March 2023 arXiv papers — page 98

Yonghui Zhou, Shuguan Ji

In this paper, we study the global conservative weak solutions for a class of nonlinear dispersive wave equations after wave breaking. We first transform the equations into an equivalent semi-linear system by introducing new variables. We then establish the global existence of solutions for the semi-linear system by using the standard theory of ordinary diff

Hugo Bertiche, Niloy J. Mitra, Kuldeep Kulkarni, Chun-Hao Paul Huang

Cinemagraphs are short looping videos created by adding subtle motions to a static image. This kind of media is popular and engaging. However, automatic generation of cinemagraphs is an underexplored area and current solutions require tedious low-level manual authoring by artists. In this paper, we present an automatic method that allows generating human cin

F. Johannesmann, J. Eckseler, H. Schlüter, J. Schnack

We investigate the one-magnon dynamics of the antiferromagnetic delta chain as a paradigmatic example of tunable equilibration. Depending on the ratio of nearest and next-nearest exchange interactions the spin system exhibits a flat band in one-magnon space - in this case equilibration happens only partially, whereas it appears to be complete with dispersive

Angela F. Harper, Kamil Iwanowski, William C. Witt, Mike C. Payne

Amorphous alumina is employed ubiquitously as a high-dielectric-constant material in electronics, and its thermal-transport properties are of key relevance for heat management in electronic chips and devices. Experiments show that the thermal conductivity of alumina depends significantly on the synthesis process, indicating the need for a theoretical study t

Yuguang Yang, Yu Pan, Jingjing Yin, Jiangyu Han

SqueezeFormer has recently shown impressive performance in automatic speech recognition (ASR). However, its inference speed suffers from the quadratic complexity of softmax-attention (SA). In addition, limited by the large convolution kernel size, the local modeling ability of SqueezeFormer is insufficient. In this paper, we propose a novel method HybridForm

Freerk Schütt, Ana M. Valencia, Caterina Cocchi

The emerging interest in tin-halide perovskites demands a robust understanding of the fundamental properties of these materials starting from the earliest steps of their synthesis. In a first-principles work based on time-dependent density-functional theory, we investigate the structural, energetic, electronic, and optical properties of 14 tin-iodide solutio

Marouane Tliba, Aladine Chetouani, Giuseppe Valenzise, Frederic Dufaux

With the increased interest in immersive experiences, point cloud came to birth and was widely adopted as the first choice to represent 3D media. Besides several distortions that could affect the 3D content spanning from acquisition to rendering, efficient transmission of such volumetric content over traditional communication systems stands at the expense of

Ario Sadafi, Oleksandra Adonkina, Ashkan Khakzar, Peter Lienemann

Explainability is a key requirement for computer-aided diagnosis systems in clinical decision-making. Multiple instance learning with attention pooling provides instance-level explainability, however for many clinical applications a deeper, pixel-level explanation is desirable, but missing so far. In this work, we investigate the use of four attribution meth

David Barber

In Reinforcement Learning the Q-learning algorithm provably converges to the optimal solution. However, as others have demonstrated, Q-learning can also overestimate the values and thereby spend too long exploring unhelpful states. Double Q-learning is a provably convergent alternative that mitigates some of the overestimation issues, though sometimes at the

Ryan Martin

Fisher's fiducial argument is widely viewed as a failed version of Neyman's theory of confidence limits. But Fisher's goal -- Bayesian-like probabilistic uncertainty quantification without priors -- was more ambitious than Neyman's, and it's not out of reach. I've recently shown that reliable, prior-free probabilistic uncertainty quantification must be groun

Pengxue Cui, Shuguan Ji

In this paper, we consider the long time behavior for the solution of a class of variable coefficient wave equation with nonlinear damping and logarithmic source. The existence and uniqueness of local weak solution can be obtained by using the Galerkin method and contraction mapping principle. However, the long time behavior of the solution is usually compli

Quanfeng Xu, Shiyin Shen, Rafael S. de Souza, Mi Chen

We present a novel approach for the dimensionality reduction of galaxy images by leveraging a combination of variational auto-encoders (VAE) and domain adaptation (DA). We demonstrate the effectiveness of this approach using a sample of low redshift galaxies with detailed morphological type labels from the Galaxy-Zoo DECaLS project. We show that 40-dimension

Aaron D. Kaplan, Carl A. Kukkonen

Analytic mathematical models for the static spin ($G_-$) and density ($G_+$) local field factors for the uniform electron gas (UEG) as functions of wavevector and density are presented. These models closely fit recent quantum Monte Carlo (QMC) data and satisfy exact asymptotic limits. This model for $G_-$ is available for the first time, and the present mode

