August 2022 arXiv papers — page 18

Ashok P, Yogesh Singh Chauhan, Amit Verma

Phase transition materials are promising for realization of switchable optics. In this work, we show reflectance resonances in the near-infrared and long-wave infrared wavelengths in highly subwavelength partially oxidized Vanadium thin films. These partially oxidized films consist of a multilayer of Vanadium dioxide and Vanadium as shown using Raman spectro

Florian Schorn, Arabella Essert, Yu Zhong, Sahib Abdullayev

We report an opto-fluidic method that enables to efficiently measure the enantiomeric excess of chiral molecules at low concentration. The approach is to monitor the optical activity induced by a Kagome-lattice hollow-core photonic crystal fiber filled with a sub-ul volume of chiral compound. The technique also allows monitoring the enzymatic racemization of

Luisa Greifenstein, Isabella Graßl, Ute Heuer, Gordon Fraser

Computational thinking is increasingly introduced at primary school level, usually with some form of programming activity. In particular, educational robots provide an opportunity for engaging students with programming through hands-on experiences. However, primary school teachers might not be adequately prepared for teaching computer science related topics,

William R Dunn

The Jovian system is a treasure trove of X-ray sources: diverse and dynamic atmospheric and auroral emissions, diffuse radiation belt and Io torus emissions, and plasma-surface interactions with Jupiter's moons. The system is a rich natural laboratory for astronomical X-rays with each region showcasing its own X-ray production processes: scattering and fluor

Shubo Kang, Keyou You

In a direct data-driven approach, this paper studies the {\em property identification(ID)} problem to analyze whether an unknown linear system has a property of interest, e.g., stabilizability and structural properties. In sharp contrast to the model-based analysis, we approach it by directly using the input and state feedback data of the unknown system. Via

Qing Yin, Hui Fang, Zhu Sun, Yew-Soon Ong

Current session-based recommender systems (SBRSs) mainly focus on maximizing recommendation accuracy, while few studies have been devoted to improve diversity beyond accuracy. Meanwhile, it is unclear how the accuracy-oriented SBRSs perform in terms of diversity. Besides, the asserted "trade-off" relationship between accuracy and diversity has been increasin

A. N. Kirdin, S. V. Sidorov, N. Y. Zolotykh

First Rosenblatt's theorem about omnipotence of shallow networks states that elementary perceptrons can solve any classification problem if there are no discrepancies in the training set. Minsky and Papert considered elementary perceptrons with restrictions on the neural inputs: a bounded number of connections or a relatively small diameter of the receptive

Francesco Scotognella

The optical properties of vanadium dioxide ($VO_2$) can be tuned via metal-insulator transition. In this work different types of one-dimensional photonic structure-based microcavities that embed vanadium dioxide have been studied in the spectral range between 900 nm and 2000 nm. In particular, $VO_2$ has been sandwiched between: i) two photonic crystals made

Xiong Yunuo, Xiong Hongwei

The exchange antisymmetry between identical fermions gives rise to the well known fermion sign problem, in the form of large cancellation between positive and negative contribution to the partition function, making any simulation methods which directly sample this partition function exponentially difficult to converge. In this work, we employ path integral m

Florian Obermüller, Robert Pernerstorfer, Lisa Bailey, Ute Heuer

Programmable robots are engaging and fun to play with, interact with the real world, and are therefore well suited to introduce young learners to programming. Introductory robot programming languages often extend existing block-based languages such as Scratch. While teaching programming with such languages is well established, the interaction with the real w

Mirko Fischer, Andreas Heuer, Diddo Diddens

We present an extensive molecular dynamics (MD) simulation study of poly(ethylene oxide) (PEO) based densely cross-linked polymers, focussing on structural properties as well as the systems dynamics in the presence of lithium salt. Motivated by experimental findings for networks with short PEO strands we employ a combination of LiTFSI (Lithium bis(trifluorom

Mher Davtyan

Media with symmetric inhomogeneity have been of great interest due to numerous effects which occur when electromagnetic waves propagate through such media. In general, the inhomogeneity of a certain medium means that the refraction index of the medium is not constant and has some sort of spatial dependency. These types of media are called gradient index (GRI

Thomas Dreyfus, Marina Poulet

In this paper we consider the problem of computing the difference Galois groups of order three equations for a large class of difference operators including the shift operator (Case S), the $q$-difference operator (Case Q), the Mahler operator (Case M) and the elliptic case (Case E). We show that the general problem can be reduced to several ancillary proble

