May 2023 arXiv papers — page 169

Jonas Hein, Nicola Cavalcanti, Daniel Suter, Lukas Zingg

State-of-the-art research of traditional computer vision is increasingly leveraged in the surgical domain. A particular focus in computer-assisted surgery is to replace marker-based tracking systems for instrument localization with pure image-based 6DoF pose estimation using deep-learning methods. However, state-of-the-art single-view pose estimation methods

Marco Fiore, Marina Mongiello

The combination between innovative topics and emerging technologies lets researchers define new processes and models. New needs regard the definition of modular and scalable approaches, with society and environment in mind. An important topic to focus on is the smart city one. The use of emerging technologies lets smart cities develop new processes to improv

O. Taran, O. Bait, M. Dessauges-Zavadsky, T. Holotyak

In our work, we examine, for the first time, the possibility of fast and efficient source localization directly from the uvobservations, omitting the recovering of the dirty or clean images. We propose a deep neural network-based framework that takes as its input a low-dimensional vector of sampled uvdata and outputs source positions on the sky. We investiga

Nikita Shanin, Simone Clochiatti, Kenneth M. Mayer, Laura Cottatellucci

In this paper, we study terahertz (THz) simultaneous wireless information and power transfer (SWIPT) for future micro-scale 6G Internet-of-Things (IoT) networks. Since Schottky diodes are not efficient for THz energy harvesting (EH), we propose resonant tunneling diodes (RTDs) for EH at the IoT receiver (RX). As the electrical properties of RTDs are differen

Suraj, Shankar Kumar Selvaraja

Ferroelectric materials exhibit interesting electric, mechanical and optical properties. Particularly,tin-film lead zirconium titanate (PZT) has been used as a standard piezo-electric material in micro-electro-mechanical systems. Interestingly, it has one of the highest electro-optic properties that can be exploited to make high-speed on-chip light modulator

Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li

Random smoothing data augmentation is a unique form of regularization that can prevent overfitting by introducing noise to the input data, encouraging the model to learn more generalized features. Despite its success in various applications, there has been a lack of systematic study on the regularization ability of random smoothing. In this paper, we aim to

Nicolas Jonason, Bob L. T. Sturm

This document presents some early explorations of applying Softly Masked Language Modelling (SMLM) to symbolic music generation. SMLM can be seen as a generalisation of masked language modelling (MLM), where instead of each element of the input set being either known or unknown, each element can be known, unknown or partly known. We demonstrate some results

Iris de Gélis, Sudipan Saha, Muhammad Shahzad, Thomas Corpetti

Change detection from traditional \added{2D} optical images has limited capability to model the changes in the height or shape of objects. Change detection using 3D point cloud \added{from photogrammetry or LiDAR surveying} can fill this gap by providing critical depth information. While most existing machine learning based 3D point cloud change detection me

Manuel Tuniz, Davide Soranzio, Davide Bidoggia, Denny Puntel

The charge-density wave (CDW) phase in the layered transition-metal dichalcogenide VTe$_{2}$ is strongly coupled to the band inversion involving vanadium and tellurium orbitals. In particular, this coupling leads to a selective disappearance of the Dirac-type states that characterize the normal phase, when the CDW phase sets in. Here, by means of broadband t

Muhammad Kashif, Saif Al-kuwari

The barren plateau problem in quantum neural networks (QNNs) is a significant challenge that hinders the practical success of QNNs. In this paper, we introduce residual quantum neural networks (ResQNets) as a solution to address this problem. ResQNets are inspired by classical residual neural networks and involve splitting the conventional QNN architecture i

Chengyi Tu, Jianhong Luo, Xuwei Pan

Complex systems are ubiquitous in nature and engineering, but their analysis and control are hampered by their high dimensionality and the influence of various factors on their dynamics. Dimensionality reduction aims to find a low-dimensional representation of the complex system that preserves its essential features and reveals its underlying mechanisms and

Shubham Sharma, Navin Kumar Chandra, Aloke Kumar, Saptarshi Basu

The present study uses Galinstan as a test fluid to investigate the shock-induced aerobreakup of a liquid metal droplet in a high Weber number regime (We ~ 400 - 8000). Atomization dynamics is examined for three test environments: oxidizing (Galinstan-air), inert (Galinstan-nitrogen), and conventional fluids (DI water-air). Due to the readily oxidizing natur

Nikita Shanin, Hedieh Ajam, Vasilis K. Papanikolaou, Bernhard Schmauss

In this paper, we study optical simultaneous wireless information and power transfer (SWIPT) systems, where a photovoltaic optical receiver (RX) is illuminated by ambient light and an intensity-modulated free space optical (FSO) signal. To facilitate simultaneous information reception and energy harvesting (EH) at the RX, the received optical signal is first

