January 2022 arXiv papers — page 50

Martin Westerkamp, Maximilian Diez

Blockchain relay schemes enable cross-chain state proofs without requiring trusted intermediaries. This is achieved by applying the source blockchain's consensus validation protocol on the target blockchain. Existing chain relays allow for the validation of blocks created using the Proof of Work (PoW) protocol. Since PoW entails high energy consumption, limi

Francisco C. De Gerónimo, Marcelo M. Miller Bertolami, Francisco Plaza, Márcio Catelan

Recent computations of the interior composition of ultra-massive white dwarfs (WD) have suggested that some white dwarfs could be composed of neon (Ne)-dominated cores. This result is at variance with our previous understanding of the chemical structure of massive white dwarfs, where oxygen is the predominant element. In addition, it is not clear whether som

Martín Solar, Catalina Arcos, Michel Curé, Ronaldo S. Levenhagen

Be stars are found to rotate close to their critical rotation and therefore they are considered as an important laboratory of study for stellar rotation. In this context, we obtain the projected rotational velocity of a sample of classical Be Southern stars in the BeSOS database via Fourier Transform in an automated way for several absorption lines at differ

Carlos Palazuelos, Julio I. de Vicente

Genuine multipartite entanglement (GME) is considered a powerful form of entanglement since it corresponds to those states that are not biseparable, i.e.\ a mixture of partially separable states across different bipartitions of the parties. In this work we study this phenomenon in the multiple-copy regime, where many perfect copies of a given state can be pr

Carlos Zapata-Carratala, Xerxes D. Arsiwalla

Analytical thinking is dominated by binary ideas. From pair-wise interactions, to algebraic operations, to compositions of processes, to network models, binary structures are deeply ingrained in the fabric of most current scientific paradigms. In this article we introduce arity as the generic conceptualization of the order of an interaction between a discret

Zhiqiang Huang

In this paper, we extend the fluctuation theorems used for quantum channels to multitime processes. The fluctuation theorems for quantum channels are less restrictive. We show that the given entropy production can be equal to the result of a closed system environment. The assumption that the system evolves under a completely positive and trace preserving map

Vinsen Marselino Andreas, Genta Indra Winata, Ayu Purwarianti

The recent development of language models has shown promising results by achieving state-of-the-art performance on various natural language tasks by fine-tuning pretrained models. In task-oriented dialogue (ToD) systems, language models can be used for end-to-end training without relying on dialogue state tracking to track the dialogue history but allowing t

Zach Smith, Hugo Jonker, Sjouke Mauw, Hyunwoo Lee

Message forwarding protocols are protocols in which a chain of agents handles transmission of a message. Each agent forwards the received message to the next agent in the chain. For example, TLS middleboxes act as intermediary agents in TLS, adding functionality such as filtering or compressing data. In such protocols, an attacker may attempt to bypass one o

V. Eswara Phanindra, A. Das, J. J. L. van Rijn, S. Chen

In recent years, spin Hall magnetoresistance (SMR) has emerged as an efficient way to probe the spontaneous magnetization state in ordered magnetic systems, by electrical current. Less known is its versatility as a probe of materials that do not possess spontaneous magnetization such as in paramagnets. In this work, SMR is used to probe paramagnetic NdGaO3 (

Jan Sawicki, Michał Burdukiewicz

The rapid influx of low-quality data visualisations is one of the main challenges in today's communication. Misleading, unreadable, or confusing visualisations spread misinformation, failing to fulfill their purpose. The lack of proper tooling further heightens the problem of the quality assessment process. Therefore, we propose VisQualdex, a systematic set

Kishaan Jeeveswaran, Senthilkumar Kathiresan, Arnav Varma, Omar Magdy

Convolutional Neural Networks (CNNs), architectures consisting of convolutional layers, have been the standard choice in vision tasks. Recent studies have shown that Vision Transformers (VTs), architectures based on self-attention modules, achieve comparable performance in challenging tasks such as object detection and semantic segmentation. However, the ima

Nathan Bowler, Florian Gut, Attila Joó, Max Pitz

We investigate Maker-Breaker games on graphs of size $\aleph_1$ in which Maker's goal is to build a copy of the host graph. We establish a firm dependence of the outcome of the game on the axiomatic framework. Relating to this, we prove that there is a winning strategy for Maker in the $K_{\omega,\omega_1}$-game under ZFC+MA+$\neg$CH and a winning strategy f