Andrei V. Konstantinov, Lev V. Utkin

A new extremely simple ensemble-based model with the uniformly generated axis-parallel hyper-rectangles as base models (HRBM) is proposed. Two types of HRBMs are studied: closed rectangles and corners. The main idea behind HRBM is to consider and count training examples inside and outside each rectangle. It is proposed to incorporate HRBMs into the gradient

E. T. Akhmedov, P. S. Zavgorodny, D. I. Sadekov, K. A. Kazarnovskii

We discuss loop-corrections to the electric current produced by strong and lengthy electric pulse. Namely we calculate one loop contribution to the electric current, distinguishing terms which depend on the pulse duration. We show that one loop correction does not lead to a strong modification of the tree-level current, which linearly grows with the pulse du

Iker de las Heras, Matteo Pintonello, Pavel Shumyatsky

Let $G$ be a profinite group. The coprime commutators $\gamma_j^*$ and $\delta_j^*$ are defined as follows. Every element of $G$ is both a $\gamma_1^*$-value and a $\delta_0^*$-value. For $j\geq 2$, let $X$ be the set of all elements of $G$ that are powers of $\gamma_{j-1}^*$-values. An element $a$ is a $\gamma_j^*$-value if there exist $x\in X$ and $g\in G$

Serin Yang, Hyunmin Hwang, Jong Chul Ye

Diffusion models have shown great promise in text-guided image style transfer, but there is a trade-off between style transformation and content preservation due to their stochastic nature. Existing methods require computationally expensive fine-tuning of diffusion models or additional neural network. To address this, here we propose a zero-shot contrastive

Kevin Sackel

Suppose $X^{N}$ is a closed oriented manifold, $\alpha \in H^*(X;\mathbb{R})$ is a cohomology class, and $Z \in H_{N-k}(X)$ is an integral homology class. We ask the following question: is there an oriented embedded submanifold $Y^{N-k} \subset X$ with homology class $Z$ such that $\alpha|_Y = 0 \in H^*(Y;\mathbb{R})$? In this article, we provide a family of

Qing Zhang, Zi-Xuan Xu, Wei Dai, Ben-Wei Zhang

Groomed jet substructure measurements, the momentum splitting fraction $z_g$ and the groomed jet radius $R_g$, of inclusive, D$^0$-tagged and B$^0$-tagged jets in $pp$ and central PbPb collisions at $\sqrt{s}=5.02$ TeV are predicted and investigated. Charged jets are constrained in a relatively low transverse momentum interval 15 $\leq p_{\rm T}^{\rm jet\ ch

Dennis Leung, Qi-Man Shao

We establish nonuniform Berry-Esseen (B-E) bounds for Studentized U-statistics of the rate $1/\sqrt{n}$ under a third-moment assumption, which covers the t-statistic that corresponds to a kernel of degree $1$ as a special case. While an interesting data example raised by Novak (2005) can show that the form of the nonuniform bound for standardized U-statistic

Daniel Spitz, Kirill Boguslavski, Jürgen Berges

We study nonequilibrium dynamics of SU(2) lattice gauge theory in Minkowski space-time in a classical-statistical regime, where characteristic gluon occupancies are much larger than unity. In this strongly correlated system far from equilibrium, the correlations of energy and topological densities show self-similar behavior related to a turbulent cascade tow

Jun Yu, Zhongpeng Cai, Renda Li, Gongpeng Zhao

Facial Expression Recognition (FER) is an important task in computer vision and has wide applications in human-computer interaction, intelligent security, emotion analysis, and other fields. However, the limited size of FER datasets limits the generalization ability of expression recognition models, resulting in ineffective model performance. To address this

R. K. Zamanov, L. Dankova, M. Moyseev, M. Minev

We report photometry of the intranight variability of the dwarf nova RX And in two bands (B and V). The observations are carried out during three nights in November-December 2022 at the 50/70~cm Schmidt telescope of the Rozhen National Astronomical Observatory. The observations indicate that the amplitude of the flickering is about 0.5 mag in B band when the

Viktor Witkovský

The Tsallis $q$-Gaussian distribution is a powerful generalization of the standard Gaussian distribution and is commonly used in various fields, including non-extensive statistical mechanics, financial markets and image processing. It belongs to the $q$-distribution family, which is characterized by a non-additive entropy. Due to their versatility and practi

