May 2022 arXiv papers — page 96

Lei Li, Tao Huang, Kun Liang, Yuan Si

Structural symmetry-breaking that could lead to exotic physical properties plays a crucial role in determining the functions of a system, especially for two-dimensional (2D) materials. Here we demonstrate that multiple functionalities of 2D chromium-based materials could be achieved by breaking inversion symmetry via replacing Y atoms in one face of pristine

Simone Creo, Maria Rosaria Lancia

We consider a parabolic semilinear non-autonomous problem $(\tilde P)$ for a fractional time dependent operator $\mathcal{B}^{s,t}_\Omega$ with Wentzell-type boundary conditions in a possibly non-smooth domain $\Omega\subset\mathbb{R}^N$. We prove existence and uniqueness of the mild solution of the associated semilinear abstract Cauchy problem $(P)$ via an

Soumyajit Mitra, Swayambhu Nath Ray, Bharat Padi, Arunasish Sen

Modern Automatic Speech Recognition (ASR) systems often use a portfolio of domain-specific models in order to get high accuracy for distinct user utterance types across different devices. In this paper, we propose an innovative approach that integrates the different per-domain per-device models into a unified model, using a combination of domain embedding, d

Matija Vidmar

We consider the class of (possibly killed) spectrally positive L\'evy process that have been time-changed by the inverse of an integral functional. Within this class we characterize the family of those processes which satisfy the following property: as functions of point of issue, the Laplace transforms of their first-passage times downwards are completely m

Hunter Handley, Brian Simanek

We demonstrate that discrete m-functions with eventually periodic continued fraction coefficients have an algebraic relationship to their second solution if and only if the periodic part of the sequence of continued fraction coefficients is doubly palindromic. In this setting, doubly palindromic means that each sequence is a repeated concatenation of two pal

Huy Huynh, Abdullah Kalkan

The construction of attractors of a dissipative difference equation is usually based on compactness assumptions. In this paper, we replace them with contractivity assumptions under which the pullback and forward attractors are identical. As a consequence, attractors degenerate to unique bounded entire solutions. As an application, we investigate attractors o

Samantha Youles, Julian E. Bautista, Andreu Font-Ribera, David Bacon

Using synthetic Lyman-$\alpha$ forests from the Dark Energy Spectroscopic Instrument (DESI) survey, we present a study of the impact of errors in the estimation of quasar redshift on the Lyman-$\alpha$ correlation functions. Estimates of quasar redshift have large uncertainties of a few hundred $\text{km s}^{-1}\,$ due to the broadness of the emission lines

Tom Steudtner

It is demonstrated that accounting for lepton flavor universality violating anomalies in $B$ meson decays via $Z'$ models implies a Landau pole problem. A family of models is proposed that resolve both issues simultaneously, fix the metastability of the Higgs and are predictive up to the Planck scale.

M. Tailo, E. Corsaro, A. Miglio, J. Montalbán

We present a new asteroseismic analysis of the stars in the Globular Cluster (GC) M4 based on the data collected by the K2 mission. We report the detection of solar-like oscillation in 37 stars, 32 red giant branch (RGB) and 6 red horizontal branch (rHB) stars, the largest sample for this kind of study in GC up to date. Combining information from asteroseism

Elijah Rippeth, Sweta Agrawal, Marine Carpuat

This paper describes the University of Maryland's submission to the Special Task on Formality Control for Spoken Language Translation at \iwslt, which evaluates translation from English into 6 languages with diverse grammatical formality markers. We investigate to what extent this problem can be addressed with a \textit{single multilingual model}, simultaneo

Ilyes Batatia, Simon Batzner, Dávid Péter Kovács, Albert Musaelian

The rapid progress of machine learning interatomic potentials over the past couple of years produced a number of new architectures. Particularly notable among these are the Atomic Cluster Expansion (ACE), which unified many of the earlier ideas around atom density-based descriptors, and Neural Equivariant Interatomic Potentials (NequIP), a message passing ne

Hariom Sogarwal, Prashant Shukla

We present a study of coherent pion production in neutrino-nucleus interactions using the formalism based on partially conserved axial current theorem which connects the neutrino-nucleus cross section to the pion-nucleus elastic scattering cross section. Pion-nucleus elastic scattering cross section is calculated using Glauber model which takes three inputs,

Rahat Masood, Wing Yan Cheng, Dinusha Vatsalan, Deepak Mishra

Sensors embedded in mobile smart devices can monitor users' activity with high accuracy to provide a variety of services to end-users ranging from precise geolocation, health monitoring, and handwritten word recognition. However, this involves the risk of accessing and potentially disclosing sensitive information of individuals to the apps that may lead to p

