April 2024 arXiv papers — page 86

Xianqiang Lyu, Hui Liu, Junhui Hou

We propose RainyScape, an unsupervised framework for reconstructing clean scenes from a collection of multi-view rainy images. RainyScape consists of two main modules: a neural rendering module and a rain-prediction module that incorporates a predictor network and a learnable latent embedding that captures the rain characteristics of the scene. Specifically,

Peixu Guo, Jiaao Hao, Chih-Yung Wen

The hypersonic flow stability over a two-dimensional compression corner is studied using resolvent analysis, linear stability theory (LST) and parabolised stability equation (PSE). The authors find that the interaction between upstream convective-type disturbances and the laminar separation bubble can be divided into two regimes, whose behaviour can be well

Eric Brandao, William Fonseca, Paulo Mareze, Carlos Resende

Estimating the sound absorption in situ relies on accurately describing the measured sound field. Evidence suggests that modeling the reflection of impinging spherical waves is important, especially for compact measurement systems. This article proposes a method for estimating the sound absorption coefficient of a material sample by mapping the sound pressur

Rong Xiao, Y. X. Zhao

The sublattice symmetry on a bipartite lattice is commonly regarded as the chiral symmetry in the AIII class of the tenfold Altland-Zirnbauer classification. Here, we reveal the spatial nature of sublattice symmetry, and show that this assertion holds only if the periodicity of primitive unit cells agrees with that of the sublattice labeling. In cases where

Thibeau Wouters, Peter T. H. Pang, Tim Dietrich, Chris Van Den Broeck

The gravitational waves emitted by binary neutron star inspirals contain information on nuclear matter above saturation density. However, extracting this information and conducting parameter estimation remains a computationally challenging and expensive task. Wong et al. introduced Jim arXiv:2302.05333, a parameter estimation pipeline that combines relative

Oleg Gutik, Marko Serivka

We describe injective monoid endomorphisms of the semigroup $\boldsymbol{B}_{\omega}^{\mathscr{F}^3}$ with a three element family $\mathscr{F}^3$ of inductive nonempty subsets of $\omega$. Also, we show that the monoid $\boldsymbol{End}_*^1(\boldsymbol{B}_{\omega}^{\mathscr{F}})$ of all injective endomorphisms of the semigroup $\boldsymbol{B}_{\omega}^{\math

Zhen Li, Xiwen Zhang, Feng He

Based on the analysis of the velocity gradient tensor, we investigate in this paper the physical interpretation and limitations of four vortex criteria: $\omega$, $Q$, $\varDelta$ and $\lambda_{ci}$, and reveal the actual physical meaning of vortex patterns which are usually illustrated by level sets of various vortex criteria. A quadruple decomposition base

Xin Fu, Wenjia Jing

We consider the Dirichlet problem for elliptic systems with periodically distributed inclusions whose conduction parameter exhibits a significant contrast compared to the background media. We develop a unified method to quantify the convergence rates both as the periodicity of inclusions tends to zero and as the parameter approaches either zero or infinity.

Cooper Watson, William Julius, Patrick Brown, Donald Salisbury

Canonical quantization of gravity in general relativity is greatly simplified by the artificial decomposition of space and time into a 3+1 formalism. Such a simplification may appear to come at the cost of general covariance. This requires tangential and perpendicular infinitesimal diffeomorphisms generated by the symmetry group under the Legendre transforma

Elif Ak, Berk Canberk, Vishal Sharma, Octavia A. Dobre

This study explores implementing a digital twin network (DTN) for efficient 6G wireless network management, aligning with the fault, configuration, accounting, performance, and security (FCAPS) model. The DTN architecture comprises the Physical Twin Layer, implemented using NS-3, and the Service Layer, featuring machine learning and reinforcement learning fo

Ruth Charney, Alexandre Martin, Rose Morris-Wright

We establish a criterion that implies the acylindrical hyperbolicity of many Artin groups admitting a visual splitting. This gives a variety of new examples of acylindrically hyperbolic Artin groups, including many Artin groups of FC-type. Our approach relies on understanding when parabolic subgroups are weakly malnormal in a given Artin group. We formulate

Piyush Mani Tripathi, Amy M. Marconnet

Battery thermal management systems (BTMSs) are critical for efficient and safe operation of lithium-ion batteries (LIBs), especially for fast charging/discharging applications that generate significant heating within the cell. Forced immersion cooling, where a dielectric fluid flows in direct contact with the LIB cells, is an effective cooling approach. But

