October 2024 arXiv papers — page 17

Junyu Fan, Matthew Steinberg, Alexander Jahn, Chunjun Cao

Quantum error correction (QEC) is a crucial prerequisite for future large-scale quantum computation. Finding and analyzing new QEC codes, along with efficient decoding and fault-tolerance protocols, is central to this effort. Holographic codes are a recent class of generalized concatenated codes derived from holographic bulk/boundary dualities. In addition t

Lin Gao

A graphical user interface (GUI) software is provided for lattice QCD simulations, aimed at streamlining the process. The current version of the software employs the Metropolis algorithm with the Wilson gauge action. It is implemented in Python, utilizing Just-In-Time (JIT) compilation to enhance computational speed while preserving Python's simplicity and e

Antonio Di Crescenzo, Paola Paraggio, Francisco Torres-Ruiz

We analyze a modification of the Richards growth model by introducing a time-dependent perturbation in the growth rate. This modification becomes effective at a special switching time, which represents the first-crossing-time of the Richards growth curve through a given constant boundary. The relevant features of the modified growth model are studied and com

Q. Liu, A. Santangelo, L. D. Kong, L. Ducci

We report a detailed timing and spectral analysis of the X-ray pulsar 2S~1417-624 using the data from Insight-HXMT during the 2018 outburst. The pulse profiles are highly variable with respect to both unabsorbed flux and energy. A double-peaked pulse profile from the low flux evolved to a multi-peaked shape in the high-flux state. The pulse fraction is negat

Takafumi Kakehi, Takahiro Tanaka

The Hamiltonian formulation with action-angle variables is very useful when considering the motion of particles undergoing a self-force reaction due to gravitational wave emission. Using the proper time as a parameter along the trajectory is considered to be appropriate when developing formal arguments, but these arguments can easily be extended to arguments

Peter Ochieng, Dennis Kaburu

We present a prosody-guided framework for speech-to-speech translation (S2ST) that aligns and translates speech \emph{without} transcripts by leveraging cross-linguistic pause synchrony. Analyzing a 6{,}000-hour East African news corpus spanning five languages, we show that \emph{within-phylum} language pairs exhibit 30--40\% lower pause variance and over 3$

Ahmet Serdar Karadeniz, Dimitrios Mallis, Nesryne Mejri, Kseniya Cherenkova

This work presents DAVINCI, a unified architecture for single-stage Computer-Aided Design (CAD) sketch parameterization and constraint inference directly from raster sketch images. By jointly learning both outputs, DAVINCI minimizes error accumulation and enhances the performance of constrained CAD sketch inference. Notably, DAVINCI achieves state-of-the-art

Ni Xiang, Yuni Xiong, Lina Zheng

In this paper, we investigate the oblique boundary value problem for degenerate Hessian quotient type equations in a smooth bounded domain. Without imposing any geometric restrictions on the domain, we establish the a priori estimates and derive the existence and uniqueness of admissible $C^{1,1}$ solutions under the condition $f^{\frac{1}{k-l}}\in C^{1,1}(\

Raphael E. Hoult, Ashish Shukla

We investigate the linearized stability and causality properties of relativistic viscous superfluid hydrodynamics. The Landau-Lifshitz-Clark-Putterman formulation for the theory of relativistic viscous superfluids suffers from the same instability and acausality issues as the relativistic Navier-Stokes equation for normal fluids when written in the formulati

Luca Franceschi, Michele Donini, Valerio Perrone, Aaron Klein

Hyperparameters are configuration variables controlling the behavior of machine learning algorithms. They are ubiquitous in machine learning and artificial intelligence and the choice of their values determines the effectiveness of systems based on these technologies. Manual hyperparameter search is often time-consuming and becomes infeasible when the number

Yueguang Hu, Hongyu Liu

This paper investigates the asymptotic behaviors of time-harmonic acoustic waves generated by an incident wave illuminating inhomogeneous medium inclusions with high-contrast material parameters. We derive sharp asymptotic estimates and obtain several effective acoustic obstacle scattering models when the material parameters take extreme values. The results

Zitong Fang, Ziming Yu, Chong Han

Terahertz (THz) integrated sensing and communication (ISAC) technology is envisioned to achieve high communication performance alongside advanced sensing abilities. For various applications of ISAC, accurate environment reconstruction including geometry reconstruction and material identification is critical. This paper presents a highly precise geometry reco

