August 2022 arXiv papers — page 125

D. N. Kobyakov

In this paper, an effective field theory for proton superconductor (SC) interacting with neutron superfluid (SF), both with scalar order parameters, is developed and applied to the surface energy (SE) of a magnetized SC body in neutron stars (NS). Essentially, the SE studied here differs from the nuclear SE: here, the proton SF density decays to zero while t

V. Mehrmann, A. J. van der Schaft

Different representations of dissipative Hamiltonian and port-Hamiltonian differential-algebraic equations (DAE) systems are presented and compared. Using global geometric and algebraic points of view, translations between the different representations are presented. Characterizations are also derived when a general DAE system can be transformed into one of

Tristan C. Collins, Yang Li

We show that if an exact special Lagrangian $N\subset \mathbb{C}^n$ has a multiplicity one, cylindrical tangent cone of the form $\mathbb{R}^{k}\times \mathbf{C}$ where $\mathbf{C}$ is a special Lagrangian cone with smooth, connected link, then this tangent cone is unique provided $\mathbf{C}$ satisfies an integrability condition. This applies, for example,

Joydeep Chakravarty, Pronobesh Maity, Amiya Mishra

The Coon amplitude is the unique solution to duality constraints with logarithmic Regge trajectories. A striking feature of this solution is that it interpolates between the Veneziano amplitude and a scalar particle amplitude. However, an analytic proof of unitarity of the amplitude is not yet known. In this short note, we explicitly compute the partial wave

Felipe Ortega, Maria Jesus Algar, Isaac Martín de Diego, Javier M. Moguerza

Similarity search based on a distance function in metric spaces is a fundamental problem for many applications. Queries for similar objects lead to the well-known machine learning task of nearest-neighbours identification. Many data indexing strategies, collectively known as Metric Access Methods (MAM), have been proposed to speed up queries for similar elem

Michael Cash, Christopher Morales-Gonzalez, Shan Wang, Xipeng Jin

KNX is one popular communication protocol for a building automation system (BAS). However, its lack of security makes it subject to a variety of attacks. We are the first to study the false data injection attack against a KNX based BAS. We design a man-in-the-middle (MITM) attack to change the data from a temperature sensor and inject false data into the BAS

Konrad K. Dabrowski, Peter Jonsson, Sebastian Ordyniak, George Osipov

Checking whether a system of linear equations is consistent is a basic computational problem with ubiquitous applications. When dealing with inconsistent systems, one may seek an assignment that minimizes the number of unsatisfied equations. This problem is NP-hard and UGC-hard to approximate within any constant even for two-variable equations over the two-e

Lalit Kumar Sahoo, Ashok Kumar Mondal, Dipali Basak, Chinmay Basu

The LiF target preparation on self-supporting Ag backing (LiF/Ag) is discussed in a detailed manner using vacuum evaporation process. The target thickness is measured using the energy loss of three line alpha source. 183.74 {\mu}g/cm 2 thickness of LiF is achieved through the evaporation process. Good uniformity of targets is observed. Non-uniformity in targ

Michele Grossi, Oriel Kiss, Francesco De Luca, Carlo Zollo

The emergence of a collective behavior in a many-body system is responsible of the quantum criticality separating different phases of matter. Interacting spin systems in a magnetic field offer a tantalizing opportunity to test different approaches to study quantum phase transitions. In this work, we exploit the new resources offered by quantum algorithms to

Luciano Maiani, Alessandro Pilloni, Antonio D. Polosa, Veronica Riquer

Tetraquarks QQq*q* are found to be described remarkably well with the Quantum Chromodynamics version of the Hydrogen bond, as treated with the Born-Oppenheimer approximation. We show the robustness of the method by computing the mass of the observed Tcc tetraquark following two different paths. Relying on this, we provide a prediction for the mass of the exp

Anudeepa Ghosh, Magdalena Birowska, Pradeepta Kumar Ghose, Miłosz Rybak

We report anisotropic magnetodielectric (MD) coupling in layered van der Waals (vdW) antiferromagnetic (AFM) FePS$_3$ (N\'eel temperature $T_{\mathrm{N}}$ $\sim$ 120K) with perpendicular anisotropy. Above $T_N$, while dielectric response function along \textit{c}-axis shows frequency dependent relaxations, in-plane data is frequency independent and reveals a

Salvatore Calì, Daniel C. Hackett, Yin Lin, Phiala E. Shanahan

This work develops neural-network--based preconditioners to accelerate solution of the Wilson-Dirac normal equation in lattice quantum field theories. The approach is implemented for the two-flavor lattice Schwinger model near the critical point. In this system, neural-network preconditioners are found to accelerate the convergence of the conjugate gradient