Isabella Graßl, Gordon Fraser

Since computer science is still mainly male dominated, academia, industry and education jointly seek ways to motivate and inspire girls, for example by introducing them to programming at an early age. The recent COVID-19 pandemic has forced many such endeavours to move to an online setting. While the gender-dependent differences in programming courses have b

Sabine Cornelsen, Gregor Diatzko

In a planar confluent orthogonal drawing (PCOD) of a directed graph (digraph) vertices are drawn as points in the plane and edges as orthogonal polylines starting with a vertical segment and ending with a horizontal segment. Edges may overlap in their first or last segment, but must not intersect otherwise. PCODs can be seen as a directed variant of Kandinsk

Christian Biefel, Martin Schmidt

We consider adjustable robust linear complementarity problems and extend the results of Biefel et al. (2022) towards convex and compact uncertainty sets. Moreover, for the case of polyhedral uncertainty sets, we prove that computing an adjustable robust solution of a given linear complementarity problem is equivalent to solving a properly chosen mixed-intege

Kelvin Titimbo, David C. Garrett, S. Süleyman Kahraman, Zhe He

We numerically study the spin flip in the Frisch$\unicode{x2013}$Segr\`e experiment, the first multi-stage Stern$\unicode{x2013}$Gerlach experiment, within the context of the novel co-quantum dynamics theory. We model the middle stage responsible for spin rotation by sampling the atoms with the Monte Carlo method and solving the dynamics of the electron and

Nikolai Meshcheriakov, Victoria Shatalova, Konstantin Stepanyantz

For renormalizable theories with a single coupling constant regularized by higher derivatives we investigate the coefficients at powers of logarithms present in the renormalization constants assuming that divergences are removed by minimal subtractions of logarithms. According to this (HD+MSL) renormalization prescription the renormalization constants includ

Zihan Lin, Xuanhua Yang, Xiaoyu Peng, Wayne Xin Zhao

In modern advertising and recommender systems, multi-task learning (MTL) paradigm has been widely employed to jointly predict diverse user feedbacks (e.g. click and purchase). While, existing MTL approaches are either rigid to adapt to different scenarios, or only capture coarse-grained task relatedness, thus making it difficult to effectively transfer knowl

Zhitong Lai, Haichao Sun, Rui Tian, Nannan Ding

Skip connections are fundamental units in encoder-decoder networks, which are able to improve the feature propagtion of the neural networks. However, most methods with skip connections just connected features with the same resolution in the encoder and the decoder, which ignored the information loss in the encoder with the layers going deeper. To leverage th

Santosh K. Das, Prabhakar Palni, Jhuma Sannigrahi, Jan-e Alam

The discovery and characterization of hot and dense QCD matter, known as Quark Gluon Plasma (QGP), remains the most international collaborative effort and synergy between theorists and experimentalists in modern nuclear physics to date. The experimentalists around the world not only collect an unprecedented amount of data in heavy-ion collisions, at Relativi

David Mogalle, Philipp Seufert, Jan Schwientek, Michael Bortz

Modeling real processes often results in several suitable models. In order to be able to distinguish, or discriminate, which model best represents a phenomenon, one is interested, e.g., in so-called T-optimal designs. These consist of the (design) points from a generally continuous design space at which the models deviate most from each other, under the cond

Philipp Reiser, David J. Wraith

We consider intermediate Ricci curvatures $Ric_k$ on a closed Riemannian manifold $M^n$. These interpolate between the Ricci curvature when $k=n-1$ and the sectional curvature when $k=1$. By establishing a surgery result for Riemannian metrics with $Ric_k>0$, we show that Gromov's upper Betti number bound for sectional curvature bounded below fails to hold f

Andrzej Herdegen

The purpose of this note is threefold: (i) to recall (with some points made more explicit) the mathematical Weyl algebra model formulation, given before, of the Staruszkiewicz theory of quantum Coulomb field; (ii) to add some new elements to the discussion of the representation of the Lorentz group within this model; (iii) to comment on some statements on th

Yifeng Zhou, Chuming Lin, Donghao Luo, Yong Liu

To achieve promising results on blind image super-resolution (SR), some attempts leveraged the low resolution (LR) images to predict the kernel and improve the SR performance. However, these Supervised Kernel Prediction (SKP) methods are impractical due to the unavailable real-world blur kernels. Although some Unsupervised Degradation Prediction (UDP) method

