April 2023 arXiv papers — page 65

Venkatesh Tentu, Dheeraj N Amudala, Anish Chattopadhyay, Rohit Budhiraja

We study the impact of channel aging on the uplink of a cell-free (CF) massive multiple-input multiple-output (mMIMO) system by considering i) spatially-correlated Rician-faded channels; ii) hardware impairments at the access points and user equipments (UEs); and iii) two-layer large-scale fading decoding (LSFD). We first derive a closed-form spectral effici

Cesare Malosso, Gaetano Senatore, Stefania De Palo

Excitonic condensation and superfluidity have recently received a renewed attention, due to the fabrication of bilayer systems in which electrons and hole are spatially separated and form stable pairs known as indirect excitons. Dichalcogenides- and graphene- based bilayers are nowadays built and investigated, giving access to systems with (i) only spin dege

Nick D. Hartmann, Jimin L. Li, David J. Luitz

The generic behavior of purely dissipative open quantum many-body systems with local dissipation processes can be investigated using random matrix theory, revealing a hierarchy of decay timescales of observables organized by their complexity as shown in [Wang et al., Phys. Rev. Lett. 124, 100604 (2020)]. This hierarchy is reflected in distinct eigenvalue clu

Theodore Andronikos, Alla Sirokofskich

Let us consider a situation where two information brokers, whose currency is, of course, information, need to reciprocally exchange information. The two brokers, being somewhat distrustful, would like a third, mutually trusted, entity to be involved in the exchange process so as to guarantee the successful completion of the transaction, and also verify that

Jianhao Chen, Junyang Ren, Wentao Ding, Yuzhong Qu

Temporal facts, the facts for characterizing events that hold in specific time periods, are attracting rising attention in the knowledge graph (KG) research communities. In terms of quality management, the introduction of time restrictions brings new challenges to maintaining the temporal consistency of KGs and detecting potential temporal conflicts. Previou

Chuancun Yin

In this work, we establish some stochastic comparison results for multivariate skew-elliptical random vectors. These multivariate stochastic comparisons involve Hessian and increasing-Hessian orderings as well as many of their special cases. Necessary and/or sufficient conditions of the orderings are provided simply based on a comparison of the underlying mo

Andrey Sobolevsky, Guillaume-Alexandre Bilodeau, Jinghui Cheng, Jin L. C. Guo

Sketching out Graphical User Interface (GUI) layout is part of the pipeline of designing a GUI and a crucial task for the success of a software application. Arranging all components inside a GUI layout manually is a time-consuming task. In order to assist designers, we developed a method named GUILGET to automatically generate GUI layouts from positional con

Di Fan, Yannian Kou, Chuanhou Gao

Disentangled representation learning aims to learn low-dimensional representations where each dimension corresponds to an underlying generative factor. While the Variational Auto-Encoder (VAE) is widely used for this purpose, most existing methods assume independence among factors, a simplification that does not hold in many real-world scenarios where factor

János Kollár, Sándor J Kovács

KSB stability holds at codimension 1 points trivially, and it is quite well understood at codimension 2 points, since we have a complete classification of 2-dimensional slc singularities. We show that it is automatic in codimension 3.

Maen Salman, Trond Saue

In this work, we propose an efficient and accurate computational method to evaluate the many-potential $\alpha\left(Z\alpha\right)^{n\ge3}$ vacuum polarization density of hydrogen-like atoms within the finite-basis approximation of the Dirac equation. To prove the performance of our computational method, we choose to work with the one-electron $_{\,\,\,92}^{

Xiaoying Dai, Miao Hu, Jack Xin, Aihui Zhou

In this paper, we propose an augmented subspace based adaptive proper orthogonal decomposition (POD) method for solving the time dependent partial differential equations. By augmenting the POD subspace with some auxiliary modes, we obtain an augmented subspace. We use the difference between the approximation obtained in this augmented subspace and that obtai

Jérôme Denis, Jack Davis, Robert B. Mann, John Martin

Quasiprobability has become an increasingly popular notion for characterising non-classicality in quantum information, thermodynamics, and metrology. Two important distributions with non-positive quasiprobability are the Wigner function and the Glauber-Sudarshan function. Here we study properties of the spin Wigner function for finite-dimensional quantum sys

Pedro Parra-Rivas, Yifan Sun, Stefan Wabnitz

In this work, we present a detailed study of the dynamics and stability of fundamental spatiotemporal solitons emerging in multimode waveguides with a parabolic transverse profile of the linear refractive index. Pulsed beam propagation in these structures can be described by using a Gross-Pitaevskii equation with a two-dimensional parabolic spatial potential