Tianwei Liang

We prove some nice properties of anti-homomorphisms, some of which are analogic to that of homomorphisms. Meanwhile, we develop a new kind of composition called $*$-composition such that the $*$-composition of two anti-homomorphisms is still an anti-homomorphism. Moreover, we develop a certain kind of categories called factorization categories, which general

Wenqian Zhao, Xufeng Yao, Ziyang Yu, Guojin Chen

Optical proximity correction (OPC) is a widely-used resolution enhancement technique (RET) for printability optimization. Recently, rigorous numerical optimization and fast machine learning are the research focus of OPC in both academia and industry, each of which complements the other in terms of robustness or efficiency. We inspect the pattern distribution

Siyu Chen, Jibang Wu, Yifan Wu, Zhuoran Yang

We study the incentivized information acquisition problem, where a principal hires an agent to gather information on her behalf. Such a problem is modeled as a Stackelberg game between the principal and the agent, where the principal announces a scoring rule that specifies the payment, and then the agent then chooses an effort level that maximizes her own pr

Egor Gorbachev, Marvin Künnemann

Klee's measure problem (computing the volume of the union of $n$ axis-parallel boxes in $\mathbb{R}^d$) is well known to have $n^{\frac{d}{2}\pm o(1)}$-time algorithms (Overmars, Yap, SICOMP'91; Chan FOCS'13). Only recently, a conditional lower bound (without any restriction to ``combinatorial'' algorithms) could be shown for $d=3$ (K\"unnemann, FOCS'22). Ca

Yuhan Bao, Lei Sun, Yuqin Ma, Diyang Gu

Fast and accurate auto-focus in adverse conditions remains an arduous task. The emergence of event cameras has opened up new possibilities for addressing the challenge. This paper presents a new high-speed and accurate event-based focusing algorithm. Specifically, the symmetrical relationship between the event polarities in focusing is investigated, and the

Anu Jagannath, Zackary Kane, Jithin Jagannath

RF fingerprinting is emerging as a physical layer security scheme to identify illegitimate and/or unauthorized emitters sharing the RF spectrum. However, due to the lack of publicly accessible real-world datasets, most research focuses on generating synthetic waveforms with software-defined radios (SDRs) which are not suited for practical deployment settings

Sungho Lee, Jaehyun Park, Seungryeol Paik, Kyogu Lee

Musicians and audio engineers sculpt and transform their sounds by connecting multiple processors, forming an audio processing graph. However, most deep-learning methods overlook this real-world practice and assume fixed graph settings. To bridge this gap, we develop a system that reconstructs the entire graph from a given reference audio. We first generate

Issaku Kanamori, Keigo Nitadori, Hideo Matsufuru

We study the implementation of the even-odd Wilson fermion matrix for lattice QCD simulations on the A64FX architecture. Efficient coding of the stencil operation is investigated for two-dimensional packing to SIMD vectors. We measure the sustained performance on the supercomputer Fugaku at RIKEN R-CCS and show the profiler result of our code, which may sign

Monica Bianchi, Enrico Miglierina, Maede Ramazannejad

In a normed space setting, this paper studies the conditions under which the projected solutions to a quasi equilibrium problem with non-self constraint map exist. Our approach is based on an iterative algorithm which gives rise to a sequence such that, under the assumption of asymptotic regularity, its limit points are projected solutions. Finally, as a par

Yuning Wu, Jiatong Shi, Tao Qian, Dongji Gao

Singing voice synthesis (SVS), as a specific task for generating the vocal singing voice from a music score, has drawn much attention in recent years. SVS faces the challenge that the singing has various pronunciation flexibility conditioned on the same music score. Most of the previous works of SVS can not well handle the misalignment between the music scor

Tong Ye, Shijing Si, Jianzong Wang, Ning Cheng

Deep neural retrieval models have amply demonstrated their power but estimating the reliability of their predictions remains challenging. Most dialog response retrieval models output a single score for a response on how relevant it is to a given question. However, the bad calibration of deep neural network results in various uncertainty for the single score

Valérie Voorsluijs, Francesco Avanzini, Gianmaria Falasco, Massimiliano Esposito

Living organisms continuously harness energy to perform complex functions for their adaptation and survival while part of that energy is dissipated in the form of heat or chemical waste. Determining the energetic cost and the efficiency of specific cellular processes remains a largely open problem. Here, we analyze the efficiency of mitochondrial adenosine t

Zizhang Li, Xiaoyang Lyu, Yuanyuan Ding, Mengmeng Wang

Recently, neural implicit surfaces have become popular for multi-view reconstruction. To facilitate practical applications like scene editing and manipulation, some works extend the framework with semantic masks input for the object-compositional reconstruction rather than the holistic perspective. Though achieving plausible disentanglement, the performance

