December 2023 arXiv papers — page 25

Victor Volfson

An approach will be proposed to determine the existence of a limit distribution of additive arithmetic functions in this work. It is based on assertions that will be proven in this work and on the properties of Dirichlet convolution and M\"obius inversion. Based on this approach, formulas will be obtained for finding the mean and variance for the limit distr

Tian Lan, Gen Yue, Longye Wang

We propose the representation principle to study physical systems with a given symmetry. In the context of symmetry enriched topological orders, we give the appropriate representation category, the category of SET orders, which include SPT orders and symmetry breaking orders as special cases. For fusion n-category symmetries, we show that the category of SET

Gabriel A. Oio, Y. Sophia Dai, C. G. Bornancini, Zi-Jian Li

Active galactic nucleus (AGN) driven outflows can have a significant impact on the evolution of the host galaxy. In this work, we compare the properties of galaxies that hosts AGNs with and without outflows. Our sample consists of 103 AGNs identified by mid-IR color-color selection, and confirmed with optical spectroscopy at a redshift range of 0.3 $\lesssim

Seonghyuk Im, Jaehoon Kim, Hyunwoo Lee, Haesong Seo

For a given collection $\mathcal{G} = (G_1,\dots, G_k)$ of graphs on a common vertex set $V$, which we call a \emph{graph system}, a graph $H$ on a vertex set $V(H) \subseteq V$ is called a \emph{rainbow subgraph} of $\mathcal{G}$ if there exists an injective function $\psi:E(H) \rightarrow [k]$ such that $e \in G_{\psi(e)}$ for each $e\in E(H)$. The maximum

Jiajun Jiang, Fengjie Li, Zijie Zhao, Zhirui Ye

Redundancy-based automated program repair (APR), which generates patches by referencing existing source code, has gained much attention since they are effective in repairing real-world bugs with good interpretability. However, since existing approaches either demand the existence of multi-line similar code or randomly reference existing code, they can only r

Karim Zayana, Bertrand Guisnet

Measurements in macrodiversity situations have been performed. Crosscorrelation of shadowing terms between two basestations and a mobile have been computed. It results that high cross-correlation coefficients may appear in practice. Afterwards, we propose a simple shadowing model, integrating both its autocorrelation and cross-correlation properties. Eventua

Karim Zayana, Daniel Duponteil

Macroscopic diversity in radiomobile systems is a technique in which the terminal is in parallel connection with two base stations. It is a fundamental element in the operation of third generation mobile networks using CDMA. (IS 95, UMTS, etc.). A representation of the propagation phenomena involved requires joint modeling of the two transmission channels. T

O. Kashuba, R. -P. Riwar

The inherent complexity of system-bath interactions often requires making critical approximations, which we here show to have a radical influence on the renormalization group flow and the resulting phase diagram. Specifically, for the Caldeira-Leggett model Schmid and Bulgadaev (SB) predicted a phase transition, whose experimental verification in resistive s

Hervé Andrès, Alexandre Boumezoued, Benjamin Jourdain

We propose a new model for the forecasting of both the implied volatility surfaces and the underlying asset price. In the spirit of Guyon and Lekeufack (2023) who are interested in the dependence of volatility indices (e.g. the VIX) on the paths of the associated equity indices (e.g. the S\&P 500), we first study how vanilla options implied volatility can be

Jae Yong Lee, Sung Woong Cho, Hyung Ju Hwang

Fast and accurate predictions for complex physical dynamics are a significant challenge across various applications. Real-time prediction on resource-constrained hardware is even more crucial in real-world problems. The deep operator network (DeepONet) has recently been proposed as a framework for learning nonlinear mappings between function spaces. However,

Zhu Sun, Kaidong Feng, Jie Yang, Xinghua Qu

Most existing bundle generation approaches fall short in generating fixed-size bundles. Furthermore, they often neglect the underlying user intents reflected by the bundles in the generation process, resulting in less intelligible bundles. This paper addresses these limitations through the exploration of two interrelated tasks, i.e., personalized bundle gene

Aurélie Bugeau, Anne-Laure Ligozat

With the climate change context, many prospective studies, generally encompassing all areas of society, imagine possible futures to expand the range of options. The role of digital technologies within these possible futures is rarely specifically targeted. Which digital technologies and methodologies do these studies envision in a world that has mitigated an

Wenjie Xi, Tian Lan, Longye Wang, Chenjie Wang

Recently, many studies are focused on generalized global symmetry, a mixture of both invertible and non-invertible symmetries in various space-time dimensions. The complete structure of generalized global symmetry is described by higher fusion category theory. In this paper, We first review the construction of fusion 2-category symmetry $\Sigma \cal B$ where

