June 2022 arXiv papers — page 4

Elizabeth J Cross, Samuel J Gibson, Matthew R Jones, Daniel J Pitchforth

The use of machine learning in Structural Health Monitoring is becoming more common, as many of the inherent tasks (such as regression and classification) in developing condition-based assessment fall naturally into its remit. This chapter introduces the concept of physics-informed machine learning, where one adapts ML algorithms to account for the physical

Florian Euchner, Marc Gauger, Sebastian Dörner, Stephan ten Brink

A distributed massive MIMO channel sounder for acquiring large CSI datasets, dubbed DICHASUS, is presented. The measured data has potential applications in the study of various machine learning algorithms for user localization, JCAS, channel charting, enabling massive MIMO in FDD operation, and many others. The proposed channel sounder architecture is distin

Philip Dittmann, Franziska Jahnke, Lothar Sebastian Krapp, Salma Kuhlmann

We study the definability of convex valuations on ordered fields, with a particular focus on the distinguished subclass of henselian valuations. In the setting of ordered fields, one can consider definability both in the language of rings $\mathcal{L}_{\mathrm{r}}$ and in the richer language of ordered rings $\mathcal{L}_{\mathrm{or}}$. We analyse and compar

Shashank Kumar Ranu, Daniel D. Stancil

Excited states of spin-chains play an important role in condensed matter physics. We present a method of calculating the single magnon excited states of the Heisenberg spin-chain that can be efficiently implemented on a quantum processor for small spin chains. Our method involves finding the stationary points of the energy vs wavenumber curve. We implement o

B. Ali, M. A. Jada, M. M. Zubairu

Let $\mathcal{CP}_n$ be the semigroup of partial contraction mappings on $[n]=\{1,2,\ldots,n\}$ and let $\mathcal{OCP}_n$ and $\mathcal{ORCP}_n$ be its subsemigroups consisting of all order-preserving and of all order-preserving or order-reversing, partial contraction mappings, respectively. In this paper we obtain the rank of the two semigroups, $\mathcal{O

Johannes Pankert, Giorgio Valsecchi, Davide Baret, Jon Zehnder

A robotic platform for mobile manipulation needs to satisfy two contradicting requirements for many real-world applications: A compact base is required to navigate through cluttered indoor environments, while the support needs to be large enough to prevent tumbling or tip over, especially during fast manipulation operations with heavy payloads or forceful in

Utkarsh Jain, Devaraj van der Meer

Wave slamming onto a structure is often accompanied by the entrapment of an air pocket. A large scale impact typically has a rapidly evolving and disturbed liquid-gas interface, such that several bubbles are entrapped upon impact. While it is largely understood how the peak pressure is created by liquid coming into contact with the solid structure, it is mor

Katharina Bendig, René Schuster, Didier Stricker

In recent years, deep neural networks showed their exceeding capabilities in addressing many computer vision tasks including scene flow prediction. However, most of the advances are dependent on the availability of a vast amount of dense per pixel ground truth annotations, which are very difficult to obtain for real life scenarios. Therefore, synthetic data

Hamid Al-Jibbouri

The dynamics of weakly interacting three-dimensional Bose-Einstein condensates (BECs), trapped in external axially symmetric plus anharmonic distortion potential are studied. Within a variational approach and time-dependent Gross-Pitaevskii equation, the coupled condensate width equations are derived. By modulating anharmonic distortion of the trapping poten

Linlin Zhong, Bingyu Wu, Yifan Wang

Plasma simulation is an important and sometimes only approach to investigating plasma behavior. In this work, we propose two general AI-driven frameworks for low-temperature plasma simulation: Coefficient-Subnet Physics-Informed Neural Network (CS-PINN) and Runge-Kutta Physics-Informed Neural Network (RK-PINN). The CS-PINN uses either a neural network or an

Zeinab Akhlaghi

In the recent paper [A generalization of Taketa's theorem on M-groups, Quaestiones Mathematicae, (2022), https://doi.org/10.2989/16073606.2022.2081632], we give an upper bound 5/2 for the average of non-monomial character degrees of a finite group G, denoted by acdnm(G), which guarantees the solvability of G. Although the result is true, the example we gave

Huangjun Zhu, Yunting Li, Tianyi Chen

Ground states of local Hamiltonians are of key interest in many-body physics and also in quantum information processing. Efficient verification of these states are crucial to many applications, but very challenging. Here we propose a simple, but powerful recipe for verifying the ground states of general frustration-free Hamiltonians based on local measuremen

