April 2023 arXiv papers — page 111

Tobias Baumgartner, Stefanie Klatt

The filming of sporting events projects and flattens the movement of athletes in the world onto a 2D broadcast image. The pixel locations of joints in these images can be detected with high validity. Recovering the actual 3D movement of the limbs (kinematics) of the athletes requires lifting these 2D pixel locations back into a third dimension, implying a ce

Robin Prinja, Eduardo Martini, Peter Jordan, Aaron Towne

This work aims to provide a more complete understanding of the resonance mechanisms that occur in turbulent jets at high subsonic Mach number, as shown by Towne et al. (J. Fluid Mech., vol. 825, 2017, pp. 1113-1152). Resonance was suggested by that study to exist between upstream- and downstream-travelling guided waves. Five possible resonance mechanisms wer

Christodoulos Skouroumounis, Ioannis Krikidis

The synergy of fluid-based reconfigurable antenna (FA) technology and full-duplex (FD) communications can be jointly beneficial, as FD can enhance the spectral efficiency of a point-to-point link, while the new degree of freedom offered by the FA technology can be exploited to handle the overall interference. Hence, in this paper, an analytical framework bas

Alexander Ivanov

This collection bundles the following memos dedicated to Gigabit Ethernet, type 1000BASE-T: [1] <this is the starting topic of the 'OVER' branch> "Data Coding Means and Event Coding Means Multiplexed Over the 1000BASE-T PMA Sublayer" (extends the IEEE 802.3ab protocol via the so called draft design approach, pp. 1-4); [2] "Spreading the Constellation Coverag

Guanghui Hu, Jiayi Zhang, Linlin Zhu

In this paper we study the variational method and integral equation methods for a conical diffraction problem for imperfectly conducting gratings modeled by the impedance boundary value problem of the Helmholtz equation in periodic structures. We justify the strong ellipticity of the sesquilinear form corresponding to the variational formulation and prove th

Takashi Tsuchiya, Bruno F. Lourenço, Masakazu Muramatsu, Takayuki Okuno

Let $({\bf P},{\bf D})$ be a primal-dual pair of SDPs with a nonzero finite duality gap. Under such circumstances, ${\bf P}$ and ${\bf D}$ are weakly feasible and if we perturb the problem data to recover strong feasibility, the (common) optimal value function $v$ as a function of the perturbation is not well-defined at zero (unperturbed data) since there ar

Dongmin Seo, Gihyeon Ahn, Gaurab Rimal, Seunghyun Khim

We performed polarized reflection and transmission measurements on the layered conducting oxide $\rm PdCoO_2$ thin films. For the ab-plane, an optical peak near $\Omega$ $\approx$ 750 cm$^{-1}$ drives the scattering rate $\gamma^{*}(\omega)$ and effective mass $m^{*}(\omega)$ of the Drude carrier to increase and decrease respectively for $\omega$ $\geqq$ $\O

Hardy Chan, Juan Luis Vázquez, David Gómez-Castro

This paper is devoted to describing a linear diffusion problem involving fractional-in-time derivatives and self-adjoint integro-differential space operators posed in bounded domains. One main concern of our paper is to deal with singular boundary data which are typical of fractional diffusion operators in space, and the other one is the consideration of the

Kensuke Akita, Michiru Niibo

Majorons are (pseudo-)Nambu-Goldstone bosons associated with lepton number symmetry breaking due to the Majorana mass term of neutrinos introduced in the seesaw mechanism. They are good dark matter candidates since their lifetime is suppressed by the lepton number breaking scale. We update constraints and discuss future prospects on majoron dark matter in th

Tao Chen, Chenhui Wang, Hongming Shan

Medical image segmentation is a challenging task with inherent ambiguity and high uncertainty, attributed to factors such as unclear tumor boundaries and multiple plausible annotations. The accuracy and diversity of segmentation masks are both crucial for providing valuable references to radiologists in clinical practice. While existing diffusion models have

Guoru Zhou, Zhongqiu Xu, Yizhe Fan, Zhe Zhang

High-resolution is a key trend in the development of synthetic aperture radar (SAR), which enables the capture of fine details and accurate representation of backscattering properties. However, traditional high-resolution SAR imaging algorithms face several challenges. Firstly, these algorithms tend to focus on local information, neglecting non-local informa

Wontae Kim, Mungon Nam

In a dilaton gravity model, we revisit the calculation of the temperature of an evaporating black hole that is initially formed by a shock wave, taking into account the quantum backreaction. Based on the holographic principle, along with the assumption of a boundary equation of motion, we show that the black hole energy is maintained for a while during the e

