November 2022 arXiv papers — page 138

Shilin Huang, Tomas Jochym-O'Connor, Theodore J. Yoder

Shor and Steane ancilla are two well-known methods for fault-tolerant logical measurements, which are successful on small codes and their concatenations. On large quantum low-density-parity-check (LDPC) codes, however, Shor and Steane measurements have impractical time and space overhead respectively. In this work, we widen the choice of ancilla codes by uni

Yun-Cheng Tsai

Since the end of 2021, the Metaverse has been booming. Many unknown possibilities are gradually being realized, but many people only determined that they use Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) in the Metaverse. It is even considered that as long as the above realities (VR, AR, MR) are used, it is equal to the Metaverse. Howe

Pushen Zuo, Zhong Sun, Ru Huang

Signal processing in wireless communications, such as precoding, detection, and channel estimation, are basically about solving inverse matrix problems, which, however, are slow and inefficient in conventional digital computers, thus requiring a radical paradigm shift to achieve fast, real-time solutions. Here, for the first time, we apply the emerging analo

Jovan Jovanovic, Ronald Fernando Garcia Ruiz

Collinear laser spectroscopy of fast atomic beams has been established as one of the main tools to perform precision experiments with atoms containing short-lived nuclei. Although highly sensitive, the spectral resolution of these techniques is typically limited to several MHz. Here, we study the use of transient interference phenomena to potentially improve

Neil Perry, Megha Srivastava, Deepak Kumar, Dan Boneh

We conduct the first large-scale user study examining how users interact with an AI Code assistant to solve a variety of security related tasks across different programming languages. Overall, we find that participants who had access to an AI assistant based on OpenAI's codex-davinci-002 model wrote significantly less secure code than those without access. A

Jin Cao, Hao-Ran Chang, Xiaolong Feng, Yugui Yao

Recent experiments have established a type of nonsymmorphic symmetry protected nodal lines in the family of two-dimensional (2D) composition tunable materials NbSi$_x$Te$_2$. Here, we theoretically study the plasmonic properties of such nonsymmorphic nodal-line semimetals. We show that the nonsymmorphic character endows the plasmons with extremely strong ani

Umberto Maio, Matteo Viel

We compare properties of high-redshift galaxies observed by JWST with hydrodynamical simulations, in the standard cold dark matter model and in warm dark matter models with a suppressed linear matter power spectrum. We find that current data are not in tension with cold dark matter nor with warm dark matter models with mWDM > 2 keV, since they probe bright a

Stavros Anastassiou

We study the local structure of vector fields on $\mathbb{R}^3$ which preserve the Martinet $1$-form $\alpha=(1+x)dy\pm zdz$. We present the classification of their singularities, up to diffeomorphisms preserving the form $\alpha$, as well as their transversal unfoldings. We are thus able to provide a fairly complete list of the bifurcations such vector fiel

A. V. Kotikov

The main steps of the process of obtaining the result [1] in terms of elliptic polylogarithms for a two-loop sunrise integral with two different internal masses with pseudothreshold kinematics for all orders of the dimensional regulator are shown.

Vincenzo Amato, Francesco Chiacchio, Andrea Gentile

In this paper we study the $p$-Poisson equation with Robin boundary conditions, where the Robin parameter is a function. By means of some weighted isoperimetric inequalities, we provide various sharp bounds for the solutions to the problems under consideration. We also derive a Faber-Krahn-type inequality.

Erxin Yu, Lan Du, Yuan Jin, Zhepei Wei

Recently, discrete latent variable models have received a surge of interest in both Natural Language Processing (NLP) and Computer Vision (CV), attributed to their comparable performance to the continuous counterparts in representation learning, while being more interpretable in their predictions. In this paper, we develop a topic-informed discrete latent va

Ali Abedi, Faranak Dayyani, Charlene Chu, Shehroz S. Khan

There is a global aging population requiring the need for the right tools that can enable older adults' greater independence and the ability to age at home, as well as assist healthcare workers. It is feasible to achieve this objective by building predictive models that assist healthcare workers in monitoring and analyzing older adults' behavioral, functiona

Aurélien Vadrot, Xiang I. A. Yang, Mahdi Abkar

This survey investigates wall modeling in large eddy simulations (LES) using data-driven machine learning (ML) techniques. To this end, we implement three ML wall models in an open-source code and compare their performances with the equilibrium wall model in LES of half-channel flow at eleven friction Reynolds numbers between $180$ and $10^{10}$. The three m