Fengmiao Ge, Bingyuan Wei

This study addressed the scalar field quasinormal ringing behavior of black holes. We investigated scalar field perturbations in Bardeen black hole spacetime in 5-dimensional Einstein-Gauss-Bonnet (EGB) gravity. Using the 3rd-order WKB approximation and the finite-difference method, we computed the frequency of quasinormal modes (QNMs) in the spacetime backg

Muhammad Kashif, Li Chunxia, Cui Mengyuan

Extended versions of the noncommutative(nc) KP equation and the nc mKP equation are constructed in a unified way, for which two types of quasideterminant solutions are also presented. In commutative setting, the quasideterminant solutions provide the known and unknown Wronskian and Grammian solutions for the bilinear KP equation with self-consistent sources

Xue-Lei Lin, Michael K. Ng

In this paper, we study a $\tau$-matrix approximation based preconditioner for the linear systems arising from discretization of unsteady state Riesz space fractional diffusion equation with non-separable variable coefficients. The structure of coefficient matrices of the linear systems is identity plus summation of diagonal-times-multilevel-Toeplitz matrice

Felicia Lucke, Ali Momeni, Daniël Paulusma, Siani Smith

The d-Cut problem is to decide if a graph has an edge cut such that each vertex has at most d neighbours at the opposite side of the cut. If $d=1$, we obtain the intensively studied Matching Cut problem. The d-Cut problem has been studied as well, but a systematic study for special graph classes was lacking. We initiate such a study and consider classes of b

Silvia Noschese, Lothar Reichel

Complex networks are made up of vertices and edges. The latter connect the vertices. There are several ways to measure the importance of the vertices, e.g., by counting the number of edges that start or end at each vertex, or by using the subgraph centrality of the vertices. It is more difficult to assess the importance of the edges. One approach is to consi

Akinsola Ahmed, Ejiofor Oluomachi, Akinde Abdullah, Njoku Tochukwu

The article discusses the emergence of Wireless Sensor Networks (WSNs) as a groundbreaking technology in data processing and communication. It outlines how WSNs, composed of dispersed autonomous sensors, are utilized to monitor physical and environmental factors, transmitting data wirelessly for analysis. The article explores various applications of WSNs in

Ubaldo Cavazos Olivas, Luis A. Peña Ardila, Krzysztof Jachymski

Ionic Bose polarons are quantum entities emerging from the interaction between an ion and a Bose-Einstein condensate (BEC), featuring long-ranged interactions that can compete with the gas healing length. This can result in strong interparticle correlations and enhancement of gas density around the ion. One possible approach to describe this complex system w

Emilia Margoni, Daniele Oriti

Among the various attempts to formulate a theory of quantum gravity, a class of approaches suggests that spacetime, as modeled by general relativity, is destined to fade away. A major issue becomes then to identify which structures may inhabit the more fundamental, non-spatiotemporal environment, as well as to explain the relationship with the higher-level s

M. Bianco, A. Scarciglia, C. Bonanno, G. Valenza

Heart rate variability (HRV) series reflects the dynamical variation of heartbeat-to-heartbeat intervals in time and is one of the outputs of the cardiovascular system. Over the years, this system has been recognized for generating nonlinear and complex heartbeat dynamics, with the latter referring to a high sensitivity to small -- theoretically infinitesima

Xiao Li, Yong Jiang, Shen Huang, Pengjun Xie

Key Point Analysis (KPA), the summarization of multiple arguments into a concise collection of key points, continues to be a significant and unresolved issue within the field of argument mining. Existing models adapt a two-stage pipeline of clustering arguments or generating key points for argument clusters. This approach rely on semantic similarity instead

Boyan Obreshkov, Tzveta Apostolova

We theoretically investigate photo-excitation of electron-hole pairs and high harmonic generation in the bulk of zinc oxide (ZnO) subjected to intense femto-second laser pulses with mid-infrared wavelength. The main microscopic mechanism of solid-state HHG is identified by separating resonant from non-resonant non-linear optical responses in the photo-excite

Yongkai Ma, Shili Liang, Zekun Chen

Surface electromyographic (sEMG) signal serve as a signal source commonly used for lower limb movement recognition, reflecting the intent of human movement. However, it has been a challenge to improve the movements recognition rate while using fewer features in this area of research area. In this paper, a method for lower limb movements recognition based on

Xinpei Zhang, Guangyan Jia

With the outstanding performance of policy gradient (PG) method in the reinforcement learning field, the convergence theory of it has aroused more and more interest recently. Meanwhile, the significant importance and abundant theoretical researches make the stochastic linear quadratic (SLQ) control problem a starting point for studying PG in model-based lear

Thomas Elgin, Nathan Reading, Salvatore Stella

We present conjectures on the scattering terms of cluster scattering diagrams of rank 2, supported by significant computational evidence.