Sasan Matinfar, Mehrdad Salehi, Daniel Suter, Matthias Seibold

Despite the undeniable advantages of image-guided surgical assistance systems in terms of accuracy, such systems have not yet fully met surgeons' needs or expectations regarding usability, time efficiency, and their integration into the surgical workflow. On the other hand, perceptual studies have shown that presenting independent but causally correlated inf

T. Patsahan, O. Pizio

We explore clustering of curcumin molecules in water by using the OPLS-UA model for the enol conformer of curcumin (J. Mol. Liq., 223, 707, 2016) and the SPC-E water model. With this purpose, solutions of 2, 4, 8, 12, 16 and 20 curcumin molecules in 3000 water molecules are studied by using extensive molecular dynamics computer simulations. Radial distributi

Rebecca Fair, Adam Jackson, David Voneshen, Dominik Jochym

Interpretation of vibrational inelastic neutron scattering spectra of complex systems is frequently reliant on accompanying simulations from theoretical models. Ab-initio codes can routinely generate force constants, but additional steps are required for direct comparison to experimental spectra. On modern spectrometers this is a computationally expensive ta

Markus Nötzold, Robert Wild, Christine Lochmann, Roland Wester

A prerequisite for laser cooling a molecular anion, which has not been achieved so far, is the precise knowledge of the relevant transition frequencies in the cooling scheme. To determine these frequencies we present a versatile method that uses one pump and one photodetachment light beam. We apply this approach to C$_{2}^{-}$ and study the laser cooling tra

Rocco Duvenhage, Samuel Skosana, Machiel Snyman

We develop a general approach to setting up and studying classes of quantum dynamical systems close to and structurally similar to systems having specified properties, in particular detailed balance. This is done in terms of transport plans and Wasserstein distances between systems on possibly different observable algebras.

Manuela Magliocchetti

Despite their relative sparseness, during the recent years it has become more and more clear that extragalactic radio sources (both AGN and star-forming galaxies) constitute an extremely interesting mix of populations, not only because of their intrinsic value, but also for their fundamental role in shaping our Universe the way we see it today. Indeed, radio

Steven Michiels, Cédric De Schryver, Lynn Houthuys, Frederik Vogeler

Machine learning (ML) may improve and automate quality control (QC) in injection moulding manufacturing. As the labelling of extensive, real-world process data is costly, however, the use of simulated process data may offer a first step towards a successful implementation. In this study, simulated data was used to develop a predictive model for the product q

Francesco Di Marcantonio, Massimiliano Incudini, Davide Tezza, Michele Grossi

Exploiting the properties of quantum information to the benefit of machine learning models is perhaps the most active field of research in quantum computation. This interest has supported the development of a multitude of software frameworks (e.g. Qiskit, Pennylane, Braket) to implement, simulate, and execute quantum algorithms. Most of them allow us to defi

Sarah J. Gascoigne, Leonard Waldmann, Mariella Panagiotopoulou, Fahmida Chowdhury

Purpose: Understanding fluctuations of seizure severity within individuals is important for defining treatment outcomes and response to therapy, as well as developing novel treatments for epilepsy. Current methods for grading seizure severity rely on qualitative interpretations from patients and clinicians. Quantitative measures of seizure severity would com

Taha Emre, Arunava Chakravarty, Antoine Rivail, Sophie Riedl

Recent contrastive learning methods achieved state-of-the-art in low label regimes. However, the training requires large batch sizes and heavy augmentations to create multiple views of an image. With non-contrastive methods, the negatives are implicitly incorporated in the loss, allowing different images and modalities as pairs. Although the meta-information

Evan Grohs, Sherwood Richers, Sean M. Couch, Francois Foucart

The flavor evolution of neutrinos in core collapse supernovae and neutron star mergers is a critically important unsolved problem in astrophysics. Following the electron flavor evolution of the neutrino system is essential for calculating the thermodynamics of compact objects as well as the chemical elements they produce. Accurately accounting for flavor tra

Jean-Christophe Pain

Although many series exist for $\pi$ and $\pi^2$, very few are known for $\pi^3$. In this article, we derive, using a trigonometric identity obtained by Euler, two representations of $\pi^3$ involving infinite sums and the golden ratio. The methodology can be generalized in order to obtain further series, relating by the way $\pi^3$ to other mathematical con

Piyush Singh, Anikesh Pal, Narinder Singh

The impact of a heavier droplet into a deep pool of lighter liquid is investigated using three-dimensional numerical simulations. Unprecedented to any numerical simulations, we demonstrate that the heavier droplets can hang from the surface of a lighter liquid using surface tension. The impact phenomenon and the evolution of the heavier droplet as a function

Jeffrey Wrighton, Angel Albavera-Mata, Hector Francisco Rodriguez, Tun S. Tan

Though calculations based on density functional theory (DFT) are used remarkably widely in chemistry, physics, materials science, and biomolecular research and though the modern form of DFT has been studied for almost 60 years, some mathematical problems remain. For context, we provide an outline of the basic structure of DFT, then pose several questions reg

Charlotte Dietze, Jinyeop Lee

We consider a gas of weakly interacting bosons in three dimensions subject to an external potential in the mean field regime. Assuming that the initial state of our system is a product state, we show that in the trace topology of one-body density matrices, the dynamics of the system can be described by the solution to the corresponding Hartree type equation.