Jianyong Liu, Wei Geng, Xiaobo Zhao

In this paper, we consider a finite horizon non-stationary inventory system with setup costs. We detail an algorithm to find an approximate optimal policy and the basic idea is to use numerical procedure for computing integrals involved in the standard method. We provide analytical error bounds, which converge to zero, between the costs of an approximate opt

I. Ozge Taspinar, M. Firat Arikan

Using square bridge position, Akbulut-Ozbagci and later Arikan gave algorithms both of which construct an explicit compatible open book decomposition on a closed contact $3$-manifold which results from a contact $(\pm 1)$-surgery on a Legendrian link in the standard contact $3$-sphere. In this article, we introduce the ``generalized square bridge position''

Anette Messinger, Michael Fellner, Wolfgang Lechner

We present a protocol to encode and decode arbitrary quantum states in the parity architecture with constant circuit depth using measurements, local nearest-neighbor and single-qubit operations only. While this procedure typically requires a quadratic overhead of simultaneous qubit measurements, it allows for a simple and low-depth implementation of logical

Yequan Wang, Hengran Zhang, Aixin Sun, Xuying Meng

Given comparative text, comparative relation extraction aims to extract two targets (\eg two cameras) in comparison and the aspect they are compared for (\eg image quality). The extracted comparative relations form the basis of further opinion analysis.Existing solutions formulate this task as a sequence labeling task, to extract targets and aspects. However

Jiale Li, Hang Dai, Hao Han, Yong Ding

LiDAR and camera are two modalities available for 3D semantic segmentation in autonomous driving. The popular LiDAR-only methods severely suffer from inferior segmentation on small and distant objects due to insufficient laser points, while the robust multi-modal solution is under-explored, where we investigate three crucial inherent difficulties: modality h

Tong Ye, Zhitao Li, Jianzong Wang, Ning Cheng

Deep neural networks have achieved remarkable performance in retrieval-based dialogue systems, but they are shown to be ill calibrated. Though basic calibration methods like Monte Carlo Dropout and Ensemble can calibrate well, these methods are time-consuming in the training or inference stages. To tackle these challenges, we propose an efficient uncertainty

Lele Luan, Nesar Ramachandra, Sandipp Krishnan Ravi, Anindya Bhaduri

Modern computational methods, involving highly sophisticated mathematical formulations, enable several tasks like modeling complex physical phenomenon, predicting key properties and design optimization. The higher fidelity in these computer models makes it computationally intensive to query them hundreds of times for optimization and one usually relies on a

Changwon Park, Young-Woo Son

Charge density wave (CDW) is a spontaneous spatial modulation of electric charges in solids whose general microscopic descriptions are yet to be completed. Layered kagome metals of $A$V$_3$Sb$_5$ ($A$ = K, Rb, Cs) provide a unique chance to realize its emergence intertwined with dimensional effects as well as their special lattice. Here, based on a state-of-

Huy Nguyen, Kien Nguyen, Sridha Sridharan, Clinton Fookes

Person re-ID matches persons across multiple non-overlapping cameras. Despite the increasing deployment of airborne platforms in surveillance, current existing person re-ID benchmarks' focus is on ground-ground matching and very limited efforts on aerial-aerial matching. We propose a new benchmark dataset - AG-ReID, which performs person re-ID matching in a

Diederik van Engelenburg, Marcin Lis

We revisit the classical phenomenon of duality between random integer-valued height functions with positive definite potentials and abelian spin models with O(2) symmetry. We use it to derive new results in quite high generality including: a universal upper bound on the variance of the height function in terms of the Green's function (a GFF bound) which amon

Junjie He, Pengyu Li, Yifeng Geng, Xuansong Xie

Recent attention in instance segmentation has focused on query-based models. Despite being non-maximum suppression (NMS)-free and end-to-end, the superiority of these models on high-accuracy real-time benchmarks has not been well demonstrated. In this paper, we show the strong potential of query-based models on efficient instance segmentation algorithm desig

H. O. Mohammed, K. N. Nigussa

In this work, we have carried out molecular dynamics (MD) simulation techniques to study the diffusion coefficient of interlayer molecules at different temperature. Within the wider context of water dynamics in soils, and with a particular emphasis on clays, we present here the translational dynamics of water in clays, in a bi-hydrated states. We focus on te