Youcai Han, Changhao Meng, Zejin Rao, Jie Qian

Manipulation of wave propagation through open resonant systems has attracted tremendous interest. When accessible to the open system, the system under study is prone to tempering to out of equilibrium, and a lack of reciprocity is the rule rather than the exception. Open systems correspond to non-hermitian Hamiltonians with very unique properties such as res

Ranjan Mukhopadhyay

We view the mind-body problem in terms of the two interconnected problems of phenomenal consciousness and mental causation, namely, how subjective conscious experience can arise from physical neurological processes and how conscious mental states can causally act upon the physical world. In order to address these problems, I develop here a non-physicalist fr

Sam Coates

Symmetry sharing facilitates coherent interfaces which can transition from periodic to aperiodic structures. Motivated by the design and construction of such systems, we present hexagonal aperiodic tilings with a single edge-length which can be considered as decorations of a periodic lattice. We introduce these tilings by modifying an existing family of gold

Haimei Huo, Zhixun Su

This paper studies the unconstrained nonconvex-strongly-convex bilevel optimization problem. A common approach to solving this problem is to alternately update the upper-level and lower-level variables using (biased) stochastic gradients or their variants, with the lower-level variable updated either one step or multiple steps. In this context, we propose tw

Aaron Conrardy, Jordi Cabot

In software engineering processes, systems are first specified using a modeling language such as UML. These initial designs are often collaboratively created, many times in meetings where different domain experts use whiteboards, paper or other types of quick supports to create drawings and blueprints that then will need to be formalized. These proper, machi

Xinghan Wang, Zixi Kang, Yadong Mu

Human motion understanding is a fundamental task with diverse practical applications, facilitated by the availability of large-scale motion capture datasets. Recent studies focus on text-motion tasks, such as text-based motion generation, editing and question answering. In this study, we introduce the novel task of text-based human motion grounding (THMG), a

Oliver Lloyd, Yi Liu, Tom R. Gaunt

Motivation: Adverse reactions from drug combinations are increasingly common, making their accurate prediction a crucial challenge in modern medicine. Laboratory-based identification of these reactions is insufficient due to the combinatorial nature of the problem. While many computational approaches have been proposed, tensor factorisation models have shown

Costantino Pacilio, Swetha Bhagwat, Roberto Cotesta

Gravitational waves emitted by a ringing black hole allow us to perform precision tests of general relativity in the strong field regime. With improvements to our current gravitational wave detectors and upcoming next-generation detectors, developing likelihood-free parameter inference infrastructure is critical as we will face complications like nonstandard

Ivan Costa, Ivone Amorim, Eva Maia, Pedro Barbosa

Healthcare data contains some of the most sensitive information about an individual, yet sharing this data with healthcare practitioners can significantly enhance patient care and support research efforts. However, current systems for sharing health data between patients and caregivers do not fully address the critical security requirements of privacy, confi

Karen Vogtmann

We study the boundary of the "Jewel space" $\mathcal J_n$ constructed in arXiv:1709.01296. This is an equivariant deformation retract of Outer space $CV_n$ on which $Out(F_n)$ acts properly and cocompactly, and is homeomorphic to the Bestvina-Feighn bordification of $CV_n$. In the current paper we analyze the structure of the boundary of $\mathcal J_n$. We t

Lujain Ibrahim, Luc Rocher, Ana Valdivia

The proliferation of applications using artificial intelligence (AI) systems has led to a growing number of users interacting with these systems through sophisticated interfaces. Human-computer interaction research has long shown that interfaces shape both user behavior and user perception of technical capabilities and risks. Yet, practitioners and researche

Eitan Kazakevich, Hadar Aharon, Ofer Kfir

Free electron beams and their quantum coupling with photons is attracting a rising interest due to the basic questions it addresses and the cutting-edge technology these particles are involved in, such as microscopy, spectroscopy, and quantum computation. This work investigates theoretically the concept of electron-photon coupling in the spatial domain. Thei

