March 2023 arXiv papers — page 13

Alessio Brini, Elisa Giovannini, Elia Smaniotto

The beekeeping sector has experienced significant production fluctuations in recent years, largely due to increasingly frequent adverse weather events linked to climate change. These events can severely affect the environment, reducing its suitability for bee activity. We conduct a forecasting analysis of honey production across Italy using a range of machin

Shagun, Jasleen Kaur

This research article introduces the concept of lightlike submanifolds of an indefinite Kenmotsu statistical manifold. Various results on geometry of contact CR and SCR-lightlike submanifolds have been developed. Some characterization theorems on the integrability of distributions and on the geodesicity of these submanifolds have been obtained. Appropriate e

Jiaozi Wang, Wen-ge Wang

In this paper, we study random features manifested in components of energy eigenfunctions of quantum chaotic systems, given in the basis of unperturbed, integrable systems. Based on semiclassical analysis, particularly on Berry's conjecture, it is shown that the components in classically allowed regions can be regarded as Gaussian random numbers in certain s

Quoc Tran-Dinh

The extragradient (EG), introduced by G. M. Korpelevich in 1976, is a well-known method to approximate solutions of saddle-point problems and their extensions such as variational inequalities and monotone inclusions. Over the years, numerous variants of EG have been proposed and studied in the literature. Recently, these methods have gained popularity due to

Gabriel Fuhrmann, Maik Gröger, Till Hauser

It is known that if each point $x$ of a dynamical system is generic for some invariant measure $\mu_x$, then there is a strong connection between certain ergodic and topological properties of that system. In particular, if the acting group is abelian and the map $x\mapsto \mu_x$ is continuous, then every orbit closure is uniquely ergodic. In this note, we sh

Gerald Höhn, Sven Möller

We classify the self-dual (or holomorphic) vertex operator superalgebras of central charge 24, or in physics parlance the purely left-moving, fermionic 2-dimensional conformal field theories with just one primary field. There are exactly 969 such vertex operator superalgebras under suitable regularity assumptions (essentially strong rationality) and the assu

Guangcong Zheng, Xianpan Zhou, Xuewei Li, Zhongang Qi

Recently, diffusion models have achieved great success in image synthesis. However, when it comes to the layout-to-image generation where an image often has a complex scene of multiple objects, how to make strong control over both the global layout map and each detailed object remains a challenging task. In this paper, we propose a diffusion model named Layo

Xiao-Yang Wang, Shaoshi Yang, Tian-Hao Yuan, Hou-Yu Zhai

We propose a high-performance yet low-complexity hierarchical frequency synchronization scheme for orthogonal frequency-division multiple-access (OFDMA) aided distributed massive multi-input multi-output (MIMO) systems, where multi-ple carrier frequency offsets (CFOs) have to be estimated in the uplink. To solve this multi-CFO estimation problem efficiently,

Suraj Kumar, Soumi Chattopadhyay, Chandranath Adak

Recently, with the rapid deployment of service APIs, personalized service recommendations have played a paramount role in the growth of the e-commerce industry. Quality-of-Service (QoS) parameters determining the service performance, often used for recommendation, fluctuate over time. Thus, the QoS prediction is essential to identify a suitable service among

Rong-Yang Sun, Tomonori Shirakawa, Seiji Yunoki

We propose an efficient circuit structure of variational quantum circuit \textit{Ans\"{a}tze} used for the variational quantum eigensolver (VQE) algorithm in calculating gapped topological phases on the currently feasible noisy intermediate-scale quantum computers. An efficient circuit \textit{Ansatz} should include two layers: the initialization layer and t

Zexin Hu, Xueli Miao, Lijing Shao

Tests of gravity are important to the development of our understanding of gravitation and spacetime. Binary pulsars provide a superb playground for testing gravity theories. In this chapter we pedagogically review the basics behind pulsar observations and pulsar timing. We illustrate various recent strong-field tests of the general relativity (GR) from the H

Clara Grazian, Alex McInnes

This work examines how the dependence structures between energy futures asset prices differ in two periods identified before and after the 2008 global financial crisis. These two periods were characterised by a difference in the number of extraordinary meetings of OPEC countries organised to announce a change of oil production. In the period immediately foll

