December 2023 arXiv papers — page 28

Asghar Ullah, Ali Pedram, M. Tahir Naseem, Özgür E. Müstecaplıoğlu

We present a quantum thermometry method utilizing an optomechanical system composed of an optical field coupled to a mechanical resonator for measuring the unknown temperature of a thermal bath. To achieve this, we connect a thermal bath to the mechanical resonator and perform measurements on the optical field, serving as a probe thermometer. Using the open

Hao Wang, Huabing Zhou, Yanduo Zhang, Tao Lu

Scene text spotting is essential in various computer vision applications, enabling extracting and interpreting textual information from images. However, existing methods often neglect the spatial semantics of word images, leading to suboptimal detection recall rates for long and short words within long-tailed word length distributions that exist prominently

Songming Zhang, Yuxiao Luo, Ziyu Lyu, Xiaofeng Chen

Knowledge Distillation (KD) transfers knowledge from large models to small models and has recently achieved remarkable success. However, the reliability of existing KD methods in real-world applications, especially under distribution shift, remains underexplored. Distribution shift refers to the data distribution drifts between the training and testing phase

Huyuan Chen, Daniel Hauer, Tobias Weth

The logarithmic Laplacian on the (whole) N-dimensional Euclidean space is defined as the first variation of the fractional Laplacian of order 2s at s=0 or, alternatively, as a singular Fourier integral operator with logarithmic symbol. While this operator has attracted fastly growing attention in recent years due to its relevance in the study of order-depend

L. Attias, K. Michaeli, M. Khodas

We investigate the planar Hall effect (PHE) in two-dimensional (2D) superconductors with spin-orbit interactions, where transport anisotropy is induced by an in-plane magnetic field. While PHE typically arises from the breaking of basal mirror symmetry, when the field exclusively couples to spin degrees of freedom, it remains negligible in non-interacting sy

Ya Li, Wanru Wang, Qizhou Wu, Youxing Chen

The wave-packet-tunable photons [Optics Express 30, 2792-2802 (2022)] generated by spontaneous Raman scattering (SRS) based on atomic ensemble lay a foundation for the hybrid quantum network to successfully connect quantum nodes with different bandwidths, but the coherence time of wave-packet photons becomes the key factor limiting the distance of entangleme

Soumick Chatterjee, Franziska Gaidzik, Alessandro Sciarra, Hendrik Mattern

In the domain of medical imaging, many supervised learning based methods for segmentation face several challenges such as high variability in annotations from multiple experts, paucity of labelled data and class imbalanced datasets. These issues may result in segmentations that lack the requisite precision for clinical analysis and can be misleadingly overco

Wei Liu, Weihao Zeng, Keqing He, Yong Jiang

Instruction tuning is a standard technique employed to align large language models to end tasks and user preferences after the initial pretraining phase. Recent research indicates the critical role of data engineering in instruction tuning -- when appropriately selected, only limited data is necessary to achieve superior performance. However, we still lack a

Yuteng Liu, Haowen Li, Haishan Zou, Jing Lu

Active headrests can reduce low-frequency noise around ears based on active noise control (ANC) system. Both the control system using fixed control filters and the remote microphone-based adaptive control system provide good noise reduction performance when the head is in the original position. However, their performance degrades significantly when the head

Itshak Lapidot

In this paper we presented a stochastic version mean-shift clustering algorithm. In the stochastic version the data points "climb" to the modes of the distribution collectively, while in the deterministic mean-shift, each datum "climbs" individually, while all other data points remains in their original coordinates. Stochastic version of the mean-shift clust

Yanying Liang, Haozhen Situ, Zhu-Jun Zheng

We study the polygamy property for tripartite and multipartite quantum systems. In tripartite system, we build a solution set for polygamy in tripartite system and find a lower bound of the set, which can be a sufficient and necessary condition for any quantum entanglement of assistance $Q$ to be polygamous. In multipartite system, we firstly provide general

Bartu Atabek, Efecan Yilmaz, Cengiz Acarturk, Murat Perit Cakir

Objective: This paper proposes a novel type of stimulus in the shape of sinusoidal gratings displayed with an imperceptibly high-frequency motion. The stimulus has been designed for use in BCI (Brain Computer Interface) applications that employ visually evoked potentials (VEPs) in an effort to mitigate discomfort associated with VEPs. The stimuli set include

Peng Ye, Yongqi Huang, Chongjun Tu, Minglei Li

Fine-tuning pre-trained foundation models has gained significant popularity in various research fields. Existing methods for fine-tuning can be roughly divided into two categories, namely Parameter-Efficient Fine-Tuning and High-Performance Fine-Tuning. The former aims at improving efficiency, while the latter focuses on enhancing performance. Beyond these m