Mann Patel

Federated Learning is a machine learning paradigm where we aim to train machine learning models in a distributed fashion. Many clients/edge devices collaborate with each other to train a single model on the central. Clients do not share their own datasets with each other, decoupling computation and data on the same device. In this paper, we propose yet anoth

Nibula Bente Rashid, Joyeeta Saha, Raonak Islam Prova, Nowshin Tasfia

State government operations comprise a large number of transactions for different processes that must be carried out across the state. This comprises new projects, maintenance and repairs, public employee compensation, and agricultural schemes. Low-level corruption, which is sometimes difficult to trace and hinders state growth, is a big challenge for the to

Ming Liu, Yaojia LV, Jingrun Zhang, Ruiji Fu

This paper presents BigCilin, the first Chinese open-domain knowledge graph with fine-grained hypernym-hyponym re-lations which are extracted automatically from multiple sources for Chinese named entities. With the fine-grained hypernym-hyponym relations, BigCilin owns flexible semantic hierarchical structure. Since the hypernym-hyponym paths are automati-ca

Anthony O. Ojo, David Escofet-Martin, Brian Peterson

This work demonstrates high-speed 2D wall temperature measurements occurring during flame-wall interaction (FWI) within a narrow channel. Such measurements are essential to understand transient wall heat transfer and flame behavior occurring within micro-combustors and designated engine crevices. Wall temperature is measured using the phosphor Bismuth-doped

Jiansheng Dai, Ziheng Huang, Michael R. Powers, Jiaxin Xu

Heavy-tailed random variables have been used in insurance research to model both loss frequencies and loss severities, with substantially more emphasis on the latter. In the present work, we take a step toward addressing this imbalance by exploring the class of heavy-tailed frequency models formed by continuous mixtures of Negative Binomial and Poisson rando

Chandrachur Chakraborty, Sudip Bhattacharyya

A primordial black hole (PBH) is thought to be made of the regular matter or ordinary mass ($M$) only, and hence could have already been decayed due to the Hawking radiation if its initial ordinary mass were $\lesssim 5 \times 10^{11}$ kg. Here, we study the role of gravitomagnetic monopole for the evaporation of PBHs, and propose that the lower energy PBHs

Santosh V Lohakare, Francisco Tello-Ortiz, S. K. Tripathy, B. Mishra

In this paper, we have studied the bouncing behavior of the cosmological models formulated at the background of the Hubble function in the F(R, G) theory of gravity, where R and G denote the Ricci scalar and Gauss-Bonnet invariant. The actions of bouncing cosmology are studied under consideration of different viable models and can resolve the difficulty of s

Tongxing Li, Silvia Frassu, Giuseppe Viglialoro

This paper is framed in a series of studies on attraction-repulsion chemotaxis models combining different effects: nonlinear diffusion and sensitivities and logistic sources, for the dynamics of the cell density, and consumption and/or production impacts, for those of the chemicals. In particular, herein we focus on the situation where the signal responsible

Oliver J. Sutton, Alexander N. Gorban, Ivan Y. Tyukin

We consider the problem of data classification where the training set consists of just a few data points. We explore this phenomenon mathematically and reveal key relationships between the geometry of an AI model's feature space, the structure of the underlying data distributions, and the model's generalisation capabilities. The main thrust of our analysis i

David Mitrouskas, Robert Seiringer

We study the spectrum of the Fr\"ohlich Hamiltonian for the polaron at fixed total momentum. We prove the existence of excited eigenvalues between the ground state energy and the essential spectrum at strong coupling. In fact, our main result shows that the number of excited energy bands diverges in the strong coupling limit. To prove this we derive upper bo

Eszter Gselmann, Gergely Kiss

The aim of this sequence of work is to investigate polynomial equations satisfied by additive functions. As a result of this, new characterization theorems for homomorphisms and derivations can be given. More exactly, in this paper the following type of equation is considered $$\sum_{i=1}^{n}f_{i}(x^{p_{i}})g_{i}(x^{q_{i}})= 0 \qquad \left(x\in \mathbb{F}\ri

George Samartzis, Nikitas Pittis

We derive a closed-form expression capturing the degree of Relative Risk Aversion (RRA) of investors for non-"fair" lotteries. We argue that our formula is superior to earlier methods that have been proposed, as it is a function of only three variables. Namely, the Treasury yields, the returns and the market capitalization of a specific market index. Our for