Joey Öhman, Severine Verlinden, Ariel Ekgren, Amaru Cuba Gyllensten

Pre-training Large Language Models (LLMs) require massive amounts of text data, and the performance of the LLMs typically correlates with the scale and quality of the datasets. This means that it may be challenging to build LLMs for smaller languages such as Nordic ones, where the availability of text corpora is limited. In order to facilitate the developmen

Clara Grazian

Clustering is a crucial task in various domains of knowledge, including medicine, epidemiology, genomics, environmental science, economics, and visual sciences, among others. Methodologies for inferring the number of clusters have often been shown to be inconsistent, and incorporating a dependence structure among clusters introduces additional challenges in

Avinash Paliwal, Andrii Tsarov, Nima Khademi Kalantari

In this paper, we propose an approach for view-time interpolation of stereo videos. Specifically, we build upon X-Fields that approximates an interpolatable mapping between the input coordinates and 2D RGB images using a convolutional decoder. Our main contribution is to analyze and identify the sources of the problems with using X-Fields in our application

Kanis Saengchote, Voraprapa Nakavachara, Yishuang Xu

When land becomes more connected, its value can change because of network externalities. This idea is intuitive and appealing to developers and policymakers, but documenting their importance is empirically challenging because it is difficult to isolate the determinants of land value in practice. We address this challenge with real estate in The Sandbox, a vi

Jonathan P. Marshall, Daniel V. Cotton, Kimberly Bott, Jeremy Bailey

Debris discs around main sequence stars have been extensively characterised from infrared to millimetre wavelengths through imaging, spectroscopic, and total intensity (scattered light and/or thermal emission) measurements. Polarimetric observations have only been used sparingly to interpret the composition, structure, and size of dust grains in these discs.

Xuepeng Fu, Shixiao Fu, Chang Liu, Mengmeng Zhang

The present study represents a data-driven turbulent model with Galilean invariance preservation based on machine learning algorithm. The fully connected neural network (FCNN) and tensor basis neural network (TBNN) [Ling et al. (2016)] are established. The models are trained based on five kinds of flow cases with Reynolds Averaged Navier-Stokes (RANS) and hi

Clara Grazian

Dirichlet processes and their extensions have reached a great popularity in Bayesian nonparametric statistics. They have also been introduced for spatial and spatio-temporal data, as a tool to analyze and predict surfaces. A popular approach to Dirichlet processes in a spatial setting relies on a stick-breaking representation of the process, where the depend

Jerone T. A. Andrews, Przemyslaw Joniak, Alice Xiang

Few datasets contain self-identified sensitive attributes, inferring attributes risks introducing additional biases, and collecting attributes can carry legal risks. Besides, categorical labels can fail to reflect the continuous nature of human phenotypic diversity, making it difficult to compare the similarity between same-labeled faces. To address these is

Olivier Brun, Rachid El-Azouzi, Quang-Trung Luu, Francesco De Pellergrini

Datacenter networks commonly facilitate the transmission of data in distributed computing frameworks through coflows, which are collections of parallel flows associated with a common task. Most of the existing research has concentrated on scheduling coflows to minimize the time required for their completion, i.e., to optimize the average dispatch rate of cof

Matteo Dalla Riva, Paolo Luzzini

We prove that the integral operators associated with the layer heat potentials depend smoothly upon a parametrization of the support of integration. The analysis is carried out in the optimal H\"older setting.

Hikaru Uchida

As the effective field theory of the superstring theory, ten-dimensional ${\cal N}=1$ supersymmetric Yang-Mills theory is induced. We consider the ten-dimensional space-time ${\cal M}_{10}$ as direct products of our four-dimensional space-time ${\cal M}_{4}$ and three two-dimensional compact spaces $X_i\ (i=1,2,3)$, i.e. ${\cal M}_{10} = {\cal M}_4 \times X_

Theresa Körner, Sascha Kurz

We determine the minimum possible column multiplicity of even, doubly-, and triply-even codes given their length. This refines a classification result for the possible lengths of $q^r$-divisible codes over $\mathbb{F}_q$. We also give a few computational results for field sizes $q>2$. Non-existence results of divisible codes with restricted column multiplici

Ganesh Prasath, Shirish Karande

Several decision problems that are encountered in various business domains can be modeled as mathematical programs, i.e. optimization problems. The process of conducting such modeling often requires the involvement of experts trained in operations research and advanced algorithms. Surprisingly, despite the significant advances in the methods for program and