Molla Basir Ahamed, Sabir Ahammed

In this paper, a significant improvement has been achieved in the classical Bohr's inequality for the class $ \mathcal{B} $ of analytic self maps defined on the unit disk $ \mathbb{D} $. More precisely, we generalize and improve several Bohr-type inequalities by combining appropriate improved and refined versions of the classical Bohr's inequality with some

Jingyao Li, Pengguang Chen, Shaozuo Yu, Shu Liu

The objective of Active Learning is to strategically label a subset of the dataset to maximize performance within a predetermined labeling budget. In this study, we harness features acquired through self-supervised learning. We introduce a straightforward yet potent metric, Cluster Distance Difference, to identify diverse data. Subsequently, we introduce a n

Song Bao, Zhao-Long Gu, Yanyan Shangguan, Zhentao Huang

Magnon polarons are novel elementary excitations possessing hybrid magnonic and phononic signatures, and are responsible for many exotic spintronic and magnonic phenomena. Despite long-term sustained experimental efforts in chasing for magnon polarons, direct spectroscopic evidence of their existence is hardly observed. Here, we report the direct observation

Zhan Lu, Qian Zheng, Boxin Shi, Xudong Jiang

Panoramic imaging research on geometry recovery and High Dynamic Range (HDR) reconstruction becomes a trend with the development of Extended Reality (XR). Neural Radiance Fields (NeRF) provide a promising scene representation for both tasks without requiring extensive prior data. However, in the case of inputting sparse Low Dynamic Range (LDR) panoramic imag

Zhen Du, Fan Liu, Yifeng Xiong, Tony Xiao Han

Integrated sensing and communications is regarded as a key enabling technology in the sixth generation networks, where a unified waveform, such as orthogonal frequency division multiplexing (OFDM) signal, is adopted to facilitate both sensing and communications (S&C). However, the random communication data embedded in the OFDM signal results in severe variab

Yann Sakref, Maitane Muñoz-Basagoiti, Zorana Zeravcic, Olivier Rivoire

Catalysis, the acceleration of product formation by a substance that is left unchanged, typically results from multiple elementary processes, including diffusion of the reactants toward the catalyst, chemical steps, and release of the products. While efforts to design catalysts are often focused on accelerating the chemical reaction on the catalyst, catalysi

Jiaming Gu, Yicheng Mou, Jianwen Ma, Haonan Chen

Light-to-electricity conversion is crucial for energy harvesting and photodetection, requesting efficient electron-hole pair separation to prevent recombination. Traditional junction-based mechanisms using built-in electric fields fail in non-barrier regions. Homogeneous material harvesting under photovoltaic effect is appealing but only realized in non-cent

Veljko Askovic, Emmanuel Trélat, Hasnaa Zidani

In this paper, we consider a linear quadratic (LQ) optimal control problem in both finite and infinite dimensions. We derive an asymptotic expansion of the value function as the fixed time horizon T tends to infinity. The leading term in this expansion, proportional to T, corresponds to the optimal value attained through the classical turnpike theory in the

Alexander M. Romanov

In this paper, we propose a new method for constructing $1$-perfect mixed codes in the Cartesian product $\mathbb{F}_{n} \times \mathbb{F}_{q}^n$, where $\mathbb{F}_{n}$ and $\mathbb{F}_{q}$ are finite fields of orders $n = q^m$ and $q$. We consider generalized Reed-Muller codes of length $n = q^m$ and order $(q - 1)m - 2$. Codes whose parameters are the sam

Yuki Kaneko, Hirokazu Tsunetsugu

We have studied the quadrupolar Kondo effect for an impurity in cubic environment with taking account of a singlet excited state $\Gamma_1$, which models a $\mathrm{Pr}^{3+}$ ion with a non-Kramers double ground state $\Gamma_3$. We have used the numerical renormalization group approach and determined the phase diagram with varying quadrupole Kondo coupling

Romain Abraham, Jean-François Delmas, Julien Weibel

We introduce probability-graphons which are probability kernels that generalize graphons to the case of weighted graphs. Probability-graphons appear as the limit objects to study sequences of large weighted graphs whose distribution of subgraph sampling converge. The edge-weights are taken from a general Polish space, which also covers the case of decorated

Thiem Hoang

The unique biosignature of life on Earth is the homochirality of organic compounds such as amino acids, proteins, and sugars. High-energy spin-polarized (spin-up or spin-down) electrons (SPEs) from the $\beta$ decay of radioactive nuclei were proposed as a source of symmetry breaking, leading to homochirality; however, their exact role is much debated. Here

