliance on labor-intensive wet-lab methods. Currently, popular methods primarily combine protein-related information and Gene Ontology (GO) terms to generate final functional p

Minzhang Zheng, Richard Sear, Lucia Illari, Nicholas J. Restrepo

Online hate is dynamic, adaptive -- and is now surging armed with AI/GPT tools. Its consequences include personal traumas, child sex abuse and violent mass attacks. Overcoming it will require knowing how it operates at scale. Here we present this missing science and show that it contradicts current thinking. Waves of adaptive links connect the hate user base

Jiaben Chen, Yichen Zhu, Dongze Lian, Jiaqi Yang

Dynamic vision sensors or event cameras provide rich complementary information for video frame interpolation. Existing state-of-the-art methods follow the paradigm of combining both synthesis-based and warping networks. However, few of those methods fully respect the intrinsic characteristics of events streams. Given that event cameras only encode intensity

Shanya Baghel, Shuvashree Mondal

The prevalence of one-shot devices is quite prolific in engineering and medical domains. Unlike typical one-shot devices, nondestructive one-shot devices (NOSD) may survive multiple tests and offer additional data for reliability estimation. This study aims to implement the Bayesian approach of the lifetime prognosis of NOSD when failures are subject to mult

Pavle Cajic, Dominic Agius, Oliver M. Cliff, James M. Shine

The participation coefficient is a widely used metric of the diversity of a node's connections with respect to a modular partition of a network. An information-theoretic formulation of this concept of connection diversity, referred to here as participation entropy, has been introduced as the Shannon entropy of the distribution of module labels across a node'

Yulin Zhu, Xing Ai, Yevgeniy Vorobeychik, Kai Zhou

The graph contrastive learning (GCL) framework has gained remarkable achievements in graph representation learning. However, similar to graph neural networks (GNNs), GCL models are susceptible to graph structural attacks. As an unsupervised method, GCL faces greater challenges in defending against adversarial attacks. Furthermore, there has been limited rese

Deepak K Roy, Mukul Kabir

The quest for quantum spin liquids has garnered significant attention due to their rich physics and disruptive prospects in quantum communication and computation. Spin-orbit coupling, electron correlation, and structural distortion play critical roles in the candidate materials that eventually order antiferromagnetically at low temperatures. We introduce qua

Yuval Dagan

This chapter explores a deterministic hydrodynamically-inspired ensemble interpretation for free relativistic particles, following the original pilot wave theory conceptualized by de Broglie in 1924 and recent advances in hydrodynamic quantum analogs. We couple a one-dimensional periodically forced Klein-Gordon wave equation and a relativistic particle equat

Xi Lin, Zhiyuan Yang, Xiaoyuan Zhang, Qingfu Zhang

Homotopy optimization is a traditional method to deal with a complicated optimization problem by solving a sequence of easy-to-hard surrogate subproblems. However, this method can be very sensitive to the continuation schedule design and might lead to a suboptimal solution to the original problem. In addition, the intermediate solutions, often ignored by cla

Yasuhiro Oki

In this paper, we study the Hasse norm principle for some non-Galois extensions of number fields. Our main theorem is that for any square-free composite number $d$ which is divisible by at least one of $3$, $55$, $91$ or $95$, there exists a finite extension of degree $d$ for which the Hasse norm principle fails. To accomplish it, we determine the structure

Kshitiz Verma, Anshu Musaddi, Ansh Mittal, Anshul Jain

Indian Judiciary is suffering from burden of millions of cases that are lying pending in its courts at all the levels. The High Court National Judicial Data Grid (HC-NJDG) indexes all the cases pending in the high courts and publishes the data publicly. In this paper, we analyze the data that we have collected from the HC-NJDG portal on 229 randomly chosen d

Lei Cai, Hao Wang, Congling Zhou, Yongqiang Wang

In real-world traffic, there are various uncertainties and complexities in road and weather conditions. To solve the problem that the feature information of pole-like obstacles in complex environments is easily lost, resulting in low detection accuracy and low real-time performance, a multi-scale hybrid attention mechanism detection algorithm is proposed in

Palash Dey, Sudeshna Kolay, Sipra Singh

We study the knapsack problem with graph theoretic constraints. That is, we assume that there exists a graph structure on the set of items of knapsack and the solution also needs to satisfy certain graph theoretic properties on top of knapsack constraints. In particular, we need to compute in the connected knapsack problem a connected subset of items which h