Anjana A Mahesh, B. Sundar Rajan

This paper deals with embedded index coding problem (EICP), introduced by A. Porter and M. Wootters, which is a decentralized communication problem among users with side information. An alternate definition of the parameter minrank of an EICP, which has reduced computational complexity compared to the existing definition, is presented. A graphical representa

Jusop Choi, Wonseok Choi, William Aiken, Hyoungshick Kim

Since Bitcoin appeared in 2009, over 6,000 different cryptocurrency projects have followed. The cryptocurrency world may be the only technology where a massive number of competitors offer similar services yet claim unique benefits, including scalability, fast transactions, and security. But are these projects really offering unique features and significant e

Frazer Chard, Cayo Fletcher-Smith

This research critically analyses blockchain scaling solutions based on their ability to realistically balance the properties of the blockchain trilemma. We have concluded this research by outlining a gap in the current body of literature and implementation of scalability solutions. An extended UTXO transaction model is proposed to overcome challenges associ

Hedda R. Schmidtke, Sara Coelho

Logics with analogous semantics, such as Fuzzy Logic, have a number of explanatory and application advantages, the most well-known being the ability to help experts develop control systems. From a cognitive systems perspective, such languages also have the advantage of being grounded in perception. For social decision making in humans, it is vital that logic

Hyeongji Kim, Pekka Parviainen, Ketil Malde

In metric learning, the goal is to learn an embedding so that data points with the same class are close to each other and data points with different classes are far apart. We propose a distance-ratio-based (DR) formulation for metric learning. Like softmax-based formulation for metric learning, it models $p(y=c|x')$, which is a probability that a query point

Jad Doughman, Wael Khreich

Language has a profound impact on our thoughts, perceptions, and conceptions of gender roles. Gender-inclusive language is, therefore, a key tool to promote social inclusion and contribute to achieving gender equality. Consequently, detecting and mitigating gender bias in texts is instrumental in halting its propagation and societal implications. However, th

Jonathan R. C. Woods, Jon Gorecki, Roman Bek, Stephen C. Richardson

Coherent laser arrays compatible with silicon photonics are demonstrated in a waveguide geometry in epitaxially grown semiconductor membrane quantum well lasers transferred on substrates of silicon carbide and oxidised silicon; we record lasing thresholds as low as 60 mW of pump power. We study the emission of single lasers and arrays of lasers in the sub-mm

Zhangyong Tang, Tianyang Xu, Hui Li, Xiao-Jun Wu

We address the problem of multi-modal object tracking in video and explore various options of fusing the complementary information conveyed by the visible (RGB) and thermal infrared (TIR) modalities including pixel-level, feature-level and decision-level fusion. Specifically, different from the existing methods, paradigm of image fusion task is heeded for fu

Philipp M. Mutter, Guido Burkard

Noise affects the coherence of qubits and thereby places a bound on the performance of quantum computers. We theoretically study a generic two-level system with fluctuating control parameters in a photonic cavity and find that basic features of the noise spectral density are imprinted in the transient transmission through the cavity. We obtain analytical exp

René D. Oudmaijer, Evgenia Koumpia

This contribution focuses on a rare example of the class of post-Red Supergiants, IRAS 17163-3907, the central star of the Fried Egg nebula. In particular, we discuss some of our recently published results in detail. The inner parts of the circumstellar environment of this evolved massive star are probed at milli-arcsec resolution using VLTI's GRAVITY instru

Alireza Koochali, Peter Schichtel, Andreas Dengel, Sheraz Ahmed

The recent developments in the machine learning domain have enabled the development of complex multivariate probabilistic forecasting models. Therefore, it is pivotal to have a precise evaluation method to gauge the performance and predictability power of these complex methods. To do so, several evaluation metrics have been proposed in the past (such as Ener

Tianyi Tang, Junyi Li, Wayne Xin Zhao, Ji-Rong Wen

Recently, pretrained language models (PLMs) have had exceptional success in language generation. To leverage the rich knowledge encoded by PLMs, a simple yet powerful paradigm is to use prompts in the form of either discrete tokens or continuous embeddings. In existing studies, these prompting methods are typically independent of the inputs, lacking sufficie

Jun-Hao Chen, Yun-Cheng Tsai

Candlestick pattern is one of the most fundamental and valuable graphical tools in financial trading that supports traders observing the current market conditions to make the proper decision. This task has a long history and, most of the time, human experts. Recently, efforts have been made to automatically classify these patterns with the deep learning mode

Mads Sloth Vinding, Torben Ellegaard Lund

Advanced radio-frequency pulse design used in magnetic resonance imaging has recently been demonstrated with deep learning of (convolutional) neural networks and reinforcement learning. For two-dimensionally selective radio-frequency pulses, the (convolutional) neural network pulse prediction time (few milliseconds) was in comparison more than three orders o