Anton A. Lunyov, Mark M. Malamud

The paper is concerned with the completeness property of the system of root vectors of a boundary value problem for the following $2 \times 2$ Dirac type equation $$ L y = -i B^{-1} y' + Q(x) y = \lambda y , \quad y= {\rm col}(y_1, y_2), \quad x \in [0,1], $$ $$ B = {\rm diag}(b_1, b_2), \quad b_1 < 0 < b_2, \quad\text{and}\quad Q \in W_1^n[0,1] \otimes \mat

Yanyan Shangguan, Song Bao, Zhao-Yang Dong, Ning Xi

Fractional magnetisation plateaus, in which the magnetisation is pinned at a fraction of its saturated value within a range of external magnetic field, are spectacular macroscopic manifestations of the collective quantum behaviours. One prominent example of the plateau phase is found in spin-1/2 triangular-lattice antiferromagnets featuring strong geometrica

Julien Chevallier

Let $B=(B_t)_{t\geq 0}$ be a standard Brownian motion. The main objective is to find a uniform (in time) control of the modulus of continuity of $B$ in the spirit of what appears in (Kurtz, 1978). More precisely, it involves the control of the exponential moments of the random variable $\sup_{0\leq s\leq t} |B_t-B_s|/w(t,|t-s|)$ for a suitable function $w$.

Andrey Yu. Chernov, Eugene A. Katz

Bronze cuboctahedral weights dated to the VIII-X centuries were found in northwest Russia near Ladoga, one of the most important trading centers in Eastern Europe in the VIII-X centuries. The history of the mathematical study of cuboctahedron and more generally of the entire family of Archimedean solids in the Middle East and Europe supports the archeologica

Nicola Zaupa, Luca Zaccarian, Isabelle Queinnec, Sophie Tarbouriech

We consider the problem of synchronizing a multi-agent system (MAS) composed of several identical linear systems connected through a directed graph.To design a suitable controller, we construct conditions based on Bilinear Matrix Inequalities (BMIs) that ensure state synchronization.Since these conditions are non-convex, we propose an iterative algorithm bas

Jitendra Dhakar, Ram Prakash Bharti

The electroviscous effects are relevant in controlling and manipulating the fluid, thermal, and mass transport microfluidic processes. The existing research has mainly focused on the fixed contraction ratio ($d_\text{c}$, i.e., the area ratio of contraction to expansion) concerning the widely used contraction-expansion geometrical arrangement. This study has

Hansong Zhang, Shikun Li, Pengju Wang, Dan Zeng

Training state-of-the-art (SOTA) deep models often requires extensive data, resulting in substantial training and storage costs. To address these challenges, dataset condensation has been developed to learn a small synthetic set that preserves essential information from the original large-scale dataset. Nowadays, optimization-oriented methods have been the p

Panlong Wu, Kangshuo Li, Ting Wang, Fangxin Wang

Foundation models have shown great success in natural language processing, computer vision, and multimodal tasks. FMs have a large number of model parameters, thus requiring a substantial amount of data to help optimize the model during the training. Federated learning has revolutionized machine learning by enabling collaborative learning from decentralized

Emmanuel Trélat

This short book is the result of various master and summer school courses I have taught. The objective is to introduce the readers to mathematical control theory, both in finite and infinite dimension. In the finite-dimensional context, we consider controlled ordinary differential equations (ODEs); in this context, existence and uniqueness issues are easily

Dong-Hyun Jung, Hongjae Nam, Junil Choi, David J. Love

The extensive coverage offered by satellites makes them effective in enhancing service continuity for users on dynamic airborne and maritime platforms, such as airplanes and ships. In particular, geosynchronous Earth orbit (GEO) satellites ensure stable connectivity for terrestrial users due to their stationary characteristics when observed from Earth. This

Chenyi Jiang, Haofeng Zhang

Compositional Zero-Shot Learning (CZSL) aims to transfer knowledge from seen state-object pairs to novel unseen pairs. In this process, visual bias caused by the diverse interrelationship of state-object combinations blurs their visual features, hindering the learning of distinguishable class prototypes. Prevailing methods concentrate on disentangling states

Varun Nathan, Ayush Kumar, Digvijay Ingle, Jithendra Vepa

Fine-tuning large language models (LLMs) with domain-specific instructions has emerged as an effective method to enhance their domain-specific understanding. Yet, there is limited work that examines the core characteristics acquired during this process. In this study, we benchmark the fundamental characteristics learned by contact-center (CC) specific instru

Huiping Huang, Musa Furkan Keskin, Henk Wymeersch, Xuesong Cai

Hybrid analog-digital beamforming stands out as a key enabler for future communication systems with a massive number of antennas. In this paper, we investigate the hybrid precoder design problem for angle-of-departure (AoD) estimation, where we take into account the practical constraint on the limited resolution of phase shifters. Our goal is to design a rad

Michael G. Cowling, Ming-Yi Lee, Ji Li, Jill Pipher

We establish hyperweak boundedness of area functions, square functions, maximal operators and Calder\'on--Zygmund operators on products of two stratified Lie groups.

