November 2022 arXiv papers — page 51

Fabio Paparella, Karni Chauhan, Theo Hofman, Mauro Salazar

The advent of vehicle autonomy, connectivity and electric powertrains is expected to enable the deployment of Autonomous Mobility-on-Demand systems. Crucially, the routing and charging activities of these fleets are impacted by the design of the individual vehicles and the surrounding charging infrastructure which, in turn, should be designed to account for

Shishir Biswas, Rajaraman Ganesh

Dynamos wherein magnetic field is produced from velocity fluctuations are fundamental to our understanding of several astrophysical and/or laboratory phenomena. Though fluid helicity is known to play a key role in the onset of dynamo action, its effect is yet to be fully understood. In this work, a fluid flow proposed recently [Yoshida et al. Phys. Rev. Lett

Claudio B. Caporusso, Leticia F. Cugliandolo, Pasquale Digregorio, Giuseppe Gonnella

We study the dynamics of clusters of Active Brownian Disks generated by Motility-Induced Phase Separation, by applying an algorithm that we devised to track cluster trajectories. We identify an aggregation mechanism that goes beyond Ostwald ripening but also yields $z=3$. Active clusters of mass $M$ self-propel with enhanced diffusivity $D\sim$ Pe$^2/\sqrt{M

Tobias Mayer, Neha Warikoo, Oliver Grimm, Andreas Reif

According to the Global Burden of Disease list provided by the World Health Organization (WHO), mental disorders are among the most debilitating disorders.To improve the diagnosis and the therapy effectiveness in recent years, researchers have tried to identify individual biomarkers. Gathering neurobiological data however, is costly and time-consuming. Anoth

Nathan Chapelier-Laget, Thomas Gerber

We define a new statistic on Weyl groups called the atomic length and investigate its combinatorial and representation-theoretic properties. In finite types, we show a number of properties of the atomic length which are reminiscent of the properties of the usual length. Moreover, we prove that, with the exception of rank two, this statistic describes an inte

Murwan Bashir, Ehsan Nassaji, Dmitri Truhachev, Alireza Bayesteh

In this paper we focus on a feedback mechanism for unsourced random access (URA) communications. We propose an algorithm to construct feedback packets broadcasted to the users by the base station (BS) as well as the feedback packet format that allows the users to estimate their channels and infer positive or negative feedback based on the presented threshold

Genly Leon, Alfredo D. Millano, Andronikos Paliathanasis

We investigate the phase space of a scalar field theory obtained by minisuperspace deformation. We consider quintessence or phantom scalar fields in the action which arise from minisuperspace deformation on the Einstein-Hilbert action. We use a modified Poisson Algebra where Poisson brackets are the $\alpha$-deformed ones and are related to the Moyal-Weyl st

Vishwas Kukreti

Being archetypal complex systems, financial markets exhibit rich set of dynamics in their interactions. In this paper, we focus on the recently evolved cryptocurrency market as an example of a complex system and analyse the evolution of cross correlation structure of cryptocurrencies in the 5 year period from 2017 to 2022. We observe characteristic correlati

Andrej Liptaj

Derivative-matching approximations are constructed as power series built from functions. The method assumes the knowledge of special values of the Bell polynomials of the second kind, for which we refer to the literature. The presented ideas may have applications in numerical mathematics.

Evangelia Ntormousi, Fabio Del Sordo, Matteo Cantiello, Andrea Ferrara

Explaining the currently observed magnetic fields in galaxies requires relatively strong seeding in the early Universe. One theory proposes that magnetic fields of the order of $\mu$G were expelled by supernova (SN) explosions after primordial, nG or weaker fields were amplified in stellar interiors. In this work, we calculate the maximum magnetic energy tha

Qihao Peng, Hong Ren, Cunhua Pan, Nan Liu

Smart factories need to support the simultaneous communication of multiple industrial Internet-of-Things (IIoT) devices with ultra-reliability and low-latency communication (URLLC). Meanwhile, short packet transmission for IIoT applications incurs performance loss compared to traditional long packet transmission for human-to-human communications. On the othe

Matías Tailanian, Álvaro Pardo, Pablo Musé

In this work we propose a one-class self-supervised method for anomaly segmentation in images that benefits both from a modern machine learning approach and a more classic statistical detection theory. The method consists of four phases. First, features are extracted using a multi-scale image Transformer architecture. Then, these features are fed into a U-sh