Bohui Wang, Rong Su

This article studies the problems of distributed dynamic platoons control and smart junction crossing optimization for a mixed traffic flow with connected automated vehicles(CAVs) and social human-driven vehicles(HDVs) in a smart city. The goal of this two-part article is to provide an automatic decision framework to ensure the safe and efficient cruising an

Ali Kashefi, Tapan Mukerji

We predict steady-state Stokes flow of fluids within porous media at pore scales using sparse point observations and a novel class of physics-informed neural networks, called "physics-informed PointNet" (PIPN). Taking the advantages of PIPN into account, three new features become available compared to physics-informed convolutional neural networks for porous

Boxi Wu, Jie Jiang, Haidong Ren, Zifan Du

Deep neural network, despite its remarkable capability of discriminating targeted in-distribution samples, shows poor performance on detecting anomalous out-of-distribution data. To address this defect, state-of-the-art solutions choose to train deep networks on an auxiliary dataset of outliers. Various training criteria for these auxiliary outliers are prop

Xiaorang Guo, MohammadAli Shaeri, Mahsa Shoaran

Spike detection plays a central role in neural data processing and brain-machine interfaces (BMIs). A challenge for future-generation implantable BMIs is to build a spike detector that features both low hardware cost and high performance. In this work, we propose a novel hardware-efficient and high-performance spike detector for implantable BMIs. The propose

Bastien Chaudet-Dumas

This work deals with shape optimization for contact mechanics. More specifically, the linear elasticity model is considered under the small deformations hypothesis, and the elastic body is assumed to be in contact (sliding or with Tresca friction) with a rigid foundation. The mathematical formulations studied are two regularized versions of the original vari

Yuanhan Ni, Zulin Wang, Peng Yuan, Qin Huang

This paper considers an affine frequency division multiplexing (AFDM)-based integrated sensing and communications (ISAC) system, where the AFDM waveform is used to simultaneously carry communications information and sense targets. To realize AFDM-based sensing functionality, two parameter estimation methods are designed to process echoes in the time domain a

Yu Wang, Wujun Xie, Haochang Chen, David Day-Uei Li

A high-resolution time-to-digital converter (TDC) based on wave union (four-edge WU A), dual-sampling, and sub-TDL methods is proposed and implemented in a 16-nm Xilinx UltraScale+ field-programmable gate array (FPGA). We combine WU and dual-sampling techniques to achieve a high resolution. Besides, we use the sub-TDL method and the proposed bidirectional en

Sergey Koshkarev, Stefan Groote

Using the GS09 model we predict the possible impact of the parton momentum correlation on the $J/\psi$-pair production at the Spin Physics Detector at the Nuclotron-based Ion Collider Facility. The double $J/\psi$ production and the effective cross sections are calculated.

Andrej Dudenhefner

Semi-unification is the combination of first-order unification and first-order matching. The undecidability of semi-unification has been proven by Kfoury, Tiuryn, and Urzyczyn in the 1990s by Turing reduction from Turing machine immortality (existence of a diverging configuration). The particular Turing reduction is intricate, uses non-computational principl

Sun Woo Park, Yun Young Choi, Dosang Joe, U Jin Choi

This paper presents the Persistent Weisfeiler-Lehman Random walk scheme (abbreviated as PWLR) for graph representations, a novel mathematical framework which produces a collection of explainable low-dimensional representations of graphs with discrete and continuous node features. The proposed scheme effectively incorporates normalized Weisfeiler-Lehman proce

Krzysztof Domino, Jarosław Adam Miszczak

Opinion formation is one of the most fascinating phenomena observed in human communities, and the ability to predict and to control the dynamics of this process is interesting from the theoretical as well as practical point of view. Although there are many sophisticated models of opinion formation, they often lack the connection with real life data, and ther

Bohui Wang, Rong Su, Yun Lu, Lingyin Huang

The unknown sharp changes of vehicle acceleration rates, also called the unknown jerk dynamics, may significantly affect the driving performance of the leader vehicle in a platoon, resulting in more drastic car-following movements in platooning tracking control, which could cause safety and traffic capacity concerns. To address these issues, in this paper, w

Stefano M. Nicoletti, E. Moritz Hahn, Marielle Stoelinga

Safety-critical infrastructures must operate safely and reliably. Fault tree analysis is a widespread method used to assess risks in these systems: fault trees (FTs) are required - among others - by the Federal Aviation Authority, the Nuclear Regulatory Commission, in the ISO26262 standard for autonomous driving and for software development in aerospace syst