Luis Angel González-Serrano, Egor A. Maximenko

We consider polynomials of the form $\operatorname{s}_\lambda(y_1^{[\varkappa_1]},\ldots,y_n^{[\varkappa_n]})$, where $\lambda$ is an integer partition, $\operatorname{s}_\lambda$ is the Schur polynomial associated to $\lambda$, and $y_j^{[\varkappa_j]}$ denotes $y_j$ repeated $\varkappa_j$ times. We represent $\operatorname{s}_\lambda(y_1^{[\varkappa_1]},\l

Jingwei Song, Ray Zhang, Qiuchen Zhu, Jianyu Lin

Purpose: Common dense stereo Simultaneous Localization and Mapping (SLAM) approaches in Minimally Invasive Surgery (MIS) require high-end parallel computational resources for real-time implementation. Yet, it is not always feasible since the computational resources should be allocated to other tasks like segmentation, detection, and tracking. To solve the pr

Srijan Chattopadhyay, Swapnaneel Bhattacharyya, Sevantee Basu

In modern scientific studies, it is often imperative to determine whether a set of phenotypes is affected by a single factor. If such an influence is identified, it becomes essential to discern whether this effect is contingent upon categories such as sex or age group, and importantly, to understand whether this dependence is rooted in purely non-environment

P. J. Heslop, A. E. Lipstein, M. Santagata

Correlators of a certain one-dimensional superconformal field theory dual to hypermultiplets in AdS$_2\times$S$^2$ exhibit a hidden four-dimensional conformal symmetry which allows one to repackage all tree-level 4-point correlators into a single four-dimensional object corresponding to a contact diagram arising from a massless $\phi^4$ theory in AdS$_2\time

Yalçın Can Kılıç

In this paper, we introduce a new series of Rogers-Ramanujan-Gordon partitions when k = 3. The combinatorial interpretation of the series is given by base partition, forward moves and backward moves. We conclude the paper with future research questions related to the generalization of this approach.

Yingtai Li, Xueming Fu, Han Li, Shang Zhao

Sparse-view computed tomography (CT) reduces radiation exposure by acquiring fewer projections, making it a valuable tool in clinical scenarios where low-dose radiation is essential. However, this often results in increased noise and artifacts due to limited data. In this paper we propose a novel 3D Gaussian representation (3DGR) based method for sparse-view

Haruya Mizutani

We prove a uniform weighted resolvent estimate for the massless Klein-Gordon operator on a curved spacetime which is sufficiently close to the Minkowski spacetime. This particularly implies the existence and H\"{o}lder continuity of the limiting resolvents at all energies, as well as the absolute continuity, of the massless Klein-Gordon operator. The proof i

Jiawei Wang, Jian Zhao, Zhengtao Cao, Ruili Feng

Multi-agent reinforcement learning shines as the pinnacle of multi-agent systems, conquering intricate real-world challenges, fostering collaboration and coordination among agents, and unleashing the potential for intelligent decision-making across domains. However, training a multi-agent reinforcement learning network is a formidable endeavor, demanding sub

Junichi Haruna, Masatoshi Yamada

Gradient Flow Exact Renormalization Group (GF-ERG) is a framework to define the renormalization group flow of Wilsonian effective action utilizing coarse-graining along the diffusion equations. We apply it for Scalar Quantum Electrodynamics and derive flow equations for the Wilsonian effective action with the perturbative expansion in the gauge coupling. We

Abdullah Guvendi, Omar Mustafa

We study the relativistic dynamics of fermion-antifermion pairs in the Bonnor-Melvin magnetic (BMM) spacetime in non-zero cosmology. We focus on the $(1+2)$-dimensional cylindrically symmetric BMM-spacetime background. Within the context of such a magnetized universe, we rigorously investigate the fully-covariant two-body Dirac equation. We derive the corres

Wei-Jiang Zou, Jun-Xu Lu, Peng-Wei Zhao, Li-Sheng Geng

Nuclear saturation is a crucial feature in nuclear physics that plays a fundamental role in understanding various nuclear phenomena, ranging from properties of finite nuclei to those of neutron stars. However, a proper description of nuclear saturation is highly nontrivial in modern nonrelativistic~\textit{ab initio}~studies because of the elusive three-body

Taras Radul

We consider a wide family of fuzzy integrals on arbitrary compactum which generalize well know Sugeno integral. Such generalization is obtained using some non-discrete analogs of pseudo-grouping functions.