V. Rollano, M. C. de Ory, A. Gomez, E. M. Gonzalez

We investigated the vortex phase diagram of needle shaped high quality NiBi3 single crystals by transport measurements. The current is applied along the crystalline b-axis of this intermetallic quasi-1D BCS superconductor. The single crystals show a Ginzburg-Levanchuk (Gi) parameter few orders of magnitude larger than other low Tc BCS superconductors. Vortex

Jakub Czartowski, Karol Życzkowski, Daniel Braun

We propose an analogue of $\text{SU}(1,1)$ interferometry to measure rotation of a spin by using two-spin squeezed states. Attainability of the Heisenberg limit for the estimation of the rotation angle is demonstrated for maximal squeezing. For a specific direction and strength an advantage in sensitivity for all equatorial rotation axes (and hence non-commu

Markus Clemens, Sebastian Schöps, Carsten Cimala, Nico Gödel

This paper addresses different aspects of "coupled" model descriptions in computational electromagnetics. This includes domain decomposition, multiscale problems, multiple or hybrid discrete field formulation and multi-physics problems. Theoretical issues of accuracy, stability and numerical efficiency of the resulting formulations are addressed along with a

Shuvankar Gupta, Jyotirmoy Sau, Manoranjan Kumar, Chandan Mazumdar

In this paper, we report the theoretical investigation and experimental realization of a new spin-gapless semiconductor (SGSs) compound CoFeMnSn belonging to the family of quaternary Heusler alloys. Through the use of several ground-state energy calculations, the most stable structure has been identified. Calculations of the spin-polarized band structure in

Zunshan Yang, Huikai Zhong, Can Wang, Yanghua Lu

Since the invention of dynamic diode, its physical properties and potential applications have attracted wide attentions. A lot of attempts have been made to harvest the rebounding current and voltage of dynamic diode. However, the underlying physical mechanism of its carrier transport characteristic was rarely explored carefully. Here, the electrical transpo

L. Frisco, M. S. Gravielle

Understanding the influence of phonon-mediated processes on grazing-incidence fast atom diffraction (GIFAD) patterns is relevant for its use as a surface analysis technique. In this work, we apply the Phonon-Surface Initial Value Representation (P0-SIVR) approximation to study lattice vibration effects on GIFAD patterns for the He-LiF(001) system at room tem

Chunyuan Shan, Xiaoyu Dai, Boyang Liu

The Josephson dynamics of the Bose-Einstein condensation with Raman-induced spin-orbit coupling is investigated. A quasi-1D trap is divided into two reservoirs by an optical barrier. Before the tunneling between the reservoirs is turned on, the system stays in its equilibrium ground state. For different spin-orbit coupling parameters and interaction strength

Piotr Pokora

The main purpose of this paper is to provide combinatorial constraints on the constructability of free and nearly free arrangements of smooth plane conics admitting certain ${\rm ADE}$ singularites.

Ahmet Kara, Milos Nikolic, Dan Olteanu, Haozhe Zhang

This article describes F-IVM, a unified approach for maintaining analytics over changing relational data. We exemplify its versatility in four disciplines: processing queries with group-by aggregates and joins; learning linear regression models using the covariance matrix of the input features; building Chow-Liu trees using pairwise mutual information of the

Max O. Hansen, Yash Palan, Viktor Hahn, Mark D. Thomson

We re-examine the effect of long-range Coulomb interactions on the collective amplitude and phase modes in the incommensurate charge-density-wave ground state of quasi-one-dimensional conductors. Using an effective action approach we show that the longitudinal acoustic phonon protects the gapless linear dispersion of the lowest phase mode in the presence of

Shuvankar Gupta, Sudip Chakraborty, Vidha Bhasin, Santanu Pakhira

In this work, we report the successful synthesis of a Fe-based novel half-metallic quaternary Heusler alloy FeMnVGa and its structural, magnetic and transport properties probed through different experimental methods and theoretical technique. Density functional theory (DFT) calculations performed on different types of structure reveal that Type-2 ordered str

Giorgia Adorni, Felix Boelter, Stefano Carlo Lambertenghi

The field of image generation through generative modelling is abundantly discussed nowadays. It can be used for various applications, such as up-scaling existing images, creating non-existing objects, such as interior design scenes, products or even human faces, and achieving transfer-learning processes. In this context, Generative Adversarial Networks (GANs

Jiachen Qian, Zhisheng Duan, Peihu Duan, Zhongkui Li

Compared with linear time invariant systems, linear periodic system can describe the periodic processes arising from nature and engineering more precisely. However, the time-varying system parameters increase the difficulty of the research on periodic system, such as stabilization and observation. This paper aims to consider the observation problem of period