Denis Simon, Lea Terracini

An algebraic integer is said large if all its real or complex embeddings have absolute value larger than $1$. An integral ideal is said \emph{large} if it admits a large generator. We investigate the notion of largeness, relating it to some arithmetic invariants of the field involved, such as the regulator and the covering radius of the lattice of units. We

Jun Wang, Fei Xue

In 1933, Borsuk made a conjecture that every $n$-dimensional bounded set can be divided into $n+1$ subsets of smaller diameter. Up to now, the problem is still open for $4\leq n\leq 63$. In this paper, we firstly discuss the Banach-Mazur distance between the $n$-dimensional cube and the $\ell_{p}$ ball $(1\leq p< 2)$, then we study the generalized Borsuk's p

Kyle Kastner, Aaron Courville

This paper introduces R-MelNet, a two-part autoregressive architecture with a frontend based on the first tier of MelNet and a backend WaveRNN-style audio decoder for neural text-to-speech synthesis. Taking as input a mixed sequence of characters and phonemes, with an optional audio priming sequence, this model produces low-resolution mel-spectral features w

Ruochen Li, Stamos Katsigiannis, Hubert P. H. Shum

Trajectory prediction of road users in real-world scenarios is challenging because their movement patterns are stochastic and complex. Previous pedestrian-oriented works have been successful in modelling the complex interactions among pedestrians, but fail in predicting trajectories when other types of road users are involved (e.g., cars, cyclists, etc.), be

Joona Pohjonen, Carolin Stürenberg, Atte Föhr, Reija Randen-Brady

Deep neural networks have achieved impressive performance in a wide variety of medical imaging tasks. However, these models often fail on data not used during training, such as data originating from a different medical centre. How to recognize models suffering from this fragility, and how to design robust models are the main obstacles to clinical adoption. H

Jesse van Oostrum, Johannes Müller, Nihat Ay

The natural gradient field is a vector field that lives on a model equipped with a distinguished Riemannian metric, e.g. the Fisher-Rao metric, and represents the direction of steepest ascent of an objective function on the model with respect to this metric. In practice, one tries to obtain the corresponding direction on the parameter space by multiplying th

Pascal Pernot

Confidence curves are used in uncertainty validation to assess how large uncertainties ($u_{E}$) are associated with large errors ($E$). An oracle curve is commonly used as reference to estimate the quality of the tested datasets. The oracle is a perfect, deterministic, error predictor, such as $|E|=\pm u_{E}$, which corresponds to a very unlikely error dist

Shunya Saito

The Grothendieck monoid of an exact category is a monoid version of the Grothendieck group. We use it to classify Serre subcategories of an exact category and to reconstruct the topology of a noetherian scheme. We first construct bijections between (i) the set of Serre subcategories of an exact category, (ii) the set of faces of its Grothendieck monoid, and

T. C. Rebocho, M. Tasinkevych, C. S. Dias

Active colloids belong to a class of non-equilibrium systems where energy uptake, conversion and dissipation occurs at the level of individual colloidal particles, which can lead to particles self-propelled motion and surprising collective behavior. Examples include coexistence of vapor and liquid-like steady states for active particles with repulsive intera

Li Meng, Morten Goodwin, Anis Yazidi, Paal Engelstad

Transformers are neural network models that utilize multiple layers of self-attention heads and have exhibited enormous potential in natural language processing tasks. Meanwhile, there have been efforts to adapt transformers to visual tasks of machine learning, including Vision Transformers and Swin Transformers. Although some researchers use Vision Transfor

Jiaqi Tang, Zhaoyang Liu, Jing Tan, Chen Qian

Generic event boundary detection (GEBD) is an important yet challenging task in video understanding, which aims at detecting the moments where humans naturally perceive event boundaries. In this paper, we present a local context modeling and global boundary decoding approach for GEBD task. Local context modeling sub-network is proposed to perceive diverse pa