Paata Ivanisvili, Dmitriy Stolyarov, Vasily Vasyunin, Pavel Zatitskii

The present paper provides a generalization of the previous authors' work on Bellman functions for integral functionals on $\mathrm{BMO}$. Those Bellman functions are the minimal locally concave functions on parabolic strips in the plane. Now we describe the algorithm for constructing minimal locally concave functions on a planar domain that is a difference

F. Lienhard, A. Mortier, H. M. Cegla, A. Collier Cameron

The photospheric unsigned magnetic flux has been shown to be highly correlated with radial velocity (RV) variations caused by solar surface activity. This activity indicator is therefore a prime candidate to unlock the potential of RV surveys to discover Earth twins orbiting Sun-like stars. We show for the first time how a precise proxy of the unsigned magne

Daniel Panario, Nihal Uyar, Qiang Wang

The R\'{e}dei function defined over a field of even characteristic has been introduced by N\"{o}bauer in 1986 \cite{even}. In this paper, inspired by the work of Fu et al. \cite{wang} in odd characteristic, employing the AGW criterion \cite{agw}, we present a recursive construction of permutation polynomials in even characteristic using the R\'{e}dei functio

Sascha Marton, Stefan Lüdtke, Christian Bartelt, Heiner Stuckenschmidt

Decision Trees (DTs) are commonly used for many machine learning tasks due to their high degree of interpretability. However, learning a DT from data is a difficult optimization problem, as it is non-convex and non-differentiable. Therefore, common approaches learn DTs using a greedy growth algorithm that minimizes the impurity locally at each internal node.

Philip L. Bowers, Lorenzo Ruffoni

We show that given an infinite triangulation $K$ of a surface with punctures (i.e., with no vertices at the punctures) and a set of target cone angles smaller than $\pi$ at the punctures that satisfy a Gauss-Bonnet inequality, there exists a hyperbolic metric that has the prescribed angles and supports a circle packing in the combinatorics of $K$. Moreover,

Daniel Blixt, Manuel Hohmann, Tomi Koivisto, Luca Marzola

We write down the teleparallel equivalent to Hassan-Rosen bigravity, which is written using a torsionful but curvature-free connection. The theories only differ by a boundary term. The equivalence was proven, both by using perturbation theory and Hamiltonian analysis. It is further shown how one can construct novel bigravity theories within the teleparallel

Willams de Lima Costa, Estefania Talavera Martinez, Lucas Silva Figueiredo, Veronica Teichrieb

Emotion recognition is the task of classifying perceived emotions in people. Previous works have utilized various nonverbal cues to extract features from images and correlate them to emotions. Of these cues, situational context is particularly crucial in emotion perception since it can directly influence the emotion of a person. In this paper, we propose an

Kevin Ancourt, Jacques Peter, Olivier Atinault

The method of characteristics is a classical method for gaining understanding in the solution of a partial differential equation. It has recently been applied to the adjoint equations of the 2D Euler equations and the first goal of this paper is to present a linear algebra analysis that greatly simplifies the discussion of the number of independant character

Esther Cabezas-Rivas, Salvador Moll, Marcos Solera

We obtain existence of minimizers for the $p$-capacity functional defined with respect to a centrally symmetric anisotropy for $1 < p<\infty$, including the case of a crystalline norm in $\mathbb R^N$. The result is obtained by a characterization of the corresponding subdifferential and it applies for unbounded domains of the form $\mathbb R^N \setminus \ove

Kunya Yang, Hong Wu, Zefang Li, Chen Ran

Layered van der Waals (vdW) magnets are prominent playgrounds for developing magnetoelectric, magneto-optic and spintronic devices. In spintronics, particularly in spincaloritronic applications, low thermal conductivity ($\kappa$) is highly desired. Here, by combining thermal transport measurements with density functional theory calculations, we demonstrate

Bo Qiang, Yuxuan Song, Minkai Xu, Jingjing Gong

Generating desirable molecular structures in 3D is a fundamental problem for drug discovery. Despite the considerable progress we have achieved, existing methods usually generate molecules in atom resolution and ignore intrinsic local structures such as rings, which leads to poor quality in generated structures, especially when generating large molecules. Fr

Qihua Ruan, Qin Huang, Fan Chen

In this paper, we study the overdetermined problem for the $p$-Laplacian equation on complete noncompact Riemannian manifolds with nonnegative Ricci curvature. We prove that the regularity results of weak solutions of the $p$-Laplacian equation and obtain some integral identities. As their applications, we give the proof of the $p$-Laplacian overdetermined p