Nakul Kumar, Nikita Sharma, Soumyarup Hait, Lalit Pandey

The generation of spin-orbital currents is crucial for advancing energy-efficient spintronic devices. Here, the intricate process involved in the generation and conversion of spin and orbital to charge currents in Zr(t=2, 3, 4.5, 6, &10nm)/Co60Fe20B20(CFB), Zr/Pt/CFB, and Zr/Pt/CFB/Pt heterostructures are investigated using spin-orbital pumping ferromagnetic

A. Curcio, G. Dattoli, E. Di Palma, P. Natalini

A class of overlooked trigonometric-like functions is explored in this article, along with the relevant applications in applications. We show indeed that Taylor series, resembling that of an ordinary cosine, are representative of wider classes of functions, naturally suited for prolems ranging from molecular to Laser Physics. The article goes through the ori

Keyu Chen, Cheng Fei, Ziqian Bi, Junyu Liu

With a focus on natural language processing (NLP) and the role of large language models (LLMs), we explore the intersection of machine learning, deep learning, and artificial intelligence. As artificial intelligence continues to revolutionize fields from healthcare to finance, NLP techniques such as tokenization, text classification, and entity recognition a

Noam Ginio, Michael Lindenbaum, Barak Fishbain, Dan Liberzon

Effective spatio-temporal measurements of water surface elevation (water waves) in laboratory experiments are essential for scientific and engineering research. Existing techniques are often cumbersome, computationally heavy and generally suffer from limited wavenumber/frequency response. To address these challenges a novel method was developed, using polari

Yongyi Jia, Shu Miao, Ao Wang, Caiding Ni

Micromanipulation systems leverage automation and robotic technologies to improve the precision, repeatability, and efficiency of various tasks at the microscale. However, current approaches are typically limited to specific objects or tasks, which necessitates the use of custom tools and specialized grasping methods. This paper proposes a novel non-contact

M. E. Malev, D. S. Kaparulin, N. N. Levin

In this paper, we investigate the thermodynamics of an ideal gas of classical particles with continuous helicity in three-dimensional Minkowski space. Using the one-particle distribution function for a particle with continuous helicity, we obtain expressions for the chemical potential, angular momentum, and entropy of the gas. We show that such a system plac

Pawandeep Kaur Betz, Tobias Hecking, Andreas Gerndt

The increasing complexity and scale of scientific datasets demand advanced tools for efficient discovery and exploration. Traditional search systems often fall short in addressing the multidimensional nature of data and their intricate relationships, limiting their utility for researchers. This paper introduces the Knowledge Graph Based Visualization Search

Shaull Almagor, Michaël Cadilhac, Asaf Yeshurun

One Counter Nets (OCNs) are finite-state automata equipped with a counter that cannot become negative, but cannot be explicitly tested for zero. Their close connection to various other models (e.g., PDAs, Vector Addition Systems, and Counter Automata) make them an attractive modeling tool. The two-way variant of OCNs (2-OCNs) was introduced in the 1980's and

Kaike Zhang, Qi Cao, Yunfan Wu, Fei Sun

Adversarial Collaborative Filtering (ACF), which typically applies adversarial perturbations at user and item embeddings through adversarial training, is widely recognized as an effective strategy for enhancing the robustness of Collaborative Filtering (CF) recommender systems against poisoning attacks. Besides, numerous studies have empirically shown that A

Sergey N. Solodukhin

Inspired by the Dirac model model of graphene, we consider a $(2+1)$-dimensional fermionic system in which fermions are described by four-component spinors. These fermions are proposed to interact with an electromagnetic field originating from a four-dimensional setting, as the graphene plate is embedded in 4d Minkowski spacetime. In this framework, a chiral

Federica Mascolo, Nora Bearth, Fabian Muny, Michael Lechner

Active labor market policies are widely used by the Swiss government, enrolling over half of all unemployed individuals. This paper evaluates the effectiveness of Swiss programs in improving employment and earnings outcomes using causal machine learning and rich administrative data on unemployed individuals in 2014 and 2015, including detailed labor market h

Anand Shripad Hegde, R. B. Sandeep, P. Shashank

Erd\H{o}s and Gy\'arf\'as conjectured in 1994 that every graph with minimum degree at least 3 has a cycle of length a power of 2. In 2022, Gao and Shan (Graphs and Combinatorics) proved that the conjecture is true for $P_8$-free graphs, i.e., graphs without any induced copies of a path on 8 vertices. In 2024, Hu and Shen (Discrete Mathematics) improved this