Saravana Kumar, Peter Cats, Mohammed B. Alotaibi, Subhash C. Ayirala

Recent experiments and a series of subsequent theoretical studies suggest the occurrence of universal underscreening in highly concentrated electrolyte solutions. We performed a set of systematic Atomic Force Spectroscopy measurements for aqueous salt solutions in a concentration range from 1 mM to 5 M using chloride salts of various alkali metals as well as

Ofer Lahav, Andrew R Liddle

This is a review article for The Review of Particle Physics 2022 (aka the Particle Data Book). It forms a compact review of knowledge of the cosmological parameters near the end of 2021. Topics included are Parametrizing the Universe; Extensions to the standard model; Probes; Bringing observations together; Outlook for the future.

M. L. Olivera-Atencio, L. Lamata, S. Kohler, J. Casado-Pascual

The response of dissipative systems to multi-chromatic fields exhibits generic properties which follow from the discrete time-translation symmetry of each driving component. We derive these properties and illustrate them with paradigmatic examples of classical and quantum dissipative systems. In addition, some computational aspects, in particular a matrix co

Raoul Müller, Dominic Schuhmacher, Jorge Mateu

We give a review of recent ANOVA-like procedures for testing group differences based on data in a metric space and present a new such procedure. Our statistic is based on the classic Levene's test for detecting differences in dispersion. It uses only pairwise distances of data points and and can be computed quickly and precisely in situations where the compu

Yue Song, Nicu Sebe, Wei Wang

Computing the matrix square root or its inverse in a differentiable manner is important in a variety of computer vision tasks. Previous methods either adopt the Singular Value Decomposition (SVD) to explicitly factorize the matrix or use the Newton-Schulz iteration (NS iteration) to derive the approximate solution. However, both methods are not computational

Junjie Luo, Pengzhan Zhao, Zhongtao Miao, Shuhan Lan

As quantum programming evolves, more and more quantum programming languages are being developed. As a result, debugging and testing quantum programs have become increasingly important. While bug fixing in classical programs has come a long way, there is a lack of research in quantum programs. To this end, this paper presents a comprehensive study on bug fixi

Moshe Levy, Guy Amit, Yuval Elovici, Yisroel Mirsky

Deep learning has shown great promise in the domain of medical image analysis. Medical professionals and healthcare providers have been adopting the technology to speed up and enhance their work. These systems use deep neural networks (DNN) which are vulnerable to adversarial samples; images with imperceivable changes that can alter the model's prediction. R

Marco Forgione, Aneri Muni, Dario Piga, Marco Gallieri

This paper presents a transfer learning approach which enables fast and efficient adaptation of Recurrent Neural Network (RNN) models of dynamical systems. A nominal RNN model is first identified using available measurements. The system dynamics are then assumed to change, leading to an unacceptable degradation of the nominal model performance on the perturb

Mads Lindskou, Torben Tvedebrink, Poul Svante Eriksen, Søren Højsgaard

We propose Unity Smoothing (US) for handling inconsistencies between a Bayesian network model and new unseen observations. We show that prediction accuracy, using the junction tree algorithm with US is comparable to that of Laplace smoothing. Moreover, in applications were sparsity of the data structures is utilized, US outperforms Laplace smoothing in terms

Ylva Ljungberg Rydin, Martin Almquist

We consider point sources in hyperbolic equations discretized by finite differences. If the source is stationary, appropriate source discretization has been shown to preserve the accuracy of the finite difference method. Moving point sources, however, pose two challenges that do not appear in the stationary case. First, the discrete source must not excite mo

Huifeng Yao, Xiaowei Hu, Xiaomeng Li

Generalizing the medical image segmentation algorithms to unseen domains is an important research topic for computer-aided diagnosis and surgery. Most existing methods require a fully labeled dataset in each source domain. Although some researchers developed a semi-supervised domain generalized method, it still requires the domain labels. This paper presents

Gianmarco Ottavi, Angelo Garofalo, Giuseppe Tagliavini, Francesco Conti

Computationally intensive algorithms such as Deep Neural Networks (DNNs) are becoming killer applications for edge devices. Porting heavily data-parallel algorithms on resource-constrained and battery-powered devices poses several challenges related to memory footprint, computational throughput, and energy efficiency. Low-bitwidth and mixed-precision arithme