Jingyuan Li, Di Peng, Peiyue Ma, Hengyuan Zhang

Identification of superconductivity in the Ruddlesden-Popper phases of nickelates under high pressure remains challenging. Here, we report a comprehensive study of the crystal structure, resistance, and Meissner effect in single crystals of La$_3$Ni$_2$O$_7$ with hydrostatic pressures up to 104 GPa. X-ray diffraction measurements reveal a structural transiti

Jan-Wilke Henke, Hao Jeng, Claus Ropers

We propose a tangible experimental scheme for demonstrating quantum entanglement between swift electrons and light, relying on coherent cathodoluminescence for photon generation in a transmission electron microscope, and a quantum eraser setup for formation and verification of entanglement. The entanglement of free electrons with light is key to developing f

Roman Krahne, Alexander Schleusener, Mehrdad Faraji, Lin-Han Li

Two-dimensional metal-halide perovskites are highly versatile for light-driven applications due to their exceptional variety in material composition, which can be exploited for tunability of mechanical and optoelectronic properties. The band edge emission is defined by structure and composition of both organic and inorganic layers, and electron-phonon coupli

Giorgio Vittorio Visco, Johannes Nauta, Tomas Scagliarini, Oriol Artime

A broad class of systems, including ecological, epidemiological, and sociological ones, are characterized by populations of individuals assigned to specific categories, e.g., a chemical species, an opinion or an epidemic state, that are modeled as compartments. Due to interactions and intrinsic dynamics, individuals are allowed to change category, leading to

Ehsan Jebellat, Iman Jebellat

Functionally graded materials (FGMs) represent a promising class of advanced materials designed with tailored microstructures to achieve optimized mechanical, thermal, and functional properties across varying gradients. The strategic integration of distinct materials within functionally graded materials offers engineers unprecedented control over properties

Mihail Stoian

Exponential-time approximation has recently gained attention as a practical way to deal with the bitter NP-hardness of well-known optimization problems. We study for the first time the $(1 + \varepsilon)$-approximate min-sum subset convolution. This enables exponential-time $(1 + \varepsilon)$-approximation schemes for problems such as minimum-cost $k$-color

Yuya Matsubara, Ryo Okabe, Ren Masayama, Nozomi Morishita Watanabe

We propose a theoretical approach to estimate the permeability coefficient of substrates (permeants) for crossing membranes from donor (D) phase to acceptor (A) phase by means of molecular dynamics (MD) simulation. A fundamental aspect of our approach involves reformulating the returning probability (RP) theory, a rigorous bimolecular reaction theory, to des

Chengxiang Zhang

This paper presents a new approach for addressing the singularly perturbed nonlinear Schr\"odinger (NLS) equation: \begin{equation} -\varepsilon^2\Delta v + V(x) v =f(v),\ v>0,\ \lim_{|x|\to \infty} v(x)=0, \end{equation} where $V$ possesses a local maximum point and $f$ satisfies the Berestycki-Lions conditions.The key to our approach is the derivation of a

Seyed M. R. Modaresi, Aomar Osmani, Mohammadreza Razzazi, Abdelghani Chibani

Medical image segmentation plays a vital role in various clinical applications, enabling accurate delineation and analysis of anatomical structures or pathological regions. Traditional CNNs have achieved remarkable success in this field. However, they often rely on fixed kernel sizes, which can limit their performance and adaptability in medical images where

Krzysztof Ptaszynski, Massimiliano Esposito

Significant attention has been devoted to the problem of thermalization of observables in isolated quantum setups by individual eigenstates. Here, we address this issue from an open quantum system perspective, examining an isolated setup where a small system (specifically, a single fermionic level) is coupled to a macroscopic fermionic bath. We argue that in

E. Filandri, L. Girlanda, A. Kievsky, L. E. Marcucci

Starting from a complete set of relativistic nucleon-nucleon contact operators up to order $O(p^4)$ of the expansion in the soft (relative or nucleon) momentum $p$, we show that non-relativistic expansions of relativistic operators involve twenty-six independent combinations, two starting at $O(p^0)$, seven at order $O(p^2)$ and seventeen at order $O(p^4)$.