Xuekai Zhu, Jian Guan, Minlie Huang, Juan Liu

Non-parallel text style transfer is an important task in natural language generation. However, previous studies concentrate on the token or sentence level, such as sentence sentiment and formality transfer, but neglect long style transfer at the discourse level. Long texts usually involve more complicated author linguistic preferences such as discourse struc

Michel Frising, Jorge Bravo-Abad, Ferry Prins

Inverse design, the process of matching a device or process parameters to exhibit a desired performance, is applied in many disciplines ranging from material design over chemical processes and to engineering. Machine learning has emerged as a promising approach to overcome current limitations imposed by the dimensionality of the parameter space and multimoda

Hao Xu, Bo Li, Fei Zhong

Fire-detection technology is of great importance for successful fire-prevention measures. Image-based fire detection is one effective method. At present, object-detection algorithms are deficient in performing detection speed and accuracy tasks when they are applied in complex fire scenarios. In this study, a lightweight fire-detection algorithm, Light-YOLOv

Johan Bergelin, Per Erik Strandberg

There is an increasing interest in research on the combination of AI techniques and methods with MDE. However, there is a gap between AI and MDE practices, as well as between researchers and practitioners. This paper tackles this gap by reporting on industrial requirements in this field. In the AIDOaRt research project, practitioners and researchers collabor

Anshul Prajapati, Punit Sharma

We derive computable formulas for the structured backward errors of a complex number $\lambda$ when considered as an approximate eigenvalue of rational matrix polynomials that carry a symmetry structure. We consider symmetric, skew-symmetric, T-even, T-odd, Hermitian, skew-Hermitian, $*$-even, $*$-odd, and $*$-palindromic structures. Numerical experiments sh

Ilan Shlesinger, Isabelle M. Palstra, A. Femius Koenderink

In analogy to cavity optomechanics, enhancing specific sidebands of a Raman process with narrowband optical resonators would allow for parametric amplification, entanglement of light and molecular vibrations, and reduced transduction noise. We report on the demonstration of waveguide-addressable sideband-resolved surface-enhanced Raman scattering (SERS). We

Jiehui Zhou, Xumeng Wang, Jason K. Wong, Huanliang Wang

Data privacy is an essential issue in publishing data visualizations. However, it is challenging to represent multiple data patterns in privacy-preserving visualizations. The prior approaches target specific chart types or perform an anonymization model uniformly without considering the importance of data patterns in visualizations. In this paper, we propose

Xiaoyu Sun, Xiao Chen, Yanjie Zhao, Pei Liu

Despite being one of the largest and most popular projects, the official Android framework has only provided test cases for less than 30% of its APIs. Such a poor test case coverage rate has led to many compatibility issues that can cause apps to crash at runtime on specific Android devices, resulting in poor user experiences for both apps and the Android ec

Chen Li

A smart home energy dataset that records miscellaneous energy consumption data is publicly offered. The proposed energy activity dataset (EAD) has a high data type diversity in contrast to existing load monitoring datasets. In EAD, a simple data point is labeled with the appliance, brand, and event information, whereas a complex data point has an extra appli

Rui Zhong, Masaharu Munetomo

In this paper, we propose a variable grouping method based on cooperative coevolution for large-scale multi-objective problems (LSMOPs), named Linkage Measurement Minimization (LMM). And for the sub-problem optimization stage, a hybrid NSGA-II with a Gaussian sampling operator based on an estimated convergence point is proposed. In the variable grouping stag

Peng Wu, Lipeng Gu, Xuefeng Yan, Haoran Xie

Large imbalance often exists between the foreground points (i.e., objects) and the background points in outdoor LiDAR point clouds. It hinders cutting-edge detectors from focusing on informative areas to produce accurate 3D object detection results. This paper proposes a novel object detection network by semantical point-voxel feature interaction, dubbed PV-

Bastien Chaudet-Dumas

This thesis deals with shape optimization for contact mechanics. More specifically, the linear elasticity model is considered under the small deformations hypothesis, and the elastic body is assumed to be in contact (sliding or with Tresca friction) with a rigid foundation. The mathematical formulations studied are two regularized versions of the original va

Bohui Wang, Rong Su

Connected automated vehicles (CAVs) have brought new opportunities to improve traffic throughput and reduce energy consumption. However, the uncertain lane-change behaviors (LCBs) of surrounding vehicles (SVs) as an uncontrollable factor significantly threaten the driving safety and the consistent movement of a group of platoon CAVs. How to ensure safe, effi