Wenjie Deng, Wei Luo, Zhaoyang Yin

In this paper, we mainly study the global strong solutions and its long time decay rates of all order spatial derivatives to a micro-macro model for compressible polymeric fluids with small initial data. This model is a coupling of isentropic compressible Navier-Stokes equations with a nonlinear Fokker-Planck equation. We first prove that the micro-macro mod

Hartmut Führ, Vignon Oussa

We study the phase retrieval property for orbits of general irreducible representations of nilpotent groups, for the classes of simply connected connected Lie groups, and for finite groups. We prove by induction that in the Lie group case, all irreducible representations do phase retrieval. For the finite group case, we mostly focus on $p$-groups. Here our m

Zi-Kui Liu

Cross phenomena, representing responses of a system to external stimuli, are ubiquitous from quantum to macro scale. The Onsager theorem is often used to describe them, stating that the coefficient matrix of cross phenomena connecting the driving forces and the fluxes of internal processes is symmetric. Here we show that this matrix is intrinsically diagonal

M. Koussour, S. H. Shekh, M. Bennai

In this paper, we study a spatially homogeneous and isotropic FLRW cosmological model in framework of the symmetric teleparallel $f(Q)$ gravity proposed by Jimenez et al. (Physical Review D 98.4 (2018): 044048), where the non-metricity $Q$ is responsible for the gravitational interaction. For the whole analysis we have considered a special form of $f\left(Q\

Xiaoyu Ma, Sylvain Sardy, Nick Hengartner, Nikolai Bobenko

To fit sparse linear associations, a LASSO sparsity inducing penalty with a single hyperparameter provably allows to recover the important features (needles) with high probability in certain regimes even if the sample size is smaller than the dimension of the input vector (haystack). More recently learners known as artificial neural networks (ANN) have shown

Manabu Machida

The Rytov approximation is known in near-infrared spectroscopy including diffuse optical tomography. In diffuse optical tomography, the Rytov approximation often gives better reconstructed images than the Born approximation. Although related inverse problems are nonlinear, the Rytov approximation is almost always accompanied by the linearization of nonlinear

Dave Murray-Rust, Luis Soares, Katya Gorkovenko, John Rooksby

Contact tracing systems control the spread of disease by discovering the set of people an infectious individual has come into contact with. Students are often mobile and sociable and therefore can contribute to the spread of disease. Controls on the movement of students studying in the UK were put in place during the Covid-19 pandemic, and some restrictions

Jakub Jan Borkała, Chellasamy Jebarathinam, Shubhayan Sarkar, Remigiusz Augusiak

While it has recently been demonstrated how to certify the maximal amount of randomness from any pure two-qubit entangled state in a device-independent way [E. Woodhead et al., Phys. Rev. Research 2, 042028(R)(2020)], the problem of optimal randomness certification from entangled states of higher local dimension remains open. Here we introduce a method for d

Sasinee Pruekprasert, Jérémy Dubut, Toru Takisaka, Clovis Eberhart

We develop a method to approximate the moments of a discrete-time stochastic polynomial system. Our method is built upon Carleman linearization with truncation. Specifically, we take a stochastic polynomial system with finitely many states and transform it into an infinite-dimensional system with linear deterministic dynamics, which describe the exact evolut

Kazuhiro Kurita, Kunihiro Wasa

\emph{$K$-best enumeration}, which asks to output $k$-best solutions without duplication, is a helpful tool in data analysis for many fields. In such fields, graphs typically represent data. Thus subgraph enumeration has been paid much attention to such fields. However, $k$-best enumeration tends to be intractable since, in many cases, finding one optimum so

Alessia Gualandris, Fazeel Mahmood Khan, Elisa Bortolas, Matteo Bonetti

Coalescing supermassive black hole binaries (BHBs) are expected to be the loudest sources of gravitational waves (GWs) in the Universe. Detection rates for ground or space-based detectors based on cosmological simulations and semi-analytic models are highly uncertain. A major difficulty stems from the necessity to model the BHB from the scale of the merger t

Norhasliza Yusof, Raphael Hirschi, Patrick Eggenberger, Sylvia Ekström

We present a grid of stellar models at super-solar metallicity (Z = 0.020) extending the previous grids of Geneva models at solar and sub-solar metallicities. A metallicity of Z = 0.020 was chosen to match that of the inner Galactic disk. A modest increase of 43% (=0.02/0.014) in metallicity compared to solar models means that the models evolve similarly to

João Araújo, Choiwah Chow, Mikoláš Janota

The enumeration of finite models is very important to the working discrete mathematician (algebra, graph theory, etc) and hence the search for effective methods to do this task is a critical goal in discrete computational mathematics. However, it is hindered by the possible existence of many isomorphic models, which usually only add noise. Typically, they ar