Chad E. Brown, Cezary Kaliszyk

Lash is a higher-order automated theorem prover created as a fork of the theorem prover Satallax. The basic underlying calculus of Satallax is a ground tableau calculus whose rules only use shallow information about the terms and formulas taking part in the rule. Lash uses new, efficient C representations of vital structures and operations. Most importantly,

Maaike Rump, Uddalok Sen, Roger Jeurissen, Hans Reinten

In practical applications of inkjet printing the nozzles in a printhead have intermittent idle periods, during which ink can evaporate from the nozzle exit. Inks are usually multicomponent where each component has its own characteristic evaporation rate resulting in concentration gradients within the ink. These gradients may directly and indirectly (via Mara

Maximilian Schörner, Bastian B. L. Witte, Andrew D. Baczewski, Attila Cangi

We investigate shock-compressed copper in the warm dense matter regime by means of density functional theory molecular dynamics simulations. We use neural-network-driven interatomic potentials to increase the size of the simulation box and extract thermodynamic properties in the hydrodynamic limit. We show the agreement of our simulation results with experim

Deqing Zhai, Xiuju Fu, Xiao Feng Yin, Haiyan Xu

In this study, a probability density-based approach for constructing trajectories is proposed and validated through an typical use-case application: Estimated Time of Arrival (ETA) prediction given origin-destination pairs. The ETA prediction is based on physics and mathematical laws given by the extracted information of probability density-based trajectorie

Haipeng Wang, Tiejun Lv, Zhipeng Lin, Jie Zeng

Roadside units (RSUs), which have strong computing capability and are close to vehicle nodes, have been widely used to process delay- and computation-intensive tasks of vehicle nodes. However, due to their high mobility, vehicles may drive out of the coverage of RSUs before receiving the task processing results. In this paper, we propose a mobile edge comput

Jeremy Coulson, Henk van Waarde, Florian Dörfler

The fundamental lemma by Willems and coauthors facilitates a parameterization of all trajectories of a linear time-invariant system in terms of a single, measured one. This result plays an important role in data-driven simulation and control. Under the hood, the fundamental lemma works by applying a persistently exciting input to the system. This ensures tha

Maaike Rump, Youssef Saade, Uddalok Sen, Kamel Fezzaa

The oscillatory flows present in an inkjet printhead can lead to strong deformations of the air-liquid interface at the nozzle exit. Such deformations may lead to an inward directed air jet with bubble pinch-off and the subsequent entrainment of an air bubble, which is highly detrimental to the stability of inkjet printing. Understanding the mechanisms of bu

Valentina Casarino, Giovanni Longobardi, Corrado Zanella

Lunardon and Polverino construct a translation plane starting from a scattered linear set of pseudoregulus type in $\mathrm{PG}(1,q^t)$. In this paper a similar construction of a translation plane $\mathcal A_f$ obtained from any scattered linearized polynomial $f(x)$ in $\mathbb F_{q^t}[x]$ is described and investigated. A class of quasifields giving rise t

Takato Mori, Hidetaka Manabe, Hiroaki Matsueda

In tensor networks, a geometric operation of pushing a bond cut surface toward a minimal surface corresponds to entanglement distillation. Cutting bonds defines a reduced transition matrix on the bond cut surface and the associated quantum state naturally emerges from it. We justify this picture quantitatively by evaluating the trace distance between the max

Inês Terrucha, Elias Fernández Domingos, Francisco C. Santos, Pieter Simoens

It is widely known how the human ability to cooperate has influenced the thriving of our species. However, as we move towards a hybrid human-machine future, it is still unclear how the introduction of AI agents in our social interactions will affect this cooperative capacity. Within the context of the one-shot collective risk dilemma, where enough members of

Marvin Geiselhart, Ahmed Elkelesh, Jannis Clausius, Stephan ten Brink

Permutation decoding gained recent interest as it can exploit the symmetries of a code in a parallel fashion. Moreover, it has been shown that by viewing permuted polar codes as polar subcodes, the set of usable permutations in permutation decoding can be increased. We extend this idea to pre-transformed polar codes, such as cyclic redundancy check (CRC)-aid

Sabina J. Haque, Matthew Satriano, Miruna-Stefana Sorea, Polly Y. Yu

Under the assumption of mass-action kinetics, a dynamical system may be induced by several different reaction networks and/or parameters. It is therefore possible for a mass-action system to exhibit complex-balancing dynamics without being weakly reversible or satisfying toric constraints on the rate constants; such systems are called disguised toric dynamic