Yueling Yang, Bingbing Yang, Jiazhi Li, Zhaojie Lu

Inspired by the observation of the ${\eta}_{t}$ meson at the LHC and the promising prospect of the ${\eta}_{t}$ meson available at the approaching HL-LHC, branching ratios for the ${\eta}_{t}$ ${\to}$ $f\bar{f}$, $gg$, ${\gamma}{\gamma}$, $W^{+}W^{-}$, $Z^{0}Z^{0}$, $Z^{0}{\gamma}$ and $Z^{0}H$ decays are roughly estimated. It is found that tens of opposite-

Allen Lobo, Vinod Kumar Sayal

In this work, the recently introduced fluid-like treatment of the phase-space has been further extended and some interesting outcomes have been presented. A modified form of the Vlasov equation has been presented which describes the diffusion of the phase-space density. This anisotropic diffusion is analysed and the flow of the phase-space probability field

Søren Vejlgaard Holm, Lars Kai Hansen, Martin Carsten Nielsen

The language technology moonshot moment of Generative Large Language Models (GLLMs) was not limited to English: These models brought a surge of technological applications, investments, and hype to low-resource languages as well. However, the capabilities of these models in languages such as Danish were, until recently, difficult to verify beyond qualitative

Pierre Jamet, Aurélien Drezet

In this work we present a new theoretical approach to interpreting and reproducing quantum mechanics using trajectory-guided wavelets. Inspired by the 1925 work of Louis de Broglie, we demonstrate that pulses composed of a difference between a retarded wave and an advanced wave (known as antisymmetric waves) are capable of following quantum trajectories pred

Kun Hu, Qingle Zhang, Maoxun Yuan, Yitian Zhang

Infrared and visible image fusion aims to utilize the complementary information from two modalities to generate fused images with prominent targets and rich texture details. Most existing algorithms only perform pixel-level or feature-level fusion from different modalities in the spatial domain. They usually overlook the information in the frequency domain,

Francesco Maria Bellussi, Matteo Ricci, Matteo Fasano, Otello Maria Roscioni

A challenging topic in materials engineering is the development of numerical models that can accurately predict material properties with atomistic accuracy, matching the scale and level of detail achieved by experiments. In this regard, coarse-grained (CG) molecular dynamics (MD) simulations are a popular method for achieving this goal. Despite the efforts o

Shinya Kanemura, Yushi Mura, Guohao Ying

The radiative seesaw model with gauged $\mathrm{U(1)}_{B-L}\times\mathbb{Z}_2$ extension is a well-motivated scenario which gives consistent predictions of active neutrino masses and the abundance of dark matter. Majorana masses of right-handed neutrinos, the lightest of which can be identified as dark matter, are given by the spontaneous breaking of the $\m

Xiao Wang

The development of future quantum devices requires understanding the dynamics of driven many-body systems, in which the Floquet-induced interactions play a central role. This understanding is crucial for coherently controlling quantum states, minimising errors, and benchmarking the performance of these devices. In this thesis, we analyse the enhancement on t

Anurag Gupta, Debojyoti Ganguly, Mini Raman, K. N. Babu

In ocean colour remote sensing, radiance at the sensor level can be modeled using molecular scattering and particle scattering based on existing mathematical models and gaseous absorption in the atmosphere. The modulation of light field by optical constituents within the seawater waters results in the spectral variation of water leaving radiances that can be

Yucheng Zhang, Qinfeng Li, Tianyu Du, Xuhong Zhang

Retrieval-Augmented Generation (RAG) systems enhance large language models (LLMs) by integrating external knowledge, making them adaptable and cost-effective for various applications. However, the growing reliance on these systems also introduces potential security risks. In this work, we reveal a novel vulnerability, the retrieval prompt hijack attack (Hija

Maciej P. Wojtkowski

We propose a new interpretation of the classical index of appearance for second order linear recursive sequences. It stems from the formula \[ C_{n}(t)-2 =\frac{\Delta}{Q^{n}}\ L_n^2,\ \ \ \text{where} \ \ t= (T^2-2Q)/Q, \ \Delta = T^2-4Q, \] connecting the Chebyshev polynomials of the first kind $C_n(x)$ with the Lucas sequence defined for integer $T,Q\neq

Hanlin Wu, Jiangwei Mo, Xiaohui Sun, Jie Ma

Recent advancements in diffusion models have significantly improved performance in super-resolution (SR) tasks. However, previous research often overlooks the fundamental differences between SR and general image generation. General image generation involves creating images from scratch, while SR focuses specifically on enhancing existing low-resolution (LR)

Chinthani Sugandhika, Chen Li, Deepu Rajan, Basura Fernando

Graph based representation has been widely used in modelling spatio-temporal relationships in video understanding. Although effective, existing graph-based approaches focus on capturing the human-object relationships while ignoring fine-grained semantic properties of the action components. These semantic properties are crucial for understanding the current s