Gabriele Franciolini, Antonio Junior Iovino, Marco Taoso, Alfredo Urbano

We discuss the issue of perturbativity in single-field inflationary models with a phase of ultra slow-roll (USR) tailor suited to generate an order-one abundance of primordial black holes (PBHs). More in detail, we impose the condition that loop corrections made up of short-wavelength modes enhanced by the USR dynamics do not alter the tree-level power spect

Houssam Boukhecham, Hamza Ounesli

This paper is dedicated to prove that the space of circle expanding maps of degree 2 preserving Lebesgue measure is an arc-connected space homeomorphic to an infinite-dimensional Lie group whose fundamental group is $\mathbb{Z}$. The techniques involved in the proof are rather unexpected and lead to a formulation of a general conjecture

Ludovico Lami, Bartosz Regula, Alexander Streltsov

The use of ancillary quantum systems known as catalysts is known to be able to enhance the capabilities of entanglement transformations under local operations and classical communication. However, the limits of these advantages have not been determined, and in particular it is not known if such assistance can overcome the known restrictions on asymptotic tra

Ray Ganardi, Tulja Varun Kondra, Alexander Streltsov

Entanglement is a fundamental resource in quantum information processing, yet understanding its manipulation and transformation remains a challenge. Many tasks rely on highly entangled pure states, but obtaining such states is often challenging due to the presence of noise. Typically, entanglement manipulation procedures involving asymptotically many copies

Canhui Tang, Yiheng Li, Shaoyi Du, Guofa Wang

Feature Descriptors and Detectors are two main components of feature-based point cloud registration. However, little attention has been drawn to the explicit representation of local and global semantics in the learning of descriptors and detectors. In this paper, we present a framework that explicitly extracts dual-level descriptors and detectors and perform

Eric Heitz, Laurent Belcour, Thomas Chambon

We derive a minimalist but powerful deterministic denoising-diffusion model. While denoising diffusion has shown great success in many domains, its underlying theory remains largely inaccessible to non-expert users. Indeed, an understanding of graduate-level concepts such as Langevin dynamics or score matching appears to be required to grasp how it works. We

Elvira Fleig, Erik Bochinski, Thomas Sikora

Research in the past years introduced Steered Mixture-of-Experts (SMoE) as a framework to form sparse, edge-aware models for 2D- and higher dimensional pixel data, applicable to compression, denoising, and beyond, and capable to compete with state-of-the-art compression methods. To circumvent the computationally demanding, iterative optimization method used

Vì Kronberg, Martijn Anthonissen, Jan ten Thije Boonkkamp, Wilbert IJzerman

We introduce a novel approach to calculating three-dimensional freeform reflectors with a scattering surface. Our method is based on optimal transport and utilizes a Fredholm integral equation to express scattering. By solving this integral equation through a process similar to deconvolution, which we call `unfolding,' we can recover a typical specular desig

Adam Jones

We examine the power series ring $R[[X]]$ over a valuation ring $R$ of rank 1, with proper, dense value group. We give a counterexample to Hilbert's syzygy theorem for $R[[X]]$, i.e. an $R[[X]]$-module $C$ that is flat over $R$ and has flat dimension at least 2 over $R[[X]]$, contradicting a previously published result. The key ingredient in our construction

Elisa Maddalena Sala, Petr Klenovský

We study (In,Ga)(As,Sb)/GaAs quantum dots embedded in a GaP (100) matrix, which are overgrown by a thin GaSb capping layer with variable thickness. Quantum dot samples are studied by temperature-dependent photoluminescence, and we observe that the quantum dot emission shows anomalous temperature dependence,~i.e., increase of energy with temperature increase

Boris Kunyavskii

We show that even within a class of varieties where the Brauer--Manin obstruction is the only obstruction to the local-to-global principle for the existence of rational points (Hasse principle), this obstruction, even in a stronger, base change invariant form, may be insufficient for explaining counter-examples to the local-to-global principle for rationalit

Zheng Ge, Zhao-Qi-Zhi Han, Yi-Yang Liu, Xiao-Hua Wang

Converting the medium infrared field to the visible band is an effective image detection method. We propose a comprehensive theory of image up-conversion under continuous optical pumping, and discuss the relationship between the experimental parameters and imaging field of view, resolution, quantum efficiency, and conversion bandwidth. Theoretical prediction