Yuuki Hayashi, Go Mishima, Yukinari Sumino, Hiromasa Takaura

We determine $|V_{cb}|$ from the inclusive semileptonic decay width of the $B$ meson with the known N$^3$LO perturbative coefficients for the first time in the $\overline{\mathrm{MS}}$ mass scheme. We make use of a recently developed method, dual-space-renormalon-subtraction (DSRS) method, to separate and subtract the order $\Lambda_{\rm QCD}^2/m_b$ infrared

Andrés González de Castilla, Simon Müller, Irina Smirnova

We present a novel, thermodynamically consistent modification of the Pitzer-Debye-H\"uckel term and its extension for concentration dependent density, molar mass and relative permittivity. This extension is validated for ionic liquids by comparison with a reference model from the literature and, in contrast to similar extensions, also applied to conventional

Sifan Long, Zhen Zhao, Junkun Yuan, Zichang Tan

Prompt learning has become one of the most efficient paradigms for adapting large pre-trained vision-language models to downstream tasks. Current state-of-the-art methods, like CoOp and ProDA, tend to adopt soft prompts to learn an appropriate prompt for each specific task. Recent CoCoOp further boosts the base-to-new generalization performance via an image-

Andrés González de Castilla, Simon Müller, Irina Smirnova

The analogy between the restricted primitive model and capacitor circuits, originally described decades ago for the Mean Spherical Approximation, is explored to demonstrate its transferability in linearized electrolyte theories. On this basis, we offer an explanation of why treating the salt diameter as a free adjustable parameter blurs differences between e

Hang Du, Xuejun Yan, Jingjing Wang, Di Xie

Most existing approaches for point cloud normal estimation aim to locally fit a geometric surface and calculate the normal from the fitted surface. Recently, learning-based methods have adopted a routine of predicting point-wise weights to solve the weighted least-squares surface fitting problem. Despite achieving remarkable progress, these methods overlook

Nobuhiko Wakai, Satoshi Sato, Yasunori Ishii, Takayoshi Yamashita

A Manhattan world lying along cuboid buildings is useful for camera angle estimation. However, accurate and robust angle estimation from fisheye images in the Manhattan world has remained an open challenge because general scene images tend to lack constraints such as lines, arcs, and vanishing points. To achieve higher accuracy and robustness, we propose a l

Lei Qin, Michael Cantoni, Ye Pu

We study a fixed step-size noisy distributed gradient descent algorithm for solving optimization problems in which the objective is a finite sum of smooth but possibly non-convex functions. Random perturbations are introduced to the gradient descent directions at each step to actively evade saddle points. Under certain regularity conditions, and with a suita

Yuhang Li, Tianyi Gan, Bijie Bai, Cagatay Isil

Free-space optical information transfer through diffusive media is critical in many applications, such as biomedical devices and optical communication, but remains challenging due to random, unknown perturbations in the optical path. In this work, we demonstrate an optical diffractive decoder with electronic encoding to accurately transfer the optical inform

N. Karjanto

We investigated some difficulties that students often face when studying linear algebra at the undergraduate level, and identified some common mistakes and difficulties they often encountered when dealing with topics that require algorithmic thinking skills such as matrix factorization. In particular, we focused on (orthogonal) diagonalization and singular v

Nikolaos Mavredakis, Anibal Pacheco-Sanchez, Md Hasibul Alam, Anton Guimerà-Brunet

1/f noise is a critical figure of merit for the performance of transistors and circuits. For two-dimensional devices (2D-FETs), and especially for applications in the GHz range where short-channel FETs are required, velocity saturation (VS) effect can result in the reduction of 1/f noise at high longitudinal electric fields. A new physics-based compact model

Sid Wang, Akshat Shrivastava, Sasha Livshits

Autoregressive (AR) encoder-decoder neural networks have proved successful in many NLP problems, including Semantic Parsing -- a task that translates natural language to machine-readable parse trees. However, the sequential prediction process of AR models can be slow. To accelerate AR for semantic parsing, we introduce a new technique called TreePiece that t

M. Murabito, I. Ermolli, T. Chatzistergos, S. Jafarzadeh

We analysed state-of-the-art observations of the solar atmosphere to investigate the dependence of the \ca brightness of several solar features on spectral bandwidth and spatial resolution of the data. Specifically, we study data obtained at the Swedish Solar Telescope with the CRiSP and CHROMIS instruments. The analyzed data, which are characterized by spec

Andrés González de Castilla, Jan Philipp Bittner, Simon Müller, Sven Jakobtorweihen

