November 2022 arXiv papers — page 44

Frédéric Vella, Flavien Clastres-Babou, Frédéric Vella, Nadine Vigouroux

The objective of this paper is to describe the implication of an interdisciplinary team involved during a user-centered design methodology to design the platform (WebSoKeyTo) that meets the needs of therapists to design augmentative and alternative communication (AAC) aids for disabled users. We describe the processes of the design process and the role of th

Diego Chamorro, Bruno Poggi

We investigate existence, Liouville type theorems and regularity results for the 3D stationary and incompressible fractional Navier-Stokes equations: in this setting the usual Laplacian is replaced by its fractional power $(-\Delta)^{\frac{\alpha}{2}}$ with $0<\alpha<2$. By applying a fixed point argument, weak solutions can be obtained in the Sobolev space

Charbella Abou Khalil

Given small initial solutions of the nonlinear quantum harmonic oscillator on $\mathbb{R}$, we are interested in their long time behavior in the energy space which is an adapted Sobolev space. We perturbate the linear part by $V$ taken as multiplicative potentials, in a way that the linear frequencies satisfy a non-resonance condition. More precisely, we pro

William B. Schoeler

A Cognitive Radio is a type of Software-Defined Radio (SDR) that automatically detects available wireless spectrum and adjusts its physical hardware, modulation, or protocol parameters to obtain optimal throughput, latency, and range. Much of prior Cognitive Radio research and design has required expensive transceivers using licensed bands that are not openl

Mathias Rose Bjare, Stefan Lattner

It has been shown in a recent publication that words in human-produced English language tend to have an information content close to the conditional entropy. In this paper, we show that the same is true for events in human-produced monophonic musical sequences. We also show how "typical sampling" influences the distribution of information around the entropy

Dmitry Svintsov, Georgy Alymov, Zhanna Devizorova, Luis Martin-Moreno

Electrical conductivity of one-dimensional (1d) disordered solids decays exponentially with their length, which is a celebrated manifestation of the localization phenomenon. Here, we study the modifications of localized conductivity induced by placement of 1d semiconductors inside of single-mode electromagnetic cavities, focusing on the regime of non-degener

Ling-Xiao Xu, Seokhoon Yun

We propose an alternative scenario for the axion misalignment mechanism based on the nontrivial interplay between the axion and a light dilaton in the early universe. Dark matter abundance is still sourced by the initial misalignment of the axion field, whose motion along the potential kicks the dilaton field away from its minimum, and dilaton starts to osci

Ahmed El Kerim, Pierre Gosselet, Frédéric Magoulès

This paper presents the first asynchronous version of the Global/Local non-invasive coupling, capable of dealing efficiently with multiple, possibly adjacent, patches. We give a new interpretation of the coupling in terms of primal domain decomposition method, and we prove the convergence of the relaxed asynchronous iteration. The asynchronous paradigm lifts

Ranveer Singh, Hitesh Wankhede

In 1983, Borowiecki and J\'o\'zwiak posed the problem ``Characterize those graphs which have purely imaginary per-spectrum.'' This problem is still open. The most general result, although a partial solution, was given in 2004 by Yan and Zhang, who show that if $G$ is a bipartite graph containing no subgraph which is an even subdivision of $K_{2,3}$, then it

Dirceu Bagio, Daniel Gonçalves, Paula Savana Estácio Moreira, Johan Öinert

Given a partial action $\alpha$ of a groupoid $G$ on a ring $R$, we study the associated partial skew groupoid ring $R \rtimes_{\alpha} G$, which carries a natural $G$-grading. We show that there is a one-to-one correspondence between the $G$-invariant ideals of $R$ and the graded ideals of the $G$-graded ring $R \rtimes_{\alpha}G.$ We provide sufficient con

Athanasios C. Tsitos, Maria Dagioglou

Socially aware robots should be able, among others, to support fluent human-robot collaboration in tasks that require interdependent actions in order to be solved. Towards enhancing mutual performance, collaborative robots should be equipped with adaptation and learning capabilities. However, co-learning can be a time consuming procedure. For this reason, tr

Huihui Yu, Yuan Zhang, Qilong Wu, Chongxin Shan

A recent experiment demonstrated heterodyne detection-based frequency measurements with superradiant pulses from coherently pumped strontium atoms in an optical lattice clock system, while another experiment has analyzed the statistics of superradiant pulses from incoherently pumped calcium atoms in a similar system. In this article, we propose to perform he