Peng Ye, Chenyu Huang, Mingzhu Shen, Tao Chen

This work targets to merge various Vision Transformers (ViTs) trained on different tasks (i.e., datasets with different object categories) or domains (i.e., datasets with the same categories but different environments) into one unified model, yielding still good performance on each task or domain. Previous model merging works focus on either CNNs or NLP mode

Wentao Tian, Zheng Wang, Yuqian Fu, Jingjing Chen

A comprehensive understanding of videos is inseparable from describing the action with its contextual action-object interactions. However, many current video understanding tasks prioritize general action classification and overlook the actors and relationships that shape the nature of the action, resulting in a superficial understanding of the action. Motiva

Jing Wang, Da-jun Zhang, Ken-ichi Maruno

In this paper, we show that all the bilinear Adler-Bobenko-Suris (ABS) equations (except Q2 and Q4) can be obtained from symmetric discrete AKP system by taking proper reductions and continuum limits. Among the bilinear ABS equations, a simpler bilinear form of the ABS H2 equation is given. In addition, an 8-point 3-dimensional lattice equation and an 8-poin

Xiao Fan, Peiran Wu, Minghua Xia

Unmanned aerial vehicle (UAV) communications have been widely accepted as promising technologies to support air-to-ground communications in the forthcoming sixth-generation (6G) wireless networks. This paper proposes a novel air-to-ground communication model consisting of aerial base stations served by UAVs and terrestrial user equipments (UEs) by integratin

Xingzhou Lou, Junge Zhang, Timothy J. Norman, Kaiqi Huang

Multi-Agent Policy Gradient (MAPG) has made significant progress in recent years. However, centralized critics in state-of-the-art MAPG methods still face the centralized-decentralized mismatch (CDM) issue, which means sub-optimal actions by some agents will affect other agent's policy learning. While using individual critics for policy updates can avoid thi

Xinliang An, Taoran He

This paper investigates the global dynamics of the apparent horizon. We present an approach to establish its existence and its long-term behaviors. Our apparent horizon is constructed by solving the marginally outer trapped surface (MOTS) along each incoming null hypersurface. Based on the nonlinear hyperbolic estimates established in [24] by Klainerman-Szef

Yongkang Wang, Xuan Liu, Feng Huang, Zhankun Xiong

Therapeutic peptides represent a unique class of pharmaceutical agents crucial for the treatment of human diseases. Recently, deep generative models have exhibited remarkable potential for generating therapeutic peptides, but they only utilize sequence or structure information alone, which hinders the performance in generation. In this study, we propose a Mu

Boning Huang, Yongguan Ke, Honghua Zhong, Yuri S. Kivshar

Bound states in the continuum (BICs) are localized modes residing in the radiation continuum. They were first predicted for single-particle states, and became a general feature of many wave systems. In many-body quantum physics, it is still unclear what would be a close analog of BICs, and whether interparticle interaction may induce BICs. Here, we predict a

Yifan Yin, Bingjie Zhang, Ke Wu

In this work, simulation-based equations to calculate propagation constant in uniform or periodic structures (SES) are deduced and verified through simulations in various types of structures. The modeling of those structures are essentially based on field distributions from a driven-mode solver, and the field distributions are used as the input parameters of

Zhihao Chen, Bin Hu, Chuang Niu, Tao Chen

Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted an increasing interest as a natural language interface across many domains. Recently, large vision-language models (VLMs) like BLIP-2 and GPT-4 have been intensively investigated, which learn rich vision-language correlation from image-text

Akifumi Chitose, Masahiro Ibe, Yuhei Nakayama, Satoshi Shirai

Metastable cosmic strings appear in models of new physics with a two-step symmetry breaking $G\to H\to 1$, where $\pi_1(H)\neq 0$ and $\pi_1(G)=0$. They decay via the monopole-antimonopole pair creation inside. Conventionally, the breaking rate has been estimated by an infinitely thin string approximation, which requires a large hierarchy between the symmetr

Yucong Luo, Mingyue Cheng, Hao Zhang, Junyu Lu

Generating user-friendly explanations regarding why an item is recommended has become increasingly common, largely due to advances in language generation technology, which can enhance user trust and facilitate more informed decision-making when using online services. However, existing explainable recommendation systems focus on using small-size language mode

Nikolay A. Tyurin

We study lagrangian submanifolds of algebraic variety Gr(1, n) equipped with the Kahler form given by the Plucker embedding. We use the correspondence between lagrangian submanifolds of Gr(1, n) and lagrangian submanifolds of variety M_{n-k}, given by symplectic reduction Gr(1, n)//T^k for some specially chosen moment maps, which generate T^k action on Gr(1,