J. Ballet, P. Bruel, T. H. Burnett, B. Lott

We present an incremental version (4FGL-DR4, for Data Release 4) of the fourth Fermi-LAT catalog containing 7194 gamma-ray sources. Based on the first 14 years of science data in the energy range from 50 MeV to 1 TeV, it uses the same analysis methods as the 4FGL-DR3 catalog did for 12 years of data, with only a few improvements. The spectral parameters, spe

Yoshimasa Kurihara

This report presents a possible attempt at renormalisable quantum gravity based on the standard BRST quantisation used for Yang-Mills theory. We have provided the BRST invariant Lagrangian of the gravitationally interacting U(1) gauge theory, namely the Quantum GraviElectro Dynamics (QGED), including the gauge fixing and the ghost Lagrangian. We have extract

Peng Wu, Jing Liu, Xiangteng He, Yuxin Peng

Video anomaly detection (VAD) has been paid increasing attention due to its potential applications, its current dominant tasks focus on online detecting anomalies% at the frame level, which can be roughly interpreted as the binary or multiple event classification. However, such a setup that builds relationships between complicated anomalous events and single

Lars van der Laan, Marco Carone, Alex Luedtke, Mark van der Laan

Debiased machine learning estimators for smooth functionals in nonparametric models can exhibit substantial variability and instability, often leading practitioners to instead rely on parametric or semiparametric working models. Such models, however, may be misspecified and can therefore introduce bias. We study how data-driven model selection can be combine

Ken Inayoshi, Akihisa Koga, Yuta Murakami

We investigate an energy flow in an extended Holstein model describing electron systems coupled to hot-phonons and heat-bath phonons. To analyze the relaxation process after the photo-excitation of electrons, we employ the nonequilibrium dynamical mean-field theory (DMFT). We find the backward energy flow during the relaxation, where the direction of energy

Meirui Jiang, Yuan Zhong, Anjie Le, Xiaoxiao Li

Despite recent progress in enhancing the privacy of federated learning (FL) via differential privacy (DP), the trade-off of DP between privacy protection and performance is still underexplored for real-world medical scenario. In this paper, we propose to optimize the trade-off under the context of client-level DP, which focuses on privacy during communicatio

Carla Cederbaum, Melanie Graf

The coordinate freedom of General Relativity makes it challenging to find mathematically rigorous and physically sound definitions for physical quantities such as the center of mass of an isolated gravitating system. We will argue that a similar phenomenon occurs in Newtonian Gravity once one ahistorically drops the restriction that one should only work in C

Yujin Lee, Harin Lim, Seoyoon Jang, Hyunsoo Yoon

Visual anomaly detection aims to learn normality from normal images, but existing approaches are fragmented across various tasks: defect detection, semantic anomaly detection, multi-class anomaly detection, and anomaly clustering. This one-task-one-model approach is resource-intensive and incurs high maintenance costs as the number of tasks increases. We pre

Tica Lin, Alexandre Aouididi, Zhutian Chen, Johanna Beyer

Badminton is a fast-paced sport that requires a strategic combination of spatial, temporal, and technical tactics. To gain a competitive edge at high-level competitions, badminton professionals frequently analyze match videos to gain insights and develop game strategies. However, the current process for analyzing matches is time-consuming and relies heavily

Hideyuki Miyahara, Hyu Yoneki, Tsuyoshi Mizohata, Vwani Roychowdhury

The Vicsek model, which was originally proposed to explain the dynamics of bird flocking, exhibits a phase transition with respect to the absolute value of the mean velocity. Although clusters of agents can be easily observed via numerical simulations of the Vicsek model, qualitative studies are lacking. We study the clustering structure of the Vicsek model

Songtao Tian, Zixiong Yu, Rui Chen

Functional sliced inverse regression (FSIR) is one of the most popular algorithms for functional sufficient dimension reduction (FSDR). However, the choice of slice scheme in FSIR is critical but challenging. In this paper, we propose a new method called functional slicing-free inverse regression (FSFIR) to estimate the central subspace in FSDR. FSFIR is bas

Sergey V. Sudoplatov

We study possibilities for algebraic closures, differences between definable and algebraic closures in first-order structures, and variations of these closures with respect to the bounds of cardinalities of definable sets and given sets of formulae. Characteristics for these possibilities and differences are introduced and described. These characteristics ar