Chao Wang, Ana Serrano, Xingang Pan, Bin Chen

Most in-the-wild images are stored in Low Dynamic Range (LDR) form, serving as a partial observation of the High Dynamic Range (HDR) visual world. Despite limited dynamic range, these LDR images are often captured with different exposures, implicitly containing information about the underlying HDR image distribution. Inspired by this intuition, in this work

Shunsuke Tsuchioka

We reformulate the Kanade-Russell conjecture modulo 9 via the vertex operators for the level 3 standard modules of type $D^{(3)}_{4}$. Along the same line, we arrive at three partition theorems which may be regarded as an $A^{(2)}_{4}$ analog of the conjecture. One had been proven by Andrews-van Ekeren-Heluani and we point out that the others are easily prov

Hou-Jian Duan, Yong-Jia Wu, Ming-Xun Deng, Ruiqiang Wang

Recently, abundant transport phenomena characterizing the surface states of Weyl semimetals (WSMs) have been reported. To generate these phenomena, electrons have to complete a closed intersurface orbit. Due to the unavoidable impurities in real materials, this orbit would be destroyed by the impurity scattering, which limits the detection of the surface sta

A. Lima, G. Alencar, J. Furtado

In this work, a regular black string solution will be presented from the method used by Simpson-Visser to regularize the Schwarzschild solution. As in the Simpson-Visser work, in this new black string solution, it is possible to represent both a regular black hole and a wormhole just by changing the value of a parameter "$a$" used in its metric. Tensors and

Yun Cheng, Yixue Liu, Tomasz Tkocz, Albert Xu

Suppose that the edges of a complete graph are assigned weights independently at random and we ask for the weight of the minimal-weight spanning tree, or perfect matching, or Hamiltonian cycle. For these and several other common optimisation problems, we establish asymptotically tight bounds when the weights are independent copies of a symmetric random varia

Lingxiao Li, Yi Zhang, Shuhui Wang

Few-shot image generation is a challenging task since it aims to generate diverse new images for an unseen category with only a few images. Existing methods suffer from the trade-off between the quality and diversity of generated images. To tackle this problem, we propose Hyperbolic Attribute Editing~(HAE), a simple yet effective method. Unlike other methods

Sotiris Anagnostidis, Arne Thomsen, Tomasz Kacprzak, Tilman Tröster

In recent years, deep learning approaches have achieved state-of-the-art results in the analysis of point cloud data. In cosmology, galaxy redshift surveys resemble such a permutation invariant collection of positions in space. These surveys have so far mostly been analysed with two-point statistics, such as power spectra and correlation functions. The usage

Adrian Goldwaser, Hong Ge

Larger and deeper networks generalise well despite their increased capacity to overfit. Understanding why this happens is theoretically and practically important. One recent approach looks at the infinitely wide limits of such networks and their corresponding kernels. However, these theoretical tools cannot fully explain finite networks as the empirical kern

Massimiliano Semeraro, Giuseppe Negro, Antonio Suma, Giuseppe Gonnella

We employ the diffusing transcription factors model for numerical simulation of chromatin topology conformations and transcriptional processes of human chromatin. Simulations of a short chromatin filament reveal different possible pathways to regulate transcription: it is shown that the transcriptional activity profile can be regulated and controlled by eith

Fabian Waschkowski, Haochen Li, Abhishek Deshmukh, Temistocle Grenga

Learning accurate numerical constants when developing algebraic models is a known challenge for evolutionary algorithms, such as Gene Expression Programming (GEP). This paper introduces the concept of adaptive symbols to the GEP framework by Weatheritt and Sandberg (2016) to develop advanced physics closure models. Adaptive symbols utilize gradient informati

Jiaming Liu, Rushil Anirudh, Jayaraman J. Thiagarajan, Stewart He

Limited-Angle Computed Tomography (LACT) is a non-destructive evaluation technique used in a variety of applications ranging from security to medicine. The limited angle coverage in LACT is often a dominant source of severe artifacts in the reconstructed images, making it a challenging inverse problem. We present DOLCE, a new deep model-based framework for L

Laura Wadleigh, Nicholas Kowalski, Brian DeMarco

We measure the thermalization dynamics of a lattice Bose gas that is Stark localized by a parabolic potential. A non-equilibrium thermal density distribution is created by quickly removing an optical barrier. The resulting spatio-temporal dynamics are resolved using Mardia's $B$ statistic, which is a measure sensitive to the shape of the entire density distr

Alejandro Cartas, Coloma Ballester, Gloria Haro

Action spotting in soccer videos is the task of identifying the specific time when a certain key action of the game occurs. Lately, it has received a large amount of attention and powerful methods have been introduced. Action spotting involves understanding the dynamics of the game, the complexity of events, and the variation of video sequences. Most approac