Chuyao Tong, Annika Kurzmann, Rebekka Garreis, Kenji Watanabe

Pauli blockade is a fundamental quantum phenomenon that also serves as a powerful tool for qubit manipulation and read-out. While most systems exhibit a simple even-odd pattern of double-dot Pauli spin blockade due to the preferred singlet pairing of spins, the additional valley degree of freedom offered by bilayer graphene greatly alters this pattern. Inspe

Gabor Facsko, David Sibeck, Ilja Honkonen, Jozsef Bor

We compare the predictions of the GUMICS$-$4 global magnetohydrodynamic model for the interaction of the solar wind with the Earth's magnetosphere with Cluster~SC3 measurements for over one year, from January 29, 2002, to February 2, 2003. In particular, we compare model predictions with the north/south component of the magnetic field ($B_{z}$) seen by the m

Matteo Castagnola, Rosario R. Riso, Alberto Barlini, Enrico Ronca

Polaritonic chemistry is an interdisciplinary emerging field that presents several challenges and opportunities in chemistry, physics, and engineering. A systematic review of polaritonic response theory is presented, following a chemical perspective based on molecular response theory. We provide the reader with a general strategy for developing response theo

Champika Ranasinghe, Auriol Degbelo

Data Physicalization focuses on understanding how physical representations of data can support communication, learning and problem-solving. As an emerging area, Data Physicalization research needs conceptual foundations to support thinking about and designing new physical representations of data. Yet, it remains unclear at the moment (i) what encoding variab

S. Geier, M. Dorsch, H. Dawson, I. Pelisoli

We report the discovery of the first hot subdwarf B (sdB) star with a massive compact companion in a wide ($P=892.5\pm60.2\,{\rm d}$) binary system. It was discovered based on an astrometric binary solution provided by the Gaia mission Data Release 3. We performed detailed analyses of the spectral energy distribution (SED) as well as spectroscopic follow-up

Anthony Baptista, Rubén J. Sánchez-García, Anaïs Baudot, Ginestra Bianconi

Networks have provided extremely successful models of data and complex systems. Yet, as combinatorial objects, networks do not have in general intrinsic coordinates and do not typically lie in an ambient space. The process of assigning an embedding space to a network has attracted lots of interest in the past few decades, and has been efficiently applied to

Yi-Yan Liu, Yu Cui, Xiao-Zhe Zhang, Ran-Bo Yang

The formation of angulon, stemming from the rotor (molecule or impurity) rotating in the quantum many-body field, adds a new member in the quasiparticle's family and has aroused intensively interests in multiple research fields. However, the analysis of the coupling strength between the rotor and its hosting environment remains a challenging task both in the

Ping Wei, Qing Zhou, Zichi Wang, Zhenxing Qian

Generative steganography (GS) is an emerging technique that generates stego images directly from secret data. Various GS methods based on GANs or Flow have been developed recently. However, existing GAN-based GS methods cannot completely recover the hidden secret data due to the lack of network invertibility, while Flow-based methods produce poor image quali

Nicola Leschke, Florian Kirsten, Frank Pallas, Elias Grünewald

Transparency and data portability are two core principles of modern privacy legislations such as the GDPR. From the regulatory perspective, providing individuals (data subjects) with access to their data is a main building block for implementing these. Different from other privacy principles and respective regulatory provisions, however, this right to data a

Ailing Wang, Tao An, Shaoguang Guo, Luis C. Ho

Measuring the proper motion of the emission component in radio-quiet quasars (RQQs) could help to distinguish between the origins of the radio emission and to understand whether the jet production mechanism is the same in radio-loud quasars (RLQs) and RQQs. PG 1351+640 is one of the few RQQs suitable for proper motion studies: it has two compact components o

Simone Göttlich, Thomas Schillinger

We consider hyperbolic partial differential equations (PDEs) for a dynamic description of the traffic behavior in road networks. These equations are coupled to a Hawkes process that models traffic accidents taking into account their self-excitation property which means that accidents are more likely in areas in which another accident just occurred. We discus

Atilla Aras

This study presents empirical evidence to support the validity of new definitions in financial markets. The author develops a new method to determine investors' risk attitudes in financial markets. The risk attitudes of investors in US financial markets from 1889-1978 are analyzed and the results indicate that equity investors who invested in the composite S

Tongxu Zhang, Bei Wang

In recent years, multitudes of researches have applied deep learning to automatic sleep stage classification. Whereas actually, these works have paid less attention to the issue of cross-subject in sleep staging. At the same time, emerging neuroscience theories on inter-subject correlations can provide new insights for cross-subject analysis. This paper pres