Lovro Šubelj

A spanning tree of a network or graph is a subgraph that connects all nodes with the least number or weight of edges. The spanning tree is one of the most straightforward techniques for network simplification and sampling, and for discovering its backbone or skeleton. Prim's algorithm and Kruskal's algorithm are well-known algorithms for computing a spanning

J. D. Camacho, J. P. Faria, P. T. P. Viana

Stellar photospheric activity is known to limit the detection and characterisation of extra-solar planets. In particular, the study of Earth-like planets around Sun-like stars requires data analysis methods that can accurately model the stellar activity phenomena affecting radial velocity (RV) measurements. Gaussian Process Regression Networks (GPRNs) offer

Pallavi Malavi, Arpita Paul, Achintya Bera, D V S Muthu

Quasi-two-dimensional layered BiSe, a natural super-lattice with Bi2Se3-Bi2-Bi2Se3 units, has recently been predicted to be a dual topological insulator, simultaneously weak topological insulator as well as topological crystalline insulator. Here using structural, transport, spectroscopic measurements and density functional theory calculations, we show that

Christoffer Olsson

We study the fundamental question of how likely it is that two randomly chosen trees are isomorphic to each other for different models of random trees. We show that the probability decays exponentially for rooted labeled trees as well as for Galton--Watson trees with bounded degrees but that this is not true for plane trees, thus providing a counterexample i

E. E. Vityaev, A. G. Kolonin, A. V. Kurpatov A. A. Molchanov

In the monograph "Strong artificial intelligence. On the Approaches to Superintelligence" contains an overview of general artificial intelligence (AGI). As an anthropomorphic research area, it includes Brain Principles Programming (BPP) -- the formalization of universal mechanisms (principles) of the brain work with information, which are implemented at all

Ling Jin, Alina Lazar, Caitlin Brown, Bingrong Sun

What makes you hold on that old car? While the vast majority of the household vehicles are still powered by conventional internal combustion engines, the progress of adopting emerging vehicle technologies will critically depend on how soon the existing vehicles are transacted out of the household fleet. Leveraging a nationally representative longitudinal dat

Antonis Maronikolakis, Philip Baader, Hinrich Schütze

To tackle the rising phenomenon of hate speech, efforts have been made towards data curation and analysis. When it comes to analysis of bias, previous work has focused predominantly on race. In our work, we further investigate bias in hate speech datasets along racial, gender and intersectional axes. We identify strong bias against African American English (

Alexander Osterkorn, Stefan Kehrein

We study the microscopic dynamics of competing ordered phases in a two-dimensional correlated electron model, which is driven with a pulsed electric field of finite duration. In order to go beyond a mean-field treatment of the electronic interactions we adopt a large-$N$ generalization of the Hubbard model and combine it with the semiclassical fermionic trun

Amra Omanović, Polona Oblak, Tomaž Curk

Matrix factorization, one of the most popular methods in machine learning, has recently benefited from introducing non-linearity in prediction tasks using tropical semiring. The non-linearity enables a better fit to extreme values and distributions, thus discovering high-variance patterns that differ from those found by standard linear algebra. However, the

Tobias Domhan, Eva Hasler, Ke Tran, Sony Trenous

Vocabulary selection, or lexical shortlisting, is a well-known technique to improve latency of Neural Machine Translation models by constraining the set of allowed output words during inference. The chosen set is typically determined by separately trained alignment model parameters, independent of the source-sentence context at inference time. While vocabula

Michele Ancona

Given a real algebraic variety $X$ of dimension $n$, a very ample divisor $D$ on $X$ and a smooth closed hypersurface $\Sigma$ of $\mathbf{R}^n$, we construct real algebraic hypersurfaces in the linear system $|mD|$ whose real locus contains many connected components diffeomorphic to $\Sigma$. As a consequence, we show the existence of real algebraic hypersu

Sören Kleine, Katharina Müller

We compare the Iwasawa invariants of fine Selmer groups of $p$-adic Galois representations over admissible $p$-adic Lie extensions of a number field $K$ to the Iwasawa invariants of ideal class groups along these Lie extensions. More precisely, let $K$ be a number field, let $V$ be a $p$-adic representation of the absolute Galois group $G_K$ of $K$, and choo

Anastasia V. Vikulova

In this paper we prove that for $n$-dimensional smooth $l$-Fano well formed weighted complete intersections, which is not isomorphic to a usual projective space, the upper bound for $l$ is equal to $\lceil \log_2(n+2) \rceil-1 .$ We also prove that the only $l$-Fano of dimension $n$ among such manifolds with inequalities $ \lceil \log_3(n+2) \rceil \leqslant