Chenyang Liu, Jing Mao, Yating Zhao

Let $\Omega$ be a bounded domain (with smooth boundary) on the hyperbolic plane $\mathscr{H}^{n}(1)$, of center at origin and radius $1$, in the $(n+1)$-dimensional Lorentz-Minkowski space $\mathbb{R}^{n+1}_{1}$. In this paper, by using a priori estimates, we can establish Pogorelov type estimates of $k$-convex solutions to a class of Hessian quotient equati

Ewoenam Kwaku Tokpo, Toon Calders

It is well known that textual data on the internet and other digital platforms contain significant levels of bias and stereotypes. Although many such texts contain stereotypes and biases that inherently exist in natural language for reasons that are not necessarily malicious, there are crucial reasons to mitigate these biases. For one, these texts are being

Anastasia Borovykh, Nikolas Kantas, Panos Parpas, Grigorios A. Pavliotis

The mirror descent algorithm is known to be effective in situations where it is beneficial to adapt the mirror map to the underlying geometry of the optimization model. However, the effect of mirror maps on the geometry of distributed optimization problems has not been previously addressed. In this paper we study an exact distributed mirror descent algorithm

Ľubomír Baňas, Christian Vieth

We derive a posteriori error estimates for a fully discrete finite element approximation of the stochastic Cahn-Hilliard equation. The a posteriori bound is obtained by a splitting of the equation into a linear stochastic partial differential equation (SPDE) and a nonlinear random partial differential equation (RPDE). The resulting estimate is robust with re

P. P. M. Jansweijer, N. A. D. Boukadida, K. Hanhijärvi, A. Wallin

A time transfer link consisting of PTP White Rabbit (PTP-WR) devices can transfer time with sub-nanosecond accuracy. Originally White Rabbit devices were calibrated as a set of two devices. Progress in calibration makes individual absolute calibrated PTP-WR devices possible. This enables exchange of PTP-WR devices without the need for expensive in-situ end-t

Shu-Guang Wu, Yang Zhang

Based on the field theory of density fluctuation under Newtonian gravity, we obtain analytically the nonlinear equation of 3-pt correlation function $\zeta$ of galaxies in a homogeneous, isotropic, static universe. The density fluctuations have been kept up to second order. By the Fry-Peebles ansatz and the Groth-Peebles ansatz, the equation of $\zeta$ becom

Kateryna Marynets, Dona Pantova

We use a numerical-analytic technique to construct a sequence of successive approximations to the solution of a system of fractional differential equations, subject to Dirichlet boundary conditions. We prove the uniform convergence of the sequence of approximations to a limit function, which is the unique solution to the boundary value problem under consider

N. Piot, B. Brun, V. Schmitt, S. Zihlmann

Semiconductor spin qubits based on spin-orbit states are responsive to electric field excitation allowing for practical, fast and potentially scalable qubit control. Spin-electric susceptibility, however, renders these qubits generally vulnerable to electrical noise, which limits their coherence time. Here we report on a spin-orbit qubit consisting of a sing

Guangwu Qian, Zhen-Qun Yang, Xu-Lu Zhang, Yaowei Wang

Class Activation Mapping (CAM) has been widely adopted to generate saliency maps which provides visual explanations for deep neural networks (DNNs). The saliency maps are conventionally generated by fusing the channels of the target feature map using a weighted average scheme. It is a weak model for the inter-channel relation, in the sense that it only model

Jens von der Linden, Clare Kimblin, Ian McKenna, Skyler Bagley

Volcanic jet flows in explosive eruptions emit radio frequency signatures, indicative of their fluid dynamic and electrostatic conditions. The emissions originate from sparks supported by an electric field built up by the ejected charged volcanic particles. When shock-defined, low-pressure regions confine the sparks, the signatures may be limited to high-fre

Hao Ma, Yang Sun, Mario Chiarelli

The layout optimization of the heat conduction is essential during design in engineering, especially for thermal sensible products. When the optimization algorithm iteratively evaluates different loading cases, the traditional numerical simulation methods used usually lead to a substantial computational cost. To effectively reduce the computational effort, d

Ciro Ciliberto, Rick Miranda, Joaquim Roé

In this paper we develop a technique for discovering (non-effective) irrational rays at the boundary of the Mori cone for linear systems on a general blowup of the plane, and give examples of such irrational rays.