Chen Zhang, Ya-Hua Yuan, Jiao-Jiao Song, Jan Rusz

We investigated the electronic structure of the antiferromagnetic Kondo lattice CePd5Al2 using high-resolution angle-resolved photoemission spectroscopy. The experimentally determined band structure of the conduction electrons is predominated by the Pd 4d character. It contains multiple hole and electron Fermi pockets, in good agreement with density function

Rakpong Kaewpuang, Minrui Xu, Stephen John Turner, Dusit Niyato

In quantum networks, effective entanglement routing facilitates remote entanglement communication between quantum source and quantum destination nodes. Unlike routing in classical networks, entanglement routing in quantum networks must consider the quality of entanglement qubits (i.e., entanglement fidelity), presenting a challenge in ensuring entanglement f

Clara Loeh

A classical result of J\o rgensen and Thurston shows that the set of volumes of finite volume complete hyperbolic $3$-manifolds is a well-ordered subset of the real numbers of order type~$\omega^\omega$; moreover, each volume can only be attained by finitely many isometry types of hyperbolic $3$-manifolds. Fujiwara and Sela established a group-theoretic comp

Thomas Blum, Norman Christ, Masashi Hayakawa, Taku Izubuchi

The hadronic light-by-light scattering contribution to the muon anomalous magnetic moment, $(g-2$)/2, is computed in the infinite volume QED framework with lattice QCD. We report $a_\mu^\text{HLbL}=12.47(1.15)(0.95) \times 10^{-10}$ where the first error is statistical and the second systematic. The result is mainly based on the 2+1 flavor M\"obius domain wa

Santanu Mondal, V. Jithesh

We present the X-ray spectral and temporal analysis of the black hole X-ray transient Swift J1658.2--4242 observed by {\it AstroSat}. Three epochs of data have been analysed using the JeTCAF model to estimate the mass accretion rates and to understand the geometry of the flow. The best-fit disc mass accretion rate ($\dot m_d$) varies between $0.90^{+0.02}_{-

Yi Xiao, Qiangqiang Yuan, Kui Jiang, Xianyu Jin

Optical-flow-based and kernel-based approaches have been extensively explored for temporal compensation in satellite Video Super-Resolution (VSR). However, these techniques are less generalized in large-scale or complex scenarios, especially in satellite videos. In this paper, we propose to exploit the well-defined temporal difference for efficient and effec

Zhijun Zhai, Jianhui Zhao, Chengjiang Long, Wenju Xu

Micro-expressions are spontaneous, rapid and subtle facial movements that can neither be forged nor suppressed. They are very important nonverbal communication clues, but are transient and of low intensity thus difficult to recognize. Recently deep learning based methods have been developed for micro-expression (ME) recognition using feature extraction and f

N. Dimakis, M. Roumeliotis, A. Paliathanasis, T. Christodoulakis

We investigate the existence of anisotropic self-similar exact solutions in symmetric teleparallel $f\left( Q\right)$-theory. For the background geometry we consider the Kantowski-Sachs and the Locally Rotationally Symmetric Bianchi type III geometries. These two anisotropic spacetimes are of special interest because in the limit of isotropy they are related

Chunyu Chen, Ruchi Guo, Huayi Wei

It has been extensively studied in the literature that solving Maxwell equations is very sensitive to the mesh structure, space conformity and solution regularity. Roughly speaking, for almost all the methods in the literature, optimal convergence for low-regularity solutions heavily relies on conforming spaces and highly-regular simplicial meshes. This can

Fangfang Zhou, Dan Zhang, Zhenming Fu

Avoiding the introduction of ghosts when synthesising LDR images as high dynamic range (HDR) images is a challenging task. Convolutional neural networks (CNNs) are effective for HDR ghost removal in general, but are challenging to deal with the LDR images if there are large movements or oversaturation/undersaturation. Existing dual-branch methods combining C

Li Xu, Mark He Huang, Xindi Shang, Zehuan Yuan

Referring expression segmentation aims to segment an object described by a language expression from an image. Despite the recent progress on this task, existing models tackling this task may not be able to fully capture semantics and visual representations of individual concepts, which limits their generalization capability, especially when handling novel co

Amílcar Branquinho, Juan E. F. Díaz, Ana Foulquié-Moren, Manuel Mañas

In this work we survey on connections of Markov chains and the theory of multiple orthogonality. Here we mainly concentrate on give a procedure to generate stochastic tetra diagonal Hessenberg matrices, coming from some specific families of multiple orthogonal, such as the ones of Jacobi--Pi\~neiro and Hypergeometric Lima--Loureiro. We show that associated w