Christian Brennecke, Changji Xu, Horng-Tzer Yau

We prove that the two point correlation matrix $ \textbf{M}= (\langle \sigma_i ; \sigma_j\rangle)_{1\leq i,j\leq N} \in \mathbb{R}^{N\times N}$ of the Sherrington-Kirkpatrick model has the property that for every $\epsilon>0$ there exists $K_\epsilon>0$, that is independent of $N$, such that \[ \mathbb{P}\big( \| \textbf{M} \|_{\text{op}} \leq K_{\epsilon}\b

Harry Cheng, Yangyang Guo, Tianyi Wang, Liqiang Nie

The existing deepfake detection methods have reached a bottleneck in generalizing to unseen forgeries and manipulation approaches. Based on the observation that the deepfake detectors exhibit a preference for overfitting the specific primary regions in input, this paper enhances the generalization capability from a novel regularization perspective. This can

Ye Dong, Wen-jie Lu, Yancheng Zheng, Haoqi Wu

With ChatGPT as a representative, tons of companies have began to provide services based on large Transformers models. However, using such a service inevitably leak users' prompts to the model provider. Previous studies have studied secure inference for Transformer models using secure multiparty computation (MPC), where model parameters and clients' prompts

Vivek Ramanujan, Thao Nguyen, Sewoong Oh, Ludwig Schmidt

Pre-training has been widely adopted in deep learning to improve model performance, especially when the training data for a target task is limited. In our work, we seek to understand the implications of this training strategy on the generalization properties of downstream models. More specifically, we ask the following question: how do properties of the pre-

Miguel Arratia, Ryan Milton, Sebouh J. Paul, Barak Schmookler

Measuring the region $0.1 < Q^{2} < 1.0$ GeV$^{2}$ is essential to support searches for gluon saturation at the future Electron-Ion Collider. Recent studies have revealed that covering this region at the highest beam energies is not feasible with current detector designs, resulting in the so-called $Q^{2}$ gap. In this work, we present a design for the Few-D

Xuanhua Wang, Ran Li, Jin Wang

It has been proposed that quantum complexity is dual to the volume of the extremal surface, the action of the Wheeler-DeWitt patch, and the spacetime volume of the patch. Recently, a generalized volume-complexity observable was formulated as an equivalently good candidate for the dual holographic complexity. This proposal is abbreviated as ``complexity=anyth

Farhad Farokhi

A new measure of information leakage for quantum encoding of classical data is defined. An adversary can access a single copy of the state of a quantum system that encodes some classical data and is interested in correctly guessing a general randomized or deterministic function of the data (e.g., a specific feature or attribute of the data in quantum machine

Junseo Jung, Hyeongmuk Lim, Bohm-Jung Yang

We study the relation between the quantum geometry of wave functions and the Landau level (LL) spectrum of two-band Hamiltonians with a quadratic band crossing point (QBCP) in two-dimensions. By investigating the influence of interband coupling parameters on the wave function geometry of general QBCPs, we demonstrate that the interband coupling parameters ca

Muhammad Subkhi Sadullah, Yinfeng Xu, Sankara Arunachalam, Himanshu Mishra

Liquid droplets hanging from solid surfaces are commonplace, but their physics is complex. Examples include dew or raindrops hanging onto wires or droplets accumulating onto a cover placed over warm food or windshields. In these scenarios, determining the force of detachment is crucial to rationally design technologies. Despite much research, a quantitative

Yixin Wang, Zihao Lin, Haoyu Dong

Knowledge Graph (KG) plays a crucial role in Medical Report Generation (MRG) because it reveals the relations among diseases and thus can be utilized to guide the generation process. However, constructing a comprehensive KG is labor-intensive and its applications on the MRG process are under-explored. In this study, we establish a complete KG on chest X-ray

Mohammad Anas, Pranav Joshi

Rotation, which stabilizes flow, can enhance the heat transfer in Rayleigh-B\'enard convection (RBC) through Ekman pumping. In this Letter, we present the results of our direct numerical simulations of rotating RBC, providing a comprehensive analysis of this heat transfer enhancement relative to non-rotating RBC in the parameter space of Rayleigh number ($Ra

Menglin Kong, Ruichen Li, Fan Liu, Xingquan Li

Landslide is a natural disaster that can easily threaten local ecology, people's lives and property. In this paper, we conduct modelling research on real unidirectional surface displacement data of recent landslides in the research area and propose a time series prediction framework named VMD-SegSigmoid-XGBoost-ClusterLSTM (VSXC-LSTM) based on variational mo