Cao Zhihao, Qu Hongchun

In contemporary scientific research, understanding the distinction between correlation and causation is crucial. While correlation is a widely used analytical standard, it does not inherently imply causation. This paper addresses the potential for misinterpretation in relying solely on correlation, especially in the context of nonlinear dynamics. Despite the

Linyi Yang, Shuibai Zhang, Zhuohao Yu, Guangsheng Bao

Large Language Models (LLMs) exhibit emerging in-context learning abilities through prompt engineering. The recent progress in large-scale generative models has further expanded their use in real-world language applications. However, the critical challenge of improving the generalizability and factuality of LLMs in natural language understanding and question

Zhen-Feng Jin, Weimin Zhang

In this paper, we consider the existence of positive solutions with prescribed $L^2$-norm for the following nonlinear Schr\"{o}dinger equation involving potential and Sobolev critical exponent \begin{equation*} \begin{cases} -\Delta u+V(x)u=\lambda u+\mu |u|^{p-2}u+|u|^{\frac{4}{N-2}}u \;\;\text { in } \mathbb{R}^N, \\ \|u\|_2=a>0,\\ \end{cases} \end{equatio

Hanhui Li, Xiaojian Lin, Xuan Huang, Zejun Yang

Current parametric models have made notable progress in 3D hand pose and shape estimation. However, due to the fixed hand topology and complex hand poses, current models are hard to generate meshes that are aligned with the image well. To tackle this issue, we introduce a dual noise estimation method in this paper. Given a single-view image as input, we firs

Zhengzhuo Xu, Sinan Du, Yiyan Qi, Chengjin Xu

Multimodal Large Language Models (MLLMs) have shown impressive capabilities in image understanding and generation. However, current benchmarks fail to accurately evaluate the chart comprehension of MLLMs due to limited chart types and inappropriate metrics. To address this, we propose ChartBench, a comprehensive benchmark designed to assess chart comprehensi

Hojeong Lee, Hyogon Kim

The Society of Automotive Engineers (SAE) has specified a wireless channel congestion control algorithm for cellular vehicle-to-everything (C-V2X) communication in J3161/1. A notable aspect of J3161/1 standard is that it addresses persistent packet collisions between neighboring vehicles. Although the chances are slim, the persistent collisions can cause so

N. C. Tsamis, R. P. Woodard, B. Yesilyurt

We consider the massless, minimally coupled scalar on de Sitter background. Although the 1-loop divergences of the graviton 1PI 2-point function are canceled by the usual Weyl ($C^2$) and Eddington ($R^2$) counterterms, there is still a finite, nonzero contribution to the graviton 1-point function. Unless this is canceled by a finite renormalization of the c

Kirill Yackushenoks, Fedor Ivanov

Krouk, Tavernier and Kabatiansky proposed new variants of the McEliece cryptosystem. In this letter, it is shown that cryptosystem based on correction of errors erasures is equal to the Mc-Eliece cryptosystem with worse parametrs public key. It will also add an organic extension of the authors' idea, although one that has its flaws...

Songmin Dai, Yifan Wu, Xiaoqiang Li, Xiangyang Xue

Recent unsupervised anomaly detection methods often rely on feature extractors pretrained with auxiliary datasets or on well-crafted anomaly-simulated samples. However, this might limit their adaptability to an increasing set of anomaly detection tasks due to the priors in the selection of auxiliary datasets or the strategy of anomaly simulation. To tackle t

Dayong Ye, Tianqing Zhu, Congcong Zhu, Derui Wang

Machine unlearning refers to the process of mitigating the influence of specific training data on machine learning models based on removal requests from data owners. However, one important area that has been largely overlooked in the research of unlearning is reinforcement learning. Reinforcement learning focuses on training an agent to make optimal decision

Renzhe Zhou, Chen-Xiao Gao, Zongzhang Zhang, Yang Yu

Generalization and sample efficiency have been long-standing issues concerning reinforcement learning, and thus the field of Offline Meta-Reinforcement Learning~(OMRL) has gained increasing attention due to its potential of solving a wide range of problems with static and limited offline data. Existing OMRL methods often assume sufficient training tasks and