Songyan Hou

Electro-optic modulators lie at the heart of complex integration and high density electro-optic systems. One of the representative electro-optic modulators is thin film lithium niobate based microring modulator which has demonstrated advantages of compact footprint, low optical loss and high modulation efficiency. However, the linewidth and extinction ratio

Evgenii Ievlev, Michael R. R. Good, Eric V. Linder

A charge accelerating in a straight line following the Schwarzschild-Planck moving mirror motion emits thermal radiation for a finite period. Such a mirror motion demonstrates quantum purity and serves as a direct analogy of a black hole with unitary evolution and complete evaporation. Extending the analog to classical electron motion, we derive the emission

Kazi Hassan Shakib, Mizanur Rahman, Mhafuzul Islam, Mashrur Chowdhury

Blockchain-based Vehicular Ad-hoc Network (VANET) is widely considered as secure communication architecture for a connected transportation system. With the advent of quantum computing, there are concerns regarding the vulnerability of this architecture against cyber-attacks. In this study, a potential threat is investigated in a blockchain-based VANET, and a

Shaowei Wang, Jin Li, Yuntong Li, Jin Li

Numerical vector aggregation plays a crucial role in privacy-sensitive applications, such as distributed gradient estimation in federated learning and statistical analysis of key-value data. In the context of local differential privacy, this study provides a tight minimax error bound of $O(\frac{ds}{n\epsilon^2})$, where $d$ represents the dimension of the n

Anuradha Jagannathan

The single electron spectrum and wavefunctions in quasicrystals continue to be a fascinating problem, with few known solutions, especially in two and higher dimensions. This paper investigates the energy spectra and gap structures in tight-binding models on a quasiperiodic tiling in two dimensions. By varying a continuous parameter, we follow the evolution o

Huiwei Lin, Baoquan Zhang, Shanshan Feng, Xutao Li

Online class-incremental continual learning is a specific task of continual learning. It aims to continuously learn new classes from data stream and the samples of data stream are seen only once, which suffers from the catastrophic forgetting issue, i.e., forgetting historical knowledge of old classes. Existing replay-based methods effectively alleviate this

Xianghong Xu, Zhibing Zhao, Tieying Zhang, Rong Kang

Query optimization is a pivotal part of every database management system (DBMS) since it determines the efficiency of query execution. Numerous works have introduced Machine Learning (ML) techniques to cost modeling, cardinality estimation, and end-to-end learned optimizer, but few of them are proven practical due to long training time, lack of interpretabil

Yong Wang

We try to clarify the relationship between interleaving concurrency and true concurrency, based on the very recent work on truly concurrent process algebra, especially, giving models of true concurrency, such as event structure, Petri net and concurrent Kleene algebra, (truly concurrent) process algebra foundations.

Yi-Heng Zhang, Zhenwei Yao

A host of elastic systems consisting of active components exhibit path-dependent elastic behaviors not found in classical elasticity, which is known as odd elasticity. Odd elasticity is characterized by antisymmetric (odd) elastic modulus tensor. Here, from the perspective of geometry, we construct the Hamiltonian formalism to show the origin of the antisymm

Amir Jalili, Jorge Segovia, Feng Pan, Yan-An Luo

A novel approach is introduced for obtaining precise solutions of the pairing Hamiltonian for tetraquarks, which utilizes an algebraic technique in infinite dimensions. The parameters involved in the transition phase are calibrated based on potential tetraquark candidates derived from phenomenology. Our investigation shows that the rotation and vibration tra

Yi Yu, Xue Yang, Qingyun Li, Yue Zhou

With the rapidly increasing demand for oriented object detection, e.g. in autonomous driving and remote sensing, the recently proposed paradigm involving weakly-supervised detector H2RBox for learning rotated box (RBox) from the more readily-available horizontal box (HBox) has shown promise. This paper presents H2RBox-v2, to further bridge the gap between HB

Chenxi Zhong, Xiaojun Yuan

The communication bottleneck of over-the-air federated learning (OA-FL) lies in uploading the gradients of local learning models. In this paper, we study the reduction of the communication overhead in the gradients uploading by using the multiple-input multiple-output (MIMO) technique. We propose a novel sparse-coded multiplexing (SCoM) approach that employs

Brenda A. Cervantes-Vergara, Santiago Perez, Juan Estrada, Ana Botti

Oscura is a proposed multi-kg skipper-CCD experiment designed for a dark matter (DM) direct detection search that will reach unprecedented sensitivity to sub-GeV DM-electron interactions with its 10 kg detector array. Oscura is planning to operate at SNOLAB with 2070 m overburden, and aims to reach a background goal of less than one event in each electron bi