Minjie Wang, Haole Jiao, Jiajin Lu, Wenxin Fan

Practical realizations of quantum repeaters require quantum memory simultaneously providing high retrieval efficiency, long lifetime and multimode storages. So far, the combination of high retrieval efficiency and spatially multiplexed storages into a single memory remains challenging. Here, we set up a ring cavity that supports an array including 6 TEM00 mo

Han Hu, Ruiqi Dong, John Grundy, Thai Minh Nguyen

With the increasing interconnection of smart devices, users often desire to adopt the same app on quite different devices for identical tasks, such as watching the same movies on both their smartphones and TVs. However, the significant differences in screen size, aspect ratio, and interaction styles make it challenging to adapt Graphical User Interfaces (GUI

Sian Nie

In this note, we introduce a natural analogue of Steinberg's cross-section in the loop group of an unramified reductive group $\mathbf G$. We show this loop Steinberg's cross-section provides a simple geometric model for the poset $B(\mathbf G)$ of Frobenius-twisted conjugacy classes (referred to as Newton strata) of the loop group. As an application, we con

Neel Bhandari, Pin-Yu Chen

Language Models today provide a high accuracy across a large number of downstream tasks. However, they remain susceptible to adversarial attacks, particularly against those where the adversarial examples maintain considerable similarity to the original text. Given the multilingual nature of text, the effectiveness of adversarial examples across translations

Menglin Kong, Ri Su, Shaojie Zhao, Muzhou Hou

Recommendation system algorithm based on multi-task learning (MTL) is the major method for Internet operators to understand users and predict their behaviors in the multi-behavior scenario of platform. Task correlation is an important consideration of MTL goals, traditional models use shared-bottom models and gating experts to realize shared representation l

Menglin Kong, Shaojie Zhao, Juan Cheng, Xingquan Li

There are two fundamental problems in applying deep learning/machine learning methods to disease classification tasks, one is the insufficient number and poor quality of training samples; another one is how to effectively fuse multiple source features and thus train robust classification models. To address these problems, inspired by the process of human lea

Pourya Shamsolmoali, Masoumeh Zareapoor

This paper focuses on an accurate and fast interpolation approach for image transformation employed in the design of CNN architectures. Standard Spatial Transformer Networks (STNs) use bilinear or linear interpolation as their interpolation, with unrealistic assumptions about the underlying data distributions, which leads to poor performance under scale vari

Cyrus Cousins, Vignesh Viswanathan, Yair Zick

We study the problem of fairly allocating indivisible goods (positively valued items) and chores (negatively valued items) among agents with decreasing marginal utilities over items. Our focus is on instances where all the agents have simple preferences; specifically, we assume the marginal value of an item can be either $-1$, $0$ or some positive integer $c

Sung Joon Maeng, Hyeokjun Kwon, Ozgur Ozdemir, İsmail Güvenç

Ensuring reliable and seamless wireless connectivity for unmanned aerial vehicles (UAVs) has emerged as a critical requirement for a wide range of applications. The increasing deployment of UAVs has increased the significance of cellular-connected UAVs (C-UAVs) in enabling beyond-visual line of sight (BVLOS) communications. To ensure the successful operation

Syota Esaki, Kazuhiro Kuwae, Zi Jian Xu

The notion of tamed Dirichlet space by distributional lower Ricci curvature bounds was proposed by Erbar--Rigoni--Sturm--Tamanini as the Dirichlet space having a weak form of Bakry--\'Emery curvature lower bounds in distribution sense. In this framework, we establish the Littlewood--Paley--Stein inequality for $L^p$-functions which partially generalizes the

Yu-Lun Wu, Hung-Lung Wang

Let $A$, $B$, and $C$ be three $n\times n$ matrices. We investigate the problem of verifying whether $AB=C$ over the ring of integers and finding the correct product $AB$. Given that $C$ is different from $AB$ by at most $k$ entries, we propose an algorithm that uses $O(\sqrt{k}n^2+k^2n)$ operations. Let $\alpha$ be the largest absolute value of an entry in

Aditya Arun, Shunsuke Saruwatari, Sureel Shah, Dinesh Bharadia

Understanding the location of ultra-wideband (UWB) tag-attached objects and people in the real world is vital to enabling a smooth cyber-physical transition. However, most UWB localization systems today require multiple anchors in the environment, which can be very cumbersome to set up. In this work, we develop XRLoc, providing an accuracy of a few centimete