Alessio Martini, Paweł Plewa

Let $G$ be the semidirect product $N \rtimes \mathbb{R}$, where $N$ is a stratified Lie group and $\mathbb{R}$ acts on $N$ via automorphic dilations. Homogeneous left-invariant sub-Laplacians on $N$ and $\mathbb{R}$ can be lifted to $G$, and their sum $\Delta$ is a left-invariant sub-Laplacian on $G$. In previous joint work of Ottazzi, Vallarino and the firs

A. A. Godizov

Single diffractive dissociation (SDD) of nucleon in high-energy proton-proton and proton-antiproton collisions is considered in terms of a simple two-Reggeon model with nonlinear Regge trajectories. It is demonstrated that the $f$-Reggeon impact on the corresponding cross-sections is not negligible up to the LHC energies. As well, it is shown that the accoun

Miloš Košprdić, Nikola Prodanović, Adela Ljajić, Bojana Bašaragin

Supervised named entity recognition (NER) in the biomedical domain depends on large sets of annotated texts with the given named entities. The creation of such datasets can be time-consuming and expensive, while extraction of new entities requires additional annotation tasks and retraining the model. To address these challenges, this paper proposes a method

David Karpuk, Razane Tajeddine

We present Modular Polynomial (MP) Codes for Secure Distributed Matrix Multiplication (SDMM). The construction is based on the observation that one can decode certain proper subsets of the coefficients of a polynomial with fewer evaluations than is necessary to interpolate the entire polynomial. We also present Generalized Gap Additive Secure Polynomial (GGA

Michel Davydov

Many phenomena can be modeled as network dynamics with punctuate interactions. However, most relevant dynamics do not allow for computational tractability. To circumvent this difficulty, the Poisson Hypothesis regime replaces interaction times between nodes by independent Poisson processes, allowing for tractability in several cases, such as intensity-based

Peng Yang, Laoming Zhang, Haifeng Liu, Guiying Li

In recent years, various companies have started to shift their data services from traditional data centers to the cloud. One of the major motivations is to save on operational costs with the aid of cloud elasticity. This paper discusses an emerging need from financial services to reduce the incidence of idle servers retaining very few user connections, witho

Fangneng Zhan, Lingjie Liu, Adam Kortylewski, Christian Theobalt

The recent advance of neural fields, such as neural radiance fields, has significantly pushed the boundary of scene representation learning. Aiming to boost the computation efficiency and rendering quality of 3D scenes, a popular line of research maps the 3D coordinate system to another measuring system, e.g., 2D manifolds and hash tables, for modeling neura

Jonghyuk Park, Alex Lascarides, Subramanian Ramamoorthy

Interactive Task Learning (ITL) concerns learning about unforeseen domain concepts via natural interactions with human users. The learner faces a number of significant constraints: learning should be online, incremental and few-shot, as it is expected to perform tangible belief updates right after novel words denoting unforeseen concepts are introduced. In t

Saveliy V. Skresanov

Let $ VG $ be a finite primitive affine permutation group, where $ V $ is a vector space of dimension $ d $ over the prime field $ \mathbb{F}_p $ and $ G $ is an irreducible linear group on $ V $. We prove that if $ p $ divides $ |G| $, then the diameters of all nondiagonal orbital graphs of $ VG $ are at most $ 9d^3 $. This improves an earlier exponential b

Roberto Cominetti, Valerio Dose, Marco Scarsini

We consider the behavior of the price of anarchy and equilibrium flows in nonatomic multi-commodity routing games as a function of the traffic demand. We analyze their smoothness with a special attention to specific values of the demand at which the support of the Wardrop equilibrium exhibits a phase transition with an abrupt change in the set of optimal rou

Yifan Wei, Fangyu Lei, Yuanzhe Zhang, Jun Zhao

Hybrid question answering (HybridQA) over the financial report contains both textual and tabular data, and requires the model to select the appropriate evidence for the numerical reasoning task. Existing methods based on encoder-decoder framework employ a expression tree-based decoder to solve numerical reasoning problems. However, encoders rely more on Mach

Hilde Weerts, Raphaële Xenidis, Fabien Tarissan, Henrik Palmer Olsen

Concerns regarding unfairness and discrimination in the context of artificial intelligence (AI) systems have recently received increased attention from both legal and computer science scholars. Yet, the degree of overlap between notions of algorithmic bias and fairness on the one hand, and legal notions of discrimination and equality on the other, is often u

Antoine Henry, Dario Fioretto, Lorenzo M. Procopio, Stéphane Monfray

Harnessing the frequency dimension in integrated photonics offers key advantages in terms of scalability, noise resilience, parallelization and compatibility with telecom multiplexing techniques. Integrated ring resonators have been used to generate frequency-entangled states through spontaneous four-wave-mixing. However, state-of-the-art integrated resonato