Zhen-Hua Zhang, Jing-Juan Qi

We introduce a set of observables representing angular distribution asymmetries, which can be viewed as a generalization of the forward-backward asymmetry of angular distributions, and can be used as an effective tool to search for $C\!P$ violation in three-body decays of bottom and charmed baryons. We propose to search for such $C\!P$ asymmetries (1) in dec

Nuttamas Tubsrinuan, Jared H. Cole, Per Delsing, Gustav Andersson

Frequency instabilities are a major source of errors in quantum devices. This study investigates frequency fluctuations in a surface acoustic wave (SAW) resonator, where reflection coefficients of 14 SAW modes are measured simultaneously for more than seven hours. We report two distinct noise characteristics. Multimode frequency noise caused by interactions

Bastien Chaudet

This work is in the field of multi-material compressible fluid flows simulation. The proposed scheme is eulerian and related to finite volumes methods, but in a Lagrange-Remap formalism on regular orthogonal meshes. The Lagrangian scheme is staggered and the remap phase is similar to a finite volume advection scheme. The multi-material extension uses classic

Jeremy Bourhill, Weichao Yu, Vincent Vlaminck, Gerrit E. W. Bauer

We experimentally realize circularly polarised unidirectional cavity magnon polaritons in a torus-shaped microwave cavity loaded by a small magnetic sphere. At special positions the clockwise and counterclockwise modes are circularly polarized, such that only one of them couples to the magnet, which breaks the mode degeneracy. We reveal the chiral nature of

Jingzhou Sun

We talk about the image of the Hilbert map. We show the necessary and sufficient condition that the Hilbert map is surjective.

Takahiro Hayakawa, Yasuo Fukui

We derived the dust-to-HI ratio of the intermediate-velocity clouds (IVCs), the high-velocity clouds (HVCs), and the local HI gas, by carrying out a multiple-regression analysis of the 21cm HI emission combined with the sub-mm dust optical depth. The method covers over 80 per cent of the sky contiguously at a resolution of 47arcmin and is distinguished from

Md. Rezaul Karim, Md. Shajalal, Alex Graß, Till Döhmen

Deep neural networks (DNNs) have been shown to outperform traditional machine learning algorithms in a broad variety of application domains due to their effectiveness in modeling complex problems and handling high-dimensional datasets. Many real-life datasets, however, are of increasingly high dimensionality, where a large number of features may be irrelevan

Junjie Hu, Chenyou Fan, Mete Ozay, Hua Feng

We study a practical yet hasn't been explored problem: how a drone can perceive in an environment from different flight heights. Unlike autonomous driving, where the perception is always conducted from a ground viewpoint, a flying drone may flexibly change its flight height due to specific tasks, requiring the capability for viewpoint invariant perception. T

Mara Graziani, Niccolò Marini, Nicolas Deutschmann, Nikita Janakarajan

Interpretability of deep learning is widely used to evaluate the reliability of medical imaging models and reduce the risks of inaccurate patient recommendations. For models exceeding human performance, e.g. predicting RNA structure from microscopy images, interpretable modelling can be further used to uncover highly non-trivial patterns which are otherwise

Koki Suetsugu

In combinatorial game theory, the lower and upper bounds of the number of games born by day $4$ have been recognized as $3.0 \cdot 10^{12}$ and $10^{434}$, respectively. In this study, we improve the lower bound to $10^{28.2}$ and the upper bound to $4.0 \cdot 10^{184}$, respectively.

Xiaolong Li, Kui Wang

We investigate the heat kernel with Robin boundary condition and prove comparison theorems for heat kernel on geodesic balls and on minimal submanifolds. We also prove an eigenvalue comparison theorem for the first Robin eigenvalues on minimal submanifolds. This generalizes corresponding results for the Dirichlet and Neumann heat kernels.

Zixuan Li, Jingtao Shi

This paper is concerned with the stochastic linear-quadratic optimal control problem with Poisson jumps. The coefficients in the state equation and the weighting matrices in the cost functional are all deterministic but are allowed indefinite. The notion of closed-loop strategies is introduced, and the optimal closed-loop strategy is characterized by a Ricca

Biying Fu, Naser Damer

Biases inherent in both data and algorithms make the fairness of widespread machine learning (ML)-based decision-making systems less than optimal. To improve the trustfulness of such ML decision systems, it is crucial to be aware of the inherent biases in these solutions and to make them more transparent to the public and developers. In this work, we aim at

Alexandru Dimca, Piotr Pokora

The aim of this paper is to provide a direct link between maximizing curves that occur in the construction of smooth algebraic surfaces having the maximal possible Picard numbers and reduced free plane curves with simple singularities. We also investigate odd degree plane curves with simple singularities having maximal total Tjurina number.