Bao-Huei Huang, Yu-Hsiang Fu, Chao-Cheng Kaun, Yu-Hui Tang

In our JunPy package, we have combined the first-principles calculated self-consistent Hamiltonian with divide-and-conquer technique to successfully determine the magnetic anisotropy (MA) in an Fe/MgO/Fe magnetic tunnel junction (MTJ). We propose a comprehensive analytical derivation to clarify the crucial roles of spin-orbit coupling that mediates the excha

Hao Xu, Jinglong Lin, Dongxiao Zhang, Fanyang Mo

A new research framework is proposed to incorporate machine learning techniques into the field of experimental chemistry to facilitate chromatographic enantioseparation. A documentary dataset of chiral molecular retention times (CMRT dataset) in high-performance liquid chromatography is established to handle the challenge of data acquisition. Based on the CM

Georg Anegg, Laura Vargas Koch, Rico Zenklusen

Recent progress on robust clustering led to constant-factor approximations for Robust Matroid Center. After a first combinatorial $7$-approximation that is based on a matroid intersection approach, two tight LP-based $3$-approximations were discovered, both relying on the Ellipsoid Method. In this paper, we show how a carefully designed, yet very simple, gre

Chenyun Luo, Junyan Zhang

We consider the 3D compressible isentropic Euler equations describing the motion of a liquid in an unbounded initial domain with a moving boundary and a fixed flat bottom at finite depth. The liquid is under the influence of gravity and surface tension, and it is not assumed to be irrotational. We prove local well-posedness by combining a carefully designed

Pranav Nuti, Jan Vondrák

In this paper, we study contention resolution schemes for matchings. Given a fractional matching $x$ and a random set $R(x)$ where each edge $e$ appears independently with probability $x_e$, we want to select a matching $M \subseteq R(x)$ such that $\Pr[e \in M \mid e \in R(x)] \geq c$, for $c$ as large as possible. We call such a selection method a $c$-bala

C. Simon Jeffery

$\upsilon$ Sgr is the prototype of four known hydrogen-deficient binary (HdB) systems. These are characterised by a hydrogen-deficient A-type primary, variable hydrogen emission lines, and a normally unseen secondary presumed to be an upper main-sequence star. Orbital periods range from tens of days to 360 d. TESS observations of all four HdBs show a flux va

Roman Goncharov, Alexei D. Kiselev, Fedor Kiselev, Eugene S. Moiseev

We present a scheme of quantum repeater that uses entangled multimode coherent states which are obtained by electro-optic modulation of symmetric and antisymmetric Schr\"odinger cat states. In this method subcarrier modes of the phase modulated states generated by the remote parties are sent to a symmetric beam splitter at the central node. The entangled coh

C. Wetterich

We discuss predictions for cosmology which result from the scaling solution of functional flow equations for a quantum field theory of gravity. A scaling solution is necessary to render quantum gravity renormalizable. Our scaling solution is directly connected to the quantum effective action for the metric coupled to a scalar field. It includes all effects o

Joe Benton, Yuyang Shi, Valentin De Bortoli, George Deligiannidis

Denoising diffusions are state-of-the-art generative models exhibiting remarkable empirical performance. They work by diffusing the data distribution into a Gaussian distribution and then learning to reverse this noising process to obtain synthetic datapoints. The denoising diffusion relies on approximations of the logarithmic derivatives of the noised data

Qiang Chen, Jian Wang, Chuchu Han, Shan Zhang

We present a strong object detector with encoder-decoder pretraining and finetuning. Our method, called Group DETR v2, is built upon a vision transformer encoder ViT-Huge~\cite{dosovitskiy2020image}, a DETR variant DINO~\cite{zhang2022dino}, and an efficient DETR training method Group DETR~\cite{chen2022group}. The training process consists of self-supervise

Zhen Du, Jiajia Li, Yinshan Wang, Xueqi Li

Sparse Matrix-Vector multiplication (SpMV) is an essential computational kernel in many application scenarios. Tens of sparse matrix formats and implementations have been proposed to compress the memory storage and speed up SpMV performance. We develop AlphaSparse, a superset of all existing works that goes beyond the scope of human-designed format(s) and im

Maarten Grothus

By relating and ordering events, causality constitutes a pivotal feature of our world. On the one hand, there are information-theoretic notions of causality defined in terms of the information processing ability of agents and on the other hand, there are relativistic notions of causality tied to a spacetime. In this thesis, we improve upon a framework introd

Guilherme Grams, Wouter Ryssens, Guillaume Scamps, Stephane Goriely

We report here the current developments on the Brussels-Skyrme-on-a-Grid (BSkG) atomic mass models. In comparison with our previous models, BSkG3 improves the infinite nuclear matter (INM) properties which opens its applications to neutron stars. The results presented here show that BSkG3 preserve the excellent agreement with experimental nuclear masses and