Jeongtaek Oh, Jaeyoung Chung, Dongwoo Lee, Kyoung Mu Lee

Although significant progress has been made in reconstructing sharp 3D scenes from motion-blurred images, a transition to real-world applications remains challenging. The primary obstacle stems from the severe blur which leads to inaccuracies in the acquisition of initial camera poses through Structure-from-Motion, a critical aspect often overlooked by previ

Hangtao Zhang, Shengshan Hu, Yichen Wang, Leo Yu Zhang

Object detection tasks, crucial in safety-critical systems like autonomous driving, focus on pinpointing object locations. These detectors are known to be susceptible to backdoor attacks. However, existing backdoor techniques have primarily been adapted from classification tasks, overlooking deeper vulnerabilities specific to object detection. This paper is

M. Dinger, W. Y. Baek, H. Rabus

To provide a comprehensive data set for track structure-based simulations of radiation damage in DNA, doubly differential electron-impact ionization cross sections of pyrimidine, a building block of the nucleobases cytosine and thymine, were measured for primary electron energies between 30 eV and 1 keV as a function of emission angle and secondary electron

Ziyu Zhou, Wenyuan Shen, Chang Liu

Colorectal cancer (CRC), which frequently originates from initially benign polyps, remains a significant contributor to global cancer-related mortality. Early and accurate detection of these polyps via colonoscopy is crucial for CRC prevention. However, traditional colonoscopy methods depend heavily on the operator's experience, leading to suboptimal polyp d

Yaqun Yang, Jinlong Lei, Guanghui Wen, Yiguang Hong

This paper considers a distributed adaptive optimization problem, where all agents only have access to their local cost functions with a common unknown parameter, whereas they mean to collaboratively estimate the true parameter and find the optimal solution over a connected network. A general mathematical framework for such a problem has not been studied yet

Philipp Heilmann, Pavlo V. Pyshkin, Björn Trauzettel

We examine 2D electron transport through a long narrow channel driven by an external electric field in presence of diffusive boundary scattering. At zero temperature, we derive an analytical solution of the transition from ballistic to diffusive transport if we increase the bulk disorder strength. This crossover yields characteristic current density profiles

Zonghang Li, Wenjiao Feng, Weibo Cai, Hongfang Yu

Distributed machine learning is becoming increasingly popular for geo-distributed data analytics, facilitating the collaborative analysis of data scattered across data centers in different regions. This paradigm eliminates the need for centralizing sensitive raw data in one location but faces the significant challenge of high parameter synchronization delays

Gautam Kumar, Ashwini Ratnoo

This article considers the problem of conflict-free distribution of point-sized agents on a circular periphery encompassing all agents. The two key elements of the proposed policy include the construction of a set of convex layers (nested convex polygons) using the initial positions of the agents, and a novel search space region for each of the agents. The s

Jiayi Huang, Sangwoo Park, Osvaldo Simeone

The application of artificial intelligence (AI) models in fields such as engineering is limited by the known difficulty of quantifying the reliability of an AI's decision. A well-calibrated AI model must correctly report its accuracy on in-distribution (ID) inputs, while also enabling the detection of out-of-distribution (OOD) inputs. A conventional approach

Gopichand Kanumolu, Lokesh Madasu, Nirmal Surange, Manish Shrivastava

News headline generation is a crucial task in increasing productivity for both the readers and producers of news. This task can easily be aided by automated News headline-generation models. However, the presence of irrelevant headlines in scraped news articles results in sub-optimal performance of generation models. We propose that relevance-based headline c

François Jauberteau, Yann Rollin

We consider the moduli space of isotropic maps from a closed surface $\Sigma$ to a symplectic affine space and construct a K\"ahler moment map geometry, on a space of differential forms on $\Sigma$, such that the isotropic maps correspond to certain zeroes of the moment map. The moment map geometry induces a modified moment map flow, whose fixed point set co

Wolfgang Kastaun, Frank Ohme

Astronomical observations place increasingly tighter and more diverse constraints on the properties of neutron stars (NS). Examples include observations of radio or gamma-ray pulsars, accreting neutron stars and x-ray bursts, magnetar giant flares, and recently, the gravitational waves (GW) from coalescing binary neutron stars. Computing NS properties for a

Sourish Das, Shouvik Sardar

The Jacobi prior offers an alternative Bayesian framework, designed to achieve superior computational efficiency without compromising predictive performance. Compared to widely used methods such as Lasso, Ridge, Elastic Net, uniLasso, the MCMC-based Horseshoe prior, and non-Bayesian machine learning methods including Support Vector Machines (SVM), Random For

Margot H. Teunisse, Martin van Hecke

Transition graphs capture the memory and sequential response of multistable media, by specifying their evolution under external driving. Microscopically, collections of bistable elements, or hysterons, provide a powerful model for these materials, with recent work highlighting the crucial role of hysteron interactions. Here, we introduce a general framework