Jiaqi Yan, Yilin Mo, Hideaki Ishii

This paper studies the synchronization of stochastic linear systems which are subject to a general class of noises, in the sense that the noises are bounded in covariance but might be correlated with the states of agents and among each other. We propose an event-based control protocol for achieving the synchronization among agents in the mean square sense an

Gunhee Lee, Jonghwa Yim, Chanran Kim, Minjae Kim

Despite recent success in conditional image synthesis, prevalent input conditions such as semantics and edges are not clear enough to express `Linear (Ridges)' and `Planar (Scale)' representations. To address this problem, we propose a novel framework StyLandGAN, which synthesizes desired landscape images using a depth map which has higher expressive power.

D. L. Bashlakov, O. E. Kvitnitskaya, G. Shipunov, S. Aswartham

PtBi2 is a Weyl semimetal, which demonstrates superconductivity with low critical temperature Tc ~ 0.6 K in the bulk. Here, we report our study of electron-phonon interaction (EPI) in trigonal PtBi2 by the Yanson point contact (PC) spectroscopy and presenting the observation of PC enhanced superconductivity. We show, that the Yansons PC spectra display a bro

Johannes Seiler, Thomas Strohm, Wolfgang P. Schleich

We show that the Hardy nonlocality condition is equivalent to the violation of the CHSH inequality with additional constraints. We adapt the geometrical optimization of the violation of the CHSH inequality to these additional constraints and show that the Hardy condition is equivalent to optimizing the length difference of two sides in a triangle. Furthermor

Shunsuke Usuki

For integers $a$ and $b\geq 2$, let $T_a$ and $T_b$ be multiplication by $a$ and $b$ on $\mathbb{T}=\mathbb{R}/\mathbb{Z}$. The action on $\mathbb{T}$ by $T_a$ and $T_b$ is called $\times a,\times b$ action and it is known that, if $a$ and $b$ are multiplicatively independent, then the only $\times a,\times b$ invariant and ergodic measure with positive entr

Ziqian Zeng, Weimin Ni, Tianqing Fang, Xiang Li

Solving text classification in a weakly supervised manner is important for real-world applications where human annotations are scarce. In this paper, we propose to query a masked language model with cloze style prompts to obtain supervision signals. We design a prompt which combines the document itself and "this article is talking about [MASK]." A masked lan

Yu Lin, Zhecheng An, Peihao Wu, Zejun Ma

Though achieving impressive results on many NLP tasks, the BERT-like masked language models (MLM) encounter the discrepancy between pre-training and inference. In light of this gap, we investigate the contextual representation of pre-training and inference from the perspective of word probability distribution. We discover that BERT risks neglecting the conte

Angelo Felice Lopez

We characterize smooth irreducible varieties with Ulrich twisted normal bundle.

Evaristo Villaseco Arribas, Federica Agostini, Neepa T. Maitra

Modeling the dynamics of non-bound states in molecules requires an accurate description of how electronic motion affects nuclear motion and vice-versa. The exact factorization (XF) approach offers a unique perspective, in that it provides potentials that act on the nuclear subsystem or electronic subsystem, which contain the effects of the coupling to the ot

W. D. Cotton, F. Camilo, W. Becker, J. J. Condon

The curious Galactic features near G357.2$-$0.2 were observed with the MeerKAT radio interferometer array in the UHF and L bands (0.56--1.68 GHz). There are two possibly related features: a newly identified faint heart-shaped partial shell (the "Heart"), and a series of previously known but now much better imaged narrow, curved features (the "Worm") interior

Gregg M. Gallatin

For a given asphere the grating equation is used to derive the design for a Computer Generated Hologram (CGH), sometimes referred to as a diffractive null corrector. The CGH converts a spherical wavefront to the shape appropriate for the given asphere as required for interferometric metrology. The derivation is effectively analytic but may require numerical

Sara Conti, Andrea Perali, Alexander R. Hamilton, Milorad V. Milosevic

A supersolid, a counter-intuitive quantum state in which a rigid lattice of particles flows without resistance, has to date not been unambiguously realised. Here we reveal a supersolid ground state of excitons in a double-layer semiconductor heterostructure over a wide range of layer separations outside the focus of recent experiments. This supersolid confor