Diana Cremoncini, Guido Francesco Frate, Aldo Bischi, Lorenzo Ferrari

Redox Flow Batteries are a promising option for large-scale stationary energy storage. The vanadium redox flow battery is the most widely commercialized system thanks to its chemical stability and performance. This work aims to optimize the scheduling of a vanadium flow battery that stores energy produced by a renewable power plant, keeping into account a th

Andrés Quilis

We develop tools to produce equivalent norms with specific local geometry around infinitely many points in the sphere of a Banach space via an inductive procedure. We combine this process with smoothness results and techniques to solve two open problems posed in the recently published monograph [GMZ22] by A. J. Guirao, V. Montesinos and V. Zizler. Specifical

Seungin Oh, Hanmin Lee, Jai-Kyung Lee, Hyungchul Yoon

This study aimed to develop a virtual sensing algorithm of structural vibration for the real-time identification of unmeasured information. First, certain local point vibration responses (such as displacement and acceleration) are measured using physical sensors, and the data sets are extended using a numerical model to cover the unmeasured quantities throug

Benjamin Bode

Semiholomorphic polynomials are functions $f:\mathbb{C}^2\to\mathbb{C}$ that can be written as polynomials in complex variables $u$, $v$ and the complex conjugate $\overline{v}$. We prove the semiholomorphic analogoue of Akbulut's and King's "All knots are algebraic", that is, every link type in the 3-sphere arises as the link of a weakly isolated singularit

Daniel Gehrig, Davide Scaramuzza

State-of-the-art machine-learning methods for event cameras treat events as dense representations and process them with conventional deep neural networks. Thus, they fail to maintain the sparsity and asynchronous nature of event data, thereby imposing significant computation and latency constraints on downstream systems. A recent line of work tackles this is

Zhenxin Lei, Ruijie He, Peter Nemeth, Joris Vos

222 hot subdwarf stars were identified with LAMOST DR8 spectra, among which 131 stars show composite spectra and have been decomposed, while 91 stars present single-lined spectra. Atmospheric parameters of all sample stars were obtained by fitting Hydrogen (H) and Helium (He) line profiles with synthetic spectra. Two long-period composite sdB binaries were n

Awad Abdelhalim, Jinhua Zhao

Accurate travel time estimation is paramount for providing transit users with reliable schedules and dependable real-time information. This paper is the first to utilize roadside urban imagery for direct transit travel time prediction. We propose and evaluate an end-to-end framework integrating traditional transit data sources with a roadside camera for auto

Erik Bédos, Roberto Conti

We revisit Fourier's approach to solve the heat equation on the circle in the context of (twisted) reduced group C*-algebras, convergence of Fourier series and semigroups associated to negative definite functions. We introduce some heat properties for countably infinite groups and investigate when they are satisfied. Kazhdan's property (T) is an obstruction

Jun Liang, Songsen Yu, Huan Yang

ResNets and its variants play an important role in various fields of image recognition. This paper gives another variant of ResNets, a kind of cross-residual learning networks called C-ResNets, which has less computation and parameters than ResNets. C-ResNets increases the information interaction between modules by densifying jumpers and enriches the role of

Andreas Blatter, Jan Draisma, Filip Rupniewski

Restriction is a natural quasi-order on $d$-way tensors. We establish a remarkable aspect of this quasi-order in the case of tensors over a fixed finite field -- namely, that it is a well-quasi-order: it admits no infinite antichains and no infinite strictly decreasing sequences. This result, reminiscent of the graph minor theorem, has important consequences

Massimo Fioravanti, Daniele Cattaneo, Federico Terraneo, Silvano Seva

Equation-based modelling is a powerful approach to tame the complexity of large-scale simulation problems. Equation-based tools automatically translate models into imperative languages. When confronted with nowadays' problems, however, well assessed model translation techniques exhibit scalability issues, that are particularly severe when models contain very

Jason Z. S. Hu, Brigitte Pientka

We investigate a simply typed modal $\lambda$-calculus, $\lambda^{\to\square}$, due to Pfenning, Wong and Davies, where we define a well-typed term with respect to a context stack that captures the possible world semantics in a syntactic way. It provides logical foundation for multi-staged meta-programming. Our main contribution in this paper is a normalizat