Sein Kim, Hongseok Kang, Seungyoon Choi, Donghyun Kim

Collaborative filtering recommender systems (CF-RecSys) have shown successive results in enhancing the user experience on social media and e-commerce platforms. However, as CF-RecSys struggles under cold scenarios with sparse user-item interactions, recent strategies have focused on leveraging modality information of user/items (e.g., text or images) based o

Joachim Hofer

Magnetically levitated superconductors in the Meissner state can be utilized as micro-mechanical oscillators with large mass, high quality factors and long coherence times. In previous works analytical solutions for the magnetic field distribution around a superconducting sphere in a quadrupole field have been found and used to derive the trap parameters, wh

Juan L. Gamella, Jonas Peters, Peter Bühlmann

In some fields of AI, machine learning and statistics, the validation of new methods and algorithms is often hindered by the scarcity of suitable real-world datasets. Researchers must often turn to simulated data, which yields limited information about the applicability of the proposed methods to real problems. As a step forward, we have constructed two devi

George Retsinas, Giorgos Sfikas, Basilis Gatos, Christophoros Nikou

Handwritten text recognition has been developed rapidly in the recent years, following the rise of deep learning and its applications. Though deep learning methods provide notable boost in performance concerning text recognition, non-trivial deviation in performance can be detected even when small pre-processing or architectural/optimization elements are cha

Dinil Mon Divakaran, Sai Teja Peddinti

Large language models (LLMs) are a class of powerful and versatile models that are beneficial to many industries. With the emergence of LLMs, we take a fresh look at cyber security, specifically exploring and summarizing the potential of LLMs in addressing challenging problems in the security and safety domains.

Runyue Wang, Riccardo Muolo, Timoteo Carletti, Ginestra Bianconi

Higher-order networks are able to capture the many-body interactions present in complex systems and to unveil new fundamental phenomena revealing the rich interplay between topology, geometry, and dynamics. Simplicial complexes are higher-order networks that encode higher-order topology and dynamics of complex systems. Specifically, simplicial complexes can

Haohua Dong

This work addresses the landing problem of an aerial vehicle, exemplified by a simple quadrotor, on a moving platform using image-based visual servo control. First, the mathematical model of the quadrotor aircraft is introduced, followed by the design of the inner-loop control. At the second stage, the image features on the textured target plane are exploite

Vladimir Somers, Victor Joos, Anthony Cioppa, Silvio Giancola

Tracking and identifying athletes on the pitch holds a central role in collecting essential insights from the game, such as estimating the total distance covered by players or understanding team tactics. This tracking and identification process is crucial for reconstructing the game state, defined by the athletes' positions and identities on a 2D top-view of

Matthias Raddant, Fariba Karimi

Diversity in leadership positions, including corporate boards, is an important aspect of equality. It is important because it is the key to better decision-making and innovation, and above all, it paves the way for future generations to participate and shape our society. Many studies emphasize the importance of the visibility of role models and the effect th

Sobhan Kazempour, Sichun Sun, Chengye Yu

We examine the thin accretion disk behaviors surrounding black holes embedded in cold dark matter halos and scalar field dark matter halos. We first calculate the event horizons and derive the equations of motion and effective potential in black hole geometries with different dark matter halos. We then compute the specific energy, specific angular momentum,

Anette Messinger, Valentin Torggler, Berend Klaver, Michael Fellner

We present a fault-tolerant universal quantum computing architecture based on a code concatenation of biased-noise qubits and the parity architecture. The parity architecture can be understood as an LDPC code tailored specifically to obtain any desired logical connectivity from nearest-neighbor physical interactions. The code layout can be dynamically adjust

Christian Di Fidio, Laura Ares, Jan Sperling

For harnessing the full potential of quantum phenomena, light-matter interfaces and complexly connected quantum networks are required, relying on the joint quantum operation of different physical platforms. In this work, we analyze the quantum properties of multipartite quantum systems, consisting of an arbitrarily large collection of optical cavities with t

Niklas Koenen, Marvin N. Wright

In recent years, neural networks have demonstrated their remarkable ability to discern intricate patterns and relationships from raw data. However, understanding the inner workings of these black box models remains challenging, yet crucial for high-stake decisions. Among the prominent approaches for explaining these black boxes are feature attribution method