Randa Herzallah, Abdessamad Belfakir

A new control method that considers all sources of uncertainty and noises that might affect the time evolutions of quantum physical systems is introduced. Under the proposed approach, the dynamics of quantum systems are characterised by probability density functions (pdfs), thus providing a complete description of their time evolution. Using this probabilist

Taika Okuda, Akifumi Sako

We give a complex two-dimensional noncommutative locally symmetric K\"{a}hler manifold via a deformation quantization with separation of variables. We present an explicit formula of its star product by solving the system of recurrence relations given by Hara-Sako. In the two-dimensional case, this system of recurrence relations gives two types of equations c

Iris Abt, Christopher Gooch, Felix Hagemann, Lukas Hauertmann

Events from alpha interactions on the surfaces of germanium detectors are a major contribution to the background in germanium-based searches for neutrinoless double-beta decay. Surface events are subject to charge trapping, affecting their pulse shape and reconstructed energy. A study of alpha events on the passivated end-plate of a segmented true-coaxial n-

Filippo Pallotta

The aim of this thesis is to bridge the gap between the world of physics research and secondary education on contemporary quantum physics. We fostered the creation of a generative learning environment formed by quantum physics researchers, high school physics teachers and student. The result was the development of an teaching approach to the core ideas of qu

Yoji Yamato

To use heterogeneous hardware, programmers needed sufficient technical skills such as OpenMP, CUDA, and OpenCL. Therefore, I have proposed environment-adaptive software that enables high-performance operation by automatically converting and configuring the code once written, and have been working on automatic conversion and proper placement. However, until n

Chi-Hsien Tai, Sayid Mondal, Wen-Yu Wen

We study the boundary CFT under supertranslation in terms of the AdS/CFT correspondence. In particular, we probe the soft hair BTZ background by several open string configurations as follows. The Ryu-Takayanaki formula of holographic entanglement remains intact under supertranslation. The U-shape string probe indicates that the flat part of meson potential i

Jan Skolimowski

To determine the impact of including edge states on the phase diagram of a spinless Falicov-Kimball model (FKM) on the Haldane lattice, a study of a corresponding ribbon geometry with zigzag edges is conducted. By varying the ribbon widths, the distinction between the effects connected to the mere presence of the edges and those originating from interference

S. V. Mousavi, S. Miret-Artes

In this review we deal with open (dissipative and stochastic) quantum systems within the Bohmian mechanics framework which has the advantage to provide a clear picture of quantum phenomena in terms of trajectories, originally in configuration space. The gradual decoherence process is studied from linear and nonlinear Schr\"odinger equations through Bohmian t

A. S. Vdovych, I. R. Zachek, R. R. Levitskii

Based on the pseudospin model of the deformed CsH$_2$PO$_4$ crystal within the Glauber method, the equation for the time-dependent mean value of the pseudospin is obtained, which is solved in the case of small deviations from the equilibrium state. Using the solution of the equation, we find expressions for the longitudinal dynamic dielectric constant and re

Hongrui Cai, Wanquan Feng, Xuetao Feng, Yan Wang

We propose Neural-DynamicReconstruction (NDR), a template-free method to recover high-fidelity geometry and motions of a dynamic scene from a monocular RGB-D camera. In NDR, we adopt the neural implicit function for surface representation and rendering such that the captured color and depth can be fully utilized to jointly optimize the surface and deformatio

Chunhua Zhang, Lian-Ping Wang, Hong Liang, Zhaoli Guo

In this paper, we proposed a central moment discrete unified gas-kinetic scheme (DUGKS) for multiphase flows with large density ratio and high Reynolds number. Two sets of kinetic equations with central-moment-based multiple relaxation time collision operator are employed to approximate the incompressible Navier-Stokes equations and a conservative phase fiel

Keiko I. Nagao, Takaaki Nomura, Hiroshi Okada

We consider an explanation of CDF II W bosom mass anomaly by $Z-Z'$ mixing with $U(1)_R$ gauge symmetry under which right-handed fermions are charged. It is found that $U(1)_R$ is preferred to be leptophobic to accommodate the anomaly while avoiding other experimental constraints. In such a case we require extra charged leptons to cancel quantum anomalies an

Yuehao Wang, Yonghao Long, Siu Hin Fan, Qi Dou

Reconstruction of the soft tissues in robotic surgery from endoscopic stereo videos is important for many applications such as intra-operative navigation and image-guided robotic surgery automation. Previous works on this task mainly rely on SLAM-based approaches, which struggle to handle complex surgical scenes. Inspired by recent progress in neural renderi