Baoning Wang, Zhiyuan Xu, Zhiyu Han, Qiwen Nie

In recent years, the realm of crystalline materials has witnessed a surge in the development of generative models, predominantly aimed at the inverse design of crystals with tailored physical properties. However, spatial symmetry, which serves as a significant inductive bias, is often not optimally harnessed in the design process. This oversight tends to res

Richard Johansson

We evaluate a battery of recent large language models on two benchmarks for word sense disambiguation in Swedish. At present, all current models are less accurate than the best supervised disambiguators in cases where a training set is available, but most models outperform graph-based unsupervised systems. Different prompting approaches are compared, with a

Julio Castaño-Amoros, Pablo Gil

Tactile sensors have been used for force estimation in the past, especially Vision-Based Tactile Sensors (VBTS) have recently become a new trend due to their high spatial resolution and low cost. In this work, we have designed and implemented several approaches to estimate the normal grasping force using different types of markerless visuotactile representat

Arsalan Jawaid, Samuel Schmidt, Marvin Lotz, Jörg Seewig

Spurious measurements frequently occur in surface data from technical components. Excluding or ignoring these spurious points may lead to incorrect surface characterization if these points inherit features of the surface. Therefore, data imputation must be applied to ensure that the estimated data points at spurious measurements do not deviate strongly from

Xiaohui Yu, Wei Zhong, Saori Kawaguchi, Hirokazu Kadobayashi

The simultaneous presence of polarity and metallicity in a material signifies an exotic polar metal state, but such materials are extremely rare, especially in bulk form, due to mutually exclusive nature of the fundamental defining properties. Here, we report experimental findings that HgPSe3 is a robust bulk polar metal at room temperature with a chiral str

Guangting Yu, Shiwei Lan, Kookjin Lee, Alex Mahalov

We present a novel method for reconstructing the thermal conductivity coefficient in 1D and 2D heat equations using moving sensors that dynamically traverse the domain to record sparse and noisy temperature measurements. We significantly reduce the computational cost associated with forward PDE evaluations by employing automatic differentiation, enabling a m

Jia Li, Ge Li, Xuanming Zhang, Yunfei Zhao

How to evaluate Large Language Models (LLMs) in code generation remains an open question. Existing benchmarks have two limitations - data leakage and lack of domain-specific evaluation. The former hurts the fairness of benchmarks, and the latter hinders practitioners from selecting superior LLMs for specific programming domains. To address these two limitati

Giacomo Como, Fabio Fagnani, Sandro Zampieri

We study stochastic pairwise interaction network systems whereby a finite population of agents, identified with the nodes of a graph, update their states in response to both individual mutations and pairwise interactions with their neighbors. The considered class of systems include the main epidemic models -such as the SIS, SIR, and SIRS models-, certain soc

Chih-Whi Chen, Shun-Jen Cheng, Uhi Rinn Suh

For a basic classical Lie superalgebra $\mathfrak s$, let $\mathfrak g$ be the central extension of the Takiff superalgebra $\mathfrak s\otimes\Lambda(\theta)$, where $\theta$ is an odd indeterminate. We study the category of $\mathfrak g$-Whittaker modules associated with a nilcharacter $\chi$ of $\mathfrak g$ and show that it is equivalent to the category

Lei Chen, Sai Zhang, Fangzhou Xu, Zhenchang Xing

In the task of code translation, neural network-based models have been shown to frequently produce semantically erroneous code that deviates from the original logic of the source code. This issue persists even with advanced large models. Although a recent approach proposed using test cases to identify these semantic errors, it relies heavily on the quality o

Tomer Barak, Yonatan Loewenstein

When individuals encounter observations that violate their expectations, when will they adjust their expectations and when will they maintain them despite these observations? For example, when individuals expect objects of type A to be smaller than objects B, but observe the opposite, when will they adjust their expectation about the relationship between the

Zhiyuan Min, Yawei Luo, Jianwen Sun, Yi Yang

Generalizable 3D Gaussian splitting (3DGS) can reconstruct new scenes from sparse-view observations in a feed-forward inference manner, eliminating the need for scene-specific retraining required in conventional 3DGS. However, existing methods rely heavily on epipolar priors, which can be unreliable in complex realworld scenes, particularly in non-overlappin

Tong Hui, Matteo Fumagalli

As aerial robots gain traction in industrial applications, there is growing interest in enhancing their physical interaction capabilities. Pushing tasks performed by aerial manipulators have been successfully demonstrated in contact-based inspections. However, more complex industrial applications require these systems to support higher-DoF (Degree of Freedom