Christian Homeyer, Oliver Lange, Christoph Schnörr

3D reconstruction of depth and motion from monocular video in dynamic environments is a highly ill-posed problem due to scale ambiguities when projecting to the 2D image domain. In this work, we investigate the performance of the current State-of-the-Art (SotA) deep multi-view systems in such environments. We find that current supervised methods work surpris

Tian Yao, Kaishun Wang

Let $\mathscr{P}$ be a symplectic polar space over a finite field $\mathbb{F}_q$, and $\mathscr{P}_m$ denote the collection of all $k$-dimensional totally isotropic subspace in $\mathscr{P}$. Let $\mathscr{F}_1\subset\mathscr{P}_{m_1}$ and $\mathscr{F}_2\subset\mathscr{P}_{m_2}$ satisfy $\dim(F_1\cap F_2)\ge t$ for any $F_1\in\mathscr{F}_1$ and $F_2\in\maths

V. Apinyan, T. K. Kopeć

In the present work, we consider the excitonic effects in the twisted bilayer graphene (tBLG) within the rotated bilayer Hubbard model. Both, intralayer and interlayer Coulomb interactions have been considered and the half-filling condition is imposed for the electronic densities is both layers of the bilayer. We calculate the excitonic pairing gap parameter

Yiming Bing, Bright Hu, Ronni Hu, Rhianna Kho

We translated the paper 'On the five-fold transitive function of 24 quantities' by \'Emile Mathieu into English. This was done to aid our project on expressing $M_{23}$ as additive functions on the finite field of $2_{11}$ elements.

E. Dondoglio, A. P. Milone, A. Renzini, E. Vesperini

Recent work has shown that NIR Hubble Space Telescope (HST) photometry allows us to disentangle multiple populations (MPs) among M dwarfs of globular clusters (GCs) and investigate this phenomenon in very low-mass (VLM) stars. Here, we present the color-magnitude diagrams (CMDs) of nine GCs and the open cluster NGC 6791 in the F110W and F160W bands of HST, s

P. Ntetsika, G. Mitrikas, G. Litsardakis, I. Panagiotopoulos

Two series of [Ru10/Cox)]12 and [Ru6/Cr3/Cox)]12 x=16-60 easy-plane anisotropy multilayers (all thicknesses in {\AA}), prepared by sputter deposition, are studied by cavity FMR. The acoustic modes are excited by setting the RF field perpendicular to the saturating in-plane field. Their resonance fields are in good agreement with the values predicted for acou

Ivana Nikoloska, Osvaldo Simeone

Quantum machine learning has emerged as a potential practical application of near-term quantum devices. In this work, we study a two-layer hybrid classical-quantum classifier in which a first layer of quantum stochastic neurons implementing generalized linear models (QGLMs) is followed by a second classical combining layer. The input to the first, hidden, la

V. Apinyan, T. K. Kopeć

We have considered the AB-stacked bilayer graphene Josephson junction. The bilayers are supposed to be in the charge equilibrium states and at the half-filling in each of the electronic layers of the construction and at each value of the external gate. By considering the interacting bilayers in both sides of the junction and by taking into account both intra

Thomas Olsson, Severine Sentilles, Efi Papatheocharous

Quality requirements deal with how well a product should perform the intended functionality, such as start-up time and learnability. Researchers argue they are important and at the same time studies indicate there are deficiencies in practice. Our goal is to review the state of evidence for quality requirements. We want to understand the empirical research o

Angel Sherletov, David Schaich

We present new results from ongoing lattice investigations of supersymmetric Yang--Mills (SYM) theories in three and four space-time dimensions. First considering the maximally supersymmetric 3d theory with $Q = 16$ supercharges, we check that the fermion pfaffian is approximately real and positive, validating phase-quenched RHMC calculations. We then initia

Attila Lengyel, Robert-Jan Bruintjes, Marcos Baptista Rios, Osman Semih Kayhan

The second edition of the "VIPriors: Visual Inductive Priors for Data-Efficient Deep Learning" challenges featured five data-impaired challenges, where models are trained from scratch on a reduced number of training samples for various key computer vision tasks. To encourage new and creative ideas on incorporating relevant inductive biases to improve the dat

Claas Abert, Sabri Koraltan, Florian Bruckner, Florian Slanovc

We present a simple atomistic model for the description of noncollinear coupling in magnetic multilayers with hybrid spacer layers made of Ru alloyed to ferromagnetic atoms such as Fe. In contrast to previous analytical and micromagnetic models that explain the noncollinear coupling by means of lateral fluctuations in the coupling constant, the presented mod