Junjie Wang, Yicheng Chen, Wangshu Zhang, Sen Hu

Leveraging knowledge from multiple tasks through introducing a small number of task specific parameters into each transformer layer, also known as adapters, receives much attention recently. However, adding an extra fusion layer to implement knowledge composition not only increases the inference time but also is non-scalable for some applications. To avoid t

Alexey Skrynnik, Anton Andreychuk, Konstantin Yakovlev, Aleksandr Panov

The Multi-Agent Pathfinding (MAPF) problem involves finding a set of conflict-free paths for a group of agents confined to a graph. In typical MAPF scenarios, the graph and the agents' starting and ending vertices are known beforehand, allowing the use of centralized planning algorithms. However, in this study, we focus on the decentralized MAPF setting, whe

Chunpu Xu, Steffi Chern, Ethan Chern, Ge Zhang

In this paper, we aim to align large language models with the ever-changing, complex, and diverse human values (e.g., social norms) across time and locations. This presents a challenge to existing alignment techniques, such as supervised fine-tuning, which internalize values within model parameters. To overcome this, we propose an On-the-fly Preference Optim

Daehee Park, Jaewoo Jeong, Kuk-Jin Yoon

Multi-agent trajectory prediction is crucial for various practical applications, spurring the construction of many large-scale trajectory datasets, including vehicles and pedestrians. However, discrepancies exist among datasets due to external factors and data acquisition strategies. External factors include geographical differences and driving styles, while

Lianyu Pang, Jian Yin, Haoran Xie, Qiping Wang

Recently, there has been a surge in face personalization techniques, benefiting from the advanced capabilities of pretrained text-to-image diffusion models. Among these, a notable method is Textual Inversion, which generates personalized images by inverting given images into textual embeddings. However, methods based on Textual Inversion still struggle with

Yi Qiu, Xisco Jiménez Forteza, Pierre Mourier

The ringdown (RD) phase of gravitational waves is of prime interest for testing general relativity (GR). The modelling of the linear quasi-normal modes (QNMs) within the Kerr spectrum -- or with agnostic parameterized deviations to that GR spectrum -- has become ordinary; however, specific attention has recently emerged to calibrate the effects of nonlinear

Chen Yang, Jin Chen, Qian Yu, Xiangdong Wu

Online recommenders have attained growing interest and created great revenue for businesses. Given numerous users and items, incremental update becomes a mainstream paradigm for learning large-scale models in industrial scenarios, where only newly arrived data within a sliding window is fed into the model, meeting the strict requirements of quick response. H

Dandan Fan, Huiqiu Lin, Hongliang Lu, Suil O

A factor of a graph is a spanning subgraph satisfying some given conditions. An earlier survey of factors can be traced back to the Akiyama and Kano [J. Graph Theory, 1985, 9: 1-42] in which they described the characterization of factors in (bipartite) graphs and digraphs, respectively. Soon after, Kouider and Vestergaard summarized the findings related to c

Zixian Guo, Yuxiang Wei, Ming Liu, Zhilong Ji

Parameter-efficient fine-tuning (PEFT) methods have provided an effective way for adapting large vision-language models to specific tasks or scenarios. Typically, they learn a very small scale of parameters for pre-trained models in a white-box formulation, which assumes model architectures to be known and parameters to be accessible. However, large models a

Zunnan Xu, Yachao Zhang, Sicheng Yang, Ronghui Li

This study aims to improve the generation of 3D gestures by utilizing multimodal information from human speech. Previous studies have focused on incorporating additional modalities to enhance the quality of generated gestures. However, these methods perform poorly when certain modalities are missing during inference. To address this problem, we suggest using

Yucheng Ji, Xiaoqian Fu, Feng Ding, Yongtao Xu

Efficiently designing lightweight alloys with combined high corrosion resistance and mechanical properties remains an enduring topic in materials engineering. To this end, machine learning (ML) coupled ab-initio calculations is proposed within this study. Due to the inadequate accuracy of conventional stress-strain ML models caused by corrosion factors, a no

Yi Xu, Yu-Hong Liu, Cheng Liu, Jie-Qiao Liao

Simultaneous ground-state cooling of two levitated nanoparticles is a crucial prerequisite for investigation of macroscopic quantum effects such as quantum entanglement and quantum correlation involving translational motion of particles. Here we consider a coupled cavity-levitated-particle system and present a detailed derivation of its Hamiltonian. We find

Kenta Tsukahara, Kanji Tanaka

A typical assumption in state-of-the-art self-localization models is that an annotated training dataset is available for the target workspace. However, this is not necessarily true when a robot travels around the general open world. This work introduces a novel training scheme for open-world distributed robot systems. In our scheme, a robot (``student") can