Sepideh Samadi, Farzad Yousefian

We consider a class of hierarchical variational inequality (VI) problems that subsumes VI-constrained optimization and several other problem classes including the optimal solution selection problem and the optimal Nash equilibrium (NE) seeking problem. Our main contributions are threefold. (i) We consider bilevel VIs with monotone and Lipschitz continuous ma

Asim Irfan, Atif Nawaz, Muhammad Turab, Muhmmad Azeem

After the pandemic, humanity has been facing different types of challenges. Social relationships, societal values, and academic and professional behavior have been hit the most. People are shifting their routines to social media and gadgets, and getting addicted to their isolation. This sudden change in their lives has caused an unusual social breakdown and

Le Yu

In this paper, we conduct an empirical evaluation of Temporal Graph Benchmark (TGB) by extending our Dynamic Graph Library (DyGLib) to TGB. Compared with TGB, we include eleven popular dynamic graph learning methods for more exhaustive comparisons. Through the experiments, we find that (1) different models depict varying performance across various datasets,

David M. Long, Andrew C. Doherty

The algebraic tools used to study topological phases of matter are not clearly suited to studying processes in which the bulk energy gap closes, such as phase transitions. We describe an elementary two edge thought experiment which reveals the effect of an anyon condensation phase transition on the robust edge properties of a sample, bypassing a limitation o

Shun-ichi Amari, Takeru Matsuda

Information geometry and Wasserstein geometry are two main structures introduced in a manifold of probability distributions, and they capture its different characteristics. We study characteristics of Wasserstein geometry in the framework of Li and Zhao (2023) for the affine deformation statistical model, which is a multi-dimensional generalization of the lo

Yimu Wang, Peng Shi, Hongyang Zhang

In this paper, we study the problem of generating obstinate (over-stability) adversarial examples by word substitution in NLP, where input text is meaningfully changed but the model's prediction does not, even though it should. Previous word substitution approaches have predominantly focused on manually designed antonym-based strategies for generating obstin

David Jewitt, Yoonyoung Kim, Jing Li, Max Mutchler

We present deep Hubble Space Telescope images taken to examine the ejecta from the DART spacecraft impact into asteroid Dimorphos. The images reveal an extensive population of co-moving boulders, the largest of which is about 7 m in diameter (geometric albedo 0.15 assumed). Measurements of 37 boulders show a mean sky-plane velocity dispersion of 0.30+/-0.03

ItaloIvo Lima Dias Pinto, Javier Omar Garcia, Kanika Bansal

Network representations have been effectively employed to analyze complex systems across various areas and applications, leading to the development of network science as a core tool to study systems with multiple components and complex interactions. There is a growing interest in understanding the temporal dynamics of complex networks to decode the underlyin

Stanley Alama, Lia Bronsard, Xinyang Lu, Chong Wang

We study a two-dimensional quaternary inhibitory system. This free energy functional combines an interface energy favoring micro-domain growth with a Coulomb-type long range interaction energy which prevents micro-domains from unlimited spreading. Here we consider a limit in which three species are vanishingly small, but interactions are correspondingly larg

Tian-Rui Liu, Kai Bai, Jia-Zheng Li, Liang Fang

Topological phases are greatly enriched by including non-Hermiticity. While most works focus on the topology of the eigenvalues and eigenstates, how topologically nontrivial non-Hermitian systems behave in dynamics has only drawn limited attention. Here, we consider a breathing honeycomb lattice known to emulate the quantum spin Hall effect and exhibits high

Chenming Li, Daoan Zhang, Wenjian Huang, Jianguo Zhang

Domain generalization (DG) aims to learn a robust model from source domains that generalize well on unseen target domains. Recent studies focus on generating novel domain samples or features to diversify distributions complementary to source domains. Yet, these approaches can hardly deal with the restriction that the samples synthesized from various domains

Borchen Li, Qingzhong Ji

Let $p, k, q$ be positive integers with $p-2 \geqslant k$ and let $K_{p,k}^{q}$ be the generalized pineapple graph which is obtained by joining independent set of $q$ vertices with $k$ vertices of a complete graph $K_{p}.$ In \cite{TSH2}, Haemers et al. constructed graphs which cospectral with $K_{p,1}^{q}.$ In this paper, we determine all graphs which are c