Tianyu Wang, Xiaowei Hu, Zhengzhe Liu, Chi-Wing Fu

LiDAR-produced point clouds are the major source for most state-of-the-art 3D object detectors. Yet, small, distant, and incomplete objects with sparse or few points are often hard to detect. We present Sparse2Dense, a new framework to efficiently boost 3D detection performance by learning to densify point clouds in latent space. Specifically, we first train

Andrew Novick, Quan Nguyen, Roman Garnett, Eric Toberer

A general method is presented for modeling high entropy alloys as ensembles of randomly sampled, ordered configurations on a given lattice. Statistical mechanics is applied post hoc to derive the ensemble properties as a function of composition and temperature, including the free energy of mixing and local structure. Random sampling is employed to address th

Steffen Bollmann, Alexander Osterkorn, Elio J. König, Salvatore R. Manmana

We use a combination of numerical matrix product states (MPS) and analytical approaches to investigate the phase diagram of the two-leg $t$-$J$ ladder in the region of low to intermediate fillings. We choose the same coupling strength along the leg- and rung-directions, but study the effect of adding a nearest-neighbor repulsion $V$. We observe a rich phase

Giulia Ballabio, Thomas J. Haworth, W. J. Henney

We study the utility of the [OI] 6300$\mathring{\mathrm A}$ forbidden line for identifying and interpreting externally driven photoevaporative winds in different environments and at a range of distances. Thermally excited [OI] 6300$\mathring{\mathrm A}$ is a well known tracer of inner disc winds, so any external contribution needs to be distinguishable. In e

Mairieli Wessel, Andy Zaidman, Marco Gerosa, Igor Steinmacher

Projects on GitHub rely on the automation provided by software development bots to uphold quality and alleviate developers' workload. Nevertheless, the presence of bots can be annoying and disruptive to the community. Backed by multiple studies with practitioners, this paper provides guidelines for developing and maintaining software bots. These guidelines a

Cris R. Hasan, Ruaidhrí Mac Cárthaigh, Sebastian Wieczorek

We propose a framework to study tipping points in reaction-diffusion equations (RDEs) in one spatial dimension, where the reaction term decays in space (asymptotically homogeneous) and varies linearly with time (nonautonomous) due to an external input. A compactification of the moving-frame coordinate together with Lin's method to construct heteroclinic orbi

Federico Cunico, Andrea Toaiari, Marco Cristani

We propose a novel image dataset focused on tiny faces wearing face masks for mask classification purposes, dubbed Small Face MASK (SF-MASK), composed of a collection made from 20k low-resolution images exported from diverse and heterogeneous datasets, ranging from 7 x 7 to 64 x 64 pixel resolution. An accurate visualization of this collection, through count

Yulong Li, Nikolay Garabedian, Johannes Schneider, Christian Greiner

To prolong lifetime and reduce energy consumption, a thorough understanding of abrasive wear is essential. The potentially crucial influence of surface topography intricacies on tribological behavior have been obscured, since roughness and waviness are often considered simple scalar quantities. Here, the complete waviness profile of the sliding track was use

Ronan Fablet, Bertrand Chapron, Julien Le Sommer, Florian Sévellec

Satellite altimetry is a unique way for direct observations of sea surface dynamics. This is however limited to the surface-constrained geostrophic component of sea surface velocities. Ageostrophic dynamics are however expected to be significant for horizontal scales below 100~km and time scale below 10~days. The assimilation of ocean general circulation mod

Frédéric Vella, Réjane Dalcé, Antonio Serpa, Thierry Val

The ability to localise a smart device is very useful to visually or cognitively impaired people. Localisation-capable technologies are becoming more readily available as off-the-shelf components. In this paper, we highlight the need for such a service in the field of health and autonomy, especially for disabled people. We introduce a model for Semantic Posi

Abhishek Muhuri, Rivu Gupta, Srijon Ghosh, Aditi Sen De

We investigate the distributed dense coding (DC) protocol, involving multiple senders and a single or two receivers under the influence of non-Markovian noise, acting on the encoded qubits transmitted from senders to the receiver(s). We compare the effects of non-Markovianity on DC both for the dephasing and depolarising channels. In the case of dephasing ch

Adrià Delhom, Gerardo García-Moreno, Manuel Hohmann, Alejandro Jiménez-Cano

In this work we study diffeomorphism-invariant metric-affine theories of gravity from the point of view of self-interacting field theories on top of Minkowski spacetime (or other background). We revise how standard metric theories couple to their own energy-momentum tensor, and discuss the generalization of these ideas when torsion and nonmetricity are also