Jabin Koo, Minwoo Jang, Jungseul Ok

Federated fine-tuning for Large Language Models (LLMs) faces significant challenges due to the heavy communication overhead of transmitting large model updates. Although Low Rank Adaptation (LoRA) has been proposed as a solution, yet its application in federated learning is complicated by discordance in aggregation. Existing methods addressing this discordan

Stephanie L. Yardley, David H. Brooks

Large gradual solar energetic particle (SEP) events can pose a radiation risk to crewed spaceflight and a significant threat to near-Earth satellites however, the origin of the SEP seed particle population, how these particles are released, accelerated and transported into the heliosphere are not well understood. We analyse NOAA active region (AR) 12673, tha

Yosuke Sato

We focus on two specific generalizations of the chromatic symmetric function: one involving universal graphs and the other concerning vertex-weighted graphs. In this paper, we introduce a unified generalization that incorporates both approaches and demonstrate that the resulting new invariants inherit characteristics from each, particularly the properties of

Apratim Dey, David Donoho

Researchers in empirical machine learning recently spotlighted their fears of so-called Model Collapse. They imagined a discard workflow, where an initial generative model is trained with real data, after which the real data are discarded, and subsequently, the model generates synthetic data on which a new model is trained. They came to the conclusion that m

Mohd. Azfar, Siddhant Bharadwaj, Ashwin Sasikumar

Enhancing and preserving the readability of document images, particularly historical ones, is crucial for effective document image analysis. Numerous models have been proposed for this task, including convolutional-based, transformer-based, and hybrid convolutional-transformer architectures. While hybrid models address the limitations of purely convolutional

Santaro Kikuura, Ryoya Igata, Yuta Shingu, Shohei Watabe

This study systematically benchmarks several non-fault-tolerant quantum computing algorithms across four distinct optimization problems: max-cut, number partitioning, knapsack, and quantum spin glass. Our benchmark includes noisy intermediate-scale quantum (NISQ) algorithms, such as the variational quantum eigensolver, quantum approximate optimization algori

Yang Zhang, Juntao You, Yimeng Bai, Jizhi Zhang

Recent advancements in recommender systems have focused on leveraging Large Language Models (LLMs) to improve user preference modeling, yielding promising outcomes. However, current LLM-based approaches struggle to fully leverage user behavior sequences, resulting in suboptimal preference modeling for personalized recommendations. In this study, we propose a

Nico Hahn, Mario Kieburg, Omri Gat, Thomas Guhr

The winding number is the topological invariant that classifies chiral symmetric Hamiltonians with one-dimensional parametric dependence. In this work we complete our study of the winding number statistics in a random matrix model belonging to the chiral unitary class AIII. We show that in the limit of large matrix dimensions the winding number distribution

Hui-Peng Du, Yang Ai, Rui-Chen Zheng, Zhen-Hua Ling

This paper proposes a novel neural audio codec, named APCodec+, which is an improved version of APCodec. The APCodec+ takes the audio amplitude and phase spectra as the coding object, and employs an adversarial training strategy. Innovatively, we propose a two-stage joint-individual training paradigm for APCodec+. In the joint training stage, the encoder, qu

Haoyang Liu, Jie Wang, Wanbo Zhang, Zijie Geng

Mixed-integer linear programming (MILP) is one of the most popular mathematical formulations with numerous applications. In practice, improving the performance of MILP solvers often requires a large amount of high-quality data, which can be challenging to collect. Researchers thus turn to generation techniques to generate additional MILP instances. However,

Yoto Fujita, Aditya Arie Nugraha, Diego Di Carlo, Yoshiaki Bando

This paper describes speech enhancement for realtime automatic speech recognition (ASR) in real environments. A standard approach to this task is to use neural beamforming that can work efficiently in an online manner. It estimates the masks of clean dry speech from a noisy echoic mixture spectrogram with a deep neural network (DNN) and then computes a enhan

Arthur Gilfanov

This study develops an algorithm to solve a variation of the Shortest Common Superstring (SCS) problem. There are two modifications to the base SCS problem. First, one string in the set S is allowed to have up to K mistakes, defined as not matching the SCS in at most K positions. Second, no string in S can be a substring of another in S. The algorithm propos

Michele Dolce, Niklas Knobel, Christian Zillinger

We consider the ideally conducting, viscous magnetohydrodynamics (MHD) equations in two dimensions. Specifically, we study the nonlinear dynamics near a combination of Couette flow and a constant magnetic field in a periodic infinite channel. In contrast to the Navier-Stokes equations this system is shown to exhibit algebraic instability and large norm infla