Jinliang Han, Xiongkuo Min, Yixuan Gao, Jun Jia

The quality of frames is significant for both research and application of video frame interpolation (VFI). In recent VFI studies, the methods of full-reference image quality assessment have generally been used to evaluate the quality of VFI frames. However, high frame rate reference videos, necessities for the full-reference methods, are difficult to obtain

Wenxuan Guo, Yanyan Xu, Yaohui Jin

Facility location problems on graphs are ubiquitous in real world and hold significant importance, yet their resolution is often impeded by NP-hardness. Recently, machine learning methods have been proposed to tackle such classical problems, but they are limited to the myopic constructive pattern and only consider the problems in Euclidean space. To overcome

Aruto Hosaka, Koichi Yanagisawa, Shota Koshikawa, Isamu Kudo

We apply preconditioning, which is widely used in classical solvers for linear systems $A\textbf{x}=\textbf{b}$, to the variational quantum linear solver. By utilizing incomplete LU factorization as a preconditioner for linear equations formed by $128\times128$ random sparse matrices, we numerically demonstrate a notable reduction in the required ansatz dept

Xinyu Cheng

Phase field models are gradient flows with their energy naturally dissipating in time. In order to preserve this property, many numerical schemes have been well-studied. In this paper we consider a well-known method, namely the exponential integrator method (EI). In the literature a few works studied several EI schemes for various phase field models and prov

Sota Arakawa

Understanding the geodesic properties of fractal aggregates is essential, as their thermal and mechanical properties are characterized by their geodesics. In this study, we investigate the root mean square (RMS) of the geodesic between two constituent particles within fractal aggregates prepared by ballistic cluster-cluster aggregation (BCCA), diffusion-limi

Yan Gui, Cheng Wang, Jingrun Chen

Magnetization dynamics in ferromagnetic materials is modeled by the Landau-Lifshitz (LL) equation, a nonlinear system of partial differential equations. Among the numerical approaches, semi-implicit schemes are widely used in the micromagnetics simulation, due to a nice compromise between accuracy and efficiency. At each time step, only a linear system needs

Jing Zhu, Gaojie Chen, Pengyu Gao, Pei Xiao

In this paper, we propose a transmission mechanism for fluid antennas (FAs) enabled multiple-input multiple-output (MIMO) communication systems based on index modulation (IM), named FA-IM, which incorporates the principle of IM into FAs-assisted MIMO system to improve the spectral efficiency (SE) without increasing the hardware complexity. In FA-IM, the info

F. L. Freitas

A generalization of associated Legendre functions is proposed and used to describe the scattering states of the Rosen-Morse potential. The functions are then given explicit formulas in terms of the hypergeometric function, their asymptotic behavior is examined and shown to match the requirements for states in the regions of total and partial reflection. Elem

Gilles Dowek, Murdoch J. Gabbay, Dominic Mulligan

Nominal terms extend first-order terms with binding. They lack some properties of first- and higher-order terms: Terms must be reasoned about in a context of 'freshness assumptions'; it is not always possible to 'choose a fresh variable symbol' for a nominal term; it is not always possible to 'alpha-convert a bound variable symbol' or to 'quotient by alpha-e

Zhong Shen, Hai Jiang, Rongfei Fan, Hongxing Guo

Device discovery has a great impact on the performance of Bluetooth low energy (BLE). The performance of device discovery is highly related to the advertising mode. BLE has two advertising modes: pseudo-random delay advertising (RDA) and periodic deterministic advertising (PDA). Generally, PDA has low discovery latency but is susceptible to persistent collis

Gilles Dowek, Murdoch J. Gabbay

Permissive-Nominal Logic (PNL) extends first-order predicate logic with term-formers that can bind names in their arguments. It takes a semantics in (permissive-)nominal sets. In PNL, the forall-quantifier or lambda-binder are just term-formers satisfying axioms, and their denotation is functions on nominal atoms-abstraction. Then we have higher-order logic

Son Tu, Jianlu Zhang

In this paper, we study the regularity of the ergodic constants for the viscous Hamilton--Jacobi equations. We also estimate the convergent rate of the ergodic constant in the vanishing viscosity process.