Kevin Frans, Phillip Isola

One of the grand challenges of reinforcement learning is the ability to generalize to new tasks. However, general agents require a set of rich, diverse tasks to train on. Designing a `foundation environment' for such tasks is tricky -- the ideal environment would support a range of emergent phenomena, an expressive task space, and fast runtime. To take a ste

Yingxiu Zhao, Yinhe Zheng, Bowen Yu, Zhiliang Tian

Lifelong learning aims to accumulate knowledge and alleviate catastrophic forgetting when learning tasks sequentially. However, existing lifelong language learning methods only focus on the supervised learning setting. Unlabeled data, which can be easily accessed in real-world scenarios, are underexplored. In this paper, we explore a novel setting, semi-supe

Xiaozhu Zhang, Jerome P. Reiter

We propose a new generator for the generalized inverse Gaussian (GIG) distribution by decomposing the density of GIG into two components. The first component is a truncated inverse Gamma density, in order to sample from which we improve the traditional inverse CDF method. The second component is the product of an exponential pdf and an inverse Gamma CDF. In

Frédéric Bayart

We give a sufficient condition for two operators to be disjointly frequently hypercyclic. We apply this criterion to composition operators acting on $H(\mathbb D)$ or on the Hardy space $H^2(\mathbb D)$. We simplify a result on disjoint frequent hypercyclicity of pseudo shifts of a recent paper of Martin et al. and we exhibit two disjointly frequently hyperc

Lucca Fazza, Tin Sulejmanpasic

We construct Villain Hamiltonians for compact scalars and abelian gauge theories. The Villain integers are promoted to integral spectrum operators, whose canonical conjugates are naturally compact scalars. Further, depending on the theory, these conjugate operators can be interpreted as (higher-form) gauge fields. If a gauge symmetry is imposed on these dual

Liu Yang, Yi Yang, Suhan Zhong

In this paper, we study the global optimality of polynomial portfolio optimization (PPO). The PPO is a kind of portfolio selection model with high-order moments and flexible risk preference parameters. We introduce a perturbation sample average approximation method, which can give a robust approximation of the PPO in form of linear conic optimization. The ap

Clément Chouard

We study sample covariance matrices arising from rectangular random matrices with i.i.d. columns. It was previously known that the resolvent of these matrices admits a deterministic equivalent when the spectral parameter stays bounded away from the real axis. We extend this work by proving quantitative bounds involving both the dimensions and the spectral pa

K. Son, D. Park, C. Lee, A. Lascialfari

Parity is a ubiquitous notion in science and serves as a fundamental principle for describing a physical system. Nanometer-scale metal objects are predicted to show dramatic differences in physical properties depending on the electron-number parity. However, the identification of the electron-number parity effects in real metal nanoparticles has remained elu

Nadine Vigouroux, Frédéric Vella, Gaëlle Lepage, Eric Campo

This paper presents a comparative usability study on tactile and vocal interaction modes for home automation control of equipment at home for different profiles of disabled people. The study is related to the HIP HOPE project concerning the construction of 19 inclusive housing in the Toulouse metropolitan area in France. The experimentation took place in a l

Andreas Freitag

Digital Identities are playing an essential role in our digital lives. Today, used Digital Identities are based on central architectures. Central Digital Identity providers control and know our data and, thereby, our Identity. Self Sovereign Identities (SSI) are based on a decentralized data storage and data exchange architecture, where the user is in sole c

Hasan Bahcivan, David J. Brady

In a companion article, we discussed the radiometric sensitivity and resolution of a new passive optical sensing technique, Space-Time Projection Optical Tomography (SPOT), to detect and track sub-cm and larger space debris for Space Situational Awareness. SPOT is based on the principle that long synthetic exposure can be achieved if the phase-space trajecto

Naoki Mitsuda, Tatsuhiro Ichimura, Kouhei Nakaji, Yohichi Suzuki

Quantum computing has a potential to accelerate the data processing efficiency, especially in machine learning, by exploiting special features such as the quantum interference. The major challenge in this application is that, in general, the task of loading a classical data vector into a quantum state requires an exponential number of quantum gates. The appr

Antje Dollmann, Julia Rau, Beatrix Bieber, Lakshmi Mantha

Microstructural evolution under tribological load is known to change the friction and wear response of the entire tribological system. It is however not yet fully understood, how these changes take place on an elementary, mechanistic level. Revealing the temporal sequence of deformation mechanisms under a tribological load by experiments is scarce. The discr

M Verseils, F Mezzadri, D Delmonte, R Cabassi

By means of single-crystal X-ray diffraction we have revealed the breaking of centrosymmetry when lowering the temperature under T$_s$ = 200 K concomitantly with the setting of a commensurate superstructure in the small A-site quadruple perovskite YMn$_3$Mn$_4$O$_{12}$. This results is in agreement with all data already reported for this compounds and solve