Zan Gao, Shenxun Wei, Weili Guan, Lei Zhu

Cloth-changing person reidentification (ReID) is a newly emerging research topic that is aimed at addressing the issues of large feature variations due to cloth-changing and pedestrian view/pose changes. Although significant progress has been achieved by introducing extra information (e.g., human contour sketching information, human body keypoints, and 3D hu

Shentong Mo, Jingfei Xia, Ihor Markevych

Visual and linguistic pre-training aims to learn vision and language representations together, which can be transferred to visual-linguistic downstream tasks. However, there exists semantic confusion between language and vision during the pre-training stage. Moreover, current pre-trained models tend to take lots of computation resources for fine-tuning when

Aldin Vehabovic, Nasir Ghani, Elias Bou-Harb, Jorge Crichigno

Ransomware uses encryption methods to make data inaccessible to legitimate users. To date a wide range of ransomware families have been developed and deployed, causing immense damage to governments, corporations, and private users. As these cyberthreats multiply, researchers have proposed a range of ransomware detection and classification schemes. Most of th

Yichuan Deng, Sridhar Mahadevan, Zhao Song

Large language models (LLMs) have shown their power in different areas. Attention computation, as an important subroutine of LLMs, has also attracted interests in theory. Recently the static computation and dynamic maintenance of attention matrix has been studied by [Alman and Song 2023] and [Brand, Song and Zhou 2023] from both algorithmic perspective and h

Weiwei Li, Dejian Tian

The paper investigates the robust optimized certainty equivalents and analyzes the relevant properties of them as risk measures for loss positions with distribution uncertainty. On this basis, the robust generalized quantiles are proposed and discussed. The robust expectiles with two specific penalization functions $\varphi_{1}$ and $\varphi_{2}$ are further

Yichen Liu, Benran Hu, Junkai Huang, Yu-Wing Tai

This paper presents one of the first learning-based NeRF 3D instance segmentation pipelines, dubbed as Instance Neural Radiance Field, or Instance NeRF. Taking a NeRF pretrained from multi-view RGB images as input, Instance NeRF can learn 3D instance segmentation of a given scene, represented as an instance field component of the NeRF model. To this end, we

Scott H. Hawley, Christian J. Steinmetz

We investigate applying audio manipulations using pretrained neural network-based autoencoders as an alternative to traditional signal processing methods, since the former may provide greater semantic or perceptual organization. To establish the potential of this approach, we first establish if representations from these models encode information about manip

San-Dong Guo, Xu-Kun Feng, Dong Huang, Shaobo Chen

The persistent spin helix (PSH) is robust against spin-independent scattering and renders an extremely long spin lifetime, which can improve the performance of potential spintronic devices. To achieve the PSH, a unidirectional spin configuration is required in the momentum space. Here, T-XY (X$\neq$Y=P, As, Sb and Bi) monolayers with dynamical, mechanical an

Svitlana Bilun, Bohdana Hladysh, Alexandr Prishlyak, Mariia Roman

We investigate topological properties of simple Morse functions with 4 critical points on immersed 2-spheres. To classify such functions, dual graph of immersion and Reeb graphs is used. We have found all possible structures of the functions:6 structures with 4 critical points on one 1-strata component, 7 structures with two points on the 1-strata and two po

Arvindh Arun, Aakash Aanegola, Amul Agrawal, Ramasuri Narayanam

Unsupervised Representation Learning on graphs is gaining traction due to the increasing abundance of unlabelled network data and the compactness, richness, and usefulness of the representations generated. In this context, the need to consider fairness and bias constraints while generating the representations has been well-motivated and studied to some exten

Kingman Cheung, Ying-nan Mao, Stefano Moretti, Rui Zhang

We propose to probe CP-violation in the heavy (pseudo)scalar sector of an extended Higgs model, in which we make simultaneous use of the $HVV$ ($V=W^\pm, Z$) and $Ht\bar{t}$ interactions of a heavy Higgs state $H$. The CP-even component of $H$ can be probed through the tree level $HVV$ interaction while the CP-odd component of $H$ can be probed if the final

Jiacheng Huang, Zequn Sun, Qijin Chen, Xiaozhou Xu

Knowledge graphs (KGs) store rich facts about the real world. In this paper, we study KG alignment, which aims to find alignment between not only entities but also relations and classes in different KGs. Alignment at the entity level can cross-fertilize alignment at the schema level. We propose a new KG alignment approach, called DAAKG, based on deep learnin

Sourav Biswas, Alessandro De Martino, Sumathi Rao, Arijit Kundu

We study the two-channel Kondo problem in the context of two interacting helical liquids coupled to a spin-$\frac12$ magnetic impurity. We show that the interactions between the two helical liquids significantly affect the phase diagram and other observable properties. Using a multichannel Luttinger liquid formalism, we analyze both the Toulouse limit, where