Deep eutectic solvents (DESs) have gained attention in recent years as attractive alternatives to traditional solvents. There is a growing number of publications dealing with the thermodynamic modeling of DESs highlighting the importance of modeling the solutions' properties. In this review, we summarize the state-of-the-art in DES modeling as well as its cu

Kaiwen Cui, Yingchen Yu, Fangneng Zhan, Shengcai Liao

Generative Adversarial Networks (GANs) rely heavily on large-scale training data for training high-quality image generation models. With limited training data, the GAN discriminator often suffers from severe overfitting which directly leads to degraded generation especially in generation diversity. Inspired by the recent advances in knowledge distillation (K

Leonardo A. Poveda, Shubin Fu, Eric T. Chung, Lina Zhao

This paper presents and analyses a Constraint Energy Minimization Generalized Multiscale Finite Element Method (CEM-GMsFEM) for solving single-phase non-linear compressible flows in highly heterogeneous media. The construction of CEM-GMsFEM hinges on two crucial steps: First, the auxiliary space is constructed by solving local spectral problems, where the ba

Ranjita Naik, Besmira Nushi

Text-to-Image (T2I) generation is enabling new applications that support creators, designers, and general end users of productivity software by generating illustrative content with high photorealism starting from a given descriptive text as a prompt. Such models are however trained on massive amounts of web data, which surfaces the peril of potential harmful

Anqi Li, Byron Boots, Ching-An Cheng

We study a new paradigm for sequential decision making, called offline policy learning from observations (PLfO). Offline PLfO aims to learn policies using datasets with substandard qualities: 1) only a subset of trajectories is labeled with rewards, 2) labeled trajectories may not contain actions, 3) labeled trajectories may not be of high quality, and 4) th

Idan Schwartz, Vésteinn Snæbjarnarson, Hila Chefer, Ryan Cotterell

Recent advances in text-to-image diffusion models have enabled the generation of diverse and high-quality images. While impressive, the images often fall short of depicting subtle details and are susceptible to errors due to ambiguity in the input text. One way of alleviating these issues is to train diffusion models on class-labeled datasets. This approach

Duiliu-Emanuel Diaconescu, Mauro Porta, Francesco Sala, Arian Vosoughinia

Using pagoda flop transitions between smooth projective threefolds, a relation is derived between the Euler numbers of moduli spaces of stable pairs which are scheme-theoretically supported on a fixed singular space curve and Euler numbers of Flag Hilbert schemes associated to a plane curve singularity. When the space curve singularity is locally complete in

Minglei Lu, Ali Mohammadi, Zhaoxu Meng, Xuhui Meng

Additive manufacturing has been recognized as an industrial technological revolution for manufacturing, which allows fabrication of materials with complex three-dimensional (3D) structures directly from computer-aided design models. The mechanical properties of interpenetrating phase composites (IPCs), especially response to dynamic loading, highly depend on

Kanji Inui

In this paper, we reformulate the definition of the iterated function systems (denoted by general IFSs in this paper) and show the existence and uniqueness (in some sense) of the limit sets generated by the general IFSs, to unify the definitions of the limit sets introduced before. Note that the general IFSs are defined on (possibly unbounded) complete metri

Kai Chen, Zhili Liu, Lanqing Hong, Hang Xu

Masked Autoencoder (MAE) has demonstrated superior performance on various vision tasks via randomly masking image patches and reconstruction. However, effective data augmentation strategies for MAE still remain open questions, different from those in contrastive learning that serve as the most important part. This paper studies the prevailing mixing augmenta

Antonio Mastropietro, Francesco Vaccarino

In cooperative game theory, associated games allow for providing meaningful characterizations of solution concepts. Moreover, generalized values allow computing an influence or power index of each coalition in a game. In this paper, we view associated games through the lens of game maps and we define the novel Shapley-Hodge Game, briefly ``SHoGa''. We charac

Kunning Tang, Zhe Li, Ying Da Wang, James McClure

Electrokinetic in-situ recovery is an alternative to conventional mining, relying on the application of an electric potential to enhance the subsurface flow of ions. Understanding the pore-scale flow and ion transport under electric potential is essential for petrophysical properties estimation and flow behavior characterization. The governing physics of ele