Ngatcha Ndengna Arno Roland

In this paper, we introduce a methodology to design genuinely two-dimensional (2D) secondorder path-conservative central-upwind (PCCU) schemes. The scheme studies dam-break with high sediment concentration over abrupt moving topography quickly spatially variable even in the presence of resonance. This study is possible via a 2D sediment transport model (incl

Kaori Niki, Rena Asano, Ryuji Sakanoue, Manabu Hagiwara

Photoemission orbital tomography (POT) from photoelectron momentum maps (PMMs) has enabled detailed analysis of the shape and energy of molecular orbitals in the adsorbed state. This study proposes a new POT method based on the PhaseLift. Molecular orbitals, including three-dimensional phases, can be identified from a single PMM by actively providing atomic

Xuelong Dai, Kaisheng Liang, Bin Xiao

Unrestricted adversarial attacks present a serious threat to deep learning models and adversarial defense techniques. They pose severe security problems for deep learning applications because they can effectively bypass defense mechanisms. However, previous attack methods often directly inject Projected Gradient Descent (PGD) gradients into the sampling of g

Gege Qi, Yuefeng Chen, Xiaofeng Mao, Xiaojun Jia

Developing a practically-robust automatic speech recognition (ASR) is challenging since the model should not only maintain the original performance on clean samples, but also achieve consistent efficacy under small volume perturbations and large domain shifts. To address this problem, we propose a novel WavAugment Guided Phoneme Adversarial Training (wapat).

Yihang Cheng, Yansong Feng, Yanbin Pan

Many lattice-based crypstosystems employ ideal lattices for high efficiency. However, the additional algebraic structure of ideal lattices usually makes us worry about the security, and it is widely believed that the algebraic structure will help us solve the hard problems in ideal lattices more efficiently. In this paper, we study the additional algebraic s

Sitan Chen, Shyam Narayanan

We revisit the well-studied problem of learning a linear combination of $k$ ReLU activations given labeled examples drawn from the standard $d$-dimensional Gaussian measure. Chen et al. [CDG+23] recently gave the first algorithm for this problem to run in $\text{poly}(d,1/\varepsilon)$ time when $k = O(1)$, where $\varepsilon$ is the target error. More preci

Yongqi Chen, Nan Gao, Guodong Zhu, Yurui Fang

We explore a hexagonal cavity that supports chiral topological whispering gallery (CTWG) modes, formed by a gyromagnetic photonic crystal. This mode is a special type of topologically protected optical mode that can propagate in photonic crystals with chiral direction. Finite element method simulations show that discrete edge states exist in the topological

Abdulaziz Alsenafi, Ahcene Ghandriche, Mourad Sini

We consider the problem of estimating the eigenvalues and the integral of the corresponding eigenfunctions, associated to the Newtonian potential operator, defined in a bounded domain $\Omega \subset \mathbb{R}^{d},$ where $d = 2, 3$, in terms of the maximum radius of $\Omega$. We first provide these estimations in the particular case of a ball and a disc. T

Shilin Lu, Yanzhu Liu, Adams Wai-Kin Kong

Text-driven diffusion models have exhibited impressive generative capabilities, enabling various image editing tasks. In this paper, we propose TF-ICON, a novel Training-Free Image COmpositioN framework that harnesses the power of text-driven diffusion models for cross-domain image-guided composition. This task aims to seamlessly integrate user-provided obje

Jianqiang Li

Given $x, y$ on an unweighted undirected graph $G$, the goal of the pathfinding problem is to find an $x$-$y$ path. In this work, we first construct a graph $G$ based on welded trees and define a pathfinding problem in the adjacency list oracle $O$. Then we provide an efficient quantum algorithm to find an $x$-$y$ path in the graph $G$. Finally, we prove tha

Shuo Zhang, Yang Liu, Li Xie, Lei Xie

To learn accurate representations of molecules, it is essential to consider both chemical and geometric features. To encode geometric information, many descriptors have been proposed in constrained circumstances for specific types of molecules and do not have the properties to be ``robust": 1. Invariant to rotations and translations; 2. Injective when embedd

Zhonghui Li, Kaiping Xue, Jian Li, Lutong Chen

Over the past few decades, significant progress has been made in quantum information technology, from theoretical studies to experimental demonstrations. Revolutionary quantum applications are now in the limelight, showcasing the advantages of quantum information technology and becoming a research hotspot in academia and industry. To enable quantum applicati