Haoran Dou, Luyi Han, Yushuang He, Jun Xu

Tumor infiltration of the recurrent laryngeal nerve (RLN) is a contraindication for robotic thyroidectomy and can be difficult to detect via standard laryngoscopy. Ultrasound (US) is a viable alternative for RLN detection due to its safety and ability to provide real-time feedback. However, the tininess of the RLN, with a diameter typically less than 3mm, po

Adam Ó Conghaile

Constraint satisfaction (CSP) and structure isomorphism (SI) are among the most well-studied computational problems in Computer Science. While neither problem is thought to be in $\texttt{PTIME},$ much work is done on $\texttt{PTIME}$ approximations to both problems. Two such historically important approximations are the $k$-consistency algorithm for CSP and

Sudhansu S. Biswal, Sushree S. Mishra, K. Sridhar

In a previous paper, we had modified Non-Relativistic QCD as it applies to quarkonium production by taking into account the effect of perturbative soft-gluon emission from the colour-octet quarkonium states. We tested the model by fitting the unknown non-perturbative parameter in the model from Tevatron data and using that to make parameter-free predictions

Allen Ibiapina, Raul Lopes, Andrea Marino, Ana Silva

A (directed) temporal graph is a (directed) graph whose edges are available only at specific times during its (discretized) lifetime $\tau$. In this setting, we ask that walks respect the temporal aspect by defining $\textit{temporal walks}$ as sequences of adjacent edges whose appearing times are either strictly increasing or non-decreasing (here called non

João Saraiva, Carlos Alemparte, Daniel Belver, Alberto Blanco

Large Resistive Plate Chamber systems have their roots in High Energy Physics experiments at the European Organization for Nuclear Research: ATLAS, CMS and ALICE, where hundreds of square meters of both trigger and timing RPCs have been deployed. These devices operate with complex gas systems, equipped with re-circulation and purification units, which requir

Volker Branding

In this article we study $p$-biharmonic curves as a natural generalization of biharmonic curves. In contrast to biharmonic curves $p$-biharmonic curves do not need to have constant geodesic curvature if $p=\frac{1}{2}$ in which case their equation reduces to the one of $\frac{1}{2}$-elastic curves. We will classify $\frac{1}{2}$-biharmonic curves on closed s

Shahar Mahpod, Noam Gaash, Hay Hoffman, Gil Ben-Artzi

We introduce a novel approach for gait transfer from unconstrained videos in-the-wild. In contrast to motion transfer, the objective here is not to imitate the source's motions by the target, but rather to replace the walking source with the target, while transferring the target's typical gait. Our approach can be trained only once with multiple sources and

Andrzej Dragan, Artur Ekert

We refute criticisms by Del Santo and Horvat towards our paper "Quantum principle of relativity": most of their counterarguments can be dismissed, and the rest provides further evidence to our claims.

L. London, S. A. Hughes

The estimation of a physical system's normal modes is a fundamental problem in physics. The quasi-normal modes of perturbed Kerr black holes, with their related spheroidal harmonics, are key examples, and have diverse applications in gravitational wave theory and data analysis. Recently, it has been shown that \textit{adjoint}-spheroidal harmonics and the re

Barbara Kaltenbacher, Mostafa Meliani, Vanja Nikolić

In this work, we investigate a class of quasilinear wave equations of Westervelt type with, in general, nonlocal-in-time dissipation. They arise as models of nonlinear sound propagation through complex media with anomalous diffusion of Gurtin--Pipkin type. Aiming at minimal assumptions on the involved memory kernels -- which we allow to be weakly singular --

Bavo D. C. Campo, Katrien Antonio

Actuaries use predictive modeling techniques to assess the loss cost on a contract as a function of observable risk characteristics. State-of-the-art statistical and machine learning methods are not well equipped to handle hierarchically structured risk factors with a large number of levels. In this paper, we demonstrate the data-driven construction of an in

Patrick Kaspar, Fabian Munkes, Philipp Neufeld, Lea Ebel

We report on Doppler-free continuous-wave optical UV-spectroscopy resolving the hyperfine structure of the $\mathrm{A}\,^2\Sigma^+ \leftarrow \mathrm{X}\,^2\Pi_{3/2}$ transition in nitric oxide for total angular momenta $J_X=1.5-19.5$ on the $\mathrm{oP_{12ee}}$ branch. The resulting line splittings are compared to calculated splittings and fitted determinin

Salma Salimi, Paola Torrico Morón, Jorge Peña Queralta, Tomi Westerlund

In recent years, multi-robot systems have received increasing attention from both industry and academia. Besides the need of accurate and robust estimation of relative localization, security and trust in the system are essential to enable wider adoption. In this paper, we propose a framework using Hyperledger Fabric for multi-robot collaboration in industria