Nikolay Khabarov, Alexey Smirnov, Michael Obersteiner

Shadow prices are well understood and are widely used in economic applications. However, there are limits to where shadow prices can be applied assuming their natural interpretation and the fact that they reflect the first order optimality conditions (FOC). In this paper, we present a simple ad-hoc example demonstrating that marginal cost associated with exe

Claudio Bonati, Niccolò Francini

We study the phase diagram and phase transitions of the three dimensional multicomponent lattice Higgs model with non-compact Abelian discrete groups. The model with non-compact U(1) gauge group is known to undergo, for a sufficiently large number of scalar fields $N$, a continuous transition associated to the charged fixed point of the continuous Abelian Hi

Juan Xu, Ruofan Wang, Yan Zhang, Hongmin Huang

Wireless NanoSensor Network (WNSN) is a new type of sensor network with broad application prospects. In view of the limited energy of nanonodes and unstable links in WNSNs, we propose a reliable multi-path routing based on link stability (RMRLS). RMRLS selects the optimal path which perfects best in the link stability evaluation model, and then selects an al

Surbhi Mittal, Kartik Thakral, Puspita Majumdar, Mayank Vatsa

The presence of bias in deep models leads to unfair outcomes for certain demographic subgroups. Research in bias focuses primarily on facial recognition and attribute prediction with scarce emphasis on face detection. Existing studies consider face detection as binary classification into 'face' and 'non-face' classes. In this work, we investigate possible bi

Abhinav Joshi, Naman Gupta, Jinang Shah, Binod Bhattarai

A real-world application or setting involves interaction between different modalities (e.g., video, speech, text). In order to process the multimodal information automatically and use it for an end application, Multimodal Representation Learning (MRL) has emerged as an active area of research in recent times. MRL involves learning reliable and robust represe

João Pandeirada, Miguel Bergano, Paulo Marques, Domingos Barbosa

The ever increasing dependence of modern societies in space based services results in a rising number of objects in orbit which grows the probability of collisions between them. The increase in space debris is a threat to space assets, space based-operations and led to a common effort to develop programs for dealing with it. As part of the Portuguese Space S

Ryan Murray, Galen Wilcox

This article revisits the instability of sharp shear interfaces, also called vortex sheets, in incompressible fluid flows. We study the Birkhoff-Rott equation, which describes the motion of vortex sheets according to the incompressible Euler equations in two dimensions. The classical Kelvin-Helmholtz instability demonstrates that an infinite, flat vortex she

Li-Hsiang Shen, Yen-Chun Lo, Kai-Ten Feng, Sau-Hsuan Wu

In this paper, we consider a prospective receiving hybrid beamforming structure consisting of several radio frequency (RF) chains and abundant antenna elements in multi-input multi-output (MIMO) systems. Due to conventional costly full connections, we design an enhanced partially connected beamformer employing a low-density parity-check (LDPC)-based structur

Max Wasserman, Gonzalo Mateos

We introduce pyGSL, a Python library that provides efficient implementations of state-of-the-art graph structure learning models along with diverse datasets to evaluate them on. The implementations are written in GPU-friendly ways, allowing one to scale to much larger network tasks. A common interface is introduced for algorithm unrolling methods, unifying i

B. -O. Demory, S. Sulis, E. Meier Valdes, L. Delrez

Past occultation and phase-curve observations of the ultra-short period super-Earth 55 Cnc e obtained at visible and infrared wavelengths have been challenging to reconcile with a planetary reflection and emission model. In this study, we analyse a set of 41 occultations obtained over a two-year timespan with the CHEOPS satellite. We report the detection of

Gabriel Senno, Thomas Strohm, Antonio Acín

Intrinsic quantum randomness is produced when a projective measurement on a given basis is implemented on a pure state that is not an element of the basis. The prepared state and implemented measurement are perfectly known, yet the measured result cannot be deterministically predicted. In realistic situations, however, measurements and state preparation are

Hélène Sol, Andreas Zech

Blazars are very broadband cosmic sources with spectra spanning over twenty orders of magnitude in frequency, down to the 100 MHz regime in the radio range, up to VHE at several tens of TeV. The modelling of their spectral energy distribution at high energies currently considers two main classes of models, leptonic and lepto-hadronic, which both succeed fair

Vladimir S. Melezhik

We have developed a quantum-quasiclassical computational scheme for quantitative treating of the nonseparable quantum-classical dynamics of the 6D hydrogen atom in a strong laser pulse. In this approach, the electron is treated quantum mechanically and the center-of-mass (CM) motion classically. Thus, the Schr\"odinger equation for the electron and the class

Yi Zhai, Yu Zhang, Shuo Liu, Xiaomeng Chu

Tensor program tuning is a non-convex objective optimization problem, to which search-based approaches have proven to be effective. At the core of the search-based approaches lies the design of the cost model. Though deep learning-based cost models perform significantly better than other methods, they still fall short and suffer from the following problems.