Jiawei Zhang

In this paper, we aim to develop a large language model (LLM) with the reasoning ability on complex graph data. Currently, LLMs have achieved very impressive performance on various natural language learning tasks, extensions of which have also been applied to study the vision tasks with multi-modal data. However, when it comes to the graph learning tasks, ex

Pengzhan Zhao, Xiongfei Wu, Zhuo Li, Jianjun Zhao

Static analysis is the process of analyzing software code without executing the software. It can help find bugs and potential problems in software that may only appear at runtime. Although many static analysis tools have been developed for classical software, due to the nature of quantum programs, these existing tools are unsuitable for analyzing quantum pro

Nitish Shukla, Sudipta Banerjee

Adversarial attacks in the input (pixel) space typically incorporate noise margins such as $L_1$ or $L_{\infty}$-norm to produce imperceptibly perturbed data that confound deep learning networks. Such noise margins confine the magnitude of permissible noise. In this work, we propose injecting adversarial perturbations in the latent (feature) space using a ge

Brandon McKinzie, Joseph Cheng, Vaishaal Shankar, Yinfei Yang

Multimodal learning is defined as learning over multiple heterogeneous input modalities such as video, audio, and text. In this work, we are concerned with understanding how models behave as the type of modalities differ between training and deployment, a situation that naturally arises in many applications of multimodal learning to hardware platforms. We pr

Musab Al Hasani, Guy Drijkoningen

Distributed Acoustic Sensing (DAS) has been limited in its use for surface-seismic reflection measurements, due to the fiber's decreased sensitivity when the fiber is deployed horizontally. Deploying the fiber in a helically wound fashion has the promise of being more sensitive to broadside waves (e.g. P-wave reflections) and less sensitive to surface waves

Jin Chen, Yongchao Lü, Xin Wang

We study the quantization of the 6d Seiberg-Witten curve for D-type minimal conformal matter theories compactified on a two-torus. The quantized 6d curve turns out to be a difference equation established via introducing codimension two and four surface defects. We show that, in the Nekrasov-Shatashvili limit, the 6d partition function with insertions of codi

Yuto Kawase

An algebraic theory, sometimes called an equational theory, is a theory defined by finitary operations and equations, such as the theories of groups and of rings. It is well known that algebraic theories are equivalent to finitary monads on $\mathbf{Set}$. In this paper, we generalize this phenomenon to locally finitely presentable categories using partial H

Md Ishtyaq Mahmud, Ahmed Abdelgawad, Venkata P. Yanambaka

Unique key generation is essential for encryption purposes between Internet of Things (IoT) devices. To produce a unique key for this encryption, Physical Unclonable Functions (PUFs) might be employed. Also, the Random Number Generator (RNG) is used in many different domains; nonetheless, security is one of the most important areas that require the best RNG.

J. Wang, I. Aravena, C. G. Petra

We propose a sequential quadratic programming (SQP) method that can incorporate adaptive sampling for stochastic nonsmooth nonconvex optimization problems with upper-C^2 objectives. Upper-$\Ctwo$ functions can be viewed as difference-of-convex (DC) functions with smooth convex parts. They are common among certain classes of solutions to parametric optimizati

Humberto Bautista Serrano, Bishnu Paudel, Chris Pinner

We obtain a complete description of the integer group determinants for SmallGroup(16,8), the semidihedral group of order 16. While this paper was in preparation, a complete descriptions for this group was independently obtained by Yuka Yamaguchi and Naoya Yamaguchi in [21] (and the other remaining group of order 16 in [20]). We offer our version here for any

Jinmyeong Kim, Boris I. Ivanov, Çağlar Kutlu, Seongtae Park

The axion is a hypothetical particle, a promising candidate for dark matter, and a solution to the strong CP problem. Axion haloscope search experiments deal with a signal power comparable to noise uncertainty at millikelvin temperature. We use a flux-driven Josephson parametric amplifier (JPA) with the aim of approaching a noise level near the theoretically

Qianqian Xie, Weiguang Han, Yanzhao Lai, Min Peng

Recently, large language models (LLMs) like ChatGPT have demonstrated remarkable performance across a variety of natural language processing tasks. However, their effectiveness in the financial domain, specifically in predicting stock market movements, remains to be explored. In this paper, we conduct an extensive zero-shot analysis of ChatGPT's capabilities

Xiaoyang Zheng, Fuyu Lv, Zilong Wang, Qingwen Liu

E-commerce search engines comprise a retrieval phase and a ranking phase, where the first one returns a candidate product set given user queries. Recently, vision-language pre-training, combining textual information with visual clues, has been popular in the application of retrieval tasks. In this paper, we propose a novel V+L pre-training method to solve th