Zhi-Fu Deng, Chao Han, Wei Wang, Jun Zeng

Momentum distributions of quarks/gluons inside a light baryon in a hard exclusive process are encoded in the light-cone distribution amplitudes (LCDAs). In this work, we point out that the leading twist LCDAs of a light baryon can be obtained through a simulation of a quasi-distribution amplitude calculable on lattice QCD within the framework of the large-mo

Bidisha Roy, Lalit Vaishya

In this survey article, we summarise the known results towards the conjecture: elliptic curves over totally real number fields are modular. For understanding these recent results in the literature, we present some necessary background along with certain applications.

S. Muller, I. Marti-Vidal, F. Combes, M. Gerin

Time variability of astronomical sources provides crude information on their typical size and on the implied physical mechanisms. PKS1830-211 is a remarkable radio-bright lensed quasar with a foreground molecular absorber at z=0.89. Small-scale morphological changes in the core-jet structure of the quasar -- which is magnified by the lensing -- result in a v

Daniel Rohe

We extend and apply a recently introduced quasi-particle functional renormalisation group scheme to the two-dimensional Hubbard model with next-nearest-neighbour hopping and away from half filling. We confirm the generation of superconducting correlations in some regions of the phase diagram, but also find that the inclusion of self-energy feedback by means

Giacomo Tendas

We capture in the context of lex colimits, introduced by Garner and Lack, the universal property of the free regular and Barr-exact completions of a weakly lex category. This is done by introducing a notion of flatness for functors $F\colon\mathcal C\to\mathcal E$ with lex codomain, and using this to describe the universal property of free $\Phi$-exact compl

Hugo Sousa, Arian Pasquali, Alípio Jorge, Catarina Sousa Santos

Textual health records of cancer patients are usually protracted and highly unstructured, making it very time-consuming for health professionals to get a complete overview of the patient's therapeutic course. As such limitations can lead to suboptimal and/or inefficient treatment procedures, healthcare providers would greatly benefit from a system that effec

Jamshaid Ul Rahman, Faiza Makhdoom, Dianchen Lu

Many industrial and real life problems exhibit highly nonlinear periodic behaviors and the conventional methods may fall short of finding their analytical or closed form solutions. Such problems demand some cutting edge computational tools with increased functionality and reduced cost. Recently, deep neural networks have gained massive research interest due

Enrico Del Re, Cristina Olaverri-Monreal

With the race towards higher levels of automation in vehicles, it is imperative to guarantee the safety of all involved traffic participants. Yet, while high-risk traffic situations between two vehicles are well understood, traffic situations involving more vehicles lack the tools to be properly analyzed. This paper proposes a method to compare Surrogate Saf

Paul H Frampton

We investigate a model of the universe where dark energy is replaced by electrically-charged extremely-massive dark matter. This was originally described only for the present cosmological time. The time dependence of the charged dark matter is different from that for dark energy and in the future the expansion will no longer accelerate and the scale factor $

N. Kellner, N. Hüttner, M. Will, P. Hakonen

From the background of microwave-optomechanical experiments involving carbon nanotubes, the optimization of superconducting coplanar waveguide resonator devices is discussed. Two devices, one with unmodified geometry compared to previous work and one integrating several improvements, are lithographically built up step by step. After each step, the low temper

Bibo Wu, Fang Fang, Xianbin Wang

In federated learning (FL), distributed clients can collaboratively train a shared global model while retaining their own training data locally. Nevertheless, the performance of FL is often limited by the slow convergence due to poor communications links when FL is deployed over wireless networks. Due to the scarceness of radio resources, it is crucial to se

Nadia Dachlythra, Adriaan J. Duivenvoorden, Jon E. Gudmundsson, Matthew Hasselfield

We use time-domain simulations of Jupiter observations to test and develop a beam reconstruction pipeline for the Simons Observatory Small Aperture Telescopes. The method relies on a map maker that estimates and subtracts correlated atmospheric noise and a beam fitting code designed to compensate for the bias caused by the map maker. We test our reconstructi

Alexander Naumann, Felix Hertlein, Laura Dörr, Kai Furmans

We focus on enabling damage and tampering detection in logistics and tackle the problem of 3D shape reconstruction of potentially damaged parcels. As input we utilize single RGB images, which corresponds to use-cases where only simple handheld devices are available, e.g. for postmen during delivery or clients on delivery. We present a novel synthetic dataset