P. Colangelo, F. De Fazio, N. Losacco, F. Loparco

The hadronic form factors of $B_c$ semileptonic decays to the $P-$wave charmonium 4-plet can be expressed near the zero-recoil point in terms of universal functions, performing a systematic expansion in QCD in the relative velocity of the heavy quarks and in $1/m_Q$. Such functions are independent of the member of the multiplet involved in the transitions. W

Domenico Tallarico, Andrea Bergamini, Bart Van Damme

In this article, we present scattering and localization phenomena in a thin elastic plate comprising an aperiodic arrangement of scatterers. By analysing the form factor of the scattering cluster, we sample the reciprocal space which shows strong scattering points associated with non trivial dispersion. Wide frequency regimes with very different dynamic resp

Ramazan Akgün

Using a transference result, several inequalities of approximation by entire functions of exponential type in $\mathcal{C}(\mathbf{R})$, the class of bounded uniformly continuous functions defined on $\mathbf{R}:=\left( -\infty ,+\infty \right) $, are extended to the Lebesgue spaces $L^{p}\left( \mathbf{\varrho }dx\right) $ $1\leq p<\infty $ with Muckenhoupt

Jiakang Bao

We focus on quiver Yangians for most generalized conifolds. We construct a coproduct of the quiver Yangian following the similar approach by Guay-Nakajima-Wendlandt. We also prove that the quiver Yangians related by Seiberg duality are indeed isomorphic. Then we discuss their connections to $\mathcal{W}$-algebras analogous to the study by Ueda. In particular

Jianbo Cui, Jialin Hong, Liying Sun

In this paper, we propose and analyze semi-implicit numerical schemes for the stochastic wave equation (SWE) with general nonlinearity and multiplicative noise. These numerical schemes, called stochastic scalar auxiliary variable (SAV) schemes, are constructed by transforming the considered SWE into a higher dimensional stochastic system with a stochastic SA

Zhenya Yan

In this letter, we present a simple and new idea to generate two types of novel integrable multi-L\'evy-index and mix-L\'evy-index (mixed) fractional nonlinear soliton hierarchies, containing multi-index and mixed fractional higher-order nonlinear Schr\"odinger (NLS) hierarchy, fractional complex modified Korteweg-de Vries (cmKdV) hierarchy, and fractional m

Dmitry Bizyaev, Yan-Mei Chen, Yong Shi, Namrata Roy

We find 132 face-on and low inclination galaxies with central star formation driven biconical gas outflows (FSFB) in the SDSS MaNGA (Mapping Nearby Galaxies at APO) survey. The FSFB galaxies show either double peaked or broadened emission line profiles at their centres. The peak and maximum outflow velocities are 58 and 212 km/s, respectively. The gas veloci

Ming Zhong, Zhenya Yan

In this paper, we firstly extend the Fourier neural operator (FNO) to discovery the soliton mapping between two function spaces, where one is the fractional-order index space $\{\epsilon|\epsilon\in (0, 1)\}$ in the fractional integrable nonlinear wave equations while another denotes the solitonic solution function space. To be specific, the fractional nonli

Mélodie Boillet, Christopher Kermorvant, Thierry Paquet

Deep neural networks are becoming increasingly powerful and large and always require more labelled data to be trained. However, since annotating data is time-consuming, it is now necessary to develop systems that show good performance while learning on a limited amount of data. These data must be correctly chosen to obtain models that are still efficient. Fo

Majid Mohammadi

This paper introduces Bayesian frameworks for tackling various aspects of multi-criteria decision-making (MCDM) problems, leveraging a probabilistic interpretation of MCDM methods and challenges. By harnessing the flexibility of Bayesian models, the proposed frameworks offer statistically elegant solutions to key challenges in MCDM, such as group decision-ma

Yang Li, Yunfei Su, Shixin Zhu, Shitao Li

Let $q=p^h$ be a prime power and $e$ be an integer with $0\leq e\leq h-1$. $e$-Galois self-orthogonal codes are generalizations of Euclidean self-orthogonal codes ($e=0$) and Hermitian self-orthogonal codes ($e=\frac{h}{2}$ and $h$ is even). In this paper, we propose two general methods to construct $e$-Galois self-orthogonal (extended) generalized Reed-Solo