Yoto Fujita, Yoshiaki Bando, Keisuke Imoto, Masaki Onishi

This paper describes sound event localization and detection (SELD) for spatial audio recordings captured by firstorder ambisonics (FOA) microphones. In this task, one may train a deep neural network (DNN) using FOA data annotated with the classes and directions of arrival (DOAs) of sound events. However, the performance of this approach is severely bounded b

Jerome Gilles, Stanley Osher

In this paper, we investigate the extension of the recently proposed weighted Fourier burst accumulation (FBA) method into the wavelet domain. The purpose of FBA is to reconstruct a clean and sharp image from a sequence of blurred frames. This concept lies in the construction of weights to amplify dominant frequencies in the Fourier spectrum of each frame. T

Sung Wook Moon, Soohaeng Yoo Willow, Tae Hyeon Park, Seung Kyu Min

Excited-state molecular dynamics (ESMD) simulations near conical intersections (CIs) pose significant challenges when using machine learning potentials (MLPs). Although MLPs have gained recognition for their integration into mixed quantum-classical (MQC) methods, such as trajectory surface hopping (TSH), and their capacity to model correlated electron-nuclea

Xue He, Shilei Ding, Hans Gløckner Giil, Jicheng Wang

Spin Seebeck effect (SSE) refers to the creation of spin currents due to a temperature gradient in the magnetic materials or across magnet-normal metal interfaces, which can be electrically detected through the inverse spin Hall effect (ISHE) when in contact with heavy metals. It offers fundamental insights into the magnetic properties of materials, includin

Zizhou Zheng, Huan Huang, Hongliang Zhang, A. Lee Swindlehurst

Dual-polarized (DP) multiple-input-multiple-output (MIMO) systems have been widely adopted in commercial mobile wireless communications. Such systems achieve multiplexing and diversity gain by exploiting the polarization dimension. However, existing studies have shown that the capacity of DP MIMO may not surpass that of single-polarized (SP) MIMO systems due

Andreas Grüneis, Evgeny Moerman, Matthias Scheffler, Tonghao Shen

In the molecular quantum chemistry community, coupled-cluster (CC) methods are well-recognized for their systematic convergence and reliability. The extension of the theory to extended systems has been comparably recent, so that developments and studies of periodic CC methods for both the ground-state and for excited states are still active fields of researc

Dohyeong Kim, Jaesung Kwon

We investigate the derived Hecke action on the cohomology of an arithmetic manifold associated to the multiplicative group over a number field. The degree one part of the action is proved to be non-vanishing modulo $p$ under mild assumptions. The main ingredient is the Grunwald--Wang theorem.

Viggo Moro, Luiz F. O. Chamon

(Partial) differential equations (PDEs) are fundamental tools for describing natural phenomena, making their solution crucial in science and engineering. While traditional methods, such as the finite element method, provide reliable solutions, their accuracy is often tied to the use of computationally intensive fine meshes. Moreover, they do not naturally ac

Vishnu Nandakumaran

Caffarelli-Hardt-Simon used the minimal surface equation on the Simons cone $C(S^3\times S^3)$ to generate newer examples of minimal hypersurfaces with isolated singularities. Hardt-Simon proved that every area-minimizing quadratic cone $\mathcal{C}$ having only an isolated singularity can be approximated by a unique foliation of $\mathbb R^{n+1}$ by smooth,

An Li, Jiaru Shi, Hao Zha, Qiang Gao

Current THz electron sources struggle with low energy gain and device miniaturization. We propose a magnetic compression method designed for relativistic electrons to perform post-compression on the beam from radiofrequency accelerators, to produce sub-THz electron beam with exceptionally high energy ($>1$ J). Through simulation studies, we longitudinally co

Guang Yang, Yu Zhou, Wei Cheng, Xiangyu Zhang

The widespread use of Large Language Models (LLMs) in software engineering has intensified the need for improved model and resource efficiency. In particular, for neural code generation, LLMs are used to translate function/method signature and DocString to executable code. DocStrings which capture user re quirements for the code and used as the prompt for LL

Huajun Zhang, Biao Wu

Two families of sets $\mathcal{A}$ and $\mathcal{B}$ are called cross-$t$-intersecting if $|A\cap B|\ge t$ for all $A\in \mathcal{A}$, $B\in \mathcal{B}$. An active problem in extremal set theory is to determine the maximum product of sizes of cross-$t$-intersecting families. This incorporates the classical Erd\H{o}s--Ko--Rado (EKR) problem. In the present p