Ahmadfikri Talek, Narakorn Kaewkhao, Watcharakorn Srikom, Farruh Atamurotov

This study investigates the dynamics of a non-minimally coupled (NMC) scalar field in modified gravity, employing the Noether gauge symmetry (NGS) approach to systematically derive exact cosmological solutions. By formulating a point-like Lagrangian and analyzing the corresponding Euler-Lagrange equations, conserved quantities were identified, reducing the c

Y. Yuan

For dynamical systems with infinite topological entropy, the classical entropy fails to quantify their complexity effectively, while the metric mean dimension provides a natural extension in this context. In this paper, we study the complexity of saturated sets from the perspective of Bowen upper and lower metric mean dimensions. We show that if a dynamical

Javad Eshtiyagh, Baotong Zhang, Yujing Sun, Linhui Wu

Gentrification--the transformation of a low-income urban area caused by the influx of affluent residents--has many revitalizing benefits. However, it also poses extremely concerning challenges to low-income residents. To help policymakers take targeted and early action in protecting low-income residents, researchers have recently proposed several machine lea

Rui Zhao, Liang Zhang, Biao Fu, Cong Hu

Sign language translation (SLT) aims to convert continuous sign language videos into textual sentences. As a typical multi-modal task, there exists an inherent modality gap between sign language videos and spoken language text, which makes the cross-modal alignment between visual and textual modalities crucial. However, previous studies tend to rely on an in

Ruicong Liu, Feng Lu

Gaze estimation has become a subject of growing interest in recent research. Most of the current methods rely on single-view facial images as input. Yet, it is hard for these approaches to handle large head angles, leading to potential inaccuracies in the estimation. To address this issue, adding a second-view camera can help better capture eye appearance. H

Jiaxin Bai, Yicheng Wang, Tianshi Zheng, Yue Guo

Abductive reasoning is the process of making educated guesses to provide explanations for observations. Although many applications require the use of knowledge for explanations, the utilization of abductive reasoning in conjunction with structured knowledge, such as a knowledge graph, remains largely unexplored. To fill this gap, this paper introduces the ta

Kota Saito, Yuta Suzuki, Wataru Takeda, Yuuya Yoshida

After the work of Bordell\`{e}s, Dai, Heyman, Pan and Shparlinki (2018) and Heyman (2019), several authors studied the averages of arithmetic functions over the sequence $[x/n]$ and the integers of the form $[x/n]$. In this paper, we give three remarks on this topic. Firstly, we improve the result of Wu and Yu (2022) on the distribution of the integers of th

Robert Söldner, Detlef Plump

In this paper, we utilize Isabelle/HOL to develop a formal framework for the basic theory of double-pushout graph transformation. Our work includes defining essential concepts like graphs, morphisms, pushouts, and pullbacks, and demonstrating their properties. We establish the uniqueness of derivations, drawing upon Rosens 1975 research, and verify the Churc

Maya Gokhale, Ganesh Gopalakrishnan, Jackson Mayo, Santosh Nagarakatte

This report is a digest of the DOE/NSF Workshop on Correctness in Scientific Computing (CSC'23) held on June 17, 2023, as part of the Federated Computing Research Conference (FCRC) 2023. CSC was conceived by DOE and NSF to address the growing concerns about correctness among those who employ computational methods to perform large-scale scientific simulations

Hao Li, Hanqi Tao, Wentao Huang, Hongcai Zhang

Despite the success of electric vehicles on land, electrification of maritime ships is challenged by the dilemma of range anxiety and cargo-carrying capacity. The longer range requires larger batteries, which inevitably eat up the precious cargo space and weight. This paper breaks new ground by proposing a coordinated planning model for offshore charging sta

Masako Kishida

This paper proposes control approaches for discrete-time linear systems subject to stochastic disturbances. It employs Kalman filter to estimate the mean and covariance of the state propagation, and the worst-case conditional value-at-risk (CVaR) to quantify the tail risk using the estimated mean and covariance. The quantified risk is then integrated into a

Yu Cheng, Jie Sheng, Tsutomu T. Yanagida

It is known that two heavy Majorana right-handed neutrinos are sufficient to generate the baryon asymmetry in the present universe. Thus, it is interesting to identify the third right-handed neutrino $N$ with the dark matter. We impose a new discrete symmetry $Z_2$ on this dark matter neutrino to stabilize it. However, the $U(1)_{B-L}$ gauge boson $A'$ coupl

Feng Zhou, Jianqin Yin, Peiyang Li

The "lifting from 2D pose" method has been the dominant approach to 3D Human Pose Estimation (3DHPE) due to the powerful visual analysis ability of 2D pose estimators. Widely known, there exists a depth ambiguity problem when estimating solely from 2D pose, where one 2D pose can be mapped to multiple 3D poses. Intuitively, the rich semantic and texture infor