Rui Li, Dong Gong, Wei Yin, Hao Chen

Multi-frame depth estimation generally achieves high accuracy relying on the multi-view geometric consistency. When applied in dynamic scenes, e.g., autonomous driving, this consistency is usually violated in the dynamic areas, leading to corrupted estimations. Many multi-frame methods handle dynamic areas by identifying them with explicit masks and compensa

Xiangru Tao, Aiqin Yang, Shuxiang Yang, Yundi Quan

Recent experimental study by Dias {\it et al.} claims to have discovered room-temperature superconductivity in lutetium-nitrogen-hydrogen system at 1 GPa [Nature 615, 244 (2023)], which sheds light on the long-held dream of ambient superconductivity. However, all follow-up experiments found no evidence of superconductivity. The compositions and the crystal s

Hyunjae Lee

This paper describes Difference-aware Deep continuous prompt for Contrastive Sentence Embeddings (D2CSE) that learns sentence embeddings. Compared to state-of-the-art approaches, D2CSE computes sentence vectors that are exceptional to distinguish a subtle difference in similar sentences by employing a simple neural architecture for continuous prompts. Unlike

Zhaoming Kong, Fangxi Deng, Haomin Zhuang, Jun Yu

The advancement of imaging devices and countless images generated everyday pose an increasingly high demand on image denoising, which still remains a challenging task in terms of both effectiveness and efficiency. To improve denoising quality, numerous denoising techniques and approaches have been proposed in the past decades, including different transforms,

Fausto Giunchiglia, Xiaolei Diao, Mayukh Bagchi

Data quality is critical for multimedia tasks, while various types of systematic flaws are found in image benchmark datasets, as discussed in recent work. In particular, the existence of the semantic gap problem leads to a many-to-many mapping between the information extracted from an image and its linguistic description. This unavoidable bias further leads

Alessandro Navone, Mauro Martini, Andrea Ostuni, Simone Angarano

Segmentation-based autonomous navigation has recently been proposed as a promising methodology to guide robotic platforms through crop rows without requiring precise GPS localization. However, existing methods are limited to scenarios where the centre of the row can be identified thanks to the sharp distinction between the plants and the sky. However, GPS si

Yuan-He Zou, Hao Liu, Yan-Rui Liu, Shao-Zhou Jiang

The chiral Lagrangians for singly heavy baryons are constructed up to the $\mathcal{O}(p^{4})$ order. The involved baryons may be in a flavor antitriplet with spin-1/2, a flavor sextet with spin-$1/2$, or a flavor sextet with spin-3/2 when one considers three light flavors. For the relativistic version of Lagrangian, from $\mathcal{O}(p^{2})$ to $\mathcal{O}

Janie Coulombe, Shu Yang

Electronic health records and other sources of observational data are increasingly used for drawing causal inferences. The estimation of a causal effect using these data not meant for research purposes is subject to confounding and irregular covariate-driven observation times affecting the inference. A doubly-weighted estimator accounting for these features

Payel Nandi, C. S. Stalin, D. J. Saikia, S. Muneer

We present a detailed multi-wavelength study of star formation in the dwarf galaxy NGC 4395 which hosts an active galactic nucleus (AGN). From our observations with the Ultra-Violet Imaging Telescope, we have compiled a catalogue of 284 star forming (SF) regions, out of which we could detect 120 SF regions in H$\alpha$ observations. Across the entire galaxy,

Bogdan-Vasile Matioc, Luigi Roberti

In this paper we study a recently derived mathematical model for nonlinear propagation of waves in the atmosphere, for which we establish the local well-posedness in the setting of classical solutions. This is achieved by formulating the model as a quasilinear parabolic evolution problem in an appropriate functional analytic framework and by using abstract t

Lenka Tětková, Lars Kai Hansen

As the use of deep neural networks continues to grow, understanding their behaviour has become more crucial than ever. Post-hoc explainability methods are a potential solution, but their reliability is being called into question. Our research investigates the response of post-hoc visual explanations to naturally occurring transformations, often referred to a

Junsoo Kim, Jin Gyu Lee, Henrik Sandberg, Karl H. Johansson

A resilient state estimation scheme for uniformly observable nonlinear systems, based on a method for local identification of sensor attacks, is presented. The estimation problem is combinatorial in nature, and so many methods require substantial computational and storage resources as the number of sensors increases. To reduce the complexity, the proposed me