Pierre-A. Vuillermot

In this article we investigate from the point of view of spectral theory the problem of relaxation to thermodynamical equilibrium of a quantum harmonic oscillator interacting with a radiation field. Our starting point is a system of infinitely many Pauli master equations governing the time evolution of the occupation probabilities of the available quantum st

Yatish Pachigolla, Lorenzo Zaniboni, Mahdi Mahvari

Channel estimation techniques for orthogonal time frequency space (OTFS) modulation scheme are investigated. The orthogonal matching pursuit algorithm is investigated with and without side channel information, and an efficient data placement is proposed alongside the pilot in the multi-user scenario based on impulse pilot-based estimation. Finally, the perfo

Luca Scofano, Alessio Sampieri, Tommaso Campari, Valentino Sacco

The success of collaboration between humans and robots in shared environments relies on the robot's real-time adaptation to human motion. Specifically, in Social Navigation, the agent should be close enough to assist but ready to back up to let the human move freely, avoiding collisions. Human trajectories emerge as crucial cues in Social Navigation, but the

George Retsinas, Niki Efthymiou, Petros Maragos

Modern agricultural applications rely more and more on deep learning solutions. However, training well-performing deep networks requires a large amount of annotated data that may not be available and in the case of 3D annotation may not even be feasible for human annotators. In this work, we develop a deep learning approach to segment mushrooms and estimate

Noah Golowich, Ankur Moitra, Dhruv Rohatgi

In this expository note we show that the learning parities with noise (LPN) assumption is robust to weak dependencies in the noise distribution of small batches of samples. This provides a partial converse to the linearization technique of [AG11]. The material in this note is drawn from a recent work by the authors [GMR24], where the robustness guarantee was

Kevin Huynh

Model averaging methods have become an increasingly popular tool for improving predictions and dealing with model uncertainty, especially in Bayesian settings. Recently, frequentist model averaging methods such as information theoretic and least squares model averaging have emerged. This work focuses on the issue of covariate uncertainty where managing the c

Leonardo Brizi, Emanuele Giacomini, Luca Di Giammarino, Simone Ferrari

This paper presents a vision and perception research dataset collected in Rome, featuring RGB data, 3D point clouds, IMU, and GPS data. We introduce a new benchmark targeting visual odometry and SLAM, to advance the research in autonomous robotics and computer vision. This work complements existing datasets by simultaneously addressing several issues, such a

Vojtěch Horný, Konstantin Burdonov, Alice Fazzini, Vincent Lelasseux

Compact laser-plasma acceleration of fast ions has made great strides since its discovery over two decades ago, resulting in the current generation of high-energy ($\geq 100\,\rm MeV$) ultracold beams over ultrashort ($\leq 1\,\rm ps$) durations. To unlock broader applications of these beams, we need the ability to tailor the ion energy spectrum. Here, we pr

Dongjae Lee, H. Jin Kim

This work proposes a saturated robust controller for a fully actuated multirotor that takes disturbance rejection and rotor thrust saturation into account. A disturbance rejection controller is required to prevent performance degradation in the presence of parametric uncertainty and external disturbance. Furthermore, rotor saturation should be properly addre

Jeffrey S. Case, Ayush Khaitan, Yueh-Ju Lin, Aaron J. Tyrrell

We describe a general procedure for computing renormalized curvature integrals on Poincar\'e-Einstein manifolds. In particular, we explain the connection between the Gauss-Bonnet-type formulas of Albin and Chang-Qing-Yang for the renormalized volume, and explicitly identify a scalar conformal invariant in the latter formula. Our approach constructs scalar co

Qiangang Du, Jinlong Peng, Changan Wang, Xu Chen

Change detection aims to identify remote sense object changes by analyzing data between bitemporal image pairs. Due to the large temporal and spatial span of data collection in change detection image pairs, there are often a significant amount of task-specific and task-agnostic noise. Previous effort has focused excessively on denoising, with this goes a gre

Zhangchi Feng, Richong Zhang, Zhijie Nie

The Composed Image Retrieval (CIR) task aims to retrieve target images using a composed query consisting of a reference image and a modified text. Advanced methods often utilize contrastive learning as the optimization objective, which benefits from adequate positive and negative examples. However, the triplet for CIR incurs high manual annotation costs, res

Yang Ye, Basile Audoly, Claire Lestringant

We propose a general approach to the higher-order homogenization of discrete elastic networks made up of linear elastic beams or springs in dimension 2 or 3. The network may be nearly (rather than exactly) periodic: its elastic and geometric properties are allowed to vary slowly in space, in addition to being periodic at the scale of the unit cell. The refer