James W. Webber, Sean Holman, Eric Todd Quinto

We present a novel analysis of a Radon transform, $R$, which maps an $L^2$ function of compact support to its integrals over smooth surfaces of revolution with centers on an embedded hypersurface in $\mathbb{R}^n$. Using microlocal analysis, we derive necessary and sufficient conditions relating to $R$ for the Bolker condition to hold, which has implications

Hongjun Wu, Xiao Xu, Zhi Jin, Fanle Meng

This paper presents an innovative feature signal transmission approach incorpo-rating block-based haptic data reduction to address time-delayed teleoperation. Numerous data reduction techniques rely on perceptual deadband (DB). In the preceding block-based approaches, the whole block within the DB is discarded. However, disregarding all signals within the DB

Ekansh Agrawal

Social media has transformed the advertising landscape, becoming an essential tool for reaching and connecting with consumers. Its sharing and engagement features amplify brand exposure, while its cost-effective options provide businesses with flexible advertising solutions. TikTok is a more recent social media platform that has gained popularity for adverti

Ahsan Baidar Bakht, Zikai Jia, Muhayy ud Din, Waseem Akram

The underwater environment presents unique challenges, including color distortions, reduced contrast, and blurriness, hindering accurate analysis. In this work, we introduce MuLA-GAN, a novel approach that leverages the synergistic power of Generative Adversarial Networks (GANs) and Multi-Level Attention mechanisms for comprehensive underwater image enhancem

PandaX Collaboration, Xiyu Yan, Zhaokan Cheng, Abdusalam Abdukerim

$^{134}$Xe is a candidate isotope for neutrinoless double beta decay~($0\nu\beta\beta$) search. In addition, the two-neutrino case ($2\nu\beta\beta$) allowed by the Standard Model of particle physics has not yet been observed. Utilizing the 10.4% of $^{134}$Xe in the natural xenon in the PandaX-4T detector and its first 94.9-day exposure, we have established

Anton Glushchenko, Konstantin Lastochkin

Existing online continuous-time parameter estimation laws provide exact (asymptotic/exponential or finite/fixed time) identification of dynamical linear/nonlinear systems parameters only if the external perturbations are equaled to zero or independent with the regressor of the system. However, in real systems the disturbances are almost always non-vanishing

Yanjin Zhu, Xin Zheng, Jianke Zhu

Despite having achieved real-time performance in mesh construction, most of the current LiDAR odometry and meshing methods may struggle to deal with complex scenes due to relying on explicit meshing schemes. They are usually sensitive to noise. To overcome these limitations, we propose a real-time mesh-based LiDAR odometry and mapping approach for large-scal

H. Hadi

The theoretical implications of a traversable wormhole between entangled black holes are significant in terms of non-locality and superluminal signaling. By utilizing the entangled states of two maximally entangled black holes, it becomes possible to construct a wormhole. In this context, the traversable wormhole can be achieved by exciting the vacuum state

Zehan Wu, Dehua Wen

The equation of state (EOS) of dense nuclear matter is a key factor to determine the internal structure and properties of neutron stars. However, the EOS of high-density nuclear matter has great uncertainty mainly because the terrestrial nuclear experiments cannot reproduce matter as dense as that in the inner core of a neutron star. Fortunately, continuous

Bingzhi Liu, Yin Cao, Haohe Liu, Yi Zhou

Diffusion models have demonstrated promising results in text-to-audio generation tasks. However, their practical usability is hindered by slow sampling speeds, limiting their applicability in high-throughput scenarios. To address this challenge, progressive distillation methods have been effective in producing more compact and efficient models. Nevertheless,

Gobinda Das Adhikary, John Daniels, Luke Giles, Rajeev Ranjan

Recently several reports showing ultra-high electrostrain (> 1 %) have appeared in Pb-free piezoceramics. However, there is lack of clarity on the nature of the ultrahigh strain. Here, we demonsrate that the ultrahigh strain is a consequence of bending of the disc. We show that the propensity for bending arises from the difference in the response magnitude o

Yi Zou, Mengying Shi, Zhongjie Chen, Zhu Deng

ESGReveal is an innovative method proposed for efficiently extracting and analyzing Environmental, Social, and Governance (ESG) data from corporate reports, catering to the critical need for reliable ESG information retrieval. This approach utilizes Large Language Models (LLM) enhanced with Retrieval Augmented Generation (RAG) techniques. The ESGReveal syste

Shusaku Egami, Takanori Ugai, Masateru Oota, Kyoumoto Matsushita

Knowledge Graphs (KGs) such as Resource Description Framework (RDF) data represent relationships between various entities through the structure of triples (<subject, predicate, object>). Knowledge graph embedding (KGE) is crucial in machine learning applications, specifically in node classification and link prediction tasks. KGE remains a vital research topi