Max T. Curie, Joel Larakers, Jason Parisi, Gary Staebler

This article presents a survey of NSTX cases to study the microtearing mode (MTM) stabilities using the newly developed global reduced model for Slab-Like Microtearing modes (SLiM). A trained neutral network version of SLiM enables rapid assessment (0.05s/mode) of MTM with $98\%$ accuracy providing an opportunity for systemic equilibrium reconstructions base

Zheng Lian, Haiyang Sun, Licai Sun, Kang Chen

The first Multimodal Emotion Recognition Challenge (MER 2023) was successfully held at ACM Multimedia. The challenge focuses on system robustness and consists of three distinct tracks: (1) MER-MULTI, where participants are required to recognize both discrete and dimensional emotions; (2) MER-NOISE, in which noise is added to test videos for modality robustne

A. S. Belozerov, V. I. Anisimov

We study the influence of Coulomb correlations on spectral and magnetic properties of fcc cobalt using a combination of density functional theory and dynamical mean-field theory. The computed uniform and local magnetic susceptibilities obey the Curie-Weiss law, which, as we demonstrate, occurs due to the partial formation of local magnetic moments. We find t

Xinyue Shen, Zeyuan Chen, Michael Backes, Yang Zhang

The way users acquire information is undergoing a paradigm shift with the advent of ChatGPT. Unlike conventional search engines, ChatGPT retrieves knowledge from the model itself and generates answers for users. ChatGPT's impressive question-answering (QA) capability has attracted more than 100 million users within a short period of time but has also raised

Hanyu Cai, Ni Ou, Junzheng Wang

This paper presents a novel visual-LiDAR odometry and mapping method with low-drift characteristics. The proposed method is based on two popular approaches, ORB-SLAM and A-LOAM, with monocular scale correction and visual-bootstrapped LiDAR poses initialization modifications. The scale corrector calculates the proportion between the depth of image keypoints r

G. E. Volovik

It is shown that the Schwarzschild-de Sitter (SdS) spacetime has the fundamental temperature. This temperature describes the thermal processes of decay of the composite particles and the other processes, which are energetically forbidden in the Minkowski spacetime, but are allowed in the de Sitter and in SdS backgrounds. In particular, this temperature descr

Raz Kupferman, Roee Leder

We solve a problem posed by Calabi more than 60 years ago, known as the Saint-Venant compatibility problem: Given a compact Riemannian manifold, generally with boundary, find a compatibility operator for Lie derivatives of the metric tensor. This problem is related to other compatibility problems in mathematical physics, and to their inherent gauge freedom.

Philipp Fleig, Vijay Balasubramanian

Every interaction of a living organism with its environment involves the placement of a bet. Armed with partial knowledge about a stochastic world, the organism must decide its next step or near-term strategy, an act that implicitly or explicitly involves the assumption of a model of the world. Better information about environmental statistics can improve th

Tommie Kerssies, Joaquin Vanschoren

This paper presents the first application of neural architecture search to the complex task of segmenting visual anomalies. Measurement of anomaly segmentation performance is challenging due to imbalanced anomaly pixels, varying region areas, and various types of anomalies. First, the region-weighted Average Precision (rwAP) metric is proposed as an alternat

Yukun Ma, Pedro H. C. Sant'Anna, Yuya Sasaki, Takuya Ura

Doubly robust (DR) estimators guard against model misspecification but remain sensitive to weak covariate overlap. We show that trimming propensity scores reduces variance but eliminates double robustness. We introduce DR estimators that retain double robustness after trimming through bias correction, preserving the original causal targets across unconfounde

Gabriel Germino Martins de Jesus, João Luiz Rebelatto, Richard Demo Souza, Onel Luis Alcaraz López

We propose and evaluate the performance of a Non-Orthogonal Multiple Access (NOMA) dual-hop multiple relay (MR) network from an information freshness perspective using the Age of Information (AoI) metric. More specifically, we consider an age dependent (AD) policy, named as AD-NOMA- MR, in which users only transmit, with a given probability, after they reach

Gustav Müller-Franzes, Fritz Müller-Franzes, Luisa Huck, Vanessa Raaff

Accurate and automatic segmentation of fibroglandular tissue in breast MRI screening is essential for the quantification of breast density and background parenchymal enhancement. In this retrospective study, we developed and evaluated a transformer-based neural network for breast segmentation (TraBS) in multi-institutional MRI data, and compared its performa