Elizabeth Bjarnason, Per Runeson, Markus Borg, Michael Unterkalmsteiner

Weak alignment of requirements engineering (RE) with verification and validation (VV) may lead to problems in delivering the required products in time with the right quality. For example, weak communication of requirements changes to testers may result in lack of verification of new requirements and incorrect verification of old invalid requirements, leading

Zhilong Wang, Lan Zhang, Chen Cao, Nanqing Luo

The Large Language Models (LLMs), such as GPT and BERT, were proposed for natural language processing (NLP) and have shown promising results as general-purpose language models. An increasing number of industry professionals and researchers are adopting LLMs for program analysis tasks. However, one significant difference between programming languages and natu

Yi-Ying Wang, Lei Lei, Guan-Wen Yuan, Yi-Zhong Fan

Early results from the James Webb Space Telescope (JWST) observations have hinted at two traces beyond the standard cosmological framework. One is the extraordinarily high stellar masses and their density at $z=7.5\sim9.1$, another is the unexpected abundance of ultraviolet (UV) bright galaxies at $z\ge10$. Nevertheless, both pieces of evidence are not stati

Ke Xu, Ming Tang, Quancheng Wang, Han Wang

Intel processors utilize the retirement to orderly retire the micro-ops that have been executed out of order. To enhance retirement utilization, the retirement is dynamically shared between two logical cores on the same physical core. However, this shared retirement mechanism creates a potential vulnerability wherein an attacker can exploit the competition f

Danyal Namakshenas

The advent of Web 3.0, underpinned by blockchain technologies, promises to transform the internet's landscape by empowering individuals with decentralized control over their data. However, this evolution brings unique security challenges that need to be addressed. This paper explores these complexities, focusing on enhancing privacy and anonymous auditing wi

Nauman bin Ali, Michael Unterkalmsteiner

Software Engineering is an applied discipline and concepts are difficult to grasp only at a theoretical level alone. In the context of a project management course, we introduced and evaluated the use of software process simulation (SPS) based games for improving students' understanding of software development processes. The effects of the intervention were m

Dong-Jie Liu, Yuan-Chuan Zou

Tremendous information is hidden in the light curve of a gamma-ray burst (GRB). Based on CGRO/BATSE data, Hakkila (2021) found a majority of GRBs can be characterized by a smooth, single-peaked component superposed with a temporally symmetrical residual structure, i.e., a mirror feature for the fast varying component. In this study, we conduct a similar anal

Hadi Hosseini, Andrew McGregor, Rik Sengupta, Rohit Vaish

The Graphical House Allocation problem asks: how can $n$ houses (each with a fixed non-negative value) be assigned to the vertices of an undirected graph $G$, so as to minimize the "aggregate local envy", i.e., the sum of absolute differences along the edges of $G$? This problem generalizes the classical Minimum Linear Arrangement problem, as well as the wel

Ronak M Soni

I show that an analog of the crossed product construction that takes type $III_{1}$ algebras to type $II$ algebras exists also in the type $I$ case. This is particularly natural when the local algebra is a non-trivial direct sum of type $I$ factors. Concretely, I rewrite the usual type $I$ trace in a different way and renormalise it. This new renormalised tr

Yao Peng, Jia Guo, Chenyang Yang

Graph neural networks (GNNs) update the hidden representations of vertices (called Vertex-GNNs) or hidden representations of edges (called Edge-GNNs) by processing and pooling the information of neighboring vertices and edges and combining to exploit topology information. When learning resource allocation policies, GNNs cannot perform well if their expressiv

Saurabh Deochake

Cloud computing has revolutionized the way organizations manage their IT infrastructure, but it has also introduced new challenges, such as managing cloud costs. The rapid adoption of artificial intelligence (AI) and machine learning (ML) workloads has further amplified these challenges, with GPU compute now representing 40-60\% of technical budgets for AI-f

J. A. Worden, M. R. von Spakovsky, C. Hin

The principal paradigm for determining the thermoelectric properties of materials is based on the Boltzmann transport equations (BTEs) or Landauer equivalent. These equations depend on the electron and phonon density of states (e-DOS and p-DOS) derived from ab initio calculations performed using density functional theory and density functional perturbation t

Michael Unterkalmsteiner, Robert Feldt, Tony Gorschek

Requirements Engineering and Software Testing are mature areas and have seen a lot of research. Nevertheless, their interactions have been sparsely explored beyond the concept of traceability. To fill this gap, we propose a definition of requirements engineering and software test (REST) alignment, a taxonomy that characterizes the methods linking the respect