Taehyeon Kim, Namgyu Ho, Donggyu Kim, Se-Young Yun

Precipitation forecasting is an important scientific challenge that has wide-reaching impacts on society. Historically, this challenge has been tackled using numerical weather prediction (NWP) models, grounded on physics-based simulations. Recently, many works have proposed an alternative approach, using end-to-end deep learning (DL) models to replace physic

Davide Lombardo, Matteo Verzobio

Let $\ell$ be a prime number. We classify the subgroups $G$ of $\operatorname{Sp}_4(\mathbb{F}_\ell)$ and $\operatorname{GSp}_4(\mathbb{F}_\ell)$ that act irreducibly on $\mathbb{F}_\ell^4$, but such that every element of $G$ fixes an $\mathbb{F}_\ell$-vector subspace of dimension 1. We use this classification to prove that the local-global principle for iso

Jesús Arjona Martínez, Ryan A. Parker, Kevin C. Chen, Carola M. Purser

Tin-vacancy centers in diamond are promising spin-photon interfaces owing to their high quantum-efficiency, large Debye-Waller factor, and compatibility with photonic nanostructuring. Benchmarking their single-photon indistinguishability is a key challenge for future applications. Here, we report the generation of single photons with $99.7^{+0.3}_{-2.5}\%$ p

Per Kristian Lehre

Co-evolutionary algorithms have a wide range of applications, such as in hardware design, evolution of strategies for board games, and patching software bugs. However, these algorithms are poorly understood and applications are often limited by pathological behaviour, such as loss of gradient, relative over-generalisation, and mediocre objective stasis. It i

Alexandros Efstratiou, Emiliano De Cristofaro

Previous work suggests that people's preference for different kinds of information depends on more than just accuracy. This could happen because the messages contained within different pieces of information may either be well-liked or repulsive. Whereas factual information must often convey uncomfortable truths, misinformation can have little regard for vera

Silvia Sellán, Alec Jacobson

We introduce a statistical extension of the classic Poisson Surface Reconstruction algorithm for recovering shapes from 3D point clouds. Instead of outputting an implicit function, we represent the reconstructed shape as a modified Gaussian Process, which allows us to conduct statistical queries (e.g., the likelihood of a point in space being on the surface

Yahav Alon

Denote by $r_g(G,\mathcal{H})$ the global resilience of a graph $G$ with respect to Hamiltonicity. That is, $r_g(G,\mathcal{H})$ is the minimal $r$ for which there exists a subgraph $H\subseteq G$ with $r$ edges, such that $G\setminus H$ is not Hamiltonian. We show that if $p$ is above the Hamiltonicity threshold and $G\sim G(n,p)$ then, with high probabilit

Konstantin Osetrin, Evgeny Osetrin, Elena Osetrina

For the gravitational wave model based on the type III Shapovalov wave space-time, test particle trajectories and the exact solution of geodesic deviation equations for the Bianchi type VII universe are obtained. Based on the found 4-vector of deviation, tidal accelerations in a gravitational wave are calculated. For the obtained solution in a privileged coo

LHCb collaboration

Many new exotic hadrons, that do not fit into the existing naming scheme for hadrons, have been discovered over the past few years. A new scheme is set out, extending the existing protocol, in order to provide a consistent naming convention for these newly discovered states, and other new hadrons that may be discovered in future.

Rebecca E. J. Allen, Holly V. Gibbons, Alex M. Sherlock, Harvey R. M. Stanfield

The Rice-Mele model has two topological and spatially-inversion symmetric phases, namely the Su-Schrieffer-Heeger (SSH) phase with alternating hopping only, and the charge-density-wave (CDW) phase with alternating energies only. The chiral symmetry of the SSH phase is robust in position space, so that it is preserved in the presence of the ends of a finite s

ATLAS Collaboration

This paper presents a measurement of fiducial and differential cross-sections for $W^{+}W^{-}$ production in proton-proton collisions at $\sqrt{s}=13$ TeV with the ATLAS experiment at the Large Hadron Collider using a dataset corresponding to an integrated luminosity of 139 fb$^{-1}$. Events with exactly one electron, one muon and no hadronic jets are studie

Yasuhiro Oki

We prove that any integer power of $2$ can be realized as the Tamagawa number of a torus attached to a CM algebra considered by Guo Sheu Yu and Liang Yang Yu. Such a result is obtained by Liang Yang Yu under assuming "a generalized Landau conjecture". The main contribution of this paper is to remove the above assumption.