Xiao Sun, Song Liang, Weiqing Cheng, Shengwei Ye

We report an AlGaInAs multiple quantum well integrated source of polarization controlled light consisting of a polarization mode converter PMC, differential phase shifter(DPS), and a side wall grating distributed-feedback DFB laser. We demonstrate an asymmetrical stepped-height ridge waveguide PMC to realize TE to TM polarization conversion and a symmetrical

Gianluca Cena, Stefano Scanzio, Adriano Valenzano

The adoption of wireless communications and, in particular, Wi-Fi, at the lowest level of the factory automation hierarchy has not increased as fast as expected so far, mainly because of serious issues concerning determinism. Actually, besides the random access scheme, disturbance and interference prevent reliable communication over the air and, as a matter

Tamara Fastovska

A nonlinear transmisson problem for an elastic full von Karman beam is considered here. We prove that the system possesses a compact global attractor.

Vitaly Magerya

Rational Tracer (Ratracer) is a tool to simplify complicated arithmetic expressions using modular arithmetics and rational function reconstruction, with the main idea of separating the construction of expressions (via tracing, i.e. recording the list of operations) and their subsequent evaluation during rational reconstruction. Ratracer can simplify arithmet

Li-Hsiang Shen, Kai-Ten Feng, Lajos Hanzo

Whilst the fifth-generation (5G) systems are being rolled out across the globe, researchers have turned their attention to the exploration of radical next-generation solutions. At this early evolutionary stage we survey five main research facets of this field, namely {\em Facet~1: next-generation architectures, spectrum and services, Facet~2: next-generation

J. Iglesias, A. Portela, A. Rovella, J. Xavier

Let $f: S^2 \to S^2$ be a continuous map of degree $d$, $|d|>1$, and let $N_nf$ denote the number of fixed points of $f^n$. We show that if $f$ is a Thurston map with non hyperbolic orbifold, then either the growth rate inequality $\limsup \frac{1}{n} \log N_nf\geq \log |d|$ holds for $f$ or $f$ has exactly two critical points which are fixed and totally inv

Julius Martinetz, Thomas Martinetz

We study over-parameterized classifiers where Empirical Risk Minimization (ERM) for learning leads to zero training error. In these over-parameterized settings there are many global minima with zero training error, some of which generalize better than others. We show that under certain conditions the fraction of "bad" global minima with a true error larger t

Tianyi Bai, Quirin Vogel

We prove the existence of Gibbs measures for the Feynman representation of the Bose gas with non-negative interaction in the grand-canonical ensemble. Our results are valid for all negative chemical potentials as well as slightly positive chemical potentials. We consider both the Gibbs property of marked points as well as a Markov--Gibbs property of paths.

Andrew M. Kingston, Lindon Roberts, Alaleh Aminzadeh, Daniele Pelliccia

Classical ghost imaging is a new paradigm in imaging where the image of an object is not measured directly with a pixelated detector. Rather, the object is subject to a set of illumination patterns and the total interaction of the object, e.g., reflected or transmitted photons or particles, is measured for each pattern with a single-pixel or bucket detector.

Adrien Courtois, Jean-Michel Morel, Pablo Arias

Neural networks trained on large datasets by minimizing a loss have become the state-of-the-art approach for resolving data science problems, particularly in computer vision, image processing and natural language processing. In spite of their striking results, our theoretical understanding about how neural networks operate is limited. In particular, what are

Allan Lo, Simón Piga, Nicolás Sanhueza-Matamala

We show that $k$-uniform hypergraphs on $n$ vertices whose codegree is at least $(2/3 + o(1))n$ can be decomposed into tight cycles, subject to the trivial divisibility conditions. As a corollary, we show those graphs contain tight Euler tours as well. In passing, we also investigate decompositions into tight paths. In addition, we also prove an alternative

Tobias Heinrich, Hung-Tzu Chang, Sergey Zayko, Kai Rossnagel

Femtosecond core-level transient absorption spectroscopy is utilized to investigate photoinduced dynamics of the charge density wave in 1T-TiSe2 at the Ti M2,3 edge (30-50 eV). Photoexcited carriers and phonons are found to primarily induce spectral red-shifts of core-level excitations, and a carrier relaxation time and phonon heating time of approximately 3