Rishabh Bhardwaj, Luke Lippstreu

We compute the angular momentum of the electromagnetic field on a late time Cauchy surface with an arbitrary constant normal vector relevant for the classical scattering of charged particles. We find a time independent contribution to the angular momentum. This demonstrates that every charged particle scattering event is accompanied by a net shift in the ang

Elena S. Dimitrova, Cameron H. Fredrickson, Nicholas A. Rondoni, Brandilyn Stigler

Over the past several decades, algebraic geometry has provided innovative approaches to biological experimental design that resolved theoretical questions and improved computational efficiency. However, guaranteeing uniqueness and perfect recovery of models are still open problems. In this work we study the problem of uniqueness of wiring diagrams. We use as

Yu Wang, L. M. Becerra, C. L. Fryer, J. A. Rueda

GRB 171205A is a low-luminosity, long-duration gamma-ray burst (GRB) associated with SN 2017iuk, a broad-line type Ic supernova (SN). It is consistent with being formed in the core-collapse of a widely separated binary, which we have called the binary-driven hypernova (BdHN) of type III. The core-collapse of the CO star forms a newborn NS ($\nu$NS) and the S

Renjie Xie, Wei Xu, Jiabao Yu, Aiqun Hu

Deep learning (DL) applied to a device's radio-frequency fingerprint~(RFF) has attracted significant attention in physical-layer authentication due to its extraordinary classification performance. Conventional DL-RFF techniques are trained by adopting maximum likelihood estimation~(MLE). Although their discriminability has recently been extended to unknown d

Jianfeng Zhang, Zimu Zhu

In this paper we consider a principal agent problem where the agent is allowed to quit, by incurring a cost. When the current agent quits the job, the principal will hire a new one, possibly with a different type. We characterize the principal's dynamic value function, which could be discontinuous at the boundary, as the (unique) minimal solution of an infin

Zhipeng Luo, Gongjie Zhang, Changqing Zhou, Tianrui Liu

3D object detection using point clouds has attracted increasing attention due to its wide applications in autonomous driving and robotics. However, most existing studies focus on single point cloud frames without harnessing the temporal information in point cloud sequences. In this paper, we design TransPillars, a novel transformer-based feature aggregation

Sichen Li

In this paper we first note a result of birational automorphisms with bounded degree of projective varieties related with the Zariski dense orbit conjecture (ZDO) and the Zariski density of periodic points. Next, we give a reduced result of ZDO for automorphisms of projective threefolds, and showed ZDO for automorphisms of projective varieties $X$ with the i

Michel Hernández Villanueva

A review of the experimental status in searches for charged Lepton Flavor Violation (LFV) is presented. Searches for LFV in decays of leptons, heavy mesons, and bosons are explored, with an emphasis on the experiments providing the best constraints in each sector. In addition, prospects for upper limits by current and upcoming experiments in the next decade

Muhammad Fitrah Alfian Rangga Sakti

Motivated by advanced progress in the holographic theory between rotating black holes and CFT, we explore the conformal invariance on dyonic Kerr-Sen black hole and its gauged family. We consider a neutral massless scalar probe on the black holes' background within the low-frequency limit and exhibit that the solution space possesses $SL(2,R)\times SL(2,R)$

Emily Adlam

In this article we set out to understand the significance of the process matrix formalism and the quantum causal modelling programme for ongoing disputes about the role of causation in fundamental physics. We argue that the process matrix programme has correctly identified a notion of 'causal order' which plays an important role in fundamental physics, but t

Sebastiaan Y. Haffert, Jared R. Males, Laird M. Close, Kyle Van Gorkom

MagAO-X system is a new adaptive optics for the Magellan Clay 6.5m telescope. MagAO-X has been designed to provide extreme adaptive optics (ExAO) performance in the visible. VIS-X is an integral-field spectrograph specifically designed for MagAO-X, and it will cover the optical spectral range (450 - 900 nm) at high-spectral (R=15.000) and high-spatial resolu

Liping Li

It is well known that a regular diffusion on an interval $I$ without killing inside is uniquely determined by a canonical scale function $s$ and a canonical speed measure $m$. Note that $s$ is a strictly increasing and continuous function and $m$ is a fully supported Radon measure on $I$. In this paper we will associate a general triple $(I,s,m)$, where $s$

Savannah L. Cuozzo, Charris Gabaldon, Pratik J. Barge, Ziqi Niu

We combine single-pixel imaging and homodyne detection to perform full object recovery (phase and amplitude). Our method does not require any prior information about the object or the illuminating fields. As a demonstration, we reconstruct the optical properties of several semi-transparent objects and find that the reconstructed complex transmission has a ph