Mahtab Vafaeefar, Kevin M. Moerman, Majid Kavousi, Ted J. Vaughan

In this study, we evaluate the performance of three algorithms as computational models of trabecular bone architecture, through systematic evaluation of morphometric, topological, and mechanical properties. Here, we consider the widely-used gyroid lattice structure, the recently-developed spinodoid structure and a structure similar to Voronoi lattices introd

Mateus Karvat Camara, Adriana Postal, Tomas Henrique Maul, Gustavo Paetzold

Despite the great impact of lies in human societies and a meager 54% human accuracy for Deception Detection (DD), Machine Learning systems that perform automated DD are still not viable for proper application in real-life settings due to data scarcity. Few publicly available DD datasets exist and the creation of new datasets is hindered by the conceptual dis

Xian Yao Gwee, Isobel Claire Gormley, Michael Fop

Interactions between actors are frequently represented using a network. The latent position model is widely used for analysing network data, whereby each actor is positioned in a latent space. Inferring the dimension of this space is challenging. Often, for simplicity, two dimensions are used or model selection criteria are employed to select the dimension,

Xavier Cabre

We establish two new estimates which control a function (after subtracting its average) in $L^1$ by only the $L^1$ norm of its radial derivative. While the interior estimate holds for all superharmonic functions, the boundary version is much more delicate. It requires the function to be a stable solution of a semilinear elliptic equation with a nonnegative,

Conor F. Hayes, Mathieu Reymond, Diederik M. Roijers, Enda Howley

In many risk-aware and multi-objective reinforcement learning settings, the utility of the user is derived from a single execution of a policy. In these settings, making decisions based on the average future returns is not suitable. For example, in a medical setting a patient may only have one opportunity to treat their illness. Making decisions using just t

D. Dicken, C. N. Tadhunter, N. P. H. Nesvadba, E. Bernhard

The far-IR/sub-mm wavelength range contains a wealth of diagnostic information that is important for understanding the role of radio AGN in galaxy evolution. Here we present the results of Herschel PACS and SPIRE observations of a complete sample of 46 powerful 2Jy radio AGN at intermediate redshifts (0.05 < z < 0.7), which represent the deepest pointed obse

Ashutosh Kotwal, Joaquim Matias, Andrea Mauri, Tom Tong

This contribution to the XVth Quark Confinement and the Hadron Spectrum conference covers a description, both theoretical and experimental, of the present status of a set of very different anomalies. The discussion ranges from the long standing $b \to sll$ anomalies, $(g-2)$ and the new $M_W$ anomaly.

F. Dell'Agli, S. Tosi, D. Kamath, P. Ventura

The study of post asymptotic giant branch (post-AGB) stars is a valuable tool to study still poorly known aspects of the evolution of the stars through the AGB. This is due to the accurate determination of their surface chemical composition and to the peculiar shape of the SED: the emission from the central star can be easily disentangled from the contributi

Rachel Minster, Zitong Li, Grey Ballard

The Tucker tensor decomposition is a natural extension of the singular value decomposition (SVD) to multiway data. We propose to accelerate Tucker tensor decomposition algorithms by using randomization and parallelization. We present two algorithms that scale to large data and many processors, significantly reduce both computation and communication cost comp

Stergios Katsanoulis, Florian Kogelbauer, Roshan Kaundinya, Jesse Ault

Instantaneous features of three-dimensional velocity fields are most directly visualized via streamsurfaces. It is generally unclear, however, which streamsurfaces one should pick for this purpose, given that infinitely many such surfaces pass through each point of the flow domain. Exceptions to this rule are vector fields with a nondegenerate first integral

Carl M. Bender, Christos Karapoulitidis, S. P. Klevansky

This paper examines the effectiveness of the Dyson-Schwinger (DS) equations as a calculational tool in quantum field theory. The DS equations are an infinite sequence of coupled equations that are satisfied exactly by the connected Green's functions $G_n$ of the field theory. These equations link lower to higher Green's functions and, if they are truncated,

Maria Dmitrieva

We propose a general method for constructing continuous Banach bundles whose fibers are algebras of holomorphic functions on subvarieties of a closed noncommutative ball. These algebras are of the form $\mathcal{A}_d/I_x$, where $\mathcal{A}_d$ is the noncommutative disk algebra introduced by G. Popescu, and $I_x$ is a graded ideal in $\mathcal{ A}_d$, which