Thibaut Arnoulx de Pirey, Guy Bunin

Models of many-species ecosystems, such as the Lotka-Volterra and replicator equations, suggest that these systems generically exhibit near-extinction processes, where population sizes go very close to zero for some time before rebounding, accompanied by a slowdown of the dynamics (aging). Here, we investigate the connection between near-extinction and aging

Amin Rasekh, Ian Eisenberg

Natural language generation models are computer systems that generate coherent language when prompted with a sequence of words as context. Despite their ubiquity and many beneficial applications, language generation models also have the potential to inflict social harms by generating discriminatory language, hateful speech, profane content, and other harmful

Jack Tacchi, Chiara Boldrini, Andrea Passarella, Marco Conti

The Ego Network Model (ENM) describes how individuals organise their social relations in concentric circles (typically five) of decreasing intimacy, and it has been found almost ubiquitously in social networks, both offline and online. The ENM gauges the tie strength between peers in terms of interaction frequency, which is easy to measure and provides a goo

Belle II Collaboration, F. Abudinén, L. Aggarwal, H. Ahmed

An absolute measurement of the $\Lambda^{+}_c$ lifetime is reported using $\Lambda_c^+\rightarrow pK^-\pi^+$ decays in events reconstructed from data collected by the Belle II experiment at the SuperKEKB asymmetric-energy electron-positron collider. The total integrated luminosity of the data sample, which was collected at center-of-mass energies at or near

Takeru Asaka, Tsukasa Ishibashi, Shunsuke Kano

We introduce a cluster algebraic generalization of Thurston's earthquake map for the cluster algebras of finite type, which we call the \emph{cluster earthquake map}. It is defined by gluing exponential maps, which is modeled after the earthquakes along ideal arcs. We prove an analogue of the earthquake theorem, which states that the cluster earthquake map g

Tomáš Peitl, Stefan Szeider

Hitting formulas, introduced by Iwama, are an unusual class of propositional CNF formulas. Not only is their satisfiability decidable in polynomial time, but even their models can be counted in closed form. This stands in stark contrast with other polynomial-time decidable classes, which usually have algorithms based on backtracking and resolution and for wh

D. Tseluiko, N. S. Alharthi, R. Barros, K. R. Khusnutdinova

Oceanic internal waves often have curvilinear fronts and propagate over various currents. We present the first study of long weakly-nonlinear internal ring waves in a three-layer fluid in the presence of a background linear shear current. The leading order of this theory leads to the angular adjustment equation - a nonlinear first-order differential equation

Igor Danilkin, Volodymyr Biloshytskyi, Xiu-Lei Ren, Marc Vanderhaeghen

In this paper, we present an improved parameterization of the elastic scattering of spin-0 particles, which is based on a dispersive representation for the inverse scattering amplitude. Besides being based on well known general principles, the requirement that the inverse amplitude should satisfy the dispersion relation significantly constrains its possible

Usama Yaseen, Stefan Langer

This paper presents our findings from participating in the multilingual acronym extraction shared task SDU@AAAI-22. The task consists of acronym extraction from documents in 6 languages within scientific and legal domains. To address multilingual acronym extraction we employed BiLSTM-CRF with multilingual XLM-RoBERTa embeddings. We pretrained the XLM-RoBERTa

E. Cavalcanti, A. P. C. Malbouisson

We present an alternative route to investigate quantum forces in a cavity, for both a free scalar field and a free fermionic field. Considering a generalized Matsubara procedure, we compute the quantum pressure on the boundaries of a compactified space in a thermal bath. Also, considering both periodic and antiperiodic boundary conditions in the cavity, we d

Alexander Lerch

The three packages libACA, pyACA, and ACA-Code provide reference implementations for basic approaches and algorithms for the analysis of musical audio signals in three different languages: C++, Python, and Matlab. All three packages cover the same algorithms, such as extraction of low level audio features, fundamental frequency estimation, as well as simple

Matti Pouke, Evan G. Center, Alexis P. Chambers, Sakaria Pouke

In this study we investigated the effect of body ownership illusion-based body scaling on physics plausibility in Virtual Reality (VR). Our interest was in examining whether body ownership illusion-based body scaling could affect the plausibility of rigid body dynamics similarly to altering VR users' scale by manipulating their virtual interpupillary distanc

Sergio Naval Marimont, Giacomo Tarroni

U-Net has been the go-to architecture for medical image segmentation tasks, however computational challenges arise when extending the U-Net architecture to 3D images. We propose the Implicit U-Net architecture that adapts the efficient Implicit Representation paradigm to supervised image segmentation tasks. By combining a convolutional feature extractor with