Tanvi Sharma, Mustafa Ali, Indranil Chakraborty, Kaushik Roy

Matrix multiplication is the dominant computation during Machine Learning (ML) inference. To efficiently perform such multiplication operations, Compute-in-memory (CiM) paradigms have emerged as a highly energy efficient solution. However, integrating compute in memory poses key questions, such as 1) What type of CiM to use: Given a multitude of CiM design c

Zhaoyang Wei, Pengfei Chen, Xuehui Yu, Guorong Li

Single-point annotation in visual tasks, with the goal of minimizing labelling costs, is becoming increasingly prominent in research. Recently, visual foundation models, such as Segment Anything (SAM), have gained widespread usage due to their robust zero-shot capabilities and exceptional annotation performance. However, SAM's class-agnostic output and high

Tianmeng Wang, Liping Tong, Jie Yang

We propose a new family of regression models for analyzing categorical responses, called multinomial link models. It consists of four classes, namely, mixed-link models that generalize existing multinomial logistic models and their extensions, two-group models that can incorporate the observations with NA or unknown responses, dichotomous conditional link mo

Suho Park, SuBeen Lee, Sangeek Hyun, Hyun Seok Seong

Few-shot segmentation aims to accurately segment novel target objects within query images using only a limited number of annotated support images. The recent works exploit support background as well as its foreground to precisely compute the dense correlations between query and support. However, they overlook the characteristics of the background that genera

Hiroyuki Ochiai, Satoshi Wakatsuki, Shun'ichi Yokoyama

In this paper, we present an algorithm to compute a basis of the space of algebraic modular forms on the maximal order of the definite quaternion algebra of discriminant $2$, and provide a database of such bases. One of our motivations is to study congruence relations of algebraic modular forms.

Saria Al Laham, Bobak H. Baghi, Pierre-Yves Lajoie, Amal Feriani

We present a human state estimation framework that allows us to estimate the location, and even the activities, of people in an indoor environment without the requirement that they carry a specific devices with them. To achieve this "device free" localization we use a small number of low-cost Ultra-Wide Band (UWB) sensors distributed across the environment o

Rong Zhang, Xiaoguang Chen, Yaoyao Wang, Bin Lu

A super-dense coding protocol based on the n-GHZ state is proposed to enable the two communicating parties to choose the number of transmitted code words according to their demand and to adapt the quantum super-dense coding protocol to multiple transmitted code word scenarios. A method is proposed that combines entanglement purification and Quantum Neural Ne

Ryota Yambe, Satoru Hayami

Noncoplanar magnetic states with a scalar spin chirality have been intensively studied in condensed matter physics, since they exhibit fascinating physical phenomena. We theoretically propose the generation of such noncoplanar magnetic states by using a circularly polarized electric field. By performing the micromagnetic simulation, we investigate a time evo

Jaehyuk Jang, Yooseung Wang, Changick Kim

Recently, multimodal prompting, which introduces learnable missing-aware prompts for all missing modality cases, has exhibited impressive performance. However, it encounters two critical issues: 1) The number of prompts grows exponentially as the number of modalities increases; and 2) It lacks robustness in scenarios with different missing modality settings

Biyan Zhou, Pao-Sheng Vincent Sun, Arindam Basu

While it is important to make implantable brain-machine interfaces (iBMI) wireless to increase patient comfort and safety, the trend of increased channel count in recent neural probes poses a challenge due to the concomitant increase in the data rate. Extracting information from raw data at the source by using edge computing is a promising solution to this p

Jiro Sekiguchi

This paper has two aims. The first one is the construction problem of algebraic potentials of Frobenius manifolds. We show examples of such potentials for the cases of reflection groups of types $H_4,E_6,E_7,E_8$ and also include those which are already known. The second one is an application of such potentials to singularity theory. We introduce families of

Yulia Meshkova

Let $\mathcal{O}\subset \mathbb{R}^d$ be a bounded domain of class $C^{1,1}$. In $ L_2(\mathcal{O};\mathbb{C}^n)$, we consider a matrix elliptic second order differential operator $A_{D,\varepsilon}$ with the Dirichlet boundary condition. Here $\varepsilon >0$ is a small parameter. The coefficients of the operator $A_{D,\varepsilon}$ are periodic and depend

Aaron N. Siegel

The universe $\mathcal{E}$ of dead-ending partizan games has emerged as an important structure in the study of mis\`ere play. Here we attempt a systematic investigation of the structure of $\mathcal{E}$ and its subuniverses. We begin by showing that the dead-ends exhibit a rich "absolute" structure, in the sense that they behave identically in any universe i

S. R. Mane

We derive a simple expression for the $r^{th}$ factorial moment $\mu_{(r)}$ of the geometric distribution of order $k$ with success parameter $p\in(0,1)$ (and $q=1-p$) in terms of its probability mass function $f_k(n)$. Specifically, $\mu_{(r)} = r!f_k((r+1)k+r)/((qp^k)^{r+1})$.