Lin Hou, Tom J. P. Irons, Yanyong Wang, James W. Furness

In density functional theory the exchange-correlation (XC) energy functional can be defined exactly through the coupling-constant ($\lambda$) averaged XC hole $\bar{n}_\text{xc}(\mathbf{r},\mathbf{r}')$, representing the probability depletion of finding an electron at $\mathbf{r}$ due to an electron at $\mathbf{r}$. Accurate knowledge of $\bar{n}_\text{xc}(\

Hanlin Yu, N. A. Liedienov, I. V. Zatovsky, D. S. Butenko

Simultaneous study of magnetic and electrocatalytic properties of cobaltites under extreme conditions expands understanding of physical and chemical processes proceeding in them with the possibility of their further practical application. Therefore, La0.6Sr0.4CoO3 (LSCO) nanopowders have been synthesized at different annealing temperatures tann = 850, 875, 9

Jingyang Zhang, Yao Yao, Shiwei Li, Jingbo Liu

We present a novel differentiable rendering framework for joint geometry, material, and lighting estimation from multi-view images. In contrast to previous methods which assume a simplified environment map or co-located flashlights, in this work, we formulate the lighting of a static scene as one neural incident light field (NeILF) and one outgoing neural ra

Plamen G. Krastev

Understanding the equation of state of dense QCD matter remains a major challenge in both nuclear physics and astrophysics. Neutron star observations from electromagnetic and gravitational wave spectra provide critical insights into the behavior of dense neutron-rich matter. The next generation of telescopes and gravitational wave observatories will offer ev

Hiroyuki Ebata, Shio Inagaki

When granular mixtures of different sizes are fluidized, each species spontaneously separates and condenses to form patterns. Although granular segregation has been extensively studied, the inability to directly observe the time evolution of the internal structure hinders the understanding of the mechanism of segregation dynamics driven by surface flow. In t

Jun-Yan He, Zhi-Qi Cheng, Chenyang Li, Wangmeng Xiang

Real-time perception, or streaming perception, is a crucial aspect of autonomous driving that has yet to be thoroughly explored in existing research. To address this gap, we present DAMO-StreamNet, an optimized framework that combines recent advances from the YOLO series with a comprehensive analysis of spatial and temporal perception mechanisms, delivering

Anubhab Roy, Stefan Kramel, Udayshankar Menon, Greg A. Voth

We present experimental and computational results for the orientation distributions of slender fibers and ramified particles settling in an isotropic turbulent flow. The rotational dynamics of the particles is modeled using a slender-body theory that includes the inertial torque due to sedimentation that tends to rotate the particles toward a broadside orien

Chongjian Ge, Jiangliu Wang, Zhan Tong, Shoufa Chen

Contrastive learning methods train visual encoders by comparing views from one instance to others. Typically, the views created from one instance are set as positive, while views from other instances are negative. This binary instance discrimination is studied extensively to improve feature representations in self-supervised learning. In this paper, we rethi

Patrick Marcel, Veronika Peralta, Faten El Outa, Panos Vassiliadis

This vision paper lays the preliminary foundations for Data Narrative Management Systems (DNMS), systems that enable the storage, sharing, and manipulation of data narratives. We motivate the need for such formal foundations and introduce a simple logical framework inspired by the relational model. The core of this framework is a Data Narrative Manipulation

Bo Tan, Qing-Long Zhou

The metrical theory of the product of consecutive partial quotients is associated with the uniform Diophantine approximation, specifically to the improvements to Dirichlet's theorem. Achieving some variant forms of metrical theory in continued fractions, we study the distribution of the at least two large partial quotients with product forms among the first

Emil J. Martinec

Radiation of conserved charges carried by a black hole is a rare process, whose probability is suppressed by the change in the entropy between the initial and final states. This universal result provides insight into the black hole's internal structure and dynamics.

Shinichi Saito

Polarisation states are described by spin expectation values, known as Stokes parameters, whose trajectories in a rotationally symmetric system form a sphere named after Poincar\'e. Here, we show that the trajectories of broken rotational symmetric systems can exhibit distinct topological structures in polarisation states. We use a phase-shifter to form a po

Sarah Allred, Emelie Curl, Shaun Fallat, Shahla Nasserasr

The utility of a matrix satisfying the Strong Spectral Property has been well established particularly in connection with the inverse eigenvalue problem for graphs. More recently the class of graphs in which all associated symmetric matrices possess the Strong Spectral Property (denoted $G^{SSP}$) were studied, and along these lines we aim to study propertie