Théo Matricon, Nathanaël Fijalkow, Gaëtan Margueritte

We tackle the problem of automatic generation of computer programs from a few pairs of input-output examples. The starting point of this work is the observation that in many applications a solution program must use external knowledge not present in the examples: we call such programs knowledge-powered since they can refer to information collected from a know

Jianyi Du, Javier Paez, Pablo Otero, Pablo B. Sanchez

It is critical to monitor the structural evolution during deformation of complex fluids for the optimization of many manufacturing processes, including textile spinning. However, in situ measurements in a textile spinning process suffer from paucity of non-destructive instruments and interpretations of the measured data. In this work, kinetic and rheo-optic

Qiankun Gong, Qingmin Man, Ye Li, Menghan Dou

The molecular energies of chemical systems have been successfully calculated on quantum computers, however, more attention has been paid to the dynamic process of chemical reactions in practical application, especially in catalyst design, material synthesis. Due to the limited the capabilities of the noisy intermediate scale quantum (NISQ) devices, directly

Iwona Chlebicka, Arttu Karppinen, Ying Li

We provide a direct proof of existence and uniqueness of weak solutions to a broad family of strongly nonlinear elliptic equations with lower order terms. The leading part of the operator satisfies general growth conditions settling the problem in the framework of fully anisotropic and inhomogeneous Musielak--Orlicz spaces generated by an $N$-function $M:\Om

Ceejay Hammond, Peter G. M. van der Heijden, Paul A. Smith

We present a method to generate contingency tables that follow loglinear models with prescribed marginal probabilities and dependence structures. We make use of (loglinear) Poisson regression, where the dependence structures, described using odds ratios, are implemented using an offset term. We apply this methodology to carry out simulation studies in the co

Bo-Yan Cui, Ya-Hui Chen

In this work, we investigate the resonant contributions of $K_0^*(1430)$ and $K_0^*(1950)$ in the three-body $B_{(s)}\to D_{(s)}K\pi$ within the perturbative QCD approach. The form factor $F_{k\pi}(s)$ are adopted to describe the nonperturbative dynamics of the S-wave $K\pi$ system. The branching ratios of all concerned decays are calculated and predicted to

Haoyu He, Jianfei Cai, Jing Zhang, Dacheng Tao

Visual Parameter-Efficient Fine-Tuning (PEFT) has become a powerful alternative for full fine-tuning so as to adapt pre-trained vision models to downstream tasks, which only tunes a small number of parameters while freezing the vast majority ones to ease storage burden and optimization difficulty. However, existing PEFT methods introduce trainable parameters

Katarzyna Maciejowska, Tomasz Serafin, Bartosz Uniejewski

This paper presents a novel hybrid approach for constricting probabilistic forecasts that combines both the Quantile Regression Averaging (QRA) method and the factor-based averaging scheme. The performance of the approach is evaluated on data sets from two European energy markets - the German EPEX SPOT and the Polish Power Exchange (TGE). The results show th

Martin Hennecke, Clemens von Korff Schmising, Kelvin Yao, Emmanuelle Jal

Coherent light-matter interactions mediated by opto-magnetic phenomena like the inverse Faraday effect (IFE) are expected to provide a non-thermal pathway for ultrafast manipulation of magnetism on timescales as short as the excitation pulse itself. As the IFE scales with the spin-orbit coupling strength of the involved electronic states, photo-exciting the

Ana Peón-Nieto

We give a birational description of the reduced schemes underlying the irreducible components of the nilpotent cone and the $\CC^\times$-fixed point locus of length two in the moduli space of Higgs bundles. Using these results, we prove Drinfeld's conjecture for the sublocus of type $(n_0,n_1)$ fixed points. We introduce the notion of $\U(n_0,n_1)$-wobblines

Weijian Huang, Hao Yang, Cheng Li, Mingtong Dai

Multi-modal representation methods have achieved advanced performance in medical applications by extracting more robust features from multi-domain data. However, existing methods usually need to train additional branches for downstream tasks, which may increase the model complexities in clinical applications as well as introduce additional human inductive bi

Yulin Pan, Xiangteng He, Biao Gong, Yuxin Peng

Existing audio analysis methods generally first transform the audio stream to spectrogram, and then feed it into CNN for further analysis. A standard CNN recognizes specific visual patterns over feature map, then pools for high-level representation, which overlooks the positional information of recognized patterns. However, unlike natural image, the semantic