Shuhang Chen, Wenjing Xu, Yueyue Ning, Ke Yang

Magnetic anisotropy is essential for stabilizing two-dimensional (2D) magnetism, which has significant applications in spintronics and the advancement of fundamental physics. In this work, we examine the electronic structure and magnetic properties of triangular prismatic MSi$_2$N$_4$ (M = V, Cr) monolayers, using crystal field theory, spin-orbital state ana

G. A. Grigorian

The Wiener-Hopf integral equations of 1-st kind relates to the class of Wiener-Hopf equations of non normal type, to which the classical Wiener-Hopf method is not applicable, but is completely applicable the special factorization method. In this paper we use the special factorization method to obtain solvability conditions for Wiener-Hopf equations of 1-st k

Oren Danieli, Daniel Nevo, Itai Walk, Bar Weinstein

The validity of instrumental variable (IV) designs is typically tested using two types of falsification tests. We characterize these tests as conditional independence tests between negative control variables -- proxies for unobserved variables posing a threat to the identification -- and the IV or the outcome. We describe the conditions that variables must s

Zacharie Van Herstraeten, Saikat Guha, Nicolas J. Cerf

We consider a quantum bosonic channel that couples the input mode via a beam splitter or two-mode squeezer to an environmental mode that is prepared in an arbitrary state. We investigate the classical capacity of this channel, which we call a non-Gaussian attenuator or amplifier channel. If the environment state is thermal, we of course recover a Gaussian ph

Qi Mao, Chongyu Wang, Meng Wang, Shiqi Wang

The accelerated proliferation of visual content and the rapid development of machine vision technologies bring significant challenges in delivering visual data on a gigantic scale, which shall be effectively represented to satisfy both human and machine requirements. In this work, we investigate how hierarchical representations derived from the advanced gene

Toshihisa Kubo, Bent Ørsted

We classify and construct $SL(n,\mathbb{R})$-intertwining differential operators $\mathcal{D}$ from a line bundle to a vector bundle over the real projective space $\mathbb{RP}^{n-1}$ by the F-method. This generalizes a classical result of Bol for $SL(2,\mathbb{R})$. Further, we classify the $K$-type formulas for the kernel $\text{Ker}(\mathcal{D})$ and imag

Kaipu Wang, Hao Wu, Bo Zhang, Xuri Yao

Quantum electronics operating in the microwave domain are burgeoning and becoming essential building blocks of quantum computers, sensors and communication devices. However, the field of microwave quantum electronics has long been dominated by the need for cryogenic conditions to maintain the delicate quantum characteristics. Here we report on a solid-state

Ziyan Chen, Jing Cheng

The Coded Aperture Snapshot Spectral Compressive Imaging (CASSI) system modulates three-dimensional hyperspectral images into two-dimensional compressed images in a single exposure. Subsequently, three-dimensional hyperspectral images (HSI) can be reconstructed from the two-dimensional compressed measurements using reconstruction algorithms. Among these meth

Masahiro Kojima, Hirotaka Mano, Kana Yamada, Keisuke Hanada

Regulatory authorities guide the use of permutation tests or randomization tests so as not to increase the type-I error rate when applying covariate-adaptive randomization in randomized clinical trials. For non-inferiority and equivalence trials, this paper derives adjusted confidence intervals using permutation and randomization methods, thus controlling th

Eduardo Ibarra-García-Padilla, Stephanie Striegel, Richard T. Scalettar, Ehsan Khatami

The development of quantum gas microscopy for two-dimensional optical lattices has provided an unparalleled tool to study the Fermi-Hubbard model (FHM) with ultracold atoms. Spin-resolved projective measurements, or snapshots, have played a significant role in quantifying correlation functions which uncover underlying physical phenomena such as antiferromagn

Huali Ren, Anli Yan, Xiaojun Ren, Pei-Gen Ye

Deep neural networks (DNNs) are extensively employed in a wide range of application scenarios. Generally, training a commercially viable neural network requires significant amounts of data and computing resources, and it is easy for unauthorized users to use the networks illegally. Therefore, network ownership verification has become one of the most crucial

Aditya Ravuri, Erica Cooper, Junichi Yamagishi

Predicting audio quality in voice synthesis and conversion systems is a critical yet challenging task, especially when traditional methods like Mean Opinion Scores (MOS) are cumbersome to collect at scale. This paper addresses the gap in efficient audio quality prediction, especially in low-resource settings where extensive MOS data from large-scale listenin