CMS Collaboration

Three searches are presented for signatures of physics beyond the standard model (SM) in $\tau\tau$ final states in proton-proton collisions at the LHC, using a data sample collected with the CMS detector at $\sqrt{s}$ = 13 TeV, corresponding to an integrated luminosity of 138 fb$^{-1}$. Upper limits at 95% confidence level (CL) are set on the products of th

Kasper S. Sørensen, Horia D. Cornean, Sergey Sorokin

We revisit the problem of constructing one-dimensional acoustic black holes. Instead of considering the Euler-Bernoulli beam theory, we use Timoshenko's approach instead, which is known to be more realistic at higher frequencies. Our goal is to minimize the reflection coefficient under a constraint imposed on the normalized wave number variation. We use the

André F. R. Guarda, Nuno M. M. Rodrigues, Manuel Ruivo, Luís Coelho

This document describes a deep learning-based point cloud geometry codec and a deep learning-based point cloud joint geometry and colour codec, submitted to the Call for Proposals on JPEG Pleno Point Cloud Coding issued in January 2022. The proposed codecs are based on recent developments in deep learning-based PC geometry coding and offer some of the key fu

Olli Hirviniemi, Lauri Hitruhin

We consider quasiconformal mappings of the unit disk that have a planar extension which have $p$-integrable distortion. In this paper, we establish a bound for the modulus of continuity for the inverse mapping and show sharpness of this bound. Furthermore, we also obtain bounds for the compression multifractal spectra of such mappings.

Saghar Bagheri, Chinthaka Dinesh, Gene Cheung, Timothy Eadie

Prediction of annual crop yields at a county granularity is important for national food production and price stability. In this paper, towards the goal of better crop yield prediction, leveraging recent graph signal processing (GSP) tools to exploit spatial correlation among neighboring counties, we denoise relevant features via graph spectral filtering that

Rodrigo Raya, Jad Hamza, Viktor Kunčak

Motivated by satisfiability of constraints with function symbols, we consider numerical inequalities on non-negative integers. The constraints we consider are a conjunction of a linear system Ax = b and a conjunction of (non-)convex constraints of the form x_i >= x_j^n (x_i <= x_j^n). We show that the satisfiability of these constraints is NP-complete even i

Zhilei Chen, Honghua Chen, Lina Gong, Xuefeng Yan

High-confidence overlap prediction and accurate correspondences are critical for cutting-edge models to align paired point clouds in a partial-to-partial manner. However, there inherently exists uncertainty between the overlapping and non-overlapping regions, which has always been neglected and significantly affects the registration performance. Beyond the c

Pranjal Awasthi, Alex Tang, Aravindan Vijayaraghavan

We provide a convergence analysis of gradient descent for the problem of agnostically learning a single ReLU function with moderate bias under Gaussian distributions. Unlike prior work that studies the setting of zero bias, we consider the more challenging scenario when the bias of the ReLU function is non-zero. Our main result establishes that starting from

Tahir Hassan, Aras Asaad, Dashti Ali, Sabah Jassim

Advances in AI based computer vision has led to a significant growth in synthetic image generation and artificial image tampering with serious implications for unethical exploitations that undermine person identification and could make render AI predictions less explainable.Morphing, Deepfake and other artificial generation of face photographs undermine the

Yao-Chih Lee, Kuan-Wei Tseng, Guan-Sheng Chen, Chu-Song Chen

Dense depth and pose estimation is a vital prerequisite for various video applications. Traditional solutions suffer from the robustness of sparse feature tracking and insufficient camera baselines in videos. Therefore, recent methods utilize learning-based optical flow and depth prior to estimate dense depth. However, previous works require heavy computatio

Yan Li, ZhenYe Li, Feng Wang

Let $G$ be a connected, complex reductive Lie group and $X$ a $\mathbb Q$-Fano $G$-spherical variety. In this paper we compute the weighed non-Archimedean functionals of a $G$-equivariant normal test configurations of $X$ via combinatory data. Also we define a modified Futaki invariant with respect to the weight $g$, and give an expression in terms of inters

Amogh Joshi, Dario Guevara, Mason Earles

In recent years, deep learning models have become the standard for agricultural computer vision. Such models are typically fine-tuned to agricultural tasks using model weights that were originally fit to more general, non-agricultural datasets. This lack of agriculture-specific fine-tuning potentially increases training time and resource use, and decreases m

Raphaël Millière

Text-guided image generation models can be prompted to generate images using nonce words adversarially designed to robustly evoke specific visual concepts. Two approaches for such generation are introduced: macaronic prompting, which involves designing cryptic hybrid words by concatenating subword units from different languages; and evocative prompting, whic