Binbin Li, Xinyu Du, Yao Hu, Hao Yu

Online camera-to-ground calibration is to generate a non-rigid body transformation between the camera and the road surface in a real-time manner. Existing solutions utilize static calibration, suffering from environmental variations such as tire pressure changes, vehicle loading volume variations, and road surface diversity. Other online solutions exploit th

Shinichi Saito

Polarisation is described by an $SU(2)$ wavefunction due to macroscopic coherence of photons emitted from a ubiquitous laser source, and thus, a laser pulse is expected to behave as a macroscopic quantum bit (qubit), i.e., a qubit realised by a macroscopic number of photons. Here, we show that an arbitrary single-qubit operation can be carried out for such a

M. Ohno, T. C. Fujita, M. Kawasaki

We present an epitaxial stabilization of pyrochlore Bi$_2$Rh$_2$O$_7$ on Y-stabilized ZrO$_2$ (YSZ) (111) substrate by inserting a pyrochlore Eu$_2$Ti$_2$O$_7$ template layer, otherwise Bi-based layered structures being formed directly on YSZ (111) substrate. This result reveals that "iso-structural crystal phase" plays an important role in the interfacial p

Shinichi Saito

Lie algebra is a hidden mathematical structure behind various quantum systems realised in nature. Here, we consider $SU(2)$ wavefunctions for polarisation states of coherent photons emitted from a laser source, and discuss the relationship to spin expectation values with SO(3) symmetry based on isomorphism theorems. In particular, we found rotated half-wave-

Kahlil Y. Dixon, Terry A. Loring, Alexander Cerjan

Photonic topological insulators exhibit bulk-boundary correspondence, which requires that boundary-localized states appear at the interface formed between topologically distinct insulating materials. However, many topological photonic devices share a boundary with free space, which raises a subtle but critical problem as free space is gapless for photons abo

Dmitry Kleinbock, Baowei Wang

In this paper, we present a general principle for the Lebesgue measure theory of limsup sets defined by rectangles under the hypothesis of ubiquity for rectangles.

Bo Han Chen, Tetsuya Hashimoto, Tomotsugu Goto, Bjorn Jasper R. Raquel

Fast radio bursts (FRBs) are astronomical transients with millisecond timescales. Although most of the FRBs are not observed to repeat, a few of them are detected to repeat more than hundreds of times. There exist a large variety of physical properties among these bursts, suggesting heterogeneous mechanisms of FRBs. In this paper, we conduct a categorisation

Nazmul Karim, Niluthpol Chowdhury Mithun, Abhinav Rajvanshi, Han-pang Chiu

Unsupervised domain adaptation (UDA) approaches focus on adapting models trained on a labeled source domain to an unlabeled target domain. UDA methods have a strong assumption that the source data is accessible during adaptation, which may not be feasible in many real-world scenarios due to privacy concerns and resource constraints of devices. In this regard

Shinichi Saito

The speed of light ($c$) in a vacuum is independent on a choice of frames to describe the propagation, according to the theory of relativity. We consider how light is characterised in a material, where the speed of light is different from that in a vacuum due to the finite dielectric constant. The phase velocity in a material is smaller than $c$, such that t

Rahul Pandey, Roger Ren, Qi Luo, Jing Liu

End-to-End (E2E) automatic speech recognition (ASR) systems used in voice assistants often have difficulties recognizing infrequent words personalized to the user, such as names and places. Rare words often have non-trivial pronunciations, and in such cases, human knowledge in the form of a pronunciation lexicon can be useful. We propose a PROnunCiation-awar

Justin Diamond, Ben Garcia

"Egyptian Ratscrew" (ERS) is a modern American card game enjoyed by millions of players worldwide. A game of ERS is won by collecting all of the cards in the deck. Typically this game is won by the player with the fastest reflexes, since the most common strategy for collecting cards is being the first to slap the pile in the center whenever legal combination

Shinichi Saito

Spin is a fundamental degree of freedom, whose existence was proven by Dirac for an electron by imposing the relativity to quantum mechanics, leading to the triumph to derive the Dirac equation. Spin of a photon should be linked to polarisation, however, the similar argument for an electron was not applicable to Maxwell equations, which are already Lorentz i

Xavier Lawrence D. Mendoza

The study was designed to determine the entrepreneurial capability and engagement of persons with disabilities toward a framework for inclusive entrepreneurship. The researcher used descriptive and correlational approaches through purposive random sampling. The sample came from the City of General Trias and the Municipality of Rosario, registered under their