Aleksandar Cikota, Jiachen Ding, Lifan Wang, Dietrich Baade

Accurate distance determination to astrophysical objects is essential for the understanding of their intrinsic brightness and size. The distance to SN 1987A has been previously measured by the expanding photosphere method, and by using the angular size of the circumstellar rings with absolute sizes derived from light curves of narrow UV emission lines, with

Nathalie Ramos, Christoph Mittermeier, Josef Kiendl

Heat transfer simulations of the fused filament fabrication process are an important tool to predict bonding, residual stresses and strength of 3D printed parts. But in order to capture the significant thermal gradients that occur in the FFF printing process, a fine mesh discretization and short time steps are required, leading to extensive computational eff

Maurizio Carbone, Michael Wilczek

Stirring a fluid through a Gaussian forcing at a vanishingly small Reynolds number produces a Gaussian random field, while flows at higher Reynolds numbers exhibit non-Gaussianity, cascades, anomalous scaling and preferential alignments. Recent works (Yakhot and Donzis, Phys. Rev. Lett., vol. 119, 2017, pp. 044501; Gotoh and Yang, Philos. Trans. Royal Soc. A

Barun Maity, Aseem Paranjape, Tirthankar Roy Choudhury

Efficient exploration of parameter spaces is crucial to extract physical information about the Epoch of Reionization from various observational probes. To this end, we propose a fast technique based on Gaussian Process Regression (GPR) training applied to a semi-numerical photon-conserving reionization model, SCRIPT. Our approach takes advantage of the numer

Riccardo Fantoni

We present a self contained derivation of the Friedel oscillations in a degenerate ideal electron plasma using a not commonly known theorem on the asymptotic behavior of the Fourier transform of a generalized function presenting some singularities.

Lei Wang, Yi Hu, Jiabang He, Xing Xu

Large Language Models (LLMs) have recently demonstrated exceptional performance in various Natural Language Processing (NLP) tasks. They have also shown the ability to perform chain-of-thought (CoT) reasoning to solve complex problems. Recent studies have explored CoT reasoning in complex multimodal scenarios, such as the science question answering task, by

Lee Sharkey

The ability of neural networks to represent more features than neurons makes interpreting them challenging. This phenomenon, known as superposition, has spurred efforts to find architectures that are more interpretable than standard multilayer perceptrons (MLPs) with elementwise activation functions. In this note, I examine bilinear layers, which are a type

Ehsan Tohidi, Sven Haesloop, Lars Thiele, Slawomir Stanczak

Due to their passive nature and thus low energy consumption, intelligent reflecting surfaces (IRSs) have shown promise as means of extending coverage as a proxy for connection reliability. The relative locations of the base station (BS), IRS, and user equipment (UE) determine the extent of the coverage that the IRS provides which demonstrates the importance

S. Saner, O. Băzăvan, M. Minder, P. Drmota

All laser-driven entangling operations for trapped-ion qubits have hitherto been performed without control of the optical phase of the light field, which precludes independent tuning of the carrier and motional coupling. By placing $^{88}$Sr$^+$ ions in a $\lambda=674$ nm standing wave, whose relative position is controlled to $\approx\lambda/100$, we suppre

Kosuke Nogaki, Hiroshi Shinaoka

Analytical continuation (AC) connects theoretical calculations and experimentally measurable quantities. The recently proposed Nevanlinna AC method is capable of accurately reproducing the sharp features of spectral functions at high frequencies while maintaining the causality of the response function. However, their use is currently limited to fermions. Her

Bastian Köpcke, Sergei Gorlatch, Michel Steuwer

Graphics Processing Units (GPU) offer tremendous computational power by following a throughput oriented computing paradigm where many thousand computational units operate in parallel. Programming this massively parallel hardware is challenging. Programmers must correctly and efficiently coordinate thousands of threads and their accesses to various shared mem

Thomas A. Henzinger, Pavol Kebis, Nicolas Mazzocchi, N. Ege Saraç

The operator precedence languages (OPLs) represent the largest known subclass of the context-free languages which enjoys all desirable closure and decidability properties. This includes the decidability of language inclusion, which is the ultimate verification problem. Operator precedence grammars, automata, and logics have been investigated and used, for ex

Dave Bowman, Dora Puljic, Agata Smoktunowicz

One of the questions investigated in deformation theory is to determine to which algebras can a given associative algebra be deformed. In this paper we investigate a different but related question, namely: for a given associative finite-dimensional C-algebra A, find algebras N which can be deformed to A. We develop a simple method which produces associative