Jan Pieter Zwart

It is well known that a triangle with side lengths 3, 4 and 5 is right-angled. Euclid was the first to give a formula for generating other right-angled triangles with integer side lengths. In this text, I present a novel algorithm to generate all possible right-angled triangles with integer side lengths, in which the three side lengths have no common divisor

Huajian Huang, Yingshu Chen, Tianjia Zhang, Sai-Kit Yeung

Virtual tour among sparse 360$^\circ$ images is widely used while hindering smooth and immersive roaming experiences. The emergence of Neural Radiance Field (NeRF) has showcased significant progress in synthesizing novel views, unlocking the potential for immersive scene exploration. Nevertheless, previous NeRF works primarily focused on object-centric scena

Afonso Eduardo, Michael U. Gutmann

Bayesian optimization is a methodology for global optimization of unknown and expensive objectives. It combines a surrogate Bayesian regression model with an acquisition function to decide where to evaluate the objective. Typical regression models are given by Gaussian processes with stationary covariance functions. However, these functions are unable to exp

Ralf Ramsauer, Stefan Huber, Konrad Schwarz, Jan Kiszka

On embedded processors that are increasingly equipped with multiple CPU cores, static hardware partitioning is an established means of consolidating and isolating workloads onto single chips. This architectural pattern is suitable for mixed-criticality workloads that need to satisfy both, real-time and safety requirements, given suitable hardware properties.

Matteo Dalla Riva, Gennady Mishuris, Paolo Musolino

In this note, we consider a Robin-type traction problem for a linearly elastic body occupying an infinite periodically perforated domain. After proving the uniqueness of the solution we use periodic elastic layer potentials to show that the solution can be written as the sum of a single layer potential, a constant function and a linear function of the space

Sophie F. Weber, Nicola A. Spaldin

We use a combination of density functional theory and Monte Carlo calculations to calculate the surface magnetization in magnetoelectric $\mathrm{Cr_2O_3}$ at finite temperatures. Such antiferromagnets, lacking both inversion and time-reversal symmetries, are required by symmetry to posses an uncompensated magnetization density on particular surface terminat

Zbigniew Szewczak, Michel Weber

We present and discuss the many results obtained concerning a famous limit theorem, the local limit theorem, which has many interfaces, with Number Theory notably, and for which, in spite of considerable efforts, the question concerning conditions of validity of the local limit theorem, has up to now no satisfactory solution. These results mostly concern suf

Ayoosh Bansal, Anant Kandikuppa, Chien-Ying Chen, Monowar Hasan

System auditing is a powerful tool that provides insight into the nature of suspicious events in computing systems, allowing machine operators to detect and subsequently investigate security incidents. While auditing has proven invaluable to the security of traditional computers, existing audit frameworks are rarely designed with consideration for Real-Time

Dugald Hepburn, Stephen M. West

We explore a Portalino-like model of dark matter and neutrino masses in which right-handed neutrino fields connect gauge neutral operators from the Standard Model and Hidden Sector. Neutrino masses are generated via a seesaw-like mechanism that can explain the light active neutrino masses. The model includes a ``Portalino'' state that connects the two sector

Jose Emilio Labra Gayo

Wikidata is one of the most successful Semantic Web projects. Its underlying Wikibase data model departs from RDF with the inclusion of several features like qualifiers and references, built-in datatypes, etc. Those features are serialized to RDF for content negotiation, RDF dumps and in the SPARQL endpoint. Wikidata adopted the entity schemas namespace usin

Tong Li, Rui-Jia Zhang

The primordial black holes (PBHs) play as a novel source to radiate light elementary particles of energies in the region of a few hundred MeV. We explore the possibility that the axion-like particles (ALPs) with mass less than 1 MeV are produced from PBH evaporation. The absorption of light ALPs in the underground detector targets then induces energetic phot

Paolo Musolino, Gennady Mishuris

We study the asymptotic behavior of the solutions of a boundary value problem for the Laplace equation in a perforated domain in $\mathbb{R}^n$, $n\geq 3$, with a (nonlinear) Robin boundary condition on the boundary of the small hole. The problem we wish to consider degenerates under three aspects: in the limit case the Robin boundary condition may degenerat

Tomáš Pevný, Viliam Lisý, Branislav Bošanský, Petr Somol

Learning from raw data input, thus limiting the need for feature engineering, is a component of many successful applications of machine learning methods in various domains. While many problems naturally translate into a vector representation directly usable in standard classifiers, a number of data sources have the natural form of structured data interchange