Michael A. Bekos, Martin Gronemann, Fabrizio Montecchiani, Antonios Symvonis

Strictly-convex straight-line drawings of $3$-connected planar graphs in small area form a classical research topic in Graph Drawing. Currently, the best-known area bound for such drawings is $O(n^2) \times O(n^2)$, as shown by B\'{a}r\'{a}ny and Rote by means of a sophisticated technique based on perturbing (non-strictly) convex drawings. Unfortunately, the

Jose A. Magpantay

In a previous paper, the author asked the question "Does a Special Relativistic Liouville Equation Exist?'. In this paper, I give an affirmative answer. In 8N phase space, a Hamiltonian is derived by breaking the reparametrization symmetry of the single, Lorentz invariant, mathematical time introduced, which defines the evolution of all phase space variables

Benyamin Ghojogh

After the development of different machine learning and manifold learning algorithms, it may be a good time to put them together to make a powerful mind for machine. In this work, we propose affective manifolds as components of a machine's mind. Every affective manifold models a characteristic group of mind and contains multiple states. We define the machine

Gerardo Valadez Huerta, Kaoru Hisama, Katsutoshi Sato, Katsutoshi Nagaoka

Catalysis informatics is constantly developing, and significant advances in data mining, molecular simulation, and automation for computational design and high-throughput experimentation have been achieved. However, efforts to reveal the mechanisms of complex supported nanoparticle catalysts in cyberspace have proven to be unsuccessful thus far. This study f

Manas Sajjan, Vinit Singh, Raja Selvarajan, Sabre Kais

We introduce and analytically illustrate that hitherto unexplored imaginary components of out-of-time correlators can provide unprecedented insight into the information scrambling capacity of a graph neural network. Furthermore, we demonstrate that it can be related to conventional measures of correlation like quantum mutual information and rigorously establ

Lingfu Zhang

We consider the Metropolis biased card shuffling (also called the multi-species ASEP on a finite interval or the random Metropolis scan). Its convergence to stationary was believed to exhibit a total-variation cutoff, and that was proved a few years ago by Labb\'e and Lacoin. In this paper, we prove that (for $N$ cards) the cutoff window is in the order of $

Samrat Roy, Michael J. Daniels, Brendan J. Kelly, Jason Roy

Mediation analysis with contemporaneously observed multiple mediators is an important area of causal inference. Recent approaches for multiple mediators are often based on parametric models and thus may suffer from model misspecification. Also, much of the existing literature either only allow estimation of the joint mediation effect, or, estimate the joint

Krzysztof Pachucki, Vladimir A. Yerokhin

We investigate the modification of the transverse electromagnetic interaction between two point-like particles when one particle acquires a finite size. It is shown that the correct treatment of such interaction cannot be accomplished within the Breit approximation but should be addressed within the QED. The complete QED formula is derived for the finite-siz

Sophia Fuhui Lin, Sara Sussman, Casey Duckering, Pranav S. Mundada

Near-term quantum computers are primarily limited by errors in quantum operations (or gates) between two quantum bits (or qubits). A physical machine typically provides a set of basis gates that include primitive 2-qubit (2Q) and 1-qubit (1Q) gates that can be implemented in a given technology. 2Q entangling gates, coupled with some 1Q gates, allow for unive

Raj Katti, Harpreet Arora, Olli-Pentti Saira, Kenji Watanabe

Due to its exceptional electronic and thermal properties, graphene is a key material for bolometry, calorimetry, and photon detection. However, despite graphene's relatively simple electronic structure, the physical processes responsible for the transport of heat from the electrons to the lattice are experimentally still elusive. Here, we measure the thermal

Suraj S. Chandran, Yanze Wu, Joseph E. Subotnik

We investigate spin-dependent electron transfer in the presence of a Duschinskii rotation. In particular, we propagate dynamics for a two-level model system for which spin-orbit coupling introduces an interstate coupling of the form $e^{iWx}$, which is both position(x)-dependent and complex-valued. We demonstrate that two-level systems coupled to Brownian os

Xikun Li

A systematic scheme is proposed to numerically estimate the quantum speed limit and temporal shape of optimal control in two-level and three-level quantum systems with bounded amplitude. For the two-level system, two quantum state transitions are studied as illustration. Comparisons between numerical and analytical results are made, and deviations are signif