Lennart Jahn, Florentin Wörgötter, Tomas Kulvicius

Movement generation, and especially generalisation to unseen situations, plays an important role in robotics. Different types of movement generation methods exist such as spline based methods, dynamical system based methods, and methods based on Gaussian mixture models (GMMs). Using a large, new dataset on human manipulations, in this paper we provide a high

Bryan J. Ranger, Kevin M. Moerman, Brian W. Anthony, Hugh M. Herr

Finite element analysis (FEA) can be used to evaluate applied interface pressures and internal tissue strains for computational prosthetic socket design. This type of framework requires realistic patient-specific limb geometry and constitutive properties. In recent studies, indentations and inverse FEA with MRI-derived 3D patient geometries were used for con

Raffaele Resta

Adiabatic transport in a many-electron system is expressed in terms of the appropriate Berry curvature, owing to the Niu-Thouless theory [J. Phys A {\bf 17}, 2453 (1984)]; the main equation is very compact and very general. I address here three paradigmatic adiabatic response tensors -- -the atomic polar tensor, the atomic axial tensor, and the rotational $g

Margaryta Myronyuk

A. Kagan introduced classes of distributions $\mathcal{D}_{m,k}$ in $m$-dimensional space $\mathbb{R}^m$. He proved that if the joint distribution of $m$ linear forms of $n$ independent random variables belong to the class $\mathcal{D}_{m,m-1}$ then the random variables are Gaussian. If $m=2$ then the Kagan theorem implies the well-known Darmois-Skitovich th

Lena Funcke, Tobias Hartung, Karl Jansen, Stefan Kühn

We propose a variational quantum eigensolver suitable for exploring the phase structure of the multi-flavor Schwinger model in the presence of a chemical potential. The parametric ansatz circuit we design is capable of incorporating the symmetries of the model, present in certain parameter regimes, which allows for reducing the number of variational paramete

Binxin Yang, Xuejin Chen, Chaoqun Wang, Chi Zhang

With recent advances in image-to-image translation tasks, remarkable progress has been witnessed in generating face images from sketches. However, existing methods frequently fail to generate images with details that are semantically and geometrically consistent with the input sketch, especially when various decoration strokes are drawn. To address this issu

Oxana Vitman, Yevhen Kostiuk, Grigori Sidorov, Alexander Gelbukh

Sarcasm detection is an essential task that can help identify the actual sentiment in user-generated data, such as discussion forums or tweets. Sarcasm is a sophisticated form of linguistic expression because its surface meaning usually contradicts its inner, deeper meaning. Such incongruity is the essential component of sarcasm, however, it makes sarcasm de

Julian Heeck, Jan Heisig, Anil Thapa

The scotogenic model generates Majorana neutrino masses radiatively, with dark matter particles running in the loop. We explore the parameter space in which the relic density of fermionic dark matter is generated via a conversion-driven freeze-out mechanism. The necessity for small Yukawa couplings to initiate chemical decoupling for conversion processes nat

Tapas Tripura, Souvik Chakraborty

We propose a model-agnostic stochastic predictive control (MASMPC) algorithm for dynamical systems. The proposed approach first discovers \textit{interpretable} governing differential equations from data using a novel algorithm and blends it with a model predictive control algorithm. One salient feature of the proposed approach resides in the fact that it re

Deniz Kasap, Alessio Carpegna, Alessandro Savino, Stefano Di Carlo

Radiation-induced soft errors are one of the most challenging issues in Safety Critical Real-Time Embedded System (SACRES) reliability, usually handled using different flavors of Double Modular Redundancy (DMR) techniques. This solution is becoming unaffordable due to the complexity of modern micro-processors in all domains. This paper addresses the promisin

Yue Tan, Yixin Liu, Guodong Long, Jing Jiang

Graph neural networks (GNNs) have shown their superiority in modeling graph data. Owing to the advantages of federated learning, federated graph learning (FGL) enables clients to train strong GNN models in a distributed manner without sharing their private data. A core challenge in federated systems is the non-IID problem, which also widely exists in real-wo

Saeed Pahlavan

In this paper, a systematic approach is employed to design a photonic crystal with a boundary between positive and negative refraction to boost the refractive properties of the crystal. Mathematical techniques are employed to turn the process of EFC engineering into a nearly mechanical process free of trial-and-error steps. The designed demultiplexers operat

Mark Kelbert, Harold A. Moreno-Franco

In this paper, we study the regularity of the value function associated with a stochastic control problem where two controls act simultaneously on a modulated multidimensional diffusion process. The first is a switching control modelling a random clock. Every time the random clock rings, the generator matrix is replaced by another, resulting in a different d