Yiming Gao, Yan-Pei Cao, Ying Shan

Online reconstructing and rendering of large-scale indoor scenes is a long-standing challenge. SLAM-based methods can reconstruct 3D scene geometry progressively in real time but can not render photorealistic results. While NeRF-based methods produce promising novel view synthesis results, their long offline optimization time and lack of geometric constraint

Arthur Vangeffelen, Geert Buckinx, Carlo De Servi, Maria Rosaria Vetrano

We investigate to what degree the steady laminar flow in typical micro- and mini-channels with offset strip fin arrays can be described as developed on a macro-scale level, in the presence of channel entrance and side-wall effects. Hereto, the extent of the developed and quasi-developed flow regions in such channels is determined through large-scale numerica

Jiayue Yang, Robert B. Mann

Treating the horizon radius as an order parameter in a thermal fluctuation, the free energy landscape model sheds light on the dynamic behaviour of black hole phase transitions. Here we carry out the first investigation of the dynamics of the recently discovered multicriticality in black holes. We specifically consider black hole quadruple points in D=4 Eins

Da Silva Gameiro Henrique, Andrei Kucharavy, Rachid Guerraoui

The self-attention revolution allowed generative language models to scale and achieve increasingly impressive abilities. Such models - commonly referred to as Large Language Models (LLMs) - have recently gained prominence with the general public, thanks to conversational fine-tuning, putting their behavior in line with public expectations regarding AI. This

Nabeel Gillani, Doug Beeferman, Cassandra Overney, Christine Vega-Pourheydarian

Educational data scientists often conduct research with the hopes of translating findings into lasting change through policy, civil society, or other channels. However, the bridge from research to practice can be fraught with sociopolitical frictions that impede, or altogether block, such translations -- especially when they are contentious or otherwise diff

Andrea Grisafi, Augustin Bussy, Mathieu Salanne, Rodolphe Vuilleumier

The computational study of energy storage and conversion processes calls for simulation techniques that can reproduce the electronic response of metal electrodes under electric fields. Despite recent advancements in machine-learning methods applied to electronic-structure properties, predicting the non-local behavior of the charge density in electronic condu

Zisheng Chen, Hongbin Xu, Weitao Chen, Zhipeng Zhou

Semantic segmentation of point clouds usually requires exhausting efforts of human annotations, hence it attracts wide attention to the challenging topic of learning from unlabeled or weaker forms of annotations. In this paper, we take the first attempt for fully unsupervised semantic segmentation of point clouds, which aims to delineate semantically meaning

Thomas Mannel, Daniel Moreno, Alexei A. Pivovarov

We consider the Heavy Quark Expansion (HQE) for the nonleptonic decay rates of heavy hadrons, and compute the NLO QCD corrections to power terms up to order $1/m_Q^2$. We neglect the masses of the final-state quarks, so the application of our result is mainly for charmed hadrons. Our result can be applied also to bottomed hadrons as they constitute the main

Johannes Bütow, Jörg S. Eismann, Varun Sharma, Dorian Brandmüller

Structured light is a key component of many modern applications, ranging from superresolution microscopy to imaging, sensing, and quantum information processing. As the utilization of these powerful tools continues to spread, the demand for technologies that enable the spatial manipulation of fundamental properties of light, such as amplitude, phase, and pol

ATLAS Collaboration

A search is made for potential $cc\bar{c}\bar{c}$ tetraquarks decaying into a pair of charmonium states in the four muon final state using proton-proton collision data at $\sqrt{s}=13$ TeV, corresponding to an integrated luminosity of 140 fb$^{-1}$ recorded by the ATLAS experiment at LHC. Two decay channels, $J/\psi+J/\psi \rightarrow 4\mu$ and $J/\psi+\psi(

Remi Abgrall

Since the celebrated theorem of Lax and Wendroff, we know a necessary condition that any numerical scheme for hyperbolic problem should satisfy: it should be written in flux form. A variant can also be formulated for the entropy. Even though some schemes, as for example those using continuous finite element, do not formally cast into this framework, it is a

David Wiesner, Julian Suk, Sven Dummer, Tereza Nečasová

Data-driven cell tracking and segmentation methods in biomedical imaging require diverse and information-rich training data. In cases where the number of training samples is limited, synthetic computer-generated data sets can be used to improve these methods. This requires the synthesis of cell shapes as well as corresponding microscopy images using generati

Wojciech Kotlarski, Kamila Kowalska, Daniele Rizzo, Enrico Maria Sessolo

The framework of trans-Planckian asymptotic safety has been shown to generate phenomenological predictions in the Standard Model and in some of its simple new physics extensions. A heuristic approach is often adopted, which bypasses the functional renormalization group by relying on a parametric description of quantum gravity with universal coefficients that