Nicholas B. Ferrante, Jerome Gilles

Long distance imaging is subject to the impact of the turbulent atmosphere. This results into geometric distortions and some blur effect in the observed frames. Despite the existence of several turbulence mitigation algorithms in the literature, no common dataset exists to objectively evaluate their efficiency. In this paper, we describe a new dataset called

Chengkai Huang, Shoujin Wang, Xianzhi Wang, Lina Yao

Sequential recommender systems (SRSs) aim to predict the subsequent items which may interest users via comprehensively modeling users' complex preference embedded in the sequence of user-item interactions. However, most of existing SRSs often model users' single low-level preference based on item ID information while ignoring the high-level preference reveal

Ivan Nasonov, Gaiane Panina

It is conjectured since long that each smooth convex body $\mathbf{P}\subset \mathbb{R}^n$ has a point in its interior which belongs to at least $2n$ normals from different points on the boundary of $\mathbf{P}$. The conjecture is proven for $n=2,3,4$. We treat the same problem for convex polytopes in $\mathbb{R}^3$ and prove that each generic polytope has a

Xinyue Zhang, Sihui Pei, Ni Yao, Shuhao Wang

Polarization-entangled photon pairs are essential sources for photonic quantum information processing. However, generating entangled photon pairs with large detuning via spontaneous parametric down-conversion (SPDC) often requires complex configurations to compensate for phase matching. Here, we propose a simple and efficient scheme to generate polarization-

Yiqin Lv, Qi Wang, Dong Liang, Zheng Xie

Meta learning is a promising paradigm in the era of large models and task distributional robustness has become an indispensable consideration in real-world scenarios. Recent advances have examined the effectiveness of tail task risk minimization in fast adaptation robustness improvement \citep{wang2023simple}. This work contributes to more theoretical invest

Juntao Xu, Tianxiang Zhan, Yong Deng

Determining the reliability of evidence sources is a crucial topic in Dempster-Shafer theory (DST). Previous approaches have addressed high conflicts between evidence sources using discounting methods, but these methods may not ensure the high efficiency of classification models. In this paper, we consider the combination of DS theory and Intuitionistic Fuzz

Daria-Ioana Visa, Tiberiu Harko, Shahab Shahidi

We consider a mimetic type extension of the Weyl geometric gravity theory, by assuming that the metric of the space-time manifold can be parameterized in terms of a scalar field, called the mimetic field. The action of the model is obtained by starting from a conformally invariant gravitational action, constructed, in Weyl geometry, from the square of the We

Tong Liu

The detection of suspended single particles (SSPs) in water is a crucial element for monitoring water ecosystems. Although there are a variety of sensory methods, it is still an unrealized goal to combine multi-wavelength polarized light scattering and fluorescence excitation-emission matrix(EEM) to characterize and classify SSP in water,which can deeply cha

Roldán A. Cala, José F. Gómez, Luis F. Miranda, Hiroshi Imai

Maser emission of SiO, H$_2$O and, OH is widespread in Asymptotic Giant Branch (AGB) stars with oxygen(O)-rich envelopes. This emission quickly disappear during the post-AGB phase and is extremely rare in planetary nebulae (PN). So far, only eight PNe have been confirmed to show OH and/or H$_2$O maser emission, and none has ever been found to show SiO maser

Omar Erak, Omar Alhussein, Wen Tong

Task-oriented semantic communication systems have emerged as a promising approach to achieving efficient and intelligent data transmission in next-generation networks, where only information relevant to a specific task is communicated. This is particularly important in 6G-enabled Internet of Things (6G-IoT) scenarios, where bandwidth constraints, latency req

Stasis Chuchurka, Milaim Kas, Andrei Benediktovitch, Nina Rohringer

In this work, we extend the x-ray constrained wavefunction fitting approach, a key method in quantum crystallography for charge density reconstruction, to incorporate experimental observables beyond x-ray diffraction. Unlike traditional quantum crystallography methods, which are typically limited to molecules in their ground states, our approach integrates e

Albert Nössig, Tobias Hell, Georg Moser

In this paper, we present an innovative iterative approach to rule learning specifically designed for (but not limited to) text-based data. Our method focuses on progressively expanding the vocabulary utilized in each iteration resulting in a significant reduction of memory consumption. Moreover, we introduce a Value of Confidence as an indicator of the reli