David Binder, Julian Jabs, Ingo Skupin, Klaus Ostermann

Data types and codata types are, as the names suggest, often seen as duals of each other. However, most programming languages do not support both of them in their full generality, or if they do, they are still seen as distinct constructs with separately defined type-checking, compilation, etc. Rendel et al. were the first to propose variants of two standard

Simon Hirsch, Florian Ziel

During the last years, European intraday power markets have gained importance for balancing forecast errors due to the rising volumes of intermittent renewable generation. However, compared to day-ahead markets, the drivers for the intraday price process are still sparsely researched. In this paper, we propose a modelling strategy for the location, shape and

Stanley Osher, Howard Heaton, Samy Wu Fung

First-order optimization algorithms are widely used today. Two standard building blocks in these algorithms are proximal operators (proximals) and gradients. Although gradients can be computed for a wide array of functions, explicit proximal formulas are only known for limited classes of functions. We provide an algorithm, HJ-Prox, for accurately approximati

Roy Shmueli

We study the random \'etale algebra generated by a random polynomial with i.i.d. coefficients distributed according to Haar measure normalized on $\mathbb{Z}_p$. We determine the probability that this random algebra is an unramified field, explicitly. In addition, we prove a private case of a conjecture made by Bhargava, Cremona, Fisher, and Gajovi\'c. More

Ruggero Biondo, Alessandro Bemporad, Paolo Pagano, Daniele Telloni

As a key feature, NASA's Parker Solar Probe (PSP) and ESA-NASA's Solar Orbiter (SO) missions cooperate to trace solar wind and transients from their sources on the Sun to the inner interplanetary space. The goal of this work is to accurately reconstruct the interplanetary Parker spiral and the connection between coronal features observed remotely by the Meti

Ruggero Biondo, Paolo Pagano, Fabio Reale, Alessandro Bemporad

The determination of the chemical composition of interplanetary coronal mass ejection (ICME) plasma is an open issue. More specifically, it is not yet fully understood how remote sensing observations of the solar corona plasma during solar disturbances evolve into plasma properties measured in situ away from the Sun. The ambient conditions of the background

Célia Griffet, Matthieu Arnhem, Stephan De Bièvre, Nicolas J. Cerf

Assessing whether a quantum state $\hat \rho$ is nonclassical ($\textit{i.e.}$, incompatible with a mixture of coherent states) is a ubiquitous question in quantum optics, yet a nontrivial experimental task because many nonclassicality witnesses are nonlinear in $\hat \rho$. In particular, if we want to witness or measure the nonclassicality of a state by ev

Silvia Nagy, Javier Peraza

Working in the self-dual sector for Yang-Mills and gravity, we show how to construct an extended phase space at null infinity, to all orders in the radial expansion. This formalises the symmetry origin of the infrared behaviour of these theories to all sub-leading orders. As a corollary, we also derive a double copy mapping from a subset of YM gauge transfor

Elre T. Oldewage, John Bronskill, Richard E. Turner

This paper examines the robustness of deployed few-shot meta-learning systems when they are fed an imperceptibly perturbed few-shot dataset. We attack amortized meta-learners, which allows us to craft colluding sets of inputs that are tailored to fool the system's learning algorithm when used as training data. Jointly crafted adversarial inputs might be expe

André Artelt, Kleanthis Malialis, Christos Panayiotou, Marios Polycarpou

Concept drift refers to a change in the data distribution affecting the data stream of future samples. Consequently, learning models operating on the data stream might become obsolete, and need costly and difficult adjustments such as retraining or adaptation. Existing methods usually implement a local concept drift adaptation scheme, where either incrementa

Yuntao Wang, Zhou Su, Qichao Xu, Ruidong Li

Unmanned aerial vehicles (UAVs) have the potential to establish flexible and reliable emergency networks in disaster sites when terrestrial communication infrastructures go down. Nevertheless, potential security threats may occur on UAVs during data transmissions due to the untrusted environment and open-access UAV networks. Moreover, UAVs typically have lim

Rafael F. Reale, Joberto S. B. Martins

Reinforcement learning (RL) is currently used in various real-life applications. RL-based solutions have the potential to generically address problems, including the ones that are difficult to solve with heuristics and meta-heuristics and, in addition, the set of problems and issues where some intelligent or cognitive approach is required. However, reinforce

Steffen Limmer, Alberto Martinez Alba, Nicola Michailow

This paper introduces a physics-informed machine learning approach for pathloss prediction. This is achieved by including in the training phase simultaneously (i) physical dependencies between spatial loss field and (ii) measured pathloss values in the field. It is shown that the solution to a proposed learning problem improves generalization and prediction

Sebastián Carrillo Santana

There have been a number of papers on statistical questions concerning the sign changes of Fourier coefficients of newforms. In one such paper, Linowitz and Thompson gave a conjecture describing when, on average, the first negative sign of the Fourier coefficients of an Eisenstein series newform occurs. In this paper, we correct their conjecture and prove th

Nathaniel Gallup, Stephen Sawin

Using linear algebraic methods we show that every (possibly infinite-dimensional) representation of a quiver with underlying graph $A_{\infty, \infty}$ is Krull-Schmidt, as long as the arrows in the quiver eventually point outward.