Yukiko Ishizuki, Tatsuki Kuribayashi, Yuichiroh Matsubayashi, Ryohei Sasano

Speakers sometimes omit certain arguments of a predicate in a sentence; such omission is especially frequent in pro-drop languages. This study addresses a question about ellipsis -- what can explain the native speakers' ellipsis decisions? -- motivated by the interest in human discourse processing and writing assistance for this choice. To this end, we first

Steven Rivetti, Ozlem Tugfe Demir, Emil Bjornson, Mikael Skoglund

Integrated sensing and communication (ISAC) has already established itself as a promising solution to the spectrum scarcity problem, even more so when paired with a reconfigurable intelligent surface (RIS), as RISs can shape the propagation environment by adjusting their phase-shift coefficients. Albeit the potential performance gain, a RIS is also a potenti

Xin Li, Kun Yuan, Yajing Pei, Yiting Lu

This paper reviews the NTIRE 2024 Challenge on Shortform UGC Video Quality Assessment (S-UGC VQA), where various excellent solutions are submitted and evaluated on the collected dataset KVQ from popular short-form video platform, i.e., Kuaishou/Kwai Platform. The KVQ database is divided into three parts, including 2926 videos for training, 420 videos for val

A. Lemos, A. O. Moura, S. Ribas, A. T. Silva

Let $G$ be a group and $A\subseteq [1,\exp(G)-1]$. We define the constant ${\sf C}_A(G),$ which is the least positive integer $\ell$ such that every sequence over $G$ of length at least $\ell$ has an $A$-weighted consecutive product-one subsequence. In this paper, among other things, we prove that ${\sf C}_A(C_n^2)=4$ with $A=[1,n-1],$ and ${\sf C}(H\times K

David Mulvey, Chuan Heng Foh, Muhammad Ali Imran, Rahim Tafazolli

In a previous paper, we have shown that a recurrent neural network (RNN) can be used to detect cellular network radio signal degradations accurately. We unexpectedly found, though, that accuracy gains diminished as we added layers to the RNN. To investigate this, in this paper, we build a parallel model to illuminate and understand the internal operation of

Dongjae Lee, Sunwoo Hwang, Jeonghyun Byun, Seung Jae Lee

Aerial unperching of multirotors has received little attention as opposed to perching that has been investigated to elongate operation time. This study presents a new aerial robot capable of both perching and unperching autonomously on/from a ferromagnetic surface during flight, and a switching controller to avoid rotor saturation and mitigate overshoot duri

Mukesh Dalal

We introduce a novel software abstraction termed "model caller," acting as an intermediary for AI and ML model calling, advocating its transformative utility beyond existing model-serving frameworks. This abstraction offers multiple advantages: enhanced accuracy and reduced latency in model predictions, superior monitoring and observability of models, more s

Leo Stewen, Martin Kleppmann

Undo and redo functionality is ubiquitous in collaboration software. In single user settings, undo and redo are well understood. However, when multiple users edit a document, concurrency may arise, leading to a non-linear operation history. This renders undo and redo more complex both in terms of their semantics and implementation. We survey the undo and red

Rui Wang, Han Chao, Jiangtao Peng

Let $G$ be a finite abelian group and $S$ a sequence with elements of $G$. Let $|S|$ denote the length of $S$ and $\mathrm{supp}(S)$ the set of all the distinct terms in $S$. For an integer $k$ with $k\in [1, |S|]$, let $\Sigma_{k}(S) \subset G$ denote the set of group elements which can be expressed as a sum of a subsequence of $S$ with length $k$. Let $\Si

Soham Ghosh, Vladlen Galetsky, Pol Juliá Farré, Christian Deppe

Physical Unclonable Functions (PUFs) leverage inherent, non-clonable physical randomness to generate unique input-output pairs, serving as secure fingerprints for cryptographic protocols like authentication. Quantum PUFs (QPUFs) extend this concept by using quantum states as input-output pairs, offering advantages over classical PUFs, such as challenge reusa

Chunwei Lin

This study showcases an augmented reality (AR) experience designed to promote gender justice and increase awareness of sexual violence in Taiwan. By leveraging AR, this project overcomes the limitations of offline exhibitions on social issues by motivating the public to participate and enhancing their willingness to delve into the topic. The discussion explo