Weijia Wu, Yuzhong Zhao, Zhuang Li, Jiahong Li

Recently, video text detection, tracking, and recognition in natural scenes are becoming very popular in the computer vision community. However, most existing algorithms and benchmarks focus on common text cases (e.g., normal size, density) and single scenarios, while ignoring extreme video text challenges, i.e., dense and small text in various scenarios. In

Takeshi Chiba, Shunichiro Kinoshita

We derive the time dilation formula for charged quantum clocks in electromagnetic fields. As a concrete example of non-inertial motion, we consider a cyclotron motion in a uniform magnetic field. Applying the time dilation formula to coherent state of the charged quantum clock, we evaluate the time dilation quantum-mechanically.

Lyudmila Korobenko, Olly Milshstein, Lucas Yong

In this paper we establish necessary and sufficient conditions for weighted Orlicz-Poincar\'e inequalities in dimension one. Our theorems generalize the main results of Chua and Wheeden, who established necessary and sufficient conditions for weighted $(q,p)$ Poincar\'e inequalities. We give an example of a weight satisfying sufficient conditions for a $(\Ph

Jirô Akahori, Nien-Lin Liu, Maria Elvira Mancino, Tommaso Mariotti

In this paper we propose an estimator of spot covariance matrix which ensure symmetric positive semi-definite estimations. The proposed estimator relies on a suitable modification of the Fourier covariance estimator in Malliavin and Mancino (2009) and it is consistent for suitable choices of the weighting kernel. The accuracy and the ability of the estimator

Zhen Chao, Weihua Geng, Robert Krasny

An integral equation method is presented for the 1D steady-state Poisson-Nernst-Planck equations modeling ion transport through membrane channels. The differential equations are recast as integral equations using Green's 3rd identity yielding a fixed-point problem for the electric potential gradient and ion concentrations. The integrals are discretized by a

Yingqiang Ge, Wenyue Hua, Kai Mei, Jianchao Ji

Human Intelligence (HI) excels at combining basic skills to solve complex tasks. This capability is vital for Artificial Intelligence (AI) and should be embedded in comprehensive AI Agents, enabling them to harness expert models for complex task-solving towards Artificial General Intelligence (AGI). Large Language Models (LLMs) show promising learning and re

Bing Gu

Conical intersections are ubiquitous in polyatomic molecules and responsible for a wide range of phenomena in chemistry and physics. We introduce and implement a local diabatic representation for the correlated electron-nuclear dynamics around conical intersections. It employs the adiabatic electronic states but avoids the singularity of nonadiabatic couplin

Wenyun Li, Guo Zhong, Xingyu Lu, Chi-Man Pun

Hashing is very popular for remote sensing image search. This article proposes a multiview hashing with learnable parameters to retrieve the queried images for a large-scale remote sensing dataset. Existing methods always neglect that real-world remote sensing data lies on a low-dimensional manifold embedded in high-dimensional ambient space. Unlike previous

Qian Zhao, Yan-Xi Wu, Mamutjan Ababekri, Zhong-Peng Li

The advent of laser-driven high-intensity $\gamma$-photon beams has opened up new opportunities for designing advanced photon-photon colliders. Such colliders have the potential to produce a large yield of linear Breit-Wheeler (LBW) pairs in a single shot, which offers a unique platform for studying the polarized LBW process. In our recent work [Phys. Rev. D

Kang Zhao, Jianru Xue, Xiangning Meng, Gengxin Li

One major issue in learning-based model predictive control (MPC) for autonomous driving is the contradiction between the system model's prediction accuracy and computation efficiency. The more situations a system model covers, the more complex it is, along with highly nonlinear and nonconvex properties. These issues make the optimization too complicated to s

Todor Milanov, Xiaokun Xia

Let $X$ be a smooth projective variety with a semisimple quantum cohomology. It is known that the blowup $\operatorname{Bl}_{\rm pt}(X)$ of $X$ at one point also has semisimple quantum cohomology. In particular, the monodromy group of the quantum cohomology of $\operatorname{Bl}_{\rm pt}(X)$ is a reflectiongroup. We found explicit formulas for certain genera

Todd Kelsey

The present study proposes a novel approach to dream recording by combining non-invasive brain-machine interfaces (BMI), thought-typing software, and generative AI-assisted multimodal software. This method aims to sublimate conscious processes into semi-conscious status during REM sleep and produce signals for thought typing. We outline a two-stage process:

Xiangwen Deng, Yufeng Wang, Yuanhao Cai, Jingxiang Sun

Domain adaptation of 3D portraits has gained more and more attention. However, the transfer mechanism of existing methods is mainly based on vision or language, which ignores the potential of vision-language combined guidance. In this paper, we propose an Image-Text multi-modal framework, namely Image and Text portrait (ITportrait), for 3D portrait domain ad

Ning Ding, Kunihiro Yananose, Carlo Rizza, Feng-Ren Fan

We study the magneto-optical Kerr effect (MOKE) of the two-dimensional heterostructure CrI3/In2Se3/CrI3 by using density functional theory calculations and symmetry analysis. The spontaneous polarization in the In2Se3 ferroelectric layer and the antiferromagnetic ordering in CrI3 layers break the mirror symmetry and the timereversal symmetry, thus activating

Yulun Tian, Yun Chang, Long Quang, Arthur Schang

This paper revisits Kimera-Multi, a distributed multi-robot Simultaneous Localization and Mapping (SLAM) system, towards the goal of deployment in the real world. In particular, this paper has three main contributions. First, we describe improvements to Kimera-Multi to make it resilient to large-scale real-world deployments, with particular emphasis on handl

Fumio Hiai

We revisit and improve joint concavity/convexity and monotonicity properties of quasi-entropies due to Petz in a new fashion. Then we characterize equality cases in the monotonicity inequalities (the data-processing inequalities) of quasi-entropies in several ways as follows: Let $\Phi:\mathcal{B}(\mathcal{H})\to\mathcal{B}(\mathcal{K})$ be a trace-preservin

Jeongbhin Seo, Dongsu Ryu

Due to the prevalence of magnetic fields in astrophysical environments, magnetohydrodynamic (MHD) simulation has become a basic tool for studying astrophysical fluid dynamics. To further advance the precision of MHD simulations, we have developed a new simulation code that solves ideal adiabatic or isothermal MHD equations with high-order accuracy. The code

Fang Liu, Ruyu Zhou, Yiming Paul Li, James Honaker

We examine privacy-preserving inferences of group mean differences in zero-inflated right-skewed (zirs) data. Zero inflation and right skewness are typical characteristics of ads clicks and purchases data collected from e-commerce and social media platforms, where we also want to preserve user privacy to ensure that individual data is protected. In this work

Hongjing Qian, Yutao Zhu, Zhicheng Dou, Haoqi Gu

In this paper, we introduce a new NLP task -- generating short factual articles with references for queries by mining supporting evidence from the Web. In this task, called WebBrain, the ultimate goal is to generate a fluent, informative, and factually-correct short article (e.g., a Wikipedia article) for a factual query unseen in Wikipedia. To enable experi

Guangyue Huang, Qi Guo, Lujun Guo

In this paper, we study gradient estimates for positive weak solutions to the following $p$-Laplacian equation $$\Delta_pu+au^{\sigma}=0$$ on a Riemannian manifold, where $p>1$ and $a,\sigma$ are two nonzero real constants. By virtue of the Morser iteration technique, we derive some gradient estimates, which show that when the Ricci curvature is nonnegative,

Tomohiro Oishi

This document is prepared to introduce and explain how to use the computing library composed by T. Oishi. The library-01 TOSPEM solves, for the spherical nucleus, (i) the Schroedinger equation for the single-nucleon states within the Woods-Saxon potential, (ii-a) the electric or magnetic transition strength, B(EJ) or B(MJ), between the arbitrary set of initi

Sandeep Singh Sandha, Bharathan Balaji, Luis Garcia, Mani Srivastava

Existing approaches for autonomous control of pan-tilt-zoom (PTZ) cameras use multiple stages where object detection and localization are performed separately from the control of the PTZ mechanisms. These approaches require manual labels and suffer from performance bottlenecks due to error propagation across the multi-stage flow of information. The large siz

Chunfeng Cui, Liqun Qi

In this paper, we first study the projections onto the set of unit dual quaternions, and the set of dual quaternion vectors with unit norms. Then we propose a power method for computing the dominant eigenvalue of a dual quaternion Hermitian matrix. For a strict dominant eigenvalue, we show the sequence generated by the power method converges to the dominant

Lin Chen, Zhijie Jia, Tian Qiu, Lechao Cheng

A surge of interest has emerged in utilizing Transformers in diverse vision tasks owing to its formidable performance. However, existing approaches primarily focus on optimizing internal model architecture designs that often entail significant trial and error with high burdens. In this work, we propose a new paradigm dubbed Decision Stream Calibration that b