Francesca E. D. Raimondi, Tadhg O'Keeffe, Hana Chockler, Andrew R. Lawrence

We describe the results of applying causal discovery methods on the data from a multi-site clinical trial, on the Treatment of Preserved Cardiac Function Heart Failure with an Aldosterone Antagonist (TOPCAT). The trial was inconclusive, with no clear benefits consistently shown for the whole cohort. However, there were questions regarding the reliability of

Thomas Webster

We study a new modification of the Arrival problem, which allows for nodes that exhibit random as well as controlled behaviour, in addition to switching nodes. We study the computational complexity of these extensions, building on existing work on Reachability Switching Games. In particular, we show for versions of the arrival problem involving just switchin

Junyu Chen, Jie An, Hanjia Lyu, Christopher Kanan

Visual-textual sentiment analysis aims to predict sentiment with the input of a pair of image and text, which poses a challenge in learning effective features for diverse input images. To address this, we propose a holistic method that achieves robust visual-textual sentiment analysis by exploiting a rich set of powerful pre-trained visual and textual prior

Austin Warner, Georgios Fellouris

The problem of sequential change diagnosis is considered, where observations are obtained on-line, an abrupt change occurs in their distribution, and the goal is to quickly detect the change and accurately identify the post-change distribution, while controlling the false alarm rate. A finite set of alternatives is postulated for the post-change regime, but

Anatol Garioud, Stéphane Peillet, Eva Bookjans, Sébastien Giordano

The French National Institute of Geographical and Forest Information (IGN) has the mission to document and measure land-cover on French territory and provides referential geographical datasets, including high-resolution aerial images and topographic maps. The monitoring of land-cover plays a crucial role in land management and planning initiatives, which can

Yujie Jiang, Ryohei Seto

Colloidal gels are widely applied in industry due to their rheological character -- no flow takes place below the yield stress. Such property enables gels to maintain uniform distribution in practical formulations; otherwise, solid components may quickly sediment without the support of gel matrix. Compared with pure gels of sticky colloids, therefore, the co

Elyassaf Loyfer, Nati Linial

The rate vs. distance problem is a long-standing open problem in coding theory. Recent papers have suggested a new way to tackle this problem by appealing to a new hierarchy of linear programs. If one can find good dual solutions to these LPs, this would result in improved upper bounds for the rate vs. distance problem of linear codes. In this work, we devel

Mohammad Reza Safari, Frank Matthes, Vasile Caciuc, Nicolae Atodiresei

From the beginning of molecular theory, the interplay of chirality and magnetism has intrigued scientists. There is still the question if enantiospecific adsorption of chiral molecules occurs on magnetic surfaces. Enantiomer discrimination was conjectured to arise from chirality-induced spin separation within the molecules and exchange interaction with the s

G. Illiano, A. Papitto, F. Ambrosino, A. Miraval Zanon

PSR J1023+0038 is the first millisecond pulsar that was ever observed as an optical and UV pulsar. So far, it is the only optical transitional millisecond pulsar. The rotation- and accretion-powered emission mechanisms hardly individually explain the observed characteristics of optical pulsations. A synergistic model, combining these standard emission proces

Thomas G. Bisbas, Ewine F. van Dishoeck, Chia-Yu Hu, Andreas Schruba

Determining the atomic and molecular content of the interstellar medium (ISM) as a function of environmental parameters is of fundamental importance to understand the star-formation process across the epochs. Although there exist various three-dimensional hydro-chemical codes modelling the ISM at different scales and redshifts, they are computationally expen

Prabhupada Dixit

In these proceedings, we report the elliptic ($v_{2}$) and triangular ($v_{3}$) flow measurements of strange and multi-strange hadrons such as $K_{S}^{0}$, ~$\Lambda$($\bar{\Lambda}$), ~$\phi$, ~$\Xi^{-}$($\bar{\Xi}^{+}$), and $\Omega^{-}$($\bar{\Omega}^{+}$) at mid-rapidity ($|y| < 1.0$) in Au+Au collisions at $\sqrt{s_{NN}}$ = 19.6 GeV using high statistic