Xiaojun Ruan, Xiaoquan Xu

In this paper, as a common generalization of $SI_{2}$-continuous spaces and $s_{2}$-quasicontinuous posets, we introduce the concepts of $SI_{2}$-quasicontinuous spaces and $\mathcal{GD}$-convergence of nets for arbitrary topological spaces by the cuts. Some characterizations of $SI_{2}$-quasicontinuity of spaces are given. The main results are: (1) a space

Satwik Bhattamishra, Arkil Patel, Varun Kanade, Phil Blunsom

Despite the widespread success of Transformers on NLP tasks, recent works have found that they struggle to model several formal languages when compared to recurrent models. This raises the question of why Transformers perform well in practice and whether they have any properties that enable them to generalize better than recurrent models. In this work, we co

Sepide Saeedi, Alessio Carpegna, Alessandro Savino, Stefano Di Carlo

Approximate Computing (AxC) techniques trade off the computation accuracy for performance, energy, and area reduction gains. The trade-off is particularly convenient when the applications are intrinsically tolerant to some accuracy loss, as in the Spiking Neural Networks (SNNs) case. SNNs are a practical choice when the target hardware reaches the edge of co

Jie Zhang, Yihui Zhao, Tianzhe Bao, Zhenhong Li

Data-driven methods have become increasingly more prominent for musculoskeletal modelling due to their conceptually intuitive simple and fast implementation. However, the performance of a pre-trained data-driven model using the data from specific subject(s) may be seriously degraded when validated using the data from a new subject, hindering the utility of t

Shengbang Fang, Matthew C Stamm

Recent advances in deep learning have enabled forensics researchers to develop a new class of image splicing detection and localization algorithms. These algorithms identify spliced content by detecting localized inconsistencies in forensic traces using Siamese neural networks, either explicitly during analysis or implicitly during training. At the same time

Dagmara Oszkiewicz, Hanna Klimczak, Benoit Carry, Antti Penttila

There is a great deal of scientific interest in characterizing the basaltic asteroids (spectrally classified as V-types), as they are the key to understanding planetesimal formation and evolution in the early Solar System. These have long been recognized as parts of the crusts of fully differentiated planetesimals. Thus, their multiplicity, distribution, and

Sid Black, Lee Sharkey, Leo Grinsztajn, Eric Winsor

Mechanistic interpretability aims to explain what a neural network has learned at a nuts-and-bolts level. What are the fundamental primitives of neural network representations? Previous mechanistic descriptions have used individual neurons or their linear combinations to understand the representations a network has learned. But there are clues that neurons a

Haiming Yao, Wenyong Yu

Industrial vision anomaly detection plays a critical role in the advanced intelligent manufacturing process, while some limitations still need to be addressed under such a context. First, existing reconstruction-based methods struggle with the identity mapping of trivial shortcuts where the reconstruction error gap is legible between the normal and abnormal

Yasuaki Fujitani

For $n$-dimensional weighted Riemannian manifolds, lower $m$-Bakry-\'{E}mery-Ricci curvature bounds with $\varepsilon$-range, introduced by Lu-Minguzzi-Ohta, integrate constant lower bounds and certain variable lower bounds in terms of weight functions. In this paper, we prove a Cheng type inequality and a local Sobolev inequality under lower $m$-Bakry-\'{E}

Rameez Raja, Samir Ahmad Wagay

Let G = (V, E) be a finite simple connected graph. We say a graph G realizes a code of the type 0^s_1 1^t_1 0^s_2 1^t_2 ... 0^s_k1^t_k if and only if G can obtained from the code by some rule. Some classes of graphs such as threshold and chain graphs realizes a code of the above mentioned type. In this paper, we develop some computationally feasible methods

Léo Simpson, Armin Nurkanović, Moritz Diehl

Mechanical systems are usually modeled by second-order Ordinary Differential Equations (ODE) which take the form $\ddot{q} = f(t, q, \dot{q})$. While simulation methods tailored to these equations have been studied, using them in direct optimal control methods is rare. Indeed, the standard approach is to perform a state augmentation, adding the velocities to

Thomas Eiter, Robert Lasarzik

We introduce the concept of energy-variational solutions for hyperbolic conservation laws. Intrinsically, these energy-variational solutions fulfill the weak-strong uniqueness principle and the semi-flow property, and the set of solutions is convex and weakly-star closed. The existence of energy-variational solutions is proven via a suitable time-discretizat

Nandrianina Randriamiarinarivo, Ed Elson, Andrew Baker

HI line observations of nearby galaxies often reveal the presence of extraplanar and/or kinematically anomalous gas that deviates from the general circular flow. In this work, we study the dependence of kinematically anomalous HI gas in galaxies taken from the Simba cosmological simulation on galaxy properties such as HI mass fraction, specific star formatio