S. Bondarenko, Ya. Dydyshka, L. Kalinovskaya, R. Sadykov

Complete one-loop electroweak corrections to neutral current Drell-Yan process $p p \to \ell^+\ell^- X$ are presented for the case of longitudinal polarization of initial particles. Cross sections for longitudinally polarized protons allow us to estimate different combinations of polarized quark distributions from single- and double-spin asymmetries. Numeric

Jeetendra Gour, Sebastian Beer, Alessandro Alberucci, Uwe Detlef Zeitner

We investigate experimentally Third Harmonic Generation (THG) from plasmonic metasurfaces consisting of two-dimensional rectangular lattices of centrosymmetric gold nano-bars. By varying the incidence angle and the lattice period, we show how Surface Lattice Resonances (SLRs) at the involved wavelengths are the major contributors in determining the magnitude

Jifen Liu, Jiaqun Wei

Let $R$ be a perfect ring and $T$ be an $R$-module. We study characterizations of sincere modules, sincere silting modules and tilting modules in terms of various vanishing conditions. It is proved that $T$ is sincere silting if and only if $T$ is presilting satisfing the vanishing condition $\mathrm{KerExt}^{0\le i\le 1}_R(T,-)=0$, and that $T$ is tilting i

Yoosik Kim, Siu-Cheong Lau, Xiao Zheng

We derive a Floer theoretical SYZ mirror for an equilateral and generic polygon space. The disk potential function of the monotone torus fiber of the caterpillar bending system is calculated by computing non-trivial open Gromov--Witten invariants from the structural result of the monotone Fukaya category, the topology of fibers of completely integrable syste

Jinzhi Shen, Xufen Wu, Yirui Zheng, Beibei Guo

Galaxies are observed to be lopsided, meaning that they are more massive and more extended along one direction than the opposite. In this work, we provide a statistical analysis of the lopsided morphology of 1780 isolated satellite galaxies generated by TNG50-1 simulation, incorporating the effect of tidal fields from halo centres. The isolated satellites ar

Bruno Carneiro da Cunha, João Paulo Cavalcante

We propose a relation the expansions of regular and irregular semiclassical conformal blocks at different branch points making use of the connection between the accessory parameters of the BPZ decoupling equations to the logarithm derivative of isomonodromic tau functions. We give support for these relations by considering two eigenvalue problems for the con

Alireza Aghelan, Modjtaba Rouhani

Single image super-resolution (SISR) models are able to enhance the resolution and visual quality of underwater images and contribute to a better understanding of underwater environments. The integration of these models in Autonomous Underwater Vehicles (AUVs) can improve their performance in vision-based tasks. Real-Enhanced Super-Resolution Generative Adve

Katsuya Kosukegawa, Yasukuni Mori, Hiroki Suyari, Kazuhiko Kawamoto

To ensure the safety of railroad operations, it is important to monitor and forecast track geometry irregularities. A higher safety requires forecasting with higher spatiotemporal frequencies, which in turn requires capturing spatial correlations. Additionally, track geometry irregularities are influenced by multiple exogenous factors. In this study, a metho

Yu. D. Fomin, E. N. Tsiok, V. N. Ryzhov

Here we present a computational study of the thermodynamic and structural properties of bulk and confined (1,1,1,3,3-pentafuorobutane) with different lengths of the carbon backbone. The DREIDING force field model has been used in the method of molecular dynamics. In order to study the effect of confinement we have placed (1,1,1,3,3-pentauorobutane) molecules

G. V. Pavan Kumar

Structured light has emerged as an important tool to interrogate and manipulate matter at micron and sub-micron scale. One form of structured light is an optical vortex beam. The helical wavefront of these vortices carry orbital angular momentum which can be transferred to a Brownian colloid. When the colloid is made of metallic nanostructures, such as silve

Xiaoran Fan, Chao Pang, Tian Yuan, He Bai

Speech representation learning has improved both speech understanding and speech synthesis tasks for single language. However, its ability in cross-lingual scenarios has not been explored. In this paper, we extend the pretraining method for cross-lingual multi-speaker speech synthesis tasks, including cross-lingual multi-speaker voice cloning and cross-lingu

Amr Gomaa

With the recently increasing capabilities of modern vehicles, novel approaches for interaction emerged that go beyond traditional touch-based and voice command approaches. Therefore, hand gestures, head pose, eye gaze, and speech have been extensively investigated in automotive applications for object selection and referencing. Despite these significant adva