Jiasheng Yang, Alexander Stroh, Sangseung Lee, Shervin Bagheri

The purpose of the present work is to examine two possibilities; firstly, predicting equivalent sand-grain roughness size $k_s$ based on the roughness height probability density function and power spectrum leveraging machine learning as a regression tool, and secondly, extracting information about relevance of different roughness scales to skin-friction drag

Christopher J. Smith, Alaa Al Khourdajie, Pu Yang, Doris Folini

Emissions pathways used in climate policy analysis are often derived from integrated assessment models. However, such emissions pathways do not typically include climate feedbacks on socioeconomic systems and by extension do not consider climate uncertainty in their construction. We use a well-known cost-benefit integrated assessment model, the Dynamic Integ

Naiyu Fang, Lemiao Qiu, Shuyou Zhang, Zili Wang

Virtual try-on is a promising computer vision topic with a high commercial value wherein a new garment is visually worn on a person with a photo-realistic effect. Previous studies conduct their shape and content inference at one stage, employing a single-scale warping mechanism and a relatively unsophisticated content inference mechanism. These approaches ha

Yuri Trakhinin

We study the local-in-time well-posedness for an interface that separates an anisotropic plasma from a vacuum. The plasma flow is governed by the ideal Chew-Goldberger-Low (CGL) equations, which are the simplest collisionless fluid model with anisotropic pressure. The vacuum magnetic and electric fields are supposed to satisfy the pre-Maxwell equations. The

Rama Mishra, Visakh Narayanan

We define plat closure for spherical braids to obtain links in $\mathbb{R}P^3$ and prove that all links in $\mathbb{R}P^3$ can be realized in this manner. Given a spherical braid $\beta$ of $2n$ strands in $\mathbb{R}P^3$ we associate a permutation $h_{\beta}$ on $n$ elements called \textit{residual permutation}. We prove that the number of components of the

Adarsh Kumar, Pedro Sarmento

Subword tokenization has been widely successful in text-based natural language processing (NLP) tasks with Transformer-based models. As Transformer models become increasingly popular in symbolic music-related studies, it is imperative to investigate the efficacy of subword tokenization in the symbolic music domain. In this paper, we explore subword tokenizat

Hongxiang Yu, Anzhe Chen, Kechun Xu, Zhongxiang Zhou

Recently, several works achieve end-to-end visual servoing (VS) for robotic manipulation by replacing traditional controller with differentiable neural networks, but lose the ability to servo arbitrary desired poses. This letter proposes a differentiable architecture for arbitrary pose servoing: a hyper-network based neural controller (HPN-NC). To achieve th

M. F. C. Martins Quintela, T. Garm Pedersen

The optical properties of two-dimensional materials are exceptional in several respects. They are highly anisotropic and frequently dominated by excitonic effects. Dipole-allowed second order non-linear optical properties require broken inversion symmetry. Hence, several two-dimensional materials show strong in-plane (IP) non-linearity but negligible out-of-

Arut Prakash Kaleeswaran, Arne Nordmann, Thomas Vogel, Lars Grunske

Context: Ensuring safety for any sophisticated system is getting more complex due to the rising number of features and functionalities. This calls for formal methods to entrust confidence in such systems. Nevertheless, using formal methods in industry is demanding because of their lack of usability and the difficulty of understanding verification results. Ob

Niko Jokela, Arttu Pönni, Tobias Rindlisbacher, Kari Rummukainen

A construction of a gravity dual to a physical gauge theory requires confronting data. We establish a proof-of-concept for precision holography, i.e., the explicit reconstruction of the dual background metric functions directly from the entanglement entropy (EE) of strip subregions that we extract from pure glue Yang-Mills theory discretized on a lattice. Ou

Tian-Sheng Zeng

The Halperin $(m',m,n)$ fractional quantum Hall effects of two-component quantum particles are studied in topological checkerboard lattice models. Here for $m\neq m'$, we demonstrate the emergence of fractional quantum hall effects with the associated $\mathbf{K}=\begin{pmatrix} m+2 & 1\\ 1 & m\\ \end{pmatrix}$ matrix (even $m=2$ for boson and odd $m=3$ for