Jenny Schmalfuss, Erik Scheurer, Heng Zhao, Nikolaos Karantzas

Blind inpainting algorithms based on deep learning architectures have shown a remarkable performance in recent years, typically outperforming model-based methods both in terms of image quality and run time. However, neural network strategies typically lack a theoretical explanation, which contrasts with the well-understood theory underlying model-based metho

Bao Zhao, Henrik R. Thomsen, Jacopo M. De Ponti, Emanuele Riva

This work studies a broadband graded metamaterial, which integrates the piezoelectric energy harvesting function targeting low-frequency structural vibrations, lying below 100 Hz. The device combines a graded metamaterial with beam-like resonators, piezoelectric patches and a self-powered piezoelectric interface circuit for energy harvesting. Based on the me

Miroslav Štrupl, Francesco Faccio, Dylan R. Ashley, Jürgen Schmidhuber

Upside-Down Reinforcement Learning (UDRL) is an approach for solving RL problems that does not require value functions and uses only supervised learning, where the targets for given inputs in a dataset do not change over time. Ghosh et al. proved that Goal-Conditional Supervised Learning (GCSL) -- which can be viewed as a simplified version of UDRL -- optimi

Constance Toulouse, Danila Amoroso, Robert Oliva, Cong Xin

In this paper, we revisit the high-pressure behavior of BaZrO3 by a combination of first-principle calculations, Raman spectroscopy, and x-ray diffraction under high pressure. We confirm experimentally the cubic-to-tetragonal transition at 10 GPa and find no evidence for any other phase transition up to 45 GPa, the highest pressures investigated, at variance

Christian Pötzsche

We present an application-oriented approach to Urysohn and Hammerstein integral operators acting between spaces of H"older continuous functions over compact metric spaces. These nonlinear mappings are formulated by means of an abstract measure theoretical integral involving a finite measure. This flexible setting creates a common framework to tackle both suc

Manana Kachakhidze, Nino Kachakhidze-Murphy

The paper represents the VLF/LF electromagnetic radiation as the earthquake's true precursor. It is shown that this parameter is capable of describing the fault formative process in the focal area. Besides, VLF/LF electromagnetic radiation frequency analysis gives the possibility simultaneously to determine all three characteristic parameters necessary for i

Dominik Schreiber, Peter Sanders

Previous efforts on making Satisfiability (SAT) solving fit for high performance computing (HPC) have lead to super-linear speedups on particular formulae, but for most inputs cannot make efficient use of a large number of processors. Moreover, long latencies (minutes to days) of job scheduling make large-scale SAT solving on demand impractical for most appl

Marcus Märtens, Dario Izzo, Emmanuel Blazquez, Moritz von Looz

Dyson spheres are hypothetical megastructures encircling stars in order to harvest most of their energy output. During the 11th edition of the GTOC challenge, participants were tasked with a complex trajectory planning related to the construction of a precursor Dyson structure, a heliocentric ring made of twelve stations. To this purpose, we developed severa

Samson Abramsky, Tomáš Jakl, Thomas Paine

Game comonads have brought forth a new approach to studying finite model theory categorically. By representing model comparison games semantically as comonads, they allow important logical and combinatorial properties to be exressed in terms of their Eilenberg-Moore coalgebras. As a result, a number of results from finite model theory, such as preservation t

Sergio Almaraz, Shaodong Wang

We study the Yamabe equation in the Euclidean half-space. We prove that any sign-changing solution has at least twice the energy of a standard bubble. Moreover, a sharper energy lower bound of the sign-changing solution set is also established via the method of moving planes. This bound increases the energy range for which Palais-Smale sequences of related v

Anna Dall'Acqua, Leonie Langer, Fabian Rupp

We consider closed planar curves with fixed length and arbitrary winding number whose elastic energy depends on an additional density variable and a spontaneous curvature. Working with the inclination angle, the associated $L^2$-gradient flow is a nonlocal quasilinear coupled parabolic system of second order. We show local well-posedness, global existence of

Oliver Diekmann, Dominik Lentrodt, Jörg Evers

Ensembles of M\"ossbauer nuclei embedded in thin-film cavities form a promising platform for x-ray quantum optics. A key feature is that the joint nuclei-cavity system can be considered as an artificial x-ray multi-level scheme in the low-excitation regime. Using the cavity environment, the structure and parameters of such level schemes can be tailored beyon

Gidon Ernst, Alexander Knapp, Toby Murray

We present a Hoare logic that extends program specifications with regular expressions that capture behaviors in terms of sequences of events that arise during the execution. The idea is similar to session types or process-like behavioral contracts, two currently popular research directions. The approach presented here strikes a particular balance between exp