Tobias Mistele, Stacy McGaugh, Sabine Hossenfelder

Superfluid dark matter (SFDM) is a model that promises to reproduce the successes of both particle dark matter on cosmological scales and those of Modified Newtonian Dynamics (MOND) on galactic scales. SFDM reproduces MOND only up to a certain distance from the galactic center, and only for kinematic observables: It does not affect trajectories of light. We

Yubo Ma, Yixin Cao, YongChing Hong, Aixin Sun

Large Language Models (LLMs) have made remarkable strides in various tasks. Whether LLMs are competitive few-shot solvers for information extraction (IE) tasks, however, remains an open problem. In this work, we aim to provide a thorough answer to this question. Through extensive experiments on nine datasets across four IE tasks, we demonstrate that current

Konstantin Warawa, Nicolas Christophel, Sergei Sobolev, Jure Demsar

We investigate experimentally both the amplitude and phase channels of the collective modes in the quasi-1D charge-density-wave (CDW) system, K0.3MoO3, by combining (i) optical impulsive-Raman pump-probe and (ii) terahertz time-domain spectroscopy (THz-TDS), with high resolution and a detailed analysis of the full complex-valued spectra in both cases. This a

Huali Xu, Shuaifeng Zhi, Shuzhou Sun, Vishal M. Patel

While deep learning excels in computer vision tasks with abundant labeled data, its performance diminishes significantly in scenarios with limited labeled samples. To address this, Few-shot learning (FSL) enables models to perform the target tasks with very few labeled examples by leveraging prior knowledge from related tasks. However, traditional FSL assume

Manoj Kumar Rajagopal, Bala Murugan MS

The use of unmanned aerial vehicles (UAV) is revolutionizing the agricultural industry. Cashews are grown by approximately 70% of small and marginal farmers, and the cashew industry plays a critical role in their economic development. To take timely counter measures against plant diseases and infections, it is imperative to monitor and detect diseases as ear

Di Jin, Jacob Klein

It was recently discovered that friction between surfaces bearing phosphatidylcholine (PC) lipid bilayers can be increased by two orders of magnitude or more via an externally-applied electric field, and that this increase is fully reversible when the field is switched off. While this striking effect holds promising application potential, its molecular origi

Hong-Po Hsieh, Amy Zavatsky, Min Chen

Glyph-based visualization is one of the main techniques for visualizing complex multivariate data. With small glyphs, data variables are typically encoded with relatively low visual and perceptual precision. Glyph designers have to contemplate the trade-offs in allocating visual channels when there is a large number of data variables. While there are many su

Clemens Grabmayer

Axiomatization and expressibility problems for Milner's process semantics (1984) of regular expressions modulo bisimilarity have turned out to be difficult for the full class of expressions with deadlock 0 and empty step~1. We report on a phenomenon that arises from the added presence of 1 when 0 is available, and that brings a crucial reason for this diffic

Benjamin Girault, Eduardo Pavez, Antonio Ortega

In this paper, we explore the topic of graph learning from the perspective of the Irregularity-Aware Graph Fourier Transform, with the goal of learning the graph signal space inner product to better model data. We propose a novel method to learn a graph with smaller edge weight upper bounds compared to combinatorial Laplacian approaches. Experimentally, our

Di Jin, Yu Zhang, Jacob Klein

It is well known that lipid membranes respond to a threshold transmembrane electric field through a reversible mechanism called electroporation, where hydrophilic water pores form across the membrane, an effect widely used in biological systems. The effect of such fields on interfacially-confined (stacked or supported) lipid membranes, on the other hand, whi

Chaoyang Jiang, Xiaoni Zheng, Zhe Jin, Chengpu Yu

This paper introduces the united monocular-stereo features into a visual-inertial tightly coupled odometry (UMS-VINS) for robust pose estimation. UMS-VINS requires two cameras and a low-cost inertial measurement unit (IMU). The UMS-VINS is an evolution of VINS-FUSION, which modifies the VINS-FUSION from the following three perspectives. 1) UMS-VINS extracts

Robert Gower, Dirk A. Lorenz, Maximilian Winkler

We propose a new randomized method for solving systems of nonlinear equations, which can find sparse solutions or solutions under certain simple constraints. The scheme only takes gradients of component functions and uses Bregman projections onto the solution space of a Newton equation. In the special case of euclidean projections, the method is known as non

Pantelis S. Apostolopoulos, Christos Tsipogiannis

In a recent paper, a new conformally flat metric was introduced, describing an expanding scalar field in a spherically symmetric geometry. The spacetime can be interpreted as a Schwarzschild-like model with an apparent horizon surrounding the curvature singularity. For the above metric, we present the complete conformal Lie algebra consisting of a six-dimens