Shinichi Saito

Spin angular momentum of a photon corresponds to a polarisation degree of freedom of lights, and such that various polarisation properties are coming from macroscopic manifestation of quantum-mechanical properties of lights. An orbital degree of freedom of lights is also manipulated to form a vortex of lights with orbital angular momentum, which is also quan

Jonathan P. Marshall, Julien Milli, Elodie Choquet, Carlos del Burgo

Planetesimals -- asteroids and comets -- are the building blocks of planets in protoplanetary discs and the source of dust, ice and gas in debris discs. Along with planets they comprise the left-over material after star formation that constitutes a planetary system. Planets influence the dynamics of planetesimals, sculpting the orbits of debris belts to prod

Ravshan Ashurov, Yusuf Fayziev, Muattar Khudoykulova

In this paper, we consider forward and inverse problems for subdiffusion equations with time-dependent coefficients. The fractional derivative is taken in the sense of Riemann-Liouville. Using the classical Fourier method, the theorem of the uniqueness and existence of forward and inverse problems for determining the right-hand side of the equation are prove

Thalaiyasingam Ajanthan, Matt Ma, Anton van den Hengel, Stephen Gould

Metric learning is a fundamental problem in computer vision whereby a model is trained to learn a semantically useful embedding space via ranking losses. Traditionally, the effectiveness of a ranking loss depends on the minibatch size, and is, therefore, inherently limited by the memory constraints of the underlying hardware. While simply accumulating the em

Yongpin Zhu

In \cite{Zhu}, the authors give a general definition of K\"ahler angle. There are many results about K\"ahler angle one can try to generalize to the general case. In this paper, we focus on the symplectic critical surfaces in Hermite surfaces which is a generalization of \cite{HL1} or \cite{HLS1}.

Jenny T. Liang, Chenyang Yang, Brad A. Myers

The software engineering community recently has witnessed widespread deployment of AI programming assistants, such as GitHub Copilot. However, in practice, developers do not accept AI programming assistants' initial suggestions at a high frequency. This leaves a number of open questions related to the usability of these tools. To understand developers' pract

Geoffrey Compère, Samuel E. Gralla, Hongji Wei

Asymptotically flat spacetimes have been studied in five separate regions: future/past timelike infinity $i^\pm$, future/past null infinity $\mathcal{I}^\pm$, and spatial infinity $i^0$. We formulate assumptions and definitions such that the five infinities share a single Bondi-Metzner-Sachs (BMS) group of asymptotic symmetries and associated charges. We sho

Chang Jiang, Fei Gao, Biao Ma, Yuhao Lin

We present a novel framework for exemplar based image translation. Recent advanced methods for this task mainly focus on establishing cross-domain semantic correspondence, which sequentially dominates image generation in the manner of local style control. Unfortunately, cross-domain semantic matching is challenging; and matching errors ultimately degrade the

Yongpin Zhu

In this paper, we give a general definition of Kahler angle. There are many results about Kahler angle one can try to generalize to the general case.

Takamasa Kanai, Kimihiro Nomura, Daisuke Yoshida

Bousso's entropy bound is a conjecture that the entropy through a null hypersurface emanating from a two-dimensional surface with a nonpositive expansion is bounded by the area of that two-dimensional surface. We investigate the validity of Bousso's entropy bound in the spatially flat, homogeneous, and isotropic universe with an adiabatic entropy current. We

Mani Valleti, Yongtao Liu, Sergei Kalinin

Electron, optical, and scanning probe microscopy methods are generating ever increasing volume of image data containing information on atomic and mesoscale structures and functionalities. This necessitates the development of the machine learning methods for discovery of physical and chemical phenomena from the data, such as manifestations of symmetry breakin

Kieran Ricardo, David Lee, Kenneth Duru

We develop a novel and efficient discontinuous Galerkin spectral element method (DG-SEM) for the spherical rotating shallow water equations in vector invariant form. We prove that the DG-SEM is energy stable, and discretely conserves mass, vorticity, and linear geostrophic balance on general curvlinear meshes. These theoretical results are possible due to ou

Hao An, Dongsheng Chen, Weiyuan Xu, Zhihong Zhu

Dialogue-based Relation Extraction (DRE) aims to predict the relation type of argument pairs that are mentioned in dialogue. The latest trigger-enhanced methods propose trigger prediction tasks to promote DRE. However, these methods are not able to fully leverage the trigger information and even bring noise to relation extraction. To solve these problems, we