Yixin Cao, Shenghua Wang

In an attempt to understanding the complexity of the independent set problem, Chv{\'a}tal defined t-perfect graphs. While a full characterization of this class is still at large, progress has been achieved for claw-free graphs [Bruhn and Stein, Math.\ Program.\ 2012] and $P_{5}$-free graphs [Bruhn and Fuchs, SIAM J.\ Discrete Math.\ 2017]. We take one more s

Friedrich Martin Schneider

We prove that, if a discrete group $G$ is not inner amenable, then the unit group of the ring of operators affiliated with the group von Neumann algebra of $G$ is non-amenable with respect to the topology generated by its rank metric. This provides examples of non-discrete irreducible, continuous rings (in von Neumann's sense) whose unit groups are non-amena

Jiahang Cao, Jinyuan Fang, Zaiqiao Meng, Shangsong Liang

Knowledge graph embedding (KGE) is an increasingly popular technique that aims to represent entities and relations of knowledge graphs into low-dimensional semantic spaces for a wide spectrum of applications such as link prediction, knowledge reasoning and knowledge completion. In this paper, we provide a systematic review of existing KGE techniques based on

Pengfei Zhang, Zhenhua Yu

In closed generic many-body systems, unitary evolution disperses local quantum information into highly non-local objects, resulting in thermalization. Such a process is called information scrambling, whose swiftness is quantified by the operator size growth. However, for quantum systems embedded in an environment, how the couplings to the environment affect

Cristian Joana

Cosmic inflation is arguably the most favoured paradigm of the very early Universe. It postulates an early phase of fast, nearly exponential, and accelerated expansion. Inflationary models are capable of explaining the overall flatness and homogeneity of today's Universe at large scales. Despite being widely accepted by the physics community, these models ar

Apoorva Upadhyaya, Marco Fisichella, Wolfgang Nejdl

Climate change has become one of the biggest challenges of our time. Social media platforms such as Twitter play an important role in raising public awareness and spreading knowledge about the dangers of the current climate crisis. With the increasing number of campaigns and communication about climate change through social media, the information could creat

Daowen Lin, Xi-Nan Ma

We use the integral by parts to get a Liouville type theorem for a class quasilinear $p$-Laplace type equation on the sphere, this $p$-Laplace type equation arises from the study of asymptotic behavior near the origin for the semi-linear $p$-Laplace equation on the puncture ball $B_1(o) \subset R^n$. This gives a positive answer to L. V\'{e}ron's question in

Subhasanket Dutta, Omar Alamoudi, Yash Shashank Vakilna, Sandipan Pati

Quenching of oscillations, namely amplitude and oscillations death, is an emerging phenomenon exhibited by many real-world complex systems. Here, we introduce a scheme that combines dissimilar couplings and repulsive feedback links for the interactions of Stuart Landau oscillators and analytically derives the conditions required for the amplitude death. Impo

Alkida Balliu, Rustam Latypov, Yannic Maus, Dennis Olivetti

We show fast deterministic algorithms for fundamental problems on forests in the challenging low-space regime of the well-known Massive Parallel Computation (MPC) model. A recent breakthrough result by Coy and Czumaj [STOC'22] shows that, in this setting, it is possible to deterministically identify connected components on graphs in $O(\log D + \log\log n)$

William H. Meeks, Joaquin Perez

Given $I,B\in\mathbb{N}\cup \{0\}$, we investigate the existence and geometry of complete finitely branched minimal surfaces $M$ in $\mathbb{R}^3$ with Morse index at most $I$ and total branching order at most $B$. Previous works of Fischer-Colbrie and Ros explain that such surfaces are precisely the complete minimal surfaces in $\mathbb{R}^3$ of finite tota

Simranjeet Singh, Furqan Zahoor, Gokulnath Rajendran, Sachin Patkar

With rapid advancements in electronic gadgets, the security and privacy aspects of these devices are significant. For the design of secure systems, physical unclonable function (PUF) and true random number generator (TRNG) are critical hardware security primitives for security applications. This paper proposes novel implementations of PUF and TRNGs on the RR

Thong Nguyen, Xiaobao Wu, Anh-Tuan Luu, Cong-Duy Nguyen

Modern Review Helpfulness Prediction systems are dependent upon multiple modalities, typically texts and images. Unfortunately, those contemporary approaches pay scarce attention to polish representations of cross-modal relations and tend to suffer from inferior optimization. This might cause harm to model's predictions in numerous cases. To overcome the afo