Guilherme P. B. Garcia, Carlos H. Grohmann, Lucas P. Soares, Mateus Espadoto

Landslides are destructive and recurrent natural disasters on steep slopes and represent a risk to lives and properties. Knowledge of relict landslides location is vital to understand their mechanisms, update inventory maps and improve risk assessment. However, relict landslide mapping is complex in tropical regions covered with rainforest vegetation. A new

D. Weßmayer, N. Przybilla, K. Butler

Context. B-type supergiants are versatile tools to address various astrophysical topics, ranging from stellar atmospheres over stellar and galactic evolution to the cosmic distance scale. Aims. A hybrid non-LTE approach - line-blanketed model atmospheres computed under the assumption of local thermodynamic equilibrium (LTE) in combination with line formation

Alexander Kozachinskiy

In this paper, we construct a winning condition $W$ over a finite set of colors such that, first, every finite arena has a strategy with 2 states of general memory which is optimal w.r.t.~$W$, and second, there exists no $k$ such that every finite arena has a strategy with $k$ states of chromatic memory which is optimal w.r.t.~$W$.

Kirill Kobialko, Igor Bogush, Dmitri Gal'tsov

We propose a generalization of Claudel, Virbhadra, and Ellis photon surfaces to the case of massive charged particles, considering a timelike hypersurface such that any worldline of a particle with mass $m$, electric charge $q$ and fixed total energy $\mathcal{E}$, initially touching it, will remain in this hypersurface forever. This definition does not dire

Carlo Bono, Mehmet Oğuz Mülâyim, Cinzia Cappiello, Mark Carman

Social media have the potential to provide timely information about emergency situations and sudden events. However, finding relevant information among millions of posts being posted every day can be difficult, and developing a data analysis project usually requires time and technical skills. This study presents an approach that provides flexible support for

Dario A. Leon, Andrea Ferretti, Daniele Varsano, Elisa Molinari

We perform a density functional theory study of the effects of oxygen adsorption on the structural and electronic properties of Gr/Co(0001) and Gr/Co/Ir(111) interfaces. In both interfaces, the graphene-Co distance increases with increasing O concentration. The oxygen intercalation effectively decreases the electronic interaction, preventing the hybridizatio

Alexandros Chatzinikolaou

Given a unital $\boldsymbol{C}^{*}$-algebra $\mathcal{A}$, we prove the existence of the coproduct of two faithful operator $\mathcal{A}$-systems. We show that we can either consider it as a subsystem of an amalgamated free product of $\boldsymbol{C}^{*}$-algebras, or as a quotient by an operator system kernel. We introduce a universal $\boldsymbol{C}^{*}$-a

CMS Collaboration

The charge-parity ($CP$) structure of the Yukawa interaction between the Higgs (H) boson and the top quark is measured in a data sample enriched in the $\mathrm{t\bar{t}}$ and tH associated production, using 138 fb$^{-1}$ of data collected in proton-proton collisions at $\sqrt{s}$ = 13 TeV by the CMS experiment at the CERN LHC. The study targets events where

Yuliya Lierler, Jose F. Morales, Carmine Dodaro, Veronica Dahl

ICLP is the premier international event for presenting research in logic programming. Contributions to ICLP 2022 were sought in all areas of logic programming, including but not limited to: Foundations: Semantics, Formalisms, Nonmonotonic reasoning, Knowledge representation. Languages issues: Concurrency, Objects, Coordination, Mobility, Higher order, Types,

Yannick Kuhn, Hannes Wolf, Arnulf Latz, Birger Horstmann

Physico-chemical continuum battery models are typically parameterized by manual fits, relying on the individual expertise of researchers. In this article, we introduce a computer algorithm that directly utilizes the experience of battery researchers to extract information from experimental data reproducibly. We extend Bayesian Optimization (BOLFI) with Expec

Radek Honzik, Chris Lambie-Hanson, Šárka Stejskalová

We show that $\mathsf{PFA}$ (Proper Forcing Axiom) implies that adding any number of Cohen subsets of $\omega$ will not add an $\omega_2$-Aronszajn tree or a weak $\omega_1$-Kurepa tree, and moreover no $\sigma$-centered forcing can add a weak $\omega_1$-Kurepa tree (a tree of height and size $\omega_1$ with at least $\omega_2$ cofinal branches). This partia

Mohamed Benzaghta, Giovanni Geraci, Rasoul Nikbakht, David Lopez-Perez

With growing interest in integrating terrestrial networks (TNs) and non-terrestrial networks (NTNs) to connect the unconnected, a key question is whether this new paradigm could also be opportunistically exploited to augment service in urban areas. We assess this possibility in the context of an integrated TN-NTN, comprising a ground cellular deployment pair