Chenxu Ke, Kai-Yuan Cai, Quan Quan

This study proposes a uniform passive fault-tolerant control (FTC) method for a quadcopter that does not rely on fault information subject to one, two adjacent, two opposite, or three rotors failure. The uniform control implies that the passive FTC is able to cover the condition from quadcopter fault-free to rotor failure without controller switching. To ach

Aleksandr Dekhovich, O. Taylan Turan, Jiaxiang Yi, Miguel A. Bessa

Data-driven modeling in mechanics is evolving rapidly based on recent machine learning advances, especially on artificial neural networks. As the field matures, new data and models created by different groups become available, opening possibilities for cooperative modeling. However, artificial neural networks suffer from catastrophic forgetting, i.e. they fo

Hidenobu Yajima, Makito Abe, Hajime Fukushima, Yoshiaki Ono

We study the formation of the first galaxies in overdense regions modelled by the FORmation and EVolution of galaxies in Extremely overdense Regions motivated by SSA22 (FOREVER22) simulation project. Our simulations successfully reproduce the star formation rates and the $M_{\rm UV}-M_{\rm star}$ relations of candidate galaxies at $z \sim 10-14$ observed by

Dongsheng Li, Chen Shen, Ye Liu, Ying Chen

The dynamic security assessment of power systems needs to scan contingencies in a preselected set through time-domain simulations. With more and more inverter-based-generation, such as wind and solar power generation, integrated into power systems, electro-magnetic transient simulation is adopted. However, the complexity of simulation will increase greatly i

Dylan Park, Changhong Mou, Honghu Liu, Adrian Sandu

We propose, analyze, and investigate numerically a novel two-level Galerkin reduced order model (2L-ROM) for the efficient and accurate numerical simulation of the steady Navier-Stokes equations. In the first step of the 2L-ROM, a relatively low-dimensional nonlinear system is solved. In the second step, the Navier-Stokes equations are linearized around the

Kartick C. Sarkar, Santanu Mondal, Prateek Sharma, Tsvi Piran

One of the leading explanations for the origin of Fermi Bubbles is a past jet activity in the Galactic center supermassive black hole Sgr A$^*$. The claimed jets are often assumed to be perpendicular to the Galactic plane. Motivated by the orientation of pc-scale nuclear stellar disk and gas streams, and a low inclination of the accretion disk around Sgr A$^

Euclid Collaboration, A. Fumagalli, A. Saro, S. Borgani

Aims. We validate a semi-analytical model for the covariance of real-space 2-point correlation function of galaxy clusters. Methods. Using 1000 PINOCCHIO light cones mimicking the expected Euclid sample of galaxy clusters, we calibrate a simple model to accurately describe the clustering covariance. Then, we use such a model to quantify the likelihood analys

Paxton C. Fitzpatrick, Jeremy R. Manning

Reproducibility is a core requirement of modern scientific research. For computational research, reproducibility means that code should produce the same results, even when run on different systems. A standard approach to ensuring reproducibility entails packaging a project's dependencies along with its primary code base. Existing solutions vary in how deeply

Christian Müller, Manar Samri, René Hensel, Eduard Arzt

Viscoelasticity is well known to cause significant hysteresis of crack closure and opening when an elastomer is brought in and out of contact with a flat, rigid, adhesive counterface. A separate origin of adhesive hysteresis is small-scale, elastic multistability. Here, we study a system in which both mechanisms act concurrently. Specifically, we compare the

S. R. Mbokop Tchounda, P. Djorwé, S. G. Nana Engo, B. Djafari-Rouhani

An efficient mass sensor based on exceptional points (EPs), engineered under synthetic magnetism requirement, is proposed. The benchmark system consists of an electromechanical (optomechanical) system where an electric (optical) field is driving two mechanical resonators which are mechanically coupled through a phase-dependent phonon-hopping. This phase indu

Chia-Wei Liu, Chao-Qiang Geng

Aiming on testing the $\Xi_c-\Xi_c'$ mixing, we study the decays of $\Xi_{cc}\to \Xi_c \pi$ with $\Xi_{cc} = (\Xi_{cc}^{++} , \Xi_{cc} ^+ )$, $\Xi_c = (\Xi_c^{(\prime)+},\Xi_c^{(\prime)0})$ and $\pi = (\pi^+ , \pi^0)$. The soft-meson limit is considered along with the pole model, and the baryon matrix elements are evaluated by the bag model with and without