Oleg Andreev

For the case of two light flavors we propose the stringy description of the system consisting of two heavy and three light quarks, with the aim of exploring the quark organization inside the system and its low-lying Born-Oppenheimer potentials as a function of the heavy quark separation. Our analysis reveals several critical separations related to the proces

G. Kanwar, A. Mariani, J. C. Pinto Barros, U. J. Wiese

Charged particles in an Abelian Coulomb phase are non-local infraparticles that are surrounded by a cloud of soft photons which extends to infinity. Gauss' law prevents the existence of charged particles in a periodic volume. In a $C$-periodic volume, which is periodic up to charge conjugation, on the other hand, charged particles can exist. This includes vo

Pushpa Panday, Binoy Krishna Patra

We have investigated the effect of a weak magnetic field on momentum transport in a thermal QCD medium at finite quark chemical potential using a semiclassical kinetic theory. In the presence of a magnetic field, the momentum transport coefficients acquire a tensor structure, reflected by the five shear $\left(\eta_0, \eta_1, \eta_2, \eta_3\right.$ and $\lef

Léo Simpson, Andrea Ghezzi, Jonas Asprion, Moritz Diehl

We present an optimization-based method for the joint estimation of system parameters and noise covariances of linear time-variant systems. Given measured data, this method maximizes the likelihood of the parameters. We solve the optimization problem of interest via a novel structure-exploiting solver. We present the advantages of the proposed approach over

Omri Ben-Eliezer, Dan Mikulincer, Elchanan Mossel, Madhu Sudan

Societal accumulation of knowledge is a complex process. The correctness of new units of knowledge depends not only on the correctness of new reasoning, but also on the correctness of old units that the new one builds on. The errors in such accumulation processes are often remedied by error correction and detection heuristics. Motivating examples include the

Keith M. Furutani, Nicholas N. Remmes, Jon J. Kruse, Michael G. Herman

Charge accumulation was measured under calibration conditions in the spread-out Bragg peak (SOBP) using the calibration bias as well as a range of voltages from 10V to 500V and a Farmer-style ion chamber. Collection efficiency was determined by extrapolating to infinite voltage. Similar measurements were taken in an identical dose distribution with a much sh

Manuel Bröchin, Bryn Pickering, Tim Tröndle, Stefan Pfenninger

Energy system models based on linear programming have been growing in size with the increasing need to model renewables with high spatial and temporal detail. Larger models lead to high computational requirements. Furthermore, seemingly small changes in a model can lead to drastic differences in runtime. Here, we investigate measures to address this issue. W

Ivan Shtepliuk, Rositsa Yakimova

The combination of wide-band gap semiconductors like zinc oxide (ZnO) and graphene quantum dots (GQDs) is a promising strategy to tune optoelectronic properties of GQDs and to develop new functionalities. Here we report on a theoretical design of not-yet-synthesized hybrid materials composed of ZnO clusters surrounded by carbon moieties, hereinafter referred

Bianca M. Poggianti, the GASP team

Integral field spectroscopic studies of galaxies in dense environments, such as clusters and groups of galaxies, have provided new insights for understanding how star formation proceeds, and quenches. I present the spatially resolved view of the star formation activity and its link with the multiphase gas in cluster galaxies based on MUSE and multi-wavelengt

Neha Warikoo, Tobias Mayer, Dana Atzil-Slonim, Amir Eliassaf

Emotions are experienced and expressed through various response systems. Coherence between emotional experience and emotional expression is considered important to clients' well being. To date, emotional coherence (EC) has been studied at a single time point using lab-based tasks with relatively small datasets. No study has examined EC between the subjective

G. Ptitcyn, M. S. Mirmoosa, A. Sotoodehfar, S. A. Tretyakov

During the last decade, possibilities to realize new phenomena and create new applications by varying system properties in time have gained increasing attention in many research fields, spanning a wide range from acoustics to optics. While the interest in using time-modulation techniques for engineering electromagnetic response has got revitalized only in re

Ran Liu, Ze Wu, Xiaodong Yang, Yuchen Li

By utilizing quantum mechanical effects, such as superposition and entanglement, quantum metrology promises higher precision than the classical strategies. It is, however, practically challenging to realize the quantum advantages. This is mainly due to the difficulties in engineering non-classical probe state and performing nontrivial measurement in practise

Shunsuke Kitamura

In this paper, we investigate the lifespan estimates of classical solutions of the initial value problems for semilinear wave equations of derivative type with characteristic weights in one space dimension. Such equations provide us basic principles on extending the general theory for nonlinear wave equations to the non-autonomous case. In our results, two c