Hossein A. Kafiabad, Jacques Vanneste

Lagrangian averaging plays an important role in the analysis of wave--mean-flow interactions and other multiscale fluid phenomena. The numerical computation of Lagrangian means, e.g. from simulation data, is however challenging. Typical implementations require tracking a large number of particles to construct Lagrangian time series which are then averaged us

Chung T. Ma, Wei Zhou, Brian J. Kirby, S. Joseph Poon

Interfacial mixing of elements is a well-known phenomenon found in thin film deposition. For thin-film magnetic heterostructures, interfacial compositional inhomogeneities can have drastic effects on the resulting functionalities. As such, care must be taken to characterize the compositional and magnetic properties of thin films intended for device use. Rece

Xufeng Zhao, Cornelius Weber, Muhammad Burhan Hafez, Stefan Wermter

Sound is one of the most informative and abundant modalities in the real world while being robust to sense without contacts by small and cheap sensors that can be placed on mobile devices. Although deep learning is capable of extracting information from multiple sensory inputs, there has been little use of sound for the control and learning of robotic action

Genqian Liu

In this note, by explaining two key methods that were employed in \cite{Liu-21} and by giving some remarks, we show that the proof of Theorem 1.1 in \cite{Liu-21} is a rigorous proof based on theory of strongly continuous semigroups and pseudodifferential operators. All remarks and comments to paper \cite{Liu-21}, which were given by Matteo Capoferri, Leonid

Szilvia Krekic, Mark Mero, Andras Der, Zsuzsanna Heiner

Next-generation communication networks require > Tbit/s single-channel data transfer and processing with sub-picosecond switches and routers at network nodes. Materials enabling ultrafast all-optical switching have high potential to solve the speed limitations of current optoelectronic circuits. Chromoproteins have been shown to exhibit a fast light-controll

Francesco Bajardi, Rocco D'Agostino

In this paper, we consider a gravitational action containing a combination of the Ricci scalar, $R$, and the topological Gauss--Bonnet term, $G$. Specifically, we study the cosmological features of a particular class of modified gravity theories selected by symmetry considerations, namely the $f(R,G)= R^n G^{1-n}$ model. In the context of a spatially flat, h

Xianghui Yang, Guosheng Lin, Luping Zhou

Single-view 3D object reconstruction is a fundamental and challenging computer vision task that aims at recovering 3D shapes from single-view RGB images. Most existing deep learning based reconstruction methods are trained and evaluated on the same categories, and they cannot work well when handling objects from novel categories that are not seen during trai

T. Dam, G. Chalvatzaki, J. Peters, J. Pajarinen

Path planning is a crucial algorithmic approach for designing robot behaviors. Sampling-based approaches, like rapidly exploring random trees (RRTs) or probabilistic roadmaps, are prominent algorithmic solutions for path planning problems. Despite its exponential convergence rate, RRT can only find suboptimal paths. On the other hand, $\textrm{RRT}^*$, a wid

Tobias Runge, Alexander Kittelmann, Marco Servetto, Alex Potanin

In security-critical software applications, confidential information must be prevented from leaking to unauthorized sinks. Static analysis techniques are widespread to enforce a secure information flow by checking a program after construction. A drawback of these systems is that incomplete programs during construction cannot be checked properly. The user is

Martin Monteiro, Cecilia Stari, Arturo C. Marti

We propose a home laboratory in which a telescopic vacuum cleaner pipe and a smartphone are used to investigate sound speed and acoustic resonance. When the pipe is hit or the hands clapped near one end the sound produced is registered by a smartphone. By means of an appropriate application the resonant frequency is obtained. Varying the pipe's length and re

Mark Sendak, Gaurav Sirdeshmukh, Timothy Ochoa, Hayley Premo

The approaches by which the machine learning and clinical research communities utilize real world data (RWD), including data captured in the electronic health record (EHR), vary dramatically. While clinical researchers cautiously use RWD for clinical investigations, ML for healthcare teams consume public datasets with minimal scrutiny to develop new algorith

Fanwei Zhu, Wendong Xiao, Yao Yu, Ziyi Wang

Demand estimation plays an important role in dynamic pricing where the optimal price can be obtained via maximizing the revenue based on the demand curve. In online hotel booking platform, the demand or occupancy of rooms varies across room-types and changes over time, and thus it is challenging to get an accurate occupancy estimate. In this paper, we propos

X. Chen, T. Gehrmann, E. W. N. Glover, M. Höfer

Isolated photon production at hadron colliders proceeds via direct production and fragmentation processes. Theory predictions for the isolated photon and photon-plus-jet cross section often impose idealised photon isolation criteria, eliminating the fragmentation contribution and introducing a systematic uncertainty in the comparison to data. We present NNLO