Deepraj Soni, Negar Neda, Naifeng Zhang, Benedict Reynwar

Ring-Learning-with-Errors (RLWE) has emerged as the foundation of many important techniques for improving security and privacy, including homomorphic encryption and post-quantum cryptography. While promising, these techniques have received limited use due to their extreme overheads of running on general-purpose machines. In this paper, we present a novel vec

Chengliang Liu, Jie Wen, Yong Xu, Bob Zhang

As a cross-topic of multi-view learning and multi-label classification, multi-view multi-label classification has gradually gained traction in recent years. The application of multi-view contrastive learning has further facilitated this process, however, the existing multi-view contrastive learning methods crudely separate the so-called negative pair, which

Shinichi Saito

Orbital Angular Momentum (OAM) of photons are already ubiquitously being used for numerous applications. However, there is a fundamental question whether photonic OAM operators satisfy standard quantum mechanical commutation relationship or not; this also poses a serious concern on the interpretation of an optical vortex as a fundamental quantum degree of fr

Matthew McMillan

In a recent paper, the author defined an operation of tensor product for a large class of $2$-representations of $\mathcal{U}^{+}$, the positive half of the $2$-category associated to $\mathfrak{sl}_{2}$. In this paper, we prove that the operation extends to give an operation of tensor product for $2$-representations of the full $2$-category $\mathcal{U}$: w

Yinqiu Liu, Hongyang Du, Dusit Niyato, Jiawen Kang

With the phenomenal success of diffusion models and ChatGPT, deep generation models (DGMs) have been experiencing explosive growth from 2022. Not limited to content generation, DGMs are also widely adopted in Internet of Things, Metaverse, and digital twin, due to their outstanding ability to represent complex patterns and generate plausible samples. In this

Jiwoong Jang

In this paper, we obtain the rate $O(\varepsilon^{1/2})$ of convergence in periodic homogenization of forced graphical mean curvature flows in the laminated setting. We also discuss with an example that a faster rate cannot be obtained by utilizing Lipscthiz estimates.

Shinichi Saito

Stokes parameters (${\bf S}$) in Poincar\'e sphere are very useful values to describe the polarisation state of photons. However, the fundamental principle of the nature of polarisation is not completely understood, yet, because we have no concrete consensus how to describe spin of photons, quantum-mechanically. Here, we have considered a monochromatic coher

Chunzhi Yi, Xiaolei Sun, Chunyu Zhang, Wei Jin

Assessing the progression of muscle fatigue for daily exercises provides vital indicators for precise rehabilitation, personalized training dose, especially under the context of Metaverse. Assessing fatigue of multi-muscle coordination-involved daily exercises requires the neuromuscular features that represent the fatigue-induced characteristics of spatiotem

Xiao Guo, Xiaohong Liu, Zhiyuan Ren, Steven Grosz

Differences in forgery attributes of images generated in CNN-synthesized and image-editing domains are large, and such differences make a unified image forgery detection and localization (IFDL) challenging. To this end, we present a hierarchical fine-grained formulation for IFDL representation learning. Specifically, we first represent forgery attributes of

Xutong Liu, Jinhang Zuo, Siwei Wang, John C. S. Lui

We study contextual combinatorial bandits with probabilistically triggered arms (C$^2$MAB-T) under a variety of smoothness conditions that capture a wide range of applications, such as contextual cascading bandits and contextual influence maximization bandits. Under the triggering probability modulated (TPM) condition, we devise the C$^2$-UCB-T algorithm and

Anant Raj, Umut Şimşekli, Alessandro Rudi

This paper deals with the problem of efficient sampling from a stochastic differential equation, given the drift function and the diffusion matrix. The proposed approach leverages a recent model for probabilities \cite{rudi2021psd} (the positive semi-definite -- PSD model) from which it is possible to obtain independent and identically distributed (i.i.d.) s

Haoqiang Wang, Zihan Zang, Yunpeng Xu, Yanjun Han

A universal and flexible design method for freeform surface that can modulate the distribution of an zero-\'etendue source to an arbitrary irradiance distribution is a significant challenge in the field of non-imaging optics. Current design methods typically formulate the problem as a partial differential equation and solve it through sophisticated numerical