Rudi Penne, Ivan De Boi, Steve Vanlanduit

We propose a new paradigm for modelling and calibrating laser scanners with rotation symmetry, as is the case for Lidars or for galvanometric laser systems with one or two rotating mirrors. Instead of bothering about the intrinsic parameters of a physical model, we use the geometric properties of the device to model it as a specific configuration of lines, w

Philipp Wicke

Figurative language is a challenge for language models since its interpretation is based on the use of words in a way that deviates from their conventional order and meaning. Yet, humans can easily understand and interpret metaphors, similes or idioms as they can be derived from embodied metaphors. Language is a proxy for embodiment and if a metaphor is conv

Miguel Fernandez-Cortizas, David Perez-Saura, Javier Rodriguez-Vazquez, Pascual Campoy

Agile autonomous drones are becoming increasingly popular in research due to the challenges they represent in fields like control, state estimation, or perception at high speeds. When all algorithms are computed onboard the uav, the computational limitations make the task of agile and robust flight even more difficult. One of the most computationally expensi

L. K. Hunt, F. Belfiore, F. Lelli, B. T. Draine

The factor relating CO emission to molecular hydrogen column density, XCO, is still subject to uncertainty, in particular at low metallicity. Here, to quantify XCO at two different spatial resolutions, we exploit a dust-based method together with ALMA 12-m and ACA data and HI maps of three nearby metal-poor starbursts, NGC625, NGC1705, and NGC5253. Dust opac

Stanislav Kruglik, Gaojun Luo, Wilton Kim, Shubhransh Singhvi

We consider the repair scheme of Guruswami-Wootters for the Reed-Solomon code and ask: can we correctly repair a failed node in the presence of erroneous nodes? Equivalently, we consider the collection of downloaded traces as a code and investigate its code-distance properties. We propose three lower bounds on its minimum distance and study methods to effici

Miguel Fernandez-Cortizas, Hriday Bavle, Jose Luis Sanchez-Lopez, Pascual Campoy

Collaborative Simultaneous Localization and Mapping (CSLAM) is a critical capability for enabling multiple robots to operate in complex environments. Most CSLAM techniques rely on the transmission of low-level features for visual and LiDAR-based approaches, which are used for pose graph optimization. However, these low-level features can lead to incorrect lo

Michal Wlodarczyk

In Chordal/Interval Vertex Deletion we ask how many vertices one needs to remove from a graph to make it chordal (respectively: interval). We study these problems under the parameterization by treewidth $tw$ of the input graph $G$. On the one hand, we present an algorithm for Chordal Vertex Deletion with running time $2^{O(tw)} \cdot |V(G)|$, improving upon

Donghyun Lim, Martin Ziegler

Second-order polynomials generalize classical first-order ones in allowing for additional variables that range over functions rather than values. We are motivated by their applications in higher-order computational complexity theory, extending for example classical classes like P or PSPACE to operators in Analysis [doi:10.1137/S0097539794263452, doi:10.1145/

K. K. Ismailov, G. A. Sekh, Mario Salerno

Dynamical and self-trapping properties of two-dimensional (2D) binary mixtures of Bose-Einstein condensates (BECs) in cross-combined lattices consisting of a one-dimensional (1D) linear optical lattice (LOL) in the $x-$ direction for the first component and a 1D non linear optical lattice (NOL) in the $y$-direction for the second component, are analytically

Giuseppe Meneghini, Marcel Reutzel, Stefan Mathias, Samuel Brem

Van der Waals heterostructures show fascinating physics including trapped moire exciton states, anomalous moire exciton transport, generalized Wigner crystals, etc. Bilayers of transition metal dichalcogenides (TMDs) are characterized by long-lived spatially separated interlayer excitons. Provided a strong interlayer tunneling, hybrid exciton states consisti

Francesco Albarelli, Matteo G. A. Paris, Bassano Vacchini, Andrea Smirne

One of the main advantages expected from using quantum probes as thermometers is non invasiveness, i.e., a negligible perturbation to the thermal sample. However, invasiveness is rarely investigated explicitly. Here, focusing on a pure-dephasing spin probe in a bosonic sample, we show that there is a non-trivial relation between the information on the temper

Steven Ndung'u, Trienko Grobler, Stefan J. Wijnholds, Dimka Karastoyanova

Modern radio telescopes will daily generate data sets on the scale of exabytes for systems like the Square Kilometre Array (SKA). Massive data sets are a source of unknown and rare astrophysical phenomena that lead to discoveries. Nonetheless, this is only plausible with the exploitation of intensive machine intelligence to complement human-aided and traditi