Ke Yin, Xianglin Hao, Yuangen Huang, Jianlong Zou

Exceptional points (EP) in non-Hermitian systems have been widely investigated due to their enhanced sensitivity in comparison to standard systems. In this letter, we report the observation of higher-order pseudo-Hermitian degeneracies in an electronic platform comprised of three inductively coupled gain-loss-loss LC resonators. Theoretical analysis demonstr

Isabella Graßl, Gordon Fraser, Stefan Trieflinger, Marco Kuhrmann

Software development teams have to face stress caused by deadlines, staff turnover, or individual differences in commitment, expertise, and time zones. While students are typically taught the theory of software project management, their exposure to such stress factors is usually limited. However, preparing students for the stress they will have to endure onc

Gunnar Brinkmann, Matthias De Pauw

We give constructive proofs for the existence of uniquely hamiltonian graphs for various sets of degrees. We give constructions for all sets with minimum 2 (a trivial case added for completeness), all sets with minimum 3 that contain an even number (for sets without an even number it is known that no uniquely hamiltonian graphs exist), and all sets with mini

Rongliang Wu, Yingchen Yu, Fangneng Zhan, Jiahui Zhang

Audio-driven talking face generation, which aims to synthesize talking faces with realistic facial animations (including accurate lip movements, vivid facial expression details and natural head poses) corresponding to the audio, has achieved rapid progress in recent years. However, most existing work focuses on generating lip movements only without handling

Dingwen Kong, Lin F. Yang

An appropriate reward function is of paramount importance in specifying a task in reinforcement learning (RL). Yet, it is known to be extremely challenging in practice to design a correct reward function for even simple tasks. Human-in-the-loop (HiL) RL allows humans to communicate complex goals to the RL agent by providing various types of feedback. However

Cid Reyes-Bustos, Masato Wakayama

The quantum Rabi model (QRM), one of the fundamental models used to describe light and matter interaction, has a deep mathematical structure revealed by the study of its spectrum. In this paper, from the explicit formulas for the partition function we directly derive various limits of the spectral zeta function with respect to the systems parameters of the a

Francesco Guarnera, Alessia Rondinella, Oliver Giudice, Alessandro Ortis

Early detection of an infection prior to prosthesis removal (e.g., hips, knees or other areas) would provide significant benefits to patients. Currently, the detection task is carried out only retrospectively with a limited number of methods relying on biometric or other medical data. The automatic detection of a periprosthetic joint infection from tomograph

Vladimir L. Popov

Here are reproduced slightly edited notes of my lectures on the classification of discrete groups generated by complex reflections of Hermitian affine spaces delivered in October of 1980 at the University of Utrecht.

Isabella Graßl, Gordon Fraser

Young learners are increasingly introduced to programming, and one of the main challenges for educators is to achieve learning success while also creating enthusiasm. As it is particularly difficult to achieve this enthusiasm initially in young females, prior work has identified gender-specific differences in the programming behavior of young learners. Since

S. Abdallah, S. A. Franchino-Viñas, M. Fröb

We review recent discussions regarding the parity-odd contribution to the trace anomaly of a chiral fermion. We pay special attention to the perturbative approach in terms of Feynman diagrams, comparing in detail the results obtained using dimensional regularization and the Breitenlohner--Maison prescription with other approaches.

Rongliang Wu, Yingchen Yu, Fangneng Zhan, Jiahui Zhang

Facial expression editing has attracted increasing attention with the advance of deep neural networks in recent years. However, most existing methods suffer from compromised editing fidelity and limited usability as they either ignore pose variations (unrealistic editing) or require paired training data (not easy to collect) for pose controls. This paper pre

Kiichiro Toyoizumi, Naoki Yamamoto, Kazuo Hoshino

Quantum computing can be used to speed up the simulation time (more precisely, the number of queries of the algorithm) for physical systems; one such promising approach is the Hamiltonian simulation (HS) algorithm. Recently, it was proven that the quantum singular value transformation (QSVT) achieves the minimum simulation time for HS. An important subroutin

Vincent E. Debets, Liesbeth M. C. Janssen

Dense or glassy active matter, as a result of its remarkable resemblance to passive glass-forming materials, is enjoying increasing scientific interest. To better grasp the subtle effect of active motion on the process of vitrification, a number of active mode-coupling theories (MCTs) have recently been developed. These have proven capable of qualitatively p

Takashi Ari-Izumi, Ioana Gheorghe, Dan Filipescu, Satoshi Hashimoto

The intensity and energy spatial distributions of collimated laser Compton scattering (LCS) $\gamma$-ray beams and of the associated bremsstrahlung beams have been investigated as functions of the electron beam energy, electron beam phase space distribution, laser optics conditions and laser polarization. We show that the beam halo is affected to different e