Quanling Deng, Pouria Behnoudfar, Victor M. Calo

We extend the softFEM idea to isogeometric analysis (IGA) to reduce the stiffness (consequently, the condition numbers) of the IGA discretized problem. We refer to the resulting approximation technique as softIGA. We obtain the resulting discretization by first removing the IGA spectral outliers to reduce the system's stiffness. We then add high-order deriva

Ankit Mishra, Tony J. Puthenpurakal

Let $A=Q/(f)$ where $(Q,\mathfrak{n})$ be a complete regular local ring of dimension $d+1$, $f\in \mathfrak{n}^i\setminus\mathfrak{n}^{i+1}$ for some $i\geq 2$ and $M$ an MCM $A-$module with $e(M)=\mu(M)i(M)+1$ then we prove that depth $G(M)\geq d-1$. If $(A,\mathfrak{m})$ is a complete hypersurface ring of dimension $d$ with infinite residue field and $e(A)

Carlos Vasconcellos, René Zuñiga, Stéphane Job, Francisco Melo

Energy absorbers and energy-harvesting devices have been under the scope of scientists and engineers for decades to fulfill specific technological needs, mainly concerned with sound and vibration absorbers, and efficient mechanical energy converters. In this paper, as a proof of concept, we build a mass-in-mass device to study the response of a linear absorb

Yang Xu, Xiaobao Li, Daniel M. Mulvihill

Persson's theory of contact is extensively used in the study of the purely normal interaction between a nominally flat rough surface and a rigid flat. In the literature, Persson's theory was successfully applied to the elastoplastic contact problem with a scale-independent hardness $H$. However, it yields a closed-form solution, $P(p, \xi)$, in terms of an i

Jesper Nederlof, Céline M. F. Swennenhuis, Karol Węgrzycki

In a classical scheduling problem, we are given a set of $n$ jobs of unit length along with precedence constraints and the goal is to find a schedule of these jobs on $m$ identical machines that minimizes the makespan. This problem is well-known to be NP-hard for an unbounded number of machines. Using standard 3-field notation, it is known as $P|\text{prec},

Guido Agapito, Daniele Vassallo, Cédric Plantet, Jesse Cranney

The MCAO Assisted Visible Imager and Spectrograph (MAVIS) is a new visible instrument for ESO Very Large Telescope (VLT). Its Adaptive Optics Module (AOM) must provide extreme adaptive optics correction level at low galactic latitude and high sky coverage at the galactic pole on the FoV of 30arcsec of its 4k x 4k optical imager and on its monolithic Integral

Guido Agapito, Lorenzo Busoni, Giulia Carlà, Cédric Plantet

The Multiconjugate adaptive Optic Relay For ELT Observations (MORFEO, formerly known as MAORY) is the adaptive optics (AO) module for the Extremely Large Telescope (ELT) aimed at providing a 1 arcmin corrected field to the Multi-AO Imaging CamerA for Deep Observations (MICADO) and to a future client instrument. It should provide resolution close to the diffr

Guido Agapito, Lorenzo Busoni, Giulia Carlà, Cédric Plantet

Laser Guide Star (LGS) Shack-Hartmann (SH) wavefront sensors for next generation Extremely Large Telescopes (ELTs) require low-noise, large format (about 1Mpx), fast detectors to match the need for a large number of subapertures and a good sampling of the very elongated spots. One path envisaged to fulfill this need has been the adoption of CMOS detectors wi

Qihan Yang, Fan Feng, Rosa Chan

With the capacity of continual learning, humans can continuously acquire knowledge throughout their lifespan. However, computational systems are not, in general, capable of learning tasks sequentially. This long-standing challenge for deep neural networks (DNNs) is called catastrophic forgetting. Multiple solutions have been proposed to overcome this limitat

Lorenzo Mercuri, Andrea Perchiazzo, Edit Rroji

In this paper we introduce a new model named CARMA(p,q)-Hawkes process as the Hawkes model with exponential kernel implies a strictly decreasing behaviour of the autocorrelation function and empirically evidences reject the monotonicity assumption on the autocorrelation function. The proposed model is a Hawkes process where the intensity follows a Continuous

Emmanuele Battista, Giampiero Esposito

This paper builds two detailed examples of generalized normal in non-Euclidean spaces, i.e. the hyperbolic and elliptic geometries. In the hyperbolic plane we define a n-sided hyperbolic polygon P, which is the Euclidean closure of the hyperbolic plane H, bounded by n hyperbolic geodesic segments. The polygon P is built by considering the unique geodesic tha