Taehee Kim, ChaeHun Park, Jimin Hong, Radhika Dua

Semantically meaningful sentence embeddings are important for numerous tasks in natural language processing. To obtain such embeddings, recent studies explored the idea of utilizing synthetically generated data from pretrained language models (PLMs) as a training corpus. However, PLMs often generate sentences much different from the ones written by human. We

Yuyang Ji, Peize Lin, Xinguo Ren, Lixin He

Hybrid density functional (HDF) approximations usually deliver higher accuracy than local and semilocal approximations to the exchange-correlation functional, but this comes with drastically increased computational cost. Practical implementations of HDFs inevitably involve numerical approximations -- even more so than their local and semilocal counterparts d

Felix Lüpke, Marek Kolmer, Jiaqiang Yan, Hao Chang

The gapped Dirac-like surface states of compensated magnetic topological insulator MnBi$_{2-x}$Sb$_x$Te$_4$ (MBST) are a promising host for exotic quantum phenomena such as the quantum anomalous Hall effect and axion insulating states. However, it has become clear that atomic defects undermine the stabilization of such quantum phases as they lead to spatial

Jiewon Park

In this paper we prove a matrix Li-Yau-Hamilton inequality for the Green function on complete K\"ahler manifolds with nonnegative holomorphic bisectional curvature. This estimate can be seen as an elliptic analogue of the matrix estimate of Cao and Ni for the heat equation on K\"ahler manifolds, or the complex analogue of the estimate for Riemannian manifold

Kalyan Dasgupta, Binoy Paine

Quantum circuits generating probability distributions has applications in several areas. Areas like finance require quantum circuits that can generate distributions that mimic some given data pattern. Hamiltonian simulations require circuits that can initialize the wave function of a physical quantum system. These wave functions, in several cases, are identi

Sandro M. Reia, P. Suresh C. Rao, Marc Barthelemy, Satish V. Ukkusuri

We show here that population growth, resolved at the county level, is spatially heterogeneous both among and within the U.S. metropolitan statistical areas. Our analysis of data for over 3,100 U.S. counties reveals that annual population flows, resulting from domestic migration during the 2015 - 2019 period, are much larger than natural demographic growth, a

Sean Eugene G. Chua, Kevin Anthony S. Sison

At the peak of the COVID-19 pandemic, numerous countries worldwide sought to mobilize vaccination campaigns in an attempt to curb the spread and number of deaths caused by the virus. One avenue in which information regarding COVID vaccinations is propagated is that of scientific articles, which provide a certain level of credibility regarding this. Hence, th

Feiyu Jiang, Emmanuel Selorm Tsyawo

In spite of the omnibus property of Integrated Conditional Moment (ICM) specification tests, they are not commonly used in empirical practice owing to features such as the non-pivotality of the test and the high computational cost of available bootstrap schemes, especially in large samples. This paper proposes specification and mean independence tests based

Razieh Ranjbar, Amin Mosallanezhad, Shahram Abbassi

We study the global solutions of slowly rotating accretion flows around the supermassive black hole in the nucleus of an elliptical galaxy. The velocity of accreted gas surrounding the black hole is initially subsonic and then falls onto the black hole supersonically, so accretion flow must be transonic. We numerically solve equations from the Bondi radius t

Negin Alamatsaz, Leyla s Tabatabaei, Mohammadreza Yazdchi, Hamidreza Payan

Electrocardiogram (ECG) is the most frequent and routine diagnostic tool used for monitoring heart electrical signals and evaluating its functionality. The human heart can suffer from a variety of diseases, including cardiac arrhythmias. Arrhythmia is an irregular heart rhythm that in severe cases can lead to heart stroke and can be diagnosed via ECG recordi

Michel Alexis

We show that solutions to Krein systems, the continuous frequency analogue of orthogonal polynomials on the unit circle, generated by an $A_2 (\mathbb{R})$ weight $w$ satisfying $w-1 \in L^1 (\mathbb{R}) + L^2 (\mathbb{R})$, are uniformly bounded in $L^p_{\mathrm{loc}} (w, \mathbb{R})$ for $p$ sufficiently close to $2$. This provides a positive answer to the

Peter Ebenfelt, Ming Xiao, Hang Xu

Obstruction flatness of a strongly pseudoconvex hypersurface $\Sigma$ in a complex manifold refers to the property that any (local) K\"ahler-Einstein metric on the pseudoconvex side of $\Sigma$, complete up to $\Sigma$, has a potential $-\log u$ such that $u$ is $C^\infty$-smooth up to $\Sigma$. In general, $u$ has only a finite degree of smoothness up to $\