Kurea Nakagawa, Minoru Kanega, Tomoyuki Yokouchi, Masahiro Sato

In two-dimensional (2D) spin systems, the augmentation of spin fluctuations gives rise to quasi-long-range order; however, how they manifest in spin transport remains unclear. Here we investigate the spin Seebeck effect (SSE) in a quasi-2D antiferromagnet, BaNi$_2$V$_2$O$_8$, which has been reported to exhibit the Berezinskii-Kosterlitz-Thouless (BKT) transi

Wentao Zou, Qi Li, Jidong Ge, Chuanyi Li

Pre-trained models (PTMs) have achieved great success in various Software Engineering (SE) downstream tasks following the ``pre-train then fine-tune'' paradigm. As fully fine-tuning all parameters of PTMs can be computationally expensive, a widely used solution is parameter-efficient fine-tuning (PEFT), which freezes PTMs while introducing extra parameters.

Yaru Liu, Chaoyu Quan, Dong Wang

This work delves into the exponential time differencing (ETD) schemes for the matrix-valued Allen-Cahn equation. In fact, the maximum bound principle (MBP) for the first- and second-order ETD schemes is presented in a prior publication [SIAM Review, 63(2), 2021], assuming a symmetric initial matrix field. Noteworthy is our novel contribution, demonstrating t

Pete Rigas

Expressions for scaling limits of random walks, such as those obtained in several areas of the Probability theory literature, are of great significance in characterizing long term, stationary behavior of random processes. Presumably, in the limit of extremely long periods of time random walks and other stochastic processes including percolation are expected

Yuxiang Yang, Yingqi Deng, Yufei Xu, Jing Zhang

Animal Pose Estimation and Tracking (APT) is a critical task in detecting and monitoring the keypoints of animals across a series of video frames, which is essential for understanding animal behavior. Past works relating to animals have primarily focused on either animal tracking or single-frame animal pose estimation only, neglecting the integration of both

Zhiwei Xu, Ziming Gan, Doudou Zhou, Shuting Shen

The effective analysis of high-dimensional Electronic Health Record (EHR) data, with substantial potential for healthcare research, presents notable methodological challenges. Employing predictive modeling guided by a knowledge graph (KG), which enables efficient feature selection, can enhance both statistical efficiency and interpretability. While various m

Yijia Weng, Kaichun Mo, Ruoxi Shi, Yanchao Yang

Some extremely low-dimensional yet crucial geometric eigen-lengths often determine the success of some geometric tasks. For example, the height of an object is important to measure to check if it can fit between the shelves of a cabinet, while the width of a couch is crucial when trying to move it through a doorway. Humans have materialized such crucial geom

Inkyu Park, Jaewoong Cho

Speech-driven 3D facial animation is challenging due to the scarcity of large-scale visual-audio datasets despite extensive research. Most prior works, typically focused on learning regression models on a small dataset using the method of least squares, encounter difficulties generating diverse lip movements from speech and require substantial effort in refi

Kui Wang, Zongdian Li, Tao Yu, Kei Sakaguchi

During the past decade, smart mobility and intelligent vehicles have attracted increasing attention, because they promise to create a highly efficient and safe transportation system in the future. Meanwhile, digital twin, as an emerging technology, will play an important role in automated driving and intelligent transportation systems. This technology is app

Manodip Routh, Sayan Ghosh, Jeroen van den Brink, Satoshi Nishimoto

Motivated by the largely unexplored domain of multi-polar ordered spin states in the Kitaev-Heisenberg (KH) systems we investigate the ground state dynamics of the spin-$\frac{1}{2}$ KH model, focusing on quadrupolar (QP) order in 2-leg ladder and two-dimensional honeycomb lattice geometries. Employing exact diagonalization and density-matrix renormalization

Yupei Zhang, Yuxin Li, Yifei Wang, Shuangshuang Wei

Learning-outcome prediction (LOP) is a long-standing and critical problem in educational routes. Many studies have contributed to developing effective models while often suffering from data shortage and low generalization to various institutions due to the privacy-protection issue. To this end, this study proposes a distributed grade prediction model, dubbed

Yi-Hsuan Lin

In this short note, we investigate an inverse source problem associated with a nonlocal elliptic equation $\left( -\nabla \cdot \sigma \nabla \right)^s u =F$ that is given in a bounded open set $\Omega\subset \mathbb{R}^n$, for $n\geq 3$ and $0<s<1$. We demonstrate both $\sigma$ and $F$ can be determined uniquely by using the exterior Dirichlet-to-Neumann (D