Apostolos Gkatzionis, Eric J. Tchetgen Tchetgen, Jon Heron, Kate Northstone

Selection bias is a common concern in epidemiologic studies. In the literature, selection bias is often viewed as a missing data problem. Popular approaches to adjust for bias due to missing data, such as inverse probability weighting, rely on the assumption that data are missing at random and can yield biased results if this assumption is violated. In obser

Mattia Cerrato, Marius Köppel, Roberto Esposito, Stefan Kramer

Representation learning algorithms offer the opportunity to learn invariant representations of the input data with regard to nuisance factors. Many authors have leveraged such strategies to learn fair representations, i.e., vectors where information about sensitive attributes is removed. These methods are attractive as they may be interpreted as minimizing t

Stefano Bagnulo, John D. Landstreet

The presence of a strong magnetic field is a feature common to a significant fraction of degenerate stars, yet little is understood about field origin and evolution. New observational constraints from volume-limited surveys point to a more complex situation than a single mechanism valid for all stars. We show that in high-mass white dwarfs, which are probabl

Hosesin Esmaeili, Ali Kariminezhad, Aydin Sezgin

{Robust transceiver design against unresolvable system uncertainties is of crucial importance for reliable communication. We consider a MIMO multi-hop system, where the source, the relay, and the destination are equipped with multiple antennas. Further, an intelligent reconfigurable surface (IRS) is established to cancel the RSI as much as possible. The cons

Jean-Thomas Baillargeon, Nicolas Garneau

This paper introduces the Beer2Vec model that allows the most popular alcoholic beverage in the world to be encoded into vectors enabling flavorful recommendations. We present our algorithm using a unique dataset focused on the analysis of craft beers. We thoroughly explain how we encode the flavors and how useful, from an empirical point of view, the beer v

Ashish Kumar, Vasundhra Dahiya, Aditi Sharan

Aspect based sentiment analysis (ABSA) deals with the identification of the sentiment polarity of a review sentence towards a given aspect. Deep Learning sequential models like RNN, LSTM, and GRU are current state-of-the-art methods for inferring the sentiment polarity. These methods work well to capture the contextual relationship between the words of a rev

Tinghui Chen, Shuai Li, Hao Wu

In pace with the electronic technology development and the production technology improvement, industrial robot Give Scope to the Advantage in social services and industrial production. However, due to long-term mechanical wear and structural deformation, the absolute positioning accuracy is low, which greatly hinders the development of manufacturing industry

Sandeep Kaur Kingra, Vivek Parmar, Deepak Verma, Alessandro Bricalli

In this work, we propose a fully-binarized XOR-based IMSS (In-Memory Similarity Search) using RRAM (Resistive Random Access Memory) arrays. XOR (Exclusive OR) operation is realized using 2T-2R bitcells arranged along the column in an array. This enables simultaneous match operation across multiple stored data vectors by performing analog column-wise XOR oper

Thomas Gehrmann, Giovanni Stagnitto

We extend the antenna subtraction method to include hadron fragmentation processes up to next-to-next-to-leading order (NNLO) in QCD in $e^+e^-$ collisions. To handle collinear singularities associated with the fragmentation process, we introduce fragmentation antenna functions in final-final kinematics with associated phase space mappings. These antenna fun

Qilong Pan

Visually evaluating the goodness of generated Multivariate Time Series (MTS) are difficult to implement, especially in the case that the generative model is Generative Adversarial Networks (GANs). We present a general framework named Gaussian GANs to visually evaluate GANs using itself under the MTS generation task. Firstly, we attempt to find the transforma

Hadass S. Inbar, Dai Q. Ho, Shouvik Chatterjee, Mihir Pendharkar

Motivated by observations of extreme magnetoresistance (XMR) in bulk crystals of rare-earth monopnictide (RE-V) compounds and emerging applications in novel spintronic and plasmonic devices based on thin-film semimetals, we have investigated the electronic band structure and transport behavior of epitaxial GdSb thin films grown on III-V semiconductor surface

Wagner C. Sgobbi, Dalton C. Silva, Daniel Vendrúscolo

We say a group $G$ has property $R_\infty$ if the number $R(\varphi)$ of twisted conjugacy classes is infinite for every automorphism $\varphi$ of $G$. For such groups, the $R_\infty$-nilpotency degree is the least integer $c$ such that $G/\gamma_{c+1}(G)$ has property $R_\infty$. In this work, we compute the $R_\infty$-nilpotency degree of all Generalized S

Bonan Li, Yinhan Hu, Xuecheng Nie, Congying Han

In this paper, we focus on analyzing and improving the dropout technique for self-attention layers of Vision Transformer, which is important while surprisingly ignored by prior works. In particular, we conduct researches on three core questions: First, what to drop in self-attention layers? Different from dropping attention weights in literature, we propose