Kenza Tazi, Emiliano Díaz Salas-Porras, Ashwin Braude, Daniel Okoh

Pyrocumulonimbus (pyroCb) clouds are storm clouds generated by extreme wildfires. PyroCbs are associated with unpredictable, and therefore dangerous, wildfire spread. They can also inject smoke particles and trace gases into the upper troposphere and lower stratosphere, affecting the Earth's climate. As global temperatures increase, these previously rare eve

Shengshan Hu, Junwei Zhang, Wei Liu, Junhui Hou

Point cloud completion, as the upstream procedure of 3D recognition and segmentation, has become an essential part of many tasks such as navigation and scene understanding. While various point cloud completion models have demonstrated their powerful capabilities, their robustness against adversarial attacks, which have been proven to be fatally malicious tow

Wei Zhang, Yi Jiang, Bin Zhou

The wireless in-band full-duplex (IBFD) technology can in theory double the system capacity over the conventional frequency division duplex (FDD) or time-division duplex (TDD) alternatives. But the strong self-interference of the IBFD can cause excessive quantization noise in the analog-to-digital converters (ADC), which represents the hurdle for its real im

Marco Cotogni, Fei Yang, Claudio Cusano, Andrew D. Bagdanov

We propose a new method for exemplar-free class incremental training of ViTs. The main challenge of exemplar-free continual learning is maintaining plasticity of the learner without causing catastrophic forgetting of previously learned tasks. This is often achieved via exemplar replay which can help recalibrate previous task classifiers to the feature drift

Guglielmo Fucci, César Romaniega Sancho

This work analyzes the Casimir energy of a massive spinor field propagating in flat space endowed with a spherically symmetric $\delta$-function potential. By utilizing the spectral zeta function regularization method, the Casimir energy is evaluated after performing a suitable analytic continuation. Explicit numerical results are provided for specific cases

Yujin Lu, Alessandro Del Buono, Tianhang Xiao, Alessandro Iafrati

The present study is concerned with the peak acceleration azmax occurring during the water impact of a symmetric wedge. This aspect can be important for design considerations of safe marine vehicles. The water-entry problem is firstly studied numerically using the finite-volume discretization of the incompressible Navier-Stokes equations and the volume-of-fl

K. Murawski, Z. E. Musielak, S. Poedts, A. K. Srivastava

\textbf{Purpose:} This paper addresses long-standing solar physics problems, namely, the heating of the solar chromosphere and the origin of the solar wind. Our aim is to reveal the related mechanisms behind chromospheric heating and plasma outflows in a quiet-Sun. \textbf{Methods:} The approach is based on a two-fluid numerical model that accounts for therm

M. Spieker, L. A. Riley, P. D. Cottle, K. W. Kemper

Enhanced octupole collectivity is expected in the neutron-deficient Ge, Se and Kr isotopes with neutron number $N \approx 40$ and has indeed been observed for $^{70,72}$Ge. Shape coexistence and configuration mixing are, however, a notorious challenge for theoretical models trying to reliably predict octupole collectivity in this mass region, which is known

Daulet Kurmantayev, Dohyun Kwun, Hyoil Kim, Sung Whan Yoon

RAN-agnostic communications can identify intrinsic features of the unknown signal without any prior knowledge, with which incompatible RANs in the same unlicensed band could achieve better coexistence performance than today's LBT-based coexistence. Blind modulation identification is its key building block, which blindly identifies the modulation type of an i

Yuhui Wu, Zhu Liu, Jinyuan Liu, Xin Fan

Infrared and visible image fusion plays a vital role in the field of computer vision. Previous approaches make efforts to design various fusion rules in the loss functions. However, these experimental designed fusion rules make the methods more and more complex. Besides, most of them only focus on boosting the visual effects, thus showing unsatisfactory perf

Brian K. S. Isaac-Medina, Chris G. Willcocks, Toby P. Breckon

Neural Radiance Fields (NeRF) have attracted significant attention due to their ability to synthesize novel scene views with great accuracy. However, inherent to their underlying formulation, the sampling of points along a ray with zero width may result in ambiguous representations that lead to further rendering artifacts such as aliasing in the final scene.