Jinzhong Zhu, Yue Mu, Guoxiang Huang

We present a scheme to realize simultaneous quantum squeezing of light polarizations and atomic spins via a perturbed double electromagnetically induced transparency (DEIT) in a cold four-level atomic ensemble coupled with a probe laser pulse of two polarization components. We derive two coupled quantum nonlinear Schr\"odinger equations from Maxwell-Heisenbe

Anthony Onoja, Francesco Raimondi

The use of machine learning (ML) techniques in the biomedical field has become increasingly important, particularly with the large amounts of data generated by the aftermath of the COVID-19 pandemic. However, due to the complex nature of biomedical datasets and the use of black-box ML models, a lack of trust and adoption by domain experts can arise. In respo

Fuhui Zhou, Yihao Li, Ming Xu, Lu Yuan

Semantic communication is envisioned as a promising technique to break through the Shannon limit. However, semantic inference and semantic error correction have not been well studied. Moreover, error correction methods of existing semantic communication frameworks are inexplicable and inflexible, which limits the achievable performance. In this paper, to tac

Jun Yu, Renda Li, Zhongpeng Cai, Gongpeng Zhao

Human affective behavior analysis plays a vital role in human-computer interaction (HCI) systems. In this paper, we introduce our submission to the CVPR 2023 Competition on Affective Behavior Analysis in-the-wild (ABAW). We propose a single-stage trained AU detection framework. Specifically, in order to effectively extract facial local region features relate

Arash Bozorgchenani, Charilaos C. Zarakovitis, Su Fong Chien, Qiang Ni

Network connectivity exposes the network infrastructure and assets to vulnerabilities that attackers can exploit. Protecting network assets against attacks requires the application of security countermeasures. Nevertheless, employing countermeasures incurs costs, such as monetary costs, along with time and energy to prepare and deploy the countermeasures. Th

Hengxi Zhang, Zhendong Shi, Yuanquan Hu, Wenbo Ding

Quantitative markets are characterized by swift dynamics and abundant uncertainties, making the pursuit of profit-driven stock trading actions inherently challenging. Within this context, reinforcement learning (RL), which operates on a reward-centric mechanism for optimal control, has surfaced as a potentially effective solution to the intricate financial d

Benjamin Wetherfield, Timothy D. Wilkinson

Recent experimental work has demonstrated the potential to combine the merits of diffractive and on-chip photonic information processing devices in a single chip by making use of planar (or slab) waveguides. Researchers have adapted key results of 3D Fourier optics to 2D, by analogy, but rigorous derivations in planar contexts have been lacking. Here, such a

Benjamin Wetherfield, Timothy D. Wilkinson

The demands of proliferating big data and massive deep learning models, against a backdrop of a mounting climate emergency and the abating of Moore's law, push technologists to develop high-speed, high-throughput, low energy and miniaturisable computer hardware. Using light as a fundamental resource, free-space optical computing and on-chip photonic computin

J. D. Langcaster, D. S. Balint, M. R. Wenman

A variant of the U-Net convolutional neural network architecture is proposed to estimate linear elastic compatibility stresses in a-Zr (hcp) polycrystalline grain structures. Training data was generated using VGrain software with a regularity alpha of 0.73 and uniform random orientation for the grain structures and ABAQUS to evaluate the stress welds using t

Marta Zagorowska, Paola Falugi, Edward O'Dwyer, Eric C. Kerrigan

Existing methods for nonlinear robust control often use scenario-based approaches to formulate the control problem as large nonlinear optimization problems. The optimization problems are challenging to solve due to their size, especially if the control problems include time-varying uncertainty. This paper draws from local reduction methods used in semi-infin

Mingyang Xia

We present the topological transitivity of a class of diffeomorphisms on the thickened torus, including the partially hyperbolic example introduced by Ittai Kan in 1994, which is well known for the first systems with the intermingled basins phenomenon.

Likun Tang, Jie Ma, Yongming Li

The health monitoring of chronic diseases is very important for people with movement disorders because of their limited mobility and long duration of chronic diseases. Machine learning-based processing of data collected from the human with movement disorders using wearable sensors is an effective method currently available for health monitoring. However, wea

Lianghao Xia, Chao Huang, Jiao Shi, Yong Xu

Graph neural networks (GNNs) have shown the power in representation learning over graph-structured user-item interaction data for collaborative filtering (CF) task. However, with their inherently recursive message propagation among neighboring nodes, existing GNN-based CF models may generate indistinguishable and inaccurate user (item) representations due to