Xujia Wang, Haiyan Zhao, Shuo Wang, Hanqing Wang

Parameter-Efficient Fine-Tuning (PEFT) methods like LoRA have significantly improved the adaptation of LLMs to downstream tasks in a resource-efficient manner. However, in multi-task scenarios, challenges such as training imbalance and the seesaw effect frequently emerge. Mixture-of-LoRA (MoLoRA), which combines LoRA with sparse Mixture-of-Experts, mitigates

Minghao Zou, Hayk Hakobyan, Rostom Mbarek, Bart Ripperda

We propose novel numerical schemes based on the Boris method in curved spacetime, incorporating both hadronic and radiative interactions for the first time. Once the proton has lost significant energy due to radiative and hadronic losses, and its gyroradius has decreased below typical scales on which the electromagnetic field varies, we apply a guiding cente

Xinyu Mu, Shulin Lyu

We study the Hankel determinant generated by the moments of the deformed Laguerre weight function $x^{\alpha}{\rm{e}}^{-x}\prod\limits_{k=1}^{N}(x+t_k)^{\lambda_k}$, where $x\in \left[0,+\infty \right)$, $\alpha,t_k >0, \lambda_k\in\mathbb{R}$ for $k=1,\cdots ,N$. By using the ladder operators for the associated monic orthogonal polynomials and three compati

Daizhan Cheng

Using projection between Euclidian spaces of different dimensions, the signal compression and decompression become straightforward. This encoding/decoding technique requires no preassigned measuring matrix as in compressed sensing. Moreover, in application there is no dimension or size restrictions. General formulas for encoding/decoding of any finite dimens

Li Zhang, Yongguan Ke, Chaohong Lee

Hilbert space fragmentation (HSF) is a mechanism for generating quantum many-body scar (QMBS), which provides a route to weakly break ergodicity. The zero-energy QMBSs widely exist across various systems due to the intertwining of chiral symmetry and spatial inversion symmetry. In this work, we study the phenomenology of the zero-energy QMBS under the interp

Jerome Gilles, Stanley Osher

In this paper, we design a very simple algorithm based on Split Bregman iterations to numerically solve the cartoon + textures decomposition model of Meyer. This results in a significant gain in speed compared to Chambolle's nonlinear projectors.

Yucong Huang, Jiesong Lian, Mingzhi Wang, Chengdong Ma

Policy Space Response Oracle (PSRO) with policy population construction has been demonstrated as an effective method for approximating Nash Equilibrium (NE) in zero-sum games. Existing studies have attempted to improve diversity in policy space, primarily by incorporating diversity regularization into the Best Response (BR). However, these methods cause the

Arash Marioriyad, Parham Rezaei, Mahdieh Soleymani Baghshah, Mohammad Hossein Rohban

Text-to-image (T2I) generative models, such as Stable Diffusion and DALL-E, have shown remarkable proficiency in producing high-quality, realistic, and natural images from textual descriptions. However, these models sometimes fail to accurately capture all the details specified in the input prompts, particularly concerning entities, attributes, and spatial r

Luca Jiang-Tao Yu, Chenshu Wu

Target detection is a fundamental task in radar sensing, serving as the precursor to any further processing for various applications. Numerous detection algorithms have been proposed. Classical methods based on signal processing, e.g., the most widely used CFAR, are challenging to tune and sensitive to environmental conditions. Deep learning-based methods ca

Sashikanta Mohapatra, Sanjay Moudgalya, Ajit C. Balram

Exact solutions for excited states in non-integrable quantum Hamiltonians have revealed novel dynamical phenomena that can occur in quantum many-body systems. This work proposes a method to analytically construct a specific set of volume-law-entangled zero-energy exact excited eigenstates in a large class of spin Hamiltonians. In particular, we show that all

Juntao Xu, Tianxiang Zhan, Yong Deng

In pattern recognition, handling uncertainty is a critical challenge that significantly affects decision-making and classification accuracy. Dempster-Shafer Theory (DST) is an effective reasoning framework for addressing uncertainty, and the Random Permutation Set (RPS) extends DST by additionally considering the internal order of elements, forming a more or

Zheng Yu, Yaohua Wang, Siying Cui, Aixi Zhang

Facial parts swapping aims to selectively transfer regions of interest from the source image onto the target image while maintaining the rest of the target image unchanged. Most studies on face swapping designed specifically for full-face swapping, are either unable or significantly limited when it comes to swapping individual facial parts, which hinders fin

Hao Li, Xiaogeng Liu

Prompt injection attacks pose a critical threat to large language models (LLMs), enabling goal hijacking and data leakage. Prompt guard models, though effective in defense, suffer from over-defense -- falsely flagging benign inputs as malicious due to trigger word bias. To address this issue, we introduce NotInject, an evaluation dataset that systematically