Anshika Bansal, Namit Mahajan, Dayanand Mishra

Recently \cite{Horowitz:2022rpp,Horowitz:2022uak}, denominator regularisation (Den. Reg.) scheme has been proposed to handle divergences in quantum field theory. It is shown to yield results as simple as in dimensional regularisation scheme and also shown to be compatible with minimal subtraction scheme by taking several examples in field theory. In this art

Michael Zacharias

There is a large variety in the models explaining blazar flares. Here, we study the flare profile induced by a moving and expanding blob with special emphasize on the gamma-gamma pair production. We first develop a simple semi-analytical model to study the evolution of the particle distribution in the expanding blob and show the influence of the pair product

Wenxuan Chen, Jun Tao, Lu Ma, Gang Qiao

Accurate channel estimation is critical to the performance of orthogonal frequency-division multiplexing (OFDM) underwater acoustic (UWA) communications, especially under multiple-input multiple-output (MIMO) scenarios. In this paper, we explore Vector Approximate Message Passing (VAMP) coupled with Expected Maximum (EM) to obtain channel estimation (CE) for

Alberto Cattaneo, Daniel Justus, Harry Mellor, Douglas Orr

We present the award-winning submission to the WikiKG90Mv2 track of OGB-LSC@NeurIPS 2022. The task is link-prediction on the large-scale knowledge graph WikiKG90Mv2, consisting of 90M+ nodes and 600M+ edges. Our solution uses a diverse ensemble of $85$ Knowledge Graph Embedding models combining five different scoring functions (TransE, TransH, RotatE, DistMu

Jiachen Li, Menglin Wang, Xiaojin Gong

Multi-grained features extracted from convolutional neural networks (CNNs) have demonstrated their strong discrimination ability in supervised person re-identification (Re-ID) tasks. Inspired by them, this work investigates the way of extracting multi-grained features from a pure transformer network to address the unsupervised Re-ID problem that is label-fre

Georges Gras

We examine the phenomenon of capitulation of the $p$-class group $H_K$ of a real number field $K$ in totally ramified cyclic p-extensions $L/K$ of degree $p^N$. Using an elementary property of the algebraic norm $\nu_{L/K}$, we show that the kernel of capitulation is in relation with the "complexity" of the structure of $H_L$ measured via its exponent $p^e(L

Lorenzo Barca, Gunnar Bali, Sara Collins

QCD matrix elements of axial and vector currents between nucleons are required for the Monte Carlo reconstruction of the energy of neutrinos that are detected in long baseline oscillation experiments in the quasi-elastic regime. The cleanest approach for determining the axial matrix elements is lattice QCD. However, the extraction of these from the correspon

Peng Wang, Jingzhou Chen, Yuntao Qian

Hierarchical classification (HC) assigns each object with multiple labels organized into a hierarchical structure. The existing deep learning based HC methods usually predict an instance starting from the root node until a leaf node is reached. However, in the real world, images interfered by noise, occlusion, blur, or low resolution may not provide sufficie

Raluca Cruceru

The ALICE Collaboration has just finished a major detector upgrade that increases the data-taking rate capability by two orders of magnitude and will allow to collect unprecedented data samples. For example, the analysis input for 1 month of Pb-Pb collisions amounts to about 5 PB. In order to enable analysis on such large data samples, the ALICE distributed

Quentin Jacquet, Riadh Zorgati

We study a tight Bennett-type concentration inequality for sums of heterogeneous and independent variables, defined as a one-dimensional minimization. We show that this refinement, which outperforms the standard known bounds, remains computationally tractable: we develop a polynomial-time algorithm to compute confidence bounds, proved to terminate with an ep

Paul Cazeaux, Drake Clark, Rebecca Engelke, Philip Kim

Moire patterns result from setting a 2D material such as graphene on another 2D material with a small twist angle or from the lattice mismatch of 2D heterostructures. We present a continuum model for the elastic energy of these bilayer moire structures that includes an intralayer elastic energy and an interlayer misfit energy that is minimized at two stackin

Hakim Gharbi, Wang Wenlong, Chloé Giraudet, Jean-Marc Allain

Background: Direct dental restoration implies a drying of the dentin substrate. This drying may induce significant strain in the dentin, affecting the bonding efficiency of the restoration. Objective: We measure the dilatation of dentine under changes of relative humidity as well as the impact of humidity on dentin elastic properties. This investigates the r

Haitao Hu, Yiqiu Zhao, Weiwei Zhao, Ligen Qiao

We systematically investigated the impact of boundary confinement on the shear-thickening rheology of dense granular suspensions. Under highly confined conditions, dense suspensions were found to exhibit size-dependent or even rarely reported non-monotonic ($S$-shaped) flow curves in steady states. By performing in-situ boundary stress microscopy measurement

Georgios Vardakas, Aristidis Likas

The $k$-means algorithm is a prevalent clustering method due to its simplicity, effectiveness, and speed. However, its main disadvantage is its high sensitivity to the initial positions of the cluster centers. The global $k$-means is a deterministic algorithm proposed to tackle the random initialization problem of k-means but its well-known that requires hig

Khaled Qazaqzeh, Ahmad Al-Rhayyel

We apply the twisting technique that was first introduced in \cite{CK} and later generalized in \cite{QCQ} to obtain an infinite family of adequate, homogeneous or alternative links from a given adequate, homogeneous or alternative link, respectively. Thus we conclude that these three classes of links are infinite.