A. Alonso-Izquierdo, A. J. Balseyro Sebastian, M. A. Gonzalez Leon

In this paper we construct a family of Hamilton-Jacobi separable non-linear $\mathbb{S}^1\times\mathbb{S}^1$ Sigma models for which the kink variety can be analytically identified and for which the linear stability of the emerging kinks is ensured. Furthermore, a model with only one vacuum point is found, where all kinks are forced to be non-topological. The

Wenjia Zhang, Lin Gui, Rob Procter, Yulan He

To enhance the ability to find credible evidence in news articles, we propose a novel task of expert recommendation, which aims to identify trustworthy experts on a specific news topic. To achieve the aim, we describe the construction of a novel NewsQuote dataset consisting of 24,031 quote-speaker pairs that appeared on a COVID-19 news corpus. We demonstrate

Kehui Tan, Tianqi Pang, Chenyou Fan, Song Yu

This perspective paper proposes a series of interactive scenarios that utilize Artificial Intelligence (AI) to enhance classroom teaching, such as dialogue auto-completion, knowledge and style transfer, and assessment of AI-generated content. By leveraging recent developments in Large Language Models (LLMs), we explore the potential of AI to augment and enri

Jens Kosiol, Daniel Strüber, Gabriele Taentzer, Steffen Zschaler

Many applications of graph transformation require rules that change a graph without introducing new consistency violations. When designing such rules, it is natural to think about the desired outcome state, i.e., the desired effect, rather than the specific steps required to achieve it; these steps may vary depending on the specific rule-application context.

Luana Martins, Denivan Campos, Railana Santana, Joselito Mota Junior

Refactorings are transformations to improve the code design without changing overall functionality and observable behavior. During the refactoring process of smelly test code, practitioners may struggle to identify refactoring candidates and define and apply corrective strategies. This paper reports on an empirical study aimed at understanding how test smell

Yan Chen, Ruo Li, Qicheng Liu

We present an arbitrary order discontinuous Galerkin finite element method for solving the biharmonic interface problem on the unfitted mesh. The approximation space is constructed by a patch reconstruction process with at most one degree freedom per element. The discrete problem is based on the symmetric interior penalty method and the jump conditions are w

Eduardo C. Garrido-Merchán, José Luis Arroyo-Barrigüete, Roberto Gozalo-Brizuela

In this paper, we present a novel approach to simulating H.P. Lovecraft's horror literature using the ChatGPT large language model, specifically the GPT-4 architecture. Our study aims to generate text that emulates Lovecraft's unique writing style and themes, while also examining the effectiveness of prompt engineering techniques in guiding the model's outpu

Alireza Ardalani, Saeed Parsa, Morteza Zakeri-Nasrabadi, Alexander Chatzigeorgiou

The responsibility of a method/function is to perform some desired computations and disseminate the results to its caller through various deliverables, including object fields and variables in output instructions. Based on this definition of responsibility, this paper offers a new algorithm to refactor long methods to those with a single responsibility. We p

Nurettin Turan, Benedikt Fesl, Wolfgang Utschick

Recently, a versatile limited feedback scheme based on a Gaussian mixture model (GMM) was proposed for frequency division duplex (FDD) systems. This scheme provides high flexibility regarding various system parameters and is applicable to both point-to-point multiple-input multiple-output (MIMO) and multi-user MIMO (MU-MIMO) communications. The GMM is learne

Hung Nguyen Viet, Duy Mai The, Thanh Vu Thi Hong

This paper introduces a new class of iterated function systems (IFSs) called R-IFSs, which include both rotation/reflection maps and contraction maps. The study of R-IFSs is motivated by the recent research direction on enriching IFSs by adding other types of mappings. The paper investigates the existence and properties of the semi-attractor and compact inva

Rupesh Kumar, Ayush Sinha, Ashutosh Bajpai, S. K Singh

Sign language is a visual language that enhances communication between people and is frequently used as the primary form of communication by people with hearing loss. Even so, not many people with hearing loss use sign language, and they frequently experience social isolation. Therefore, it is necessary to create human-computer interface systems that can off

Albara Ah Ramli, Xin Liu, Erik K. Henricson

We introduce Walk4Me, a telehealth community mobility assessment system designed to facilitate early diagnosis, severity, and progression identification. Our system achieves this by 1) enabling early diagnosis, 2) identifying early indicators of clinical severity, and 3) quantifying and tracking the progression of the disease across the ambulatory phase of t