Takeshi Ishida

This study explores the emergence of life through a simulation model approach. The model "Multi-set chemical lattice model" is a model that allows virtual molecules of multiple types to be placed in each lattice cell on a two-dimensional space. This model is capable of describing a wide variety of states and interactions in a limited number of lattice cell s

Yanming Che, Clemens Gneiting, Franco Nori

Solving the ground state and the ground-state properties of quantum many-body systems is generically a hard task for classical algorithms. For a family of Hamiltonians defined on an $m$-dimensional space of physical parameters, the ground state and its properties at an arbitrary parameter configuration can be predicted via a machine learning protocol up to a

Abel Castorena, P. Rubí Pantaleón-Mondragón, Juan Vásquez Aquino

Applying Geometric Invariant Theory (GIT), we study the stability of foliations of degree 3 on P^2 with a unique singular point of multiplicity 1, 2, or 3 and Milnor number 13. In particular, we characterize those foliations for multiplicity 2 in three cases: stable, strictly semistable, and unstable.

Qihang Fang, Yafei Song, Keqiang Li, Li Shen

A radiance field is an effective representation of 3D scenes, which has been widely adopted in novel-view synthesis and 3D reconstruction. It is still an open and challenging problem to evaluate the geometry, i.e., the density field, as the ground-truth is almost impossible to obtain. One alternative indirect solution is to transform the density field into a

David Laines, Gissella Bejarano, Miguel Gonzalez-Mendoza, Gilberto Ochoa-Ruiz

Sign Language Recognition (SLR) systems aim to be embedded in video stream platforms to recognize the sign performed in front of a camera. SLR research has taken advantage of recent advances in pose estimation models to use skeleton sequences estimated from videos instead of RGB information to predict signs. This approach can make HAR-related tasks less comp

Laura Shimabukuro, Antonio Ortega

In this paper we consider the problem of constructing graph Fourier transforms (GFTs) for directed graphs (digraphs), with a focus on developing multiple GFT designs that can capture different types of variation over the digraph node-domain. Specifically, for any given digraph we propose three GFT designs based on the polar decomposition. Our method is close

Laura Wakelin

A slope $p/q \in \mathbb{Q}$ is characterising for a knot $K \subset \mathbb{S}^3$ if the oriented homeomorphism type of the manifold $\mathbb{S}^3_K(p/q)$ obtained by Dehn surgery of slope $p/q$ on $K$ uniquely determines the knot $K$. We combine analysis of JSJ decompositions with techniques involving lengths of shortest geodesics to find explicit conditio

L. Y. Aaron Yung, Rachel S. Somerville, Steven L. Finkelstein, Stephen M. Wilkins

A substantial number of ultra-high redshift (8 < z < 17) galaxy candidates have been detected with JWST, posing the question: are these observational results surprising in the context of current galaxy formation models? We address this question using the well-established Santa Cruz semi-analytic models, implemented within merger trees from the new suite of c

Xiaoyu Sun, Xiao Chen, Yonghui Liu, John Grundy

Android fragmentation refers to the overwhelming diversity of Android devices and OS versions. These lead to the impossibility of testing an app on every supported device, leaving a number of compatibility bugs scattered in the community and thereby resulting in poor user experiences. To mitigate this, our fellow researchers have designed various works to au

Dengwang Tang, Ashutosh Nayyar, Rahul Jain

The Common Information (CI) approach provides a systematic way to transform a multi-agent stochastic control problem to a single-agent partially observed Markov decision problem (POMDP) called the coordinator's POMDP. However, such a POMDP can be hard to solve due to its extraordinarily large action space. We propose a new algorithm for multi-agent stochasti

Aizitiaili Abulikemu, Muneaki Hase

We report on a direct generation of efficient and wavelength-tunable third-harmonic generation (THG) from ultrapure electronic-grade (EG) diamond crystals. Under an ultrafast infrared excitation at 1280 nm, the considerably high optical conversion efficiency of ~ 0.7% at a THG wavelength of 427 nm is obtained, and the THG signal can be tuned over ultra-broad

Nikita Starodubcev, Dmitry Baranchuk, Valentin Khrulkov, Artem Babenko

Recent advances in diffusion models enable many powerful instruments for image editing. One of these instruments is text-driven image manipulations: editing semantic attributes of an image according to the provided text description. % Popular text-conditional diffusion models offer various high-quality image manipulation methods for a broad range of text pro

Hanbin Hong, Xinyu Zhang, Binghui Wang, Zhongjie Ba

Black-box adversarial attacks have demonstrated strong potential to compromise machine learning models by iteratively querying the target model or leveraging transferability from a local surrogate model. Recently, such attacks can be effectively mitigated by state-of-the-art (SOTA) defenses, e.g., detection via the pattern of sequential queries, or injecting