Ehud Lehrer, Tao Wang

We consider stopping problems in which a decision maker (DM) faces an unknown state of nature and decides sequentially whether to stop and take an irreversible action; pay a fee and obtain additional information; or wait without acquiring information. We discuss the value and quality of information. The former is the maximal discounted expected revenue the D

Larry Read

We prove an upper bound on the sum of the distances between the eigenvalues of a perturbed Schr\"odinger operator $H_0-V$ and the lowest eigenvalue of $H_0$. Our results hold for operators $H_0=-\Delta-V_0$ in one dimension with single-well potentials. We rely on a variation of the well-known commutation method. In the P\"oschl-Teller and Coulomb cases we ar

Mesay Addisu Jima, Alessandro Tonello, Alioune Niang, Tigran Mansuryan

Recent experimental results have reported the observation of beam self-cleaning or, more generally, nonlinear beam reshaping in active multimode fibers. In this work we present a numerical analysis of these processes, by considering the ideal case of a diode-pumped signal amplifier made of a graded-index multimode fiber with uniform Yb doping. Simulations co

Thanh Tam Nguyen, Thanh Trung Huynh, Hongzhi Yin, Matthias Weidlich

Today's social networks continuously generate massive streams of data, which provide a valuable starting point for the detection of rumours as soon as they start to propagate. However, rumour detection faces tight latency bounds, which cannot be met by contemporary algorithms, given the sheer volume of high-velocity streaming data emitted by social networks.

P. Welter, B. A. Josteinsson, S. Josephy, A. Wittmann

We demonstrate a spectrum demodulation technique for greatly speeding up the data acquisition rate in scanning nitrogen-vacancy center magnetometry. Our method relies on a periodic excitation of the electron spin resonance by fast, wide-band frequency sweeps combined with a phase-locked detection of the photo-luminescence signal. The method can be extended b

Blandine Feneuil, Kazi Tassawar Iqbal, Atle Jensen, Luca Brandt

We study the interaction-induced migration of bubbles in shear flow and observe that bubbles suspended in elastoviscoplastic emulsions organise into chains aligned in the flow direction, similarly to particles in viscoelastic fluids. To investigate the driving mechanism, we perform experiments and simulations on bubble pairs, using suspending fluids with dif

Longquan Jiang, Ricardo Usbeck

Existing approaches on Question Answering over Knowledge Graphs (KGQA) have weak generalizability. That is often due to the standard i.i.d. assumption on the underlying dataset. Recently, three levels of generalization for KGQA were defined, namely i.i.d., compositional, zero-shot. We analyze 25 well-known KGQA datasets for 5 different Knowledge Graphs (KGs)

David Winkelmann, Matthias Ulrich, Michael Römer, Roland Langrock

E-grocery retailing enables ordering products online to be delivered at a future time slot chosen by the customer. This emerging field of business provides retailers with large and comprehensive new data sets, yet creates several challenges for the inventory management process. For example, the risk of a single item's stock-out leading to a complete cancella

Wentao Huang, Haizhang Zhang

Various powerful deep neural network architectures have made great contribution to the exciting successes of deep learning in the past two decades. Among them, deep Residual Networks (ResNets) are of particular importance because they demonstrated great usefulness in computer vision by winning the first place in many deep learning competitions. Also, ResNets

Wentao Huang, Yuesheng Xu, Haizhang Zhang

Deep neural networks, as a powerful system to represent high dimensional complex functions, play a key role in deep learning. Convergence of deep neural networks is a fundamental issue in building the mathematical foundation for deep learning. We investigated the convergence of deep ReLU networks and deep convolutional neural networks in two recent researche

A. Kirwan, A. Murphy, P. C Schneider, E. T. Whelan

HD163296 is a Herbig Ae star which drives a bipolar knotty jet with a total length of ~6000au. Strong evidence exists that the disk of HD163296 harbors planets. Studies have shown that the presence of companions around jet-driving stars could affect the morphology of the jets. This includes a `wiggling' of the jet axis and a periodicity in the positions of t

Chaoqin Huang, Qinwei Xu, Yanfeng Wang, Yu Wang

Recently, anomaly detection and localization in multimedia data have received significant attention among the machine learning community. In real-world applications such as medical diagnosis and industrial defect detection, anomalies only present in a fraction of the images. To extend the reconstruction-based anomaly detection architecture to the localized a

Mihai Ordean, Flavio D. Garcia

Millimeter-wave radar systems are one of the core components of the safety-critical Advanced Driver Assistant System (ADAS) of a modern vehicle. Due to their ability to operate efficiently despite bad weather conditions and poor visibility, they are often the only reliable sensor a car has to detect and evaluate potential dangers in the surrounding environme