Oliver Knill

If T is an ergodic automorphism of a Lebesgue probability space (X,A,m), the set of coboundries B = db =T(b)+b with symmetric difference + form a subgroup of the set of cocycles A. Using tools from descriptive set theory, Greg Hjorth showed in 1995 that the first cohomology group H=A/B is uncountable. This can surprise, given that in the case of a finite erg

Hui-Huang Chen

In this paper, we consider the dynamics of R\'enyi negativities after a quantum quench in the free-boson chain with homogeneous dissipation. Initially we prepare the system in the squeezed thermal state, and then let it evolves under the tight-binding bosonic Hamiltonian with local linear dissipation. We use the Lindblad equation to solve the time evolution

Avik Dayal, Vijay K. Shah, Harpreet S. Dhillon, Jeffrey H. Reed

Decentralized vehicle-to-everything (V2X) networks (i.e., C-V2X Mode-4 and NR-V2X Mode-2) utilize sensing-based semi-persistent scheduling (SPS) where vehicles sense and reserve suitable radio resources for Basic Safety Message (BSM) transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). Vehicles rely on these receive

Jonathan P Williams

Conformal prediction (CP) was developed to provide finite-sample probabilistic prediction guarantees. While CP algorithms are a relatively general-purpose approach to uncertainty quantification, with finite-sample guarantees, they lack versatility. Namely, the CP approach does not {\em prescribe} how to quantify the degree to which a data set provides eviden

Luis Fernando Herbozo Contreras, Nhan Duy Truong, Jason K. Eshraghian, Zhangyu Xu

Neuromodulation techniques have emerged as promising approaches for treating a wide range of neurological disorders, precisely delivering electrical stimulation to modulate abnormal neuronal activity. While leveraging the unique capabilities of artificial intelligence (AI) holds immense potential for responsive neurostimulation, it appears as an extremely ch

Aleksandar Cikota, Ivonne Toro Bertolla, Xiaosheng Huang, Saul Baltasar

Gravitational lensing provides unique insights into astrophysics and cosmology, including the determination of galaxy mass profiles and constraining cosmological parameters. We present spectroscopic confirmation and lens modeling of the strong lensing system DESI-253.2534+26.8843, discovered in the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging S

Cen Zhang, Yaowen Zheng, Mingqiang Bai, Yeting Li

LLM-based (Large Language Model) fuzz driver generation is a promising research area. Unlike traditional program analysis-based method, this text-based approach is more general and capable of harnessing a variety of API usage information, resulting in code that is friendly for human readers. However, there is still a lack of understanding regarding the funda

Yulong Dong, Lin Lin, Hongkang Ni, Jiasu Wang

This paper addresses the problem of solving nonlinear systems in the context of symmetric quantum signal processing (QSP), a powerful technique for implementing matrix functions on quantum computers. Symmetric QSP focuses on representing target polynomials as products of matrices in SU(2) that possess symmetry properties. We present a novel Newton's method t

Dmitry Khangulyan, Felix Aharonian, Andrew M. Taylor

Relativistic electrons are an essential component in many astrophysical sources, and their radiation may dominate the high-energy bands. Inverse Compton (IC) emission is the radiation mechanism that plays the most important role in these bands. The basic properties of IC, such as the total and differential cross sections, have long been studied; the properti

Naman Jain, Shubham Gandhi, Atharv Sonwane, Aditya Kanade

Static analysis tools are traditionally used to detect and flag programs that violate properties. We show that static analysis tools can also be used to perturb programs that satisfy a property to construct variants that violate the property. Using this insight we can construct paired data sets of unsafe-safe program pairs, and learn strategies to automatica

Pravin Kumar Dahal

Surface gravity plays a pivotal role in the characterization of black holes and also in formulating the laws of black hole thermodynamics. Despite its significance, defining surface gravity in general spacetimes is a nontrivial task and thus has multiple definitions that lack equivalence in dynamical scenarios. This paper reviews different notions of dynamic

Wen-Xiang Chen, Yao-Guang Zheng

According to traditional theory, it is believed that Fermions do not exhibit superradiation. However, when predetermined boundary conditions are in place, there is a possibility of combining the wave function of coupled Fermions, which can result in the emergence of superradiation phenomena. This article presents a novel perspective, proposing that Fermions