Richard H. Price, Ritesh Bachhar, Gaurav Khanna

The major source of ground-based gravitational wave detectors, the inspiral and merger of comparable mass binary black holes (BBH), consists of a slow quasicircular inspiral, a merger to form a single remnant hole, and the quasinormal ringing of that remnant. The first and last of these epochs are amenable to well developed and familiar approximations: Newto

S. S. AbdusSalam, S. S. Barzani, L. Kalhor, M. Mohammadidoust

The minimal supersymmetric standard model (MSSM) particles can generate loop-level radiative corrections that contribute to the electric dipole moment (EDM) of an electron. The upper bound on the EDM can therefore be used for delineating the MSSM parameters space. We use this setting to describe a direction of particle physics phenomenology research -- the g

Xinke Jiang, Ruizhe Zhang, Yongxin Xu, Rihong Qiu

In this paper, we investigate the retrieval-augmented generation (RAG) based on Knowledge Graphs (KGs) to improve the accuracy and reliability of Large Language Models (LLMs). Recent approaches suffer from insufficient and repetitive knowledge retrieval, tedious and time-consuming query parsing, and monotonous knowledge utilization. To this end, we develop a

Elnaz Rostampour, Badie Ghavami, Karin Larsson

The optical absorption spectrum of $C_{60}$-dimers and polymers was investigated by Kikuo et al. in 1996\cite{harigaya1996charge}. As a compliment to these earlier studies, the optical absorption spectrum of the $C_{70}$ fullerene has been investigated in the present study. The main purpose was then to compare the absorption spectrum of the $C_{70}$-dimers a

Yao Liu, Binghao Li, Xianzhi Wang, Claude Sammut

Trajectory prediction is fundamental to various intelligent technologies, such as autonomous driving and robotics. The motion prediction of pedestrians and vehicles helps emergency braking, reduces collisions, and improves traffic safety. Current trajectory prediction research faces problems of complex social interactions, high dynamics and multi-modality. E

Tiezheng Guo, Qingwen Yang, Chen Wang, Yanyi Liu

Large language model (LLM) has achieved outstanding performance on various downstream tasks with its powerful natural language understanding and zero-shot capability, but LLM still suffers from knowledge limitation. Especially in scenarios that require long logical chains or complex reasoning, the hallucination and knowledge limitation of LLM limit its perfo

Deguang Zhong, Fangming Cai, Dongping Wei

Suppose that $1<p\leq\infty$ and $\varphi\in L^{p}(\mathbb{B}^{n},\mathbb{R}^{n}).$ In this note, we use H\"{o}lder inequality and some basic properties of hypergeometric functions to establish the sharp constant $C_{p}$ and function $C_{p}(x)$ in the following inequalities $$|u(x)|\leq \frac{C_{p}}{(1-|x|^{2})^{(n-1)/p}}\cdot||\varphi||_{L^{p}}$$ and $$|u(x

Liang-Liang Wang, Wenjun Shao, Jian Li

We investigate the collisions of Majorana zero modes, which are presented as inter-soliton collisional events in fermionic superfluids with spin-orbit coupling. Our results demonstrate that, the zero energy splitting, induced by the overlapping of inter-soliton Majorana wave-functions upon collision, generates an effective repulsive force for Majorana states

Yong Lai, Zhenghang Xu, Minghao Yin

In Weighted Model Counting (WMC), we assign weights to literals and compute the sum of the weights of the models of a given propositional formula where the weight of an assignment is the product of the weights of its literals. The current WMC solvers work on Conjunctive Normal Form (CNF) formulas. However, CNF is not a natural representation for human-being

Shuichi Sato

We give an alternative proof of a result on the uniform overlap of the algebraic sums of the sets arising from a decomposition of a neighborhood of a circular cone in $\Bbb R^3$. It is known that the uniform overlap result can be applied to make a unified approach for the proofs of a theorem on the maximal Bochner-Riesz operator on $\Bbb R^2$ and a theorem o

Yawer Hussain Shah, Paolo Grigolini

The main purpose of this paper is to attract the attention of researchers working in the field of physiological processes, towards crucial events. Crucial events are often confused with extreme events thereby generating the misleading impression that their treatment should be based on quantum mechanical formalism. We show that crucial events are invisible an