Denis S. Grebenkov

Diffusive search for a static target is a common problem in statistical physics with numerous applications in chemistry and biology. We look at this problem from a different perspective and investigate the statistics of encounters between the diffusing particle and the target. While an exact solution of this problem was recently derived in the form of a spec

Ferenc Bencs, Márton Borbényi, Péter Csikvári

For a graph $G=(V,E)$ with $v(G)$ vertices the partition function of the random cluster model is defined by $$Z_G(q,w)=\sum_{A\subseteq E(G)}q^{k(A)}w^{|A|},$$ where $k(A)$ denotes the number of connected components of the graph $(V,A)$. Furthermore, let $g(G)$ denote the girth of the graph $G$, that is, the length of the shortest cycle. In this paper we sho

Alan F. T. Winfield, Anouk van Maris, Pericle Salvini, Marina Jirotka

This paper introduces a draft open standard for the robot equivalent of an aircraft flight data recorder, which we call an ethical black box. This is a device, or software module, capable of securely recording operational data (sensor, actuator and control decisions) for a social robot, in order to support the investigation of accidents or near-miss incident

Yuki K. Wakabayashi, Masaki Kobayashi, Yukiharu Takeda, Miho Kitamura

Epitaxially strained SrRuO3 films have been a model system for understanding the magnetic anisotropy in metallic oxides. In this paper, we investigate the anisotropy of the Ru 4d and O 2p electronic structure and magnetic properties using high-quality epitaxially strained (compressive and tensile) SrRuO3 films grown by machine-learning-assisted molecular bea

Vasilis Krokos, Stéphane P. A. Bordas, Pierre Kerfriden

Stress prediction in porous materials and structures is challenging due to the high computational cost associated with direct numerical simulations. Convolutional Neural Network (CNN) based architectures have recently been proposed as surrogates to approximate and extrapolate the solution of such multiscale simulations. These methodologies are usually limite

Nishikanta Mohanty, Bikash K. Behera, Christopher Ferrie

The vehicle routing problem (VRP) is an NP-hard optimization problem that has been an interest of research for decades in science and industry. The objective is to plan routes of vehicles to deliver goods to a fixed number of customers with optimal efficiency. Classical tools and methods provide good approximations to reach the optimal global solution. Quant

Hassan Firouzjahi

We study the quantum vacuum zero point energy in the Schwarzschild black hole as well as in the Nariai limit of the dS-Schwarzschild backgrounds. We show that the regularized vacuum energy density near the black hole and also in the Nariai setup match exactly with the corresponding value in the flat background, scaling with the fourth power of the mass of th

Caglar Demir, Julian Lienen, Axel-Cyrille Ngonga Ngomo

Knowledge graph embedding research has mainly focused on learning continuous representations of entities and relations tailored towards the link prediction problem. Recent results indicate an ever increasing predictive ability of current approaches on benchmark datasets. However, this effectiveness often comes with the cost of over-parameterization and incre

Alberto Daza-Garcia, Alberto Elduque, Umut Sayin

The nontrivial unital composition superalgebras, of dimension 3 and 6, which exist only in characteristic 3, are obtained from the split Cayley algebra and its order 3 automorphisms, by means of the process of semisimplification of the symmetric tensor category of representations of the cyclic group of order 3. Connections with the extended Freudenthal Magic

Kimet Jusufi, Salvatore Capozziello, Sebastian Bahamonde, Mubasher Jamil

We use observational data from the S2 star orbiting around the Galactic Center to constrain a black hole solution of extended teleparallel gravity models. Subsequently, we construct the shadow images of Sgr A$^{\star}$ black hole. In particular, we constrain the parameter $\alpha=1/\lambda$ which appears in the Born-Infeld $f(T)$ model. In the strong gravity

Nikhil Bansal, William Kuszmaul

In the 2-choice allocation problem, $m$ balls are placed into $n$ bins, and each ball must choose between two random bins $i, j \in [n]$ that it has been assigned to. It has been known for more than two decades, that if each ball follows the Greedy strategy (i.e., always pick the less-full bin), then the maximum load will be $m/n + O(\log \log n)$ with high

D. Kolotinskii, A. Timofeev

We present the first open-source, GPU-based code for complex plasmas. The code, OpenDust, aims to provide researchers both experimenters and theorists user-friendly and high-performance tool for self-consistent calculation forces, acting on microparticles, and microparticles' charges in a plasma flow. OpenDust performance originates from highly-optimized Cud