Suryanarayana Maddu, Quentin Vagne, Ivo F. Sbalzarini

We present a principled data-driven strategy for learning deterministic hydrodynamic models directly from stochastic non-equilibrium active particle trajectories. We apply our method to learning a hydrodynamic model for the propagating density lanes observed in self-propelled particle systems and to learning a continuum description of cell dynamics in epithe

Sean MacAvaney, Craig Macdonald, Iadh Ounis

Despite its troubled past, the AOL Query Log continues to be an important resource to the research community -- particularly for tasks like search personalisation. When using the query log these ranking experiments, little attention is usually paid to the document corpus. Recent work typically uses a corpus containing versions of the documents collected long

Peiyuan Huang, Ruifang Wang

Magnetic vortex is topologically nontrivial and commonly found in ferromagnetic nanodisks. So far, three classes spin-wave eigenmodes, i.e., gyrotropic, azimuthal and radial modes, have been identified in ferromagnetic nanodisks. Here, using micromagnetic simulation and analytical calculation, we reveal twisted spin-wave modes in a thick permalloy (Ni0.8Fe0.

Frank Schöpfer, Dirk A Lorenz, Lionel Tondji, Maximilian Winkler

The Extended Randomized Kaczmarz method is a well known iterative scheme which can find the Moore-Penrose inverse solution of a possibly inconsistent linear system and requires only one additional column of the system matrix in each iteration in comparison with the standard randomized Kaczmarz method. Also, the Sparse Randomized Kaczmarz method has been show

Leila Ismail, Huned Materwala, Hossam S. Hassanein

The Internet of Vehicles over Vehicular Ad-hoc Networks is an emerging technology enabling the development of smart city applications focused on improving traffic safety, traffic efficiency, and the overall driving experience. These applications have stringent requirements detailed in Service Level Agreement. Since vehicles have limited computational and sto

Hua Ma, Yinshan Li, Yansong Gao, Alsharif Abuadbba

Deep learning models have been shown to be vulnerable to recent backdoor attacks. A backdoored model behaves normally for inputs containing no attacker-secretly-chosen trigger and maliciously for inputs with the trigger. To date, backdoor attacks and countermeasures mainly focus on image classification tasks. And most of them are implemented in the digital w

Robert V. Harlander, Fabian Lange

The effective electroweak Hamiltonian in the gradient-flow formalism is constructed for the current-current operators through next-to-next-to-leading order QCD. The results are presented for two common choices of the operator basis. This paves the way for a consistent matching of perturbatively evaluated Wilson coefficients and non-perturbative matrix elemen

Kobra Mahdavipour, Mahshid Khazaei Shadfar, Hossein Rangani Jahromi, Roberto Morandotti

A witness of non-Markovianity based on the Hilbert-Schmidt speed (HSS), a special type of quantum statistical speed, has been recently introduced for low-dimensional quantum systems. Such a non-Markovianity witness is particularly useful, being easily computable since no diagonalization of the system density matrix is required. We investigate the sensitivity

Haolin Liu, Xinyuan Lian, Dengji Zhao

We consider an auction design problem where a seller sells multiple homogeneous items to a set of connected buyers. Each buyer only knows the buyers she directly connects with and has a diminishing marginal utility valuation for the items. The seller initially only connects to some buyers who can be directly invited to the sale by the seller. Our goal is to

Yuegao Liu

In the solar system, oldhamite (CaS) is generally considered to be formed by the condensation of solar nebula gas. Enstatite chondrites, one of the most important repositories of oldhamite, are believed to be the representative of the material which formed Earth. Thus, the formation mechanism and the evolution process of oldhamite are of great significance t

Ludovico Boratto, Gianni Fenu, Mirko Marras, Giacomo Medda

Enabling non-discrimination for end-users of recommender systems by introducing consumer fairness is a key problem, widely studied in both academia and industry. Current research has led to a variety of notions, metrics, and unfairness mitigation procedures. The evaluation of each procedure has been heterogeneous and limited to a mere comparison with models

Can Wang, Sheng Jin, Yingda Guan, Wentao Liu

Localizing keypoints of an object is a basic visual problem. However, supervised learning of a keypoint localization network often requires a large amount of data, which is expensive and time-consuming to obtain. To remedy this, there is an ever-growing interest in semi-supervised learning (SSL), which leverages a small set of labeled data along with a large

Anisha Banerjee, Antonia Wachter-Zeh, Eitan Yaakobi

Synthetic polymer-based storage seems to be a particularly promising candidate that could help to cope with the ever-increasing demand for archival storage requirements. It involves designing molecules of distinct masses to represent the respective bits $\{0,1\}$, followed by the synthesis of a polymer of molecular units that reflects the order of bits in th