Maria Rosaria Pati

We prove one divisibility relation of the anticyclotomic Iwasawa Main Conjecture for a higher weight ordinary modular form $f$ and an imaginary quadratic field satisfying a "relaxed" Heegner hypothesis. Let $\Lambda$ be the anticyclotomic Iwasawa algebra. Following the approach of Howard and Longo--Vigni, we construct the $\Lambda$-adic Kolyvagin system of g

Fidel F. Villaseñor

The Ricci version of the Schur theorem is shown to hold for a wide class of Finsler metrics. What is more, let $F$ be any (positive definite) Finsler metric such that $\text{Ric} =\rho F^2$ with $\rho\colon M^n\rightarrow\mathbb{R}$ (i.e., $(M^n,F)$ is Einstein) and $n\geq 3$. For $x\in M$, we express $\text{d}\rho_x$ as an average over the indicatrix in $\t

Savvas Papaioannou, Panayiotis Kolios, Theocharis Theocharides, Christos G. Panayiotou

In this work, a novel distributed search-planning framework is proposed, where a dynamically varying team of autonomous agents cooperate in order to search multiple objects of interest in three-dimension (3-D). It is assumed that the agents can enter and exit the mission space at any point in time, and as a result the number of agents that actively participa

Janvijay Singh, Vilém Zouhar, Mrinmaya Sachan

Textbooks are one of the main mediums for delivering high-quality education to students. In particular, explanatory and illustrative visuals play a key role in retention, comprehension and general transfer of knowledge. However, many textbooks lack these interesting visuals to support student learning. In this paper, we investigate the effectiveness of visio

Geanina Zaharia, Diana-Rodica Munteanu

In this paper, we present some numerical applications for the equation $x^2+ax+b=0$, where $a, b$ are two quaternionic elements in $\mathbb{H}(\alpha,\beta)$. Based on well-known solving methods, we have developed a new numerical algorithm that solves the equation for any quaternions a and b in any algebra $\mathbb{H}(\alpha,\beta)$.

Leida Zhang, Zhengda Lu, Kai Liu, Yiqun Wang

Learning-based point cloud registration methods can handle clean point clouds well, while it is still challenging to generalize to noisy, partial, and density-varying point clouds. To this end, we propose a novel point cloud registration framework for these imperfect point clouds. By introducing a neural implicit representation, we replace the problem of rig

Valery N. Pilipchuk, Krystian Polczyński, Maksymilian Bednarek, Jan Awrejcewicz

This paper presents a methodology of controlling the resonance energy exchange in mechanical system consisting of two weakly coupled magnetic pendulums interacting with the magnetic field generated by coils placed underneath. It is shown that properly guided magnetic fields can effectively change mechanical potentials in a way that the energy flow between th

Sina Sajadmanesh, Daniel Gatica-Perez

Graph Neural Networks (GNNs) have become a popular tool for learning on graphs, but their widespread use raises privacy concerns as graph data can contain personal or sensitive information. Differentially private GNN models have been recently proposed to preserve privacy while still allowing for effective learning over graph-structured datasets. However, ach

Berat Can Senel, Maxime Mouchet, Justin Cappos, Olivier Fourmaux

Cloud computing, offering on-demand access to computing resources through the Internet and the pay-as-you-go model, has marked the last decade with its three main service models; Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS). The lightweight nature of containers compared to virtual machines has led to the

Pramod C. Mane, Snehal Ratnaparkhi

The problem of how to achieve cooperation among rational peers in order to discourage free riding is one that has received a lot of attention in peer-to-peer computing and is still an important one. The field of game theory is applied to the task of finding solutions that will encourage cooperation while discouraging free riding. The cooperative conduct of p

Swati, Uttam Singh, Giulio Chiribella

Active states, from which work can be extracted by time-dependent perturbations, are an important resource for quantum thermodynamics in the absence of heat baths. Here we characterize this resource, establishing a resource theory that captures the operational scenario where an experimenter manipulates a quantum system by means of energy-preserving operation

Ping Gong, Yuxin Ma, Cheng Li, Xiaosong Ma

In this paper, we primarily focus on understanding the data preprocessing pipeline for DNN Training in the public cloud. First, we run experiments to test the performance implications of the two major data preprocessing methods using either raw data or record files. The preliminary results show that data preprocessing is a clear bottleneck, even with the mos