C. D. Parmee, K. E. Ballantine, J. Ruostekoski

We demonstrate the presence of an optical phase transition with frustration-induced spontaneous symmetry breaking in a triangular planar atomic array due to cooperative light-mediated interactions. We show how the array geometry of triangle unit cells at low light intensities leads to degenerate collective radiative excitations forming nearly flat bands. We

Kamel Lahouel, Michael Wells, Victor Rielly, Ethan Lew

Learning nonparametric systems of Ordinary Differential Equations (ODEs) dot x = f(t,x) from noisy data is an emerging machine learning topic. We use the well-developed theory of Reproducing Kernel Hilbert Spaces (RKHS) to define candidates for f for which the solution of the ODE exists and is unique. Learning f consists of solving a constrained optimization

Şeyda Şen, Reynier F. Peletier, Alexandre Vazdekis

We perform a detailed study of the stellar populations in a sample of massive Fornax dwarf galaxies using a set of newly defined line indices. Using data from the Integral field spectroscopic data, we study abundance ratios of eight dEs with stellar mass ranging from 10$^8$ to 10$^{9.5}$ M$_\odot$ in the Fornax cluster. We present the definitions of a new se

Di Wang

In this note, we investigate a kind of double centralizer property for general linear supergroups. For the super space $V=\mathbb{K}^{m\mid n}$ over an algebraically closed field $\mathbb{K}$ whose characteristic is not equal to $2$, we consider its $\mathbb{Z}_2$-homogeneous one-dimensional extension $\underline V=V\oplus\mathbb{K}v$, and the natural action

A. L. Khoroshilov, K. M. Krasikov, A. N. Azarevich, A. V. Bogach

A detailed study of charge transport in the paramagnetic phase of Ho0.8Lu0.2B12 strongly correlated antiferromagnet was carried out at temperatures 1.9-300 K in magnetic fields up to 80 kOe. Four mono-domain single crystals with different orientation of normal vectors to the lateral surface of Ho0.8Lu0.2B12 samples were investigated in order to establish the

Junior Costa de Jesus, Victor Augusto Kich, Alisson Henrique Kolling, Ricardo Bedin Grando

Reinforcement Learning (RL) has presented an impressive performance in video games through raw pixel imaging and continuous control tasks. However, RL performs poorly with high-dimensional observations such as raw pixel images. It is generally accepted that physical state-based RL policies such as laser sensor measurements give a more sample-efficient result

Vitaly Zuevsky

Electronic voting consistently fails to supplant conventional paper ballot due to a plethora of security shortcomings. Not only are traditional voting methods mediocre in terms of convenience and interface, they also encompass principal-agent problem, where the state may have vested interest in the outcome of the ballot. Electronic voting protocol using cryp

Parnashree Ghosh, Neena Gupta

Let $k$ be a field, $m$ a positive integer, $\mathbb{V}$ an affine subvariety of $\mathbb{A}^{m+3}$ defined by a linear relation of the form $x_{1}^{r_{1}}\cdots x_{m}^{r_{m}}y=F(x_{1}, \ldots , x_{m},z,t)$, $A$ the coordinate ring of $\mathbb{V}$ and $G= X_1^{r_1}\cdots X_m^{r_m}Y-F(X_1, \dots, X_m,Z,T)$. In \cite{com}, the second author had studied the cas

Alessandro Lanteri, Samantha Leorato, Jesús López-Fidalgo, Chiara Tommasi

We consider the problem of designing experiments to detect the presence of a specified heteroscedastity in a non-linear Gaussian regression model. In this framework, we focus on the ${\rm D}_s$- and KL-criteria and study their relationship with the noncentrality parameter of the asymptotic chi-squared distribution of a likelihood-based test, for local altern

Tomislav Gužvić, Borna Vukorepa

Let $E/\mathbb{Q}$ be an elliptic curve and $p \in \{5,7,11 \}$ be a prime. We determine the possibilities for $E(\mathbb{Q}(\zeta_{p}))_{tors}$. Additionally, we determine all the possibilities for $E(\mathbb{Q}(\zeta_{16}))_{tors}$ and $E(\mathbb{Q}(\zeta_{27}))_{tors}$. Using these results we are able to determine the possibilities for $E(\mathbb{Q}(\mu_{

H. Hirvonen, K. J. Eskola, H. Niemi

We extend the applicability of the hydrodynamics, perturbative QCD and saturation -based EKRT (Eskola-Kajantie-Ruuskanen-Tuominen) framework for ultrarelativistic heavy-ion collisions to peripheral collisions by introducing dynamical freeze-out conditions. As a new ingredient compared to the previous EKRT computations we also introduce a non-zero bulk viscos