Paola Natalia Canas, Juan Diego Ortega, Marcos Nieto, Oihana Otaegui

Strategies that include the generation of synthetic data are beginning to be viable as obtaining real data can be logistically complicated, very expensive or slow. Not only the capture of the data can lead to complications, but also its annotation. To achieve high-fidelity data for training intelligent systems, we have built a 3D scenario and set-up to resem

Hilario Espinós, Iván Panadero, Juan José García-Ripoll, Erik Torrontegui

We analyse the implementation of a fast nonadiabatic CZ gate between two transmon qubits with tuneable coupling. The gate control method is based on a theory of dynamical invariants which leads to reduced leakage and robustness against decoherence. The gate is based on a description of the resonance between the $|11\rangle$ and $|20\rangle$ using an effectiv

Debamalya Dutta, Arko Roy, Kush Saha

We theoretically study the electric pulse-driven non-linear response of interacting bosons loaded in an optical lattice in the presence of an incommensurate superlattice potential. In the non-interacting limit $(U=0)$, the model admits both localized and delocalized phases depending on the strength of the incommensurate potential $V_0$. We show that the part

Nour Ramzy, Soren Auer, Javad Chamanara, Hans Ehm

Semiconductor supply chains are described by significant demand fluctuation that increases as one moves up the supply chain, the so-called bullwhip effect. To counteract, semiconductor manufacturers aim to optimize capacity utilization, to deliver with shorter lead times and exploit this to generate revenue. Additionally, in a competitive market, firms seek

Jin-Hui Fang, Csaba Sándor

For nonempty sets $A,B$ of nonnegative integers and an integer $n$, let $r_{A,B}(n)$ be the number of representations of $n$ as $a+b$ and $d_{A,B}(n)$ be the number of representations of $n$ as $a-b$, where $a\in A, b\in B$. In this paper, we determine the sets $A,B$ such that $r_{A,B}(n)=1$ for every nonnegative integer $n$. We also consider the \emph{diffe

B. Posselt, G. G. Pavlov

We report on the study of six Chandra observations (four epochs) of the Central Compact Object (CCO) in the Cassiopeia A supernova remnant with the ACIS instrument in the subarray mode. This mode minimizes spectrum-distorting instrumental effects such as pileup. The data were taken over a time span ~ 14 years. If a non-magnetic carbon atmosphere is assumed f

Ran Gu, Jiangshan Lu, Jingyang Zhang, Wenhui Lei

Efficiently utilizing discriminative features is crucial for convolutional neural networks to achieve remarkable performance in medical image segmentation and is also important for model generalization across multiple domains, where letting model recognize domain-specific and domain-invariant information among multi-site datasets is a reasonable strategy for

Anuj Dash, Aloke Paul

The estimation of (n-1)2 interdiffusion coefficients in an n component system requires (n-1) diffusion paths to intersect or pass closely in the (n-1) dimensional space according to the body diagonal diffusion couple method. These interdiffusion coefficients are related to n(n-1) intrinsic (or n tracer diffusion coefficients), which cannot be estimated easil

Mei Wang, Weihong Deng, Cheng-Lin Liu

Oracle bone script is the earliest-known Chinese writing system of the Shang dynasty and is precious to archeology and philology. However, real-world scanned oracle data are rare and few experts are available for annotation which make the automatic recognition of scanned oracle characters become a challenging task. Therefore, we aim to explore unsupervised d

Mei Wang, Yaobin Zhang, Weihong Deng

Although deep face recognition has achieved impressive progress in recent years, controversy has arisen regarding discrimination based on skin tone, questioning their deployment into real-world scenarios. In this paper, we aim to systematically and scientifically study this bias from both data and algorithm aspects. First, using the dermatologist approved Fi

Orsolya Csiszár, Luca Sára Pusztaházi, Lehel Dénes-Fazakas, Michael S. Gashler

We present a deep learning model for finding human-understandable connections between input features. Our approach uses a parameterized, differentiable activation function, based on the theoretical background of nilpotent fuzzy logic and multi-criteria decision-making (MCDM). The learnable parameter has a semantic meaning indicating the level of compensation

Tristan Gomez, Thomas Fréour, Harold Mouchère

An important limitation to the development of AI-based solutions for In Vitro Fertilization (IVF) is the black-box nature of most state-of-the-art models, due to the complexity of deep learning architectures, which raises potential bias and fairness issues. The need for interpretable AI has risen not only in the IVF field but also in the deep learning commun