Julian Sitarek

During the last 20 years, TeV astronomy turned from a fledgling field, with only a handful of sources into a fully-developed astronomy discipline, broadening our knowledge on a variety of types of TeV gamma-ray sources. This progress has been mainly achieved due to currently operating instruments: Imaging Atmospheric Cherenkov Telescopes, Surface Array and W

Balazs Varga, Balazs Kulcsar, Morteza Haghir Chehreghani

In this paper, we place deep Q-learning into a control-oriented perspective and study its learning dynamics with well-established techniques from robust control. We formulate an uncertain linear time-invariant model by means of the neural tangent kernel to describe learning. We show the instability of learning and analyze the agent's behavior in frequency-do

Aarón López-García, Rafael Benítez

Fake news are affecting a large proportion of the population even becoming a danger to the society. Mostly, this disinformation flow take place through Internet. Being aware of that problem, in this work we propose a synthetic indicator that measures the user reputation in Twitter in order to analyze the credibility of the content in this social network. In

Zion Hazan, Michael Averbukh, Yishay Manassen

Electron Spin Resonance-Scanning Tunneling Microscopy (ESR-STM) of C60 radical ion on graphene is a first demonstration on radical ions. ESR-STM signal at g=2.00 was measured in accordance with macroscopic ESR of fullerene radical ion. The ESR-STM signal was bias voltage dependent, as it reflects the charge state of the molecule. The signal appears in the bi

E. I. Khukhro, W. A. Moens

Let $f(x)$ be a non-zero polynomial with integer coefficients. An automorphism $\varphi$ of a group $G$ is said to satisfy the elementary abelian identity $f(x)$ if the linear transformation induced by $\varphi$ on every characteristic elementary abelian section $S$ of $G$ is annihilated by $f(x)$. We prove that if a finite (soluble) group $G$ admits a fixed

Andreu Puy, Alvar Daza, Alexandre Wagemakers, Miguel A. F. Sanjuán

In dynamical systems, basins of attraction connect a given set of initial conditions in phase space to their asymptotic states. The basin entropy and related tools quantify the unpredictability in the final state of a system when there is an initial perturbation or uncertainty in the initial state. Based on the basin entropy, the $\ln 2$ criterion allows for

Tianze Wang, Amir H. Payberah, Desta Haileselassie Hagos, Vladimir Vlassov

Modern neural networks require long training to reach decent performance on massive datasets. One common approach to speed up training is model parallelization, where large neural networks are split across multiple devices. However, different device placements of the same neural network lead to different training times. Most of the existing device placement

Sheikh Salman Hassan, Do Hyeon Kim, Yan Kyaw Tun, Nguyen H. Tran

Non-terrestrial networks (NTNs), which integrate space and aerial networks with terrestrial systems, are a key area in the emerging sixth-generation (6G) wireless networks. As part of 6G, NTNs must provide pervasive connectivity to a wide range of devices, including smartphones, vehicles, sensors, robots, and maritime users. However, due to the high mobility

Simos G. Meintanis, Bojana Milošević, Marko Obradović

We study the Bahadur efficiency of several weighted L2--type goodness--of--fit tests based on the empirical characteristic function. The methods considered are for normality and exponentiality testing, and for testing goodness--of--fit to the logistic distribution. Our results are helpful in deciding which specific test a potential practitioner should apply.

Georgios Zacharopoulos, Adel Ejjeh, Ying Jing, En-Yu Yang

The design of heterogeneous systems that include domain specific accelerators is a challenging and time-consuming process. While taking into account area constraints, designers must decide which parts of an application to accelerate in hardware and which to leave in software. Moreover, applications in domains such as Extended Reality (XR) offer opportunities

Yike Xu

The transverse spin transfer, $D_{TT}$, of $\Lambda$ and $\overline{\Lambda}$ hyperons in $p$+$p$ collisions is expected to be sensitive to the $s$ and $\bar{s}$ quark transversity distributions in the proton and to the transversely polarized fragmentation functions. The STAR experiment has published the first measurement of the transverse spin transfer of $

Jun Zhang, Xiancheng Wang, Long Zhou, Gangxiu Liu

The search of novel quasi one-dimensional (1D) materials is one of the important aspects in the field of material science. Toroidal moment, the order parameter of ferrotoroidic order, can be generated by a head-to-tail configuration of magnetic moment. It has been theoretically proposed that one-dimensional (1D) dimerized and antiferromagnetic-like spin chai