Chengjie Fu, Shao-Jiang Wang

The primordial black hole (PBH) productions from the inflationary potential with an inflection point usually rely heavily on the fine-tuning of the model parameters. We propose in this work a new kind of the $\alpha$-attractor inflation with asymmetric double poles that naturally and easily lead to a period of non-attractor inflation, during which the PBH pr

Alexis Jacq, Manu Orsini, Gabriel Dulac-Arnold, Olivier Pietquin

Recent advances in ML suggest that the quantity of data available to a model is one of the primary bottlenecks to high performance. Although for language-based tasks there exist almost unlimited amounts of reasonably coherent data to train from, this is generally not the case for Reinforcement Learning, especially when dealing with a novel environment. In ef

Tao Chen, Arindam Ghosh, Jörg Enderlein

Graphene-induced energy transfer (GIET) is a recently developed fluorescence-spectroscopic technique that achieves sub-nanometric optical localization of fluorophores along the optical axis of a microscope. GIET is based on the near-field energy transfer from an optically excited fluorescent molecule to a single sheet of graphene. It has been successfully us

S. G. Menshikova, N. M. Chtchelkatchev, V. V. Brazhkin

High pressures allow the synthesis of new metastable compounds that remain intact for a sufficiently long time at normal conditions. Until now, it has not been fully understood how pressure, glass-forming ability and solidification of liquids are interconnected. We have investigated the structure of the glass-forming eutectic alloy Al86Ni2Co6Gd6 obtained by

Rajdeep Adak, Abhishek Kumbhar, Rajas Pathare, Sagar Gowda

We present a YOLOv3-CNN pipeline for detecting vehicles, segregation of number plates, and local storage of final recognized characters. Vehicle identification is performed under various image correction schemes to determine the effect of environmental factors (angle of perception, luminosity, motion-blurring, and multi-line custom font etc.). A YOLOv3 objec

Eda Okur, Saurav Sahay, Roddy Fuentes Alba, Lama Nachman

The advances in language-based Artificial Intelligence (AI) technologies applied to build educational applications can present AI for social-good opportunities with a broader positive impact. Across many disciplines, enhancing the quality of mathematics education is crucial in building critical thinking and problem-solving skills at younger ages. Conversatio

Jianing Bai, Ren Wang, Zuyi Li

The advances in deep learning (DL) techniques have the potential to deliver transformative technological breakthroughs to numerous complex tasks in modern power systems that suffer from increasing uncertainty and nonlinearity. However, the vulnerability of DL has yet to be thoroughly explored in power system tasks under various physical constraints. This wor

Zijie Lou, Gang Cao, Man Lin

Visually realistic GAN-generated facial images raise obvious concerns on potential misuse. Many effective forensic algorithms have been developed to detect such synthetic images in recent years. It is significant to assess the vulnerability of such forensic detectors against adversarial attacks. In this paper, we propose a new black-box attack method against

Csaba L. Korpa, Matthias F. M. Lutz, Xiao-Yu Guo, Yonggoo Heo

We consider the isospin one-half example system, with $D \,\pi , D\,\eta, D_s \bar K, D^* \pi , D^*\eta, D^*\bar K$ coupled channels in the $J^P = 1^-$ partial wave, chosen such that various phenomena that come with the opening of an anomalous threshold can be illustrated in a step-wise procedure by a suitable variation of up, down and strange quark masses.

Laurent Seugnet

The branched-chain amino acids: leucine, isoleucine and valine occupy a special place among the essential amino acids because of their importance not only in the structure of proteins but also in general and cerebral metabolism. Among the first amino acids absorbed after food intake, they play a major role in the regulation of protein synthesis and insulin s

Henri Hänninen, Heikki Mäntysaari, Risto Paatelainen, Jani Penttala

We predict heavy quark production cross sections in Deep Inelastic Scattering at high energy by applying the Color Glass Condensate effective theory. We demonstrate that when the calculation is performed consistently at next-to-leading order accuracy with massive quarks it becomes possible, for the first time in the dipole picture with perturbatively calcula

Divya Oberoi, Susanta Kumar Bisoi, K. Sasikumar Raja, Devojyoti Kansabanik

The Square Kilometre Array Observatory (SKAO) is perhaps the most ambitious radio telescope envisaged yet. It will enable unprecedented studies of the Sun, the corona and the heliosphere and help to answer many of the outstanding questions in these areas. Its ability to make a vast previously unexplored phase space accessible, also promises a large discovery