Prerona Chatterjee, Deepanshu Kush, Shubhangi Saraf, Amir Shpilka

In this paper, we prove super-polynomial lower bounds for the model of \emph{sum of ordered set-multilinear algebraic branching programs}, each with a possibly different ordering ($\sum \mathsf{smABP}$). Specifically, we give an explicit $nd$-variate polynomial of degree $d$ such that any $\sum \mathsf{smABP}$ computing it must have size $n^{\omega(1)}$ for

Xiangtong Wang, Xiaodong Han, Menglong Yang, Chuan Xing

Low Earth orbit (LEO) mega-constellations rely on inter-satellite links (ISLs) to provide global connectivity. We note that in addition to the general constellation parameters, the ISL spanning patterns are also greatly influence the final network structure and thus the network performance. In this work, we formulate the ISL spanning patterns, apply differen

Jia Cheng Hu, Roberto Cavicchioli, Giulia Berardinelli, Alessandro Capotondi

Although the Transformer is currently the best-performing architecture in the homogeneous configuration (self-attention only) in Neural Machine Translation, many State-of-the-Art models in Natural Language Processing are made of a combination of different Deep Learning approaches. However, these models often focus on combining a couple of techniques only and

Guoming Wang, Angus Kan

We develop quantum algorithms for pricing Asian and barrier options under the Heston model, a popular stochastic volatility model, and estimate their costs, in terms of T-count, T-depth and number of logical qubits, on instances under typical market conditions. These algorithms are based on combining well-established numerical methods for stochastic differen

Vyacheslav Ivanovich Dokuchaev, Konstantin Eduardovich Prokopev

We generalize the notion of Einstein-Rosen bridge by defining it as a space-like connection between two universes with regions of asymptotically minkowskian space-time infinities. The corresponding symmetry and asymmetry properties of the generalized Einstein-Rosen bridge are considered at the cases of Reissner-Nordstr\"om and Kerr metrics. We elucidate the

Ruoqing Zhao, Xi Wang, Hongliang Dai, Pan Gao

Automated radiology report generation has the potential to improve radiology reporting and alleviate the workload of radiologists. However, the medical report generation task poses unique challenges due to the limited availability of medical data and the presence of data bias. To maximize the utility of available data and reduce data bias, we propose MSCL (M

Yan Han, Xiaogang Xu, Yingqi Lin, Jiafei Wu

In existing restoration-oriented Video Frame Interpolation (VFI) approaches, the motion estimation between neighboring frames plays a crucial role. However, the estimation accuracy in existing methods remains a challenge, primarily due to the inherent ambiguity in identifying corresponding areas in adjacent frames for interpolation. Therefore, enhancing accu

Xuan Sheng, Zhicheng Li, Zhaoyang Han, Xiangmao Chang

Recent studies have pointed out that natural language processing (NLP) models are vulnerable to backdoor attacks. A backdoored model produces normal outputs on the clean samples while performing improperly on the texts with triggers that the adversary injects. However, previous studies on textual backdoor attack pay little attention to stealthiness. Moreover

Vishwam Khapre, Kang Lyu, Andrew Yu

We study eigenvalues of the Dirac operator with canonical form \begin{equation} L_{p,q} \begin{pmatrix} u \\ v \end{pmatrix}= \begin{pmatrix} 0 & -1 \\ 1 & 0 \end{pmatrix}\frac{d}{dt} \begin{pmatrix} u \\ v \end{pmatrix}+\begin{pmatrix} -p & q \\ q & p \end{pmatrix}\begin{pmatrix} u \\ v \end{pmatrix},\nonumber \end{equation} where $ p$ and $q$ are real func

Saleh Ghobbe, Mahdi Nohekhan

The environmental conservation issue has led consumers to rethink the products they purchase. Nowadays, many consumers are willing to pay more for products that genuinely adhere to environmental standards to support the environment. Consequently, concepts like green marketing have gradually infiltrated marketing literature, making environmental consideration

Yingkai Xiao, Jingjin Liu, Hankz Hankui Zhuo

Constraint Optimization Problems (COP) pose intricate challenges in combinatorial problems usually addressed through Branch and Bound (B\&B) methods, which involve maintaining priority queues and iteratively selecting branches to search for solutions. However, conventional approaches take a considerable amount of time to find optimal solutions, and it is als

Hangyu Mao, Rui Zhao, Ziyue Li, Zhiwei Xu

Designing better deep networks and better reinforcement learning (RL) algorithms are both important for deep RL. This work studies the former. Specifically, the Perception and Decision-making Interleaving Transformer (PDiT) network is proposed, which cascades two Transformers in a very natural way: the perceiving one focuses on \emph{the environmental percep