Zesen Cheng, Pengchong Qiao, Kehan Li, Siheng Li

Weakly supervised semantic segmentation is typically inspired by class activation maps, which serve as pseudo masks with class-discriminative regions highlighted. Although tremendous efforts have been made to recall precise and complete locations for each class, existing methods still commonly suffer from the unsolicited Out-of-Candidate (OC) error predictio

Marc Hoffmann, Kolyan Ray

We consider nonparametric Bayesian inference in a multidimensional diffusion model with reflecting boundary conditions based on discrete high-frequency observations. We prove a general posterior contraction rate theorem in $L^2$-loss, which is applied to Gaussian priors. The resulting posteriors, as well as their posterior means, are shown to converge to the

Przemyslaw Chelminiak

Evaluating the completion time of a random algorithm or a running stochastic process is a valuable tip not only from a purely theoretical, but also pragmatic point of view. In the formal sense, this kind of a task is specified in terms of the first-passage time statistics. Although first-passage properties of diffusive processes, usually modeled by different

Jianfeng Wu, Sijie Mai, Haifeng Hu

Relation prediction is a task designed for knowledge graph completion which aims to predict missing relationships between entities. Recent subgraph-based models for inductive relation prediction have received increasing attention, which can predict relation for unseen entities based on the extracted subgraph surrounding the candidate triplet. However, they a

Shiyu Shen, Hao Yang, Wangchen Dai, Hong Zhang

Digital signatures are fundamental building blocks in various protocols to provide integrity and authenticity. The development of the quantum computing has raised concerns about the security guarantees afforded by classical signature schemes. CRYSTALS-Dilithium is an efficient post-quantum digital signature scheme based on lattice cryptography and has been s

Haitao Yang, Yuhan Ye, Zhen Zhao, Jiali Liu

Fabrication of new types of superconductors with novel physical properties has always been a major thread in the research of superconducting materials. An example is the enormous interests generated by the cascade of correlated topological quantum states in the newly discovered vanadium-based kagome superconductors AV3Sb5 (A=K, Rb, and Cs) with a Z2 topologi

Fahad Al Saadi, Pedro Parra-Rivas

Spatially extended patterns and multistability of possible different states is common in many ecosystems, and their combination has an important impact on their dynamical behaviours. One potential combination involves tristability between a patterned state and two different uniform states. Using a simplified version of the Gilad-Meron model for dryland ecosy

Hang Wang, Yanru Wang, Jianguo Zhang, Dapeng Zhou

In this paper, we study the persistence approximation property for quantitative $K$-theory of filtered $L^p$ operator algebras. Moreover, we define quantitative assembly maps for $L^p$ operator algebras when $p\in [1,\infty)$. Finally, in the case of $L^{p}$ crossed products and $L^{p}$ Roe algebras, we find sufficient conditions for the persistence approxim

Cornelius Grunwald, Gudrun Hiller, Kevin Kröninger, Lara Nollen

We present a global fit of Drell-Yan, top-quark and beauty-physics data in the Standard Model Effective Field Theory framework using the Minimal Flavor Violation ansatz for the quark-flavor structure. The different energy scales are thereby connected by applying the renormalization group equation and matching onto the Weak Effective Theory in order to incorp

Hakan Ozturk, Fikret Anli, Abdelouahab Kadem

Special functions have been used widely in many problems of applied sciences. However, there are considerable numbers of problems in which exact solutions could not be achieved because of undefined sums or integrals involving special functions. These handicaps force researchers to seek new properties of special functions. Many problems that could not be solv

G. Carlet, J. van de Leur, H. Posthuma, S. Shadrin

We consider the Hurwitz Dubrovin--Frobenius manifold structure on the space of meromorphic functions on the Riemann sphere with exactly two poles, one simple and one of arbitrary order. We prove that the all genera partition function (also known as the total descendant potential) associated with this Dubrovin--